From 61658c4c4e2c545cc7c039e62cb9e5f2eb83e44b Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 19 Nov 2024 15:14:13 -0500 Subject: [PATCH 01/38] Handle new anomaly detection method --- nbs/src/nixtla_client.ipynb | 37 ++++++++++++++++++++++++++++++++++++- nixtla/nixtla_client.py | 35 ++++++++++++++++++++++++++++++++++- 2 files changed, 70 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 5bf9b8cf..25a47e95 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -171,6 +171,7 @@ "_Loss = Literal[\"default\", \"mae\", \"mse\", \"rmse\", \"mape\", \"smape\"]\n", "_Model = Literal[\"azureai\", \"timegpt-1\", \"timegpt-1-long-horizon\"]\n", "_Finetune_Depth = Literal[1, 2, 3, 4, 5]\n", + "_Threshold_Method = Literal[\"univariate\", \"multivariate\", \"historical\"]\n", "\n", "_date_features_by_freq = {\n", " # Daily frequencies\n", @@ -565,6 +566,9 @@ ") -> DFType:\n", " if intervals is None:\n", " return df\n", + " first_key = next(iter(intervals), None)\n", + " if first_key is None or intervals[first_key] is None:\n", + " return df\n", " intervals_df = type(df)(\n", " {f'TimeGPT-{k}': intervals[k] for k in sorted(intervals.keys())}\n", " )\n", @@ -582,6 +586,7 @@ " id_col: str,\n", " time_col: str,\n", " target_col: str,\n", + " detection_size: Optional[int]\n", ") -> DataFrame:\n", " times = df[time_col].to_numpy()\n", " targets = df[target_col].to_numpy()\n", @@ -603,6 +608,10 @@ " 'TimeGPT': in_sample_output['mean'],\n", " }\n", " )\n", + " if detection_size is not None:\n", + " out = (out.groupby(id_col)\n", + " .tail(detection_size)\n", + " .reset_index(drop=True))\n", " return _maybe_add_intervals(out, in_sample_output['intervals']) # type: ignore\n", "\n", "def _restrict_input_samples(level, input_size, model_horizon, h) -> int:\n", @@ -1296,6 +1305,7 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", + " detection_size=None\n", " )\n", " in_sample_df = ufp.drop_columns(in_sample_df, target_col)\n", " out = ufp.vertical_concat([in_sample_df, out])\n", @@ -1322,6 +1332,9 @@ " def _distributed_detect_anomalies(\n", " self,\n", " df: DistributedDFType,\n", + " h: _PositiveInt,\n", + " detection_size: _PositiveInt,\n", + " threshold_method: _Threshold_Method,\n", " freq: Optional[str],\n", " id_col: str,\n", " time_col: str,\n", @@ -1352,6 +1365,9 @@ " schema=schema,\n", " params=dict(\n", " client=self,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1372,6 +1388,9 @@ " def detect_anomalies(\n", " self,\n", " df: AnyDFType,\n", + " h: _PositiveInt,\n", + " detection_size: _PositiveInt,\n", + " threshold_method: _Threshold_Method = 'univariate',\n", " freq: Optional[str] = None, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", @@ -1400,6 +1419,15 @@ " - id_col:\n", " Column name in `df` that identifies unique time series. Each unique value in this column\n", " corresponds to a unique time series.\n", + " h : int\n", + " Forecast horizon.\n", + " detection_size: int\n", + " The length of the sequence where anomalies will be detected starting from the end of the dataset.\n", + " threshold_method: str (default='univariate')\n", + " The method used to calculate the intervals for anomaly detection.\n", + " Use `univariate` to flag anomalies independently for each series in the dataset.\n", + " Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series\n", + " must have the same length.\n", " freq : str\n", " Frequency of the data. By default, the freq will be inferred automatically.\n", " See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases).\n", @@ -1443,6 +1471,9 @@ " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", " return self._distributed_detect_anomalies(\n", " df=df,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1496,6 +1527,9 @@ " 'sizes': np.diff(processed.indptr),\n", " 'X': X,\n", " },\n", + " 'h': h,\n", + " 'detection_size': detection_size,\n", + " 'threshold_method': threshold_method,\n", " 'model': model,\n", " 'freq': standard_freq,\n", " 'clean_ex_first': clean_ex_first,\n", @@ -1518,10 +1552,11 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", + " detection_size=detection_size\n", " )\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", + " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", - " self._maybe_assign_weights(weights=resp['weights_x'], df=df, x_cols=x_cols)\n", " return out\n", "\n", " def _distributed_cross_validation(\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 514323f1..dac2801e 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -100,6 +100,7 @@ _Loss = Literal["default", "mae", "mse", "rmse", "mape", "smape"] _Model = Literal["azureai", "timegpt-1", "timegpt-1-long-horizon"] _Finetune_Depth = Literal[1, 2, 3, 4, 5] +_Threshold_Method = Literal["univariate", "multivariate", "historical"] _date_features_by_freq = { # Daily frequencies @@ -502,6 +503,9 @@ def _maybe_add_intervals( ) -> DFType: if intervals is None: return df + first_key = next(iter(intervals), None) + if first_key is None or intervals[first_key] is None: + return df intervals_df = type(df)( {f"TimeGPT-{k}": intervals[k] for k in sorted(intervals.keys())} ) @@ -521,6 +525,7 @@ def _parse_in_sample_output( id_col: str, time_col: str, target_col: str, + detection_size: Optional[int], ) -> DataFrame: times = df[time_col].to_numpy() targets = df[target_col].to_numpy() @@ -538,6 +543,8 @@ def _parse_in_sample_output( "TimeGPT": in_sample_output["mean"], } ) + if detection_size is not None: + out = out.groupby(id_col).tail(detection_size).reset_index(drop=True) return _maybe_add_intervals(out, in_sample_output["intervals"]) # type: ignore @@ -1228,6 +1235,7 @@ def forecast( id_col=id_col, time_col=time_col, target_col=target_col, + detection_size=None, ) in_sample_df = ufp.drop_columns(in_sample_df, target_col) out = ufp.vertical_concat([in_sample_df, out]) @@ -1260,6 +1268,9 @@ def forecast( def _distributed_detect_anomalies( self, df: DistributedDFType, + h: _PositiveInt, + detection_size: _PositiveInt, + threshold_method: _Threshold_Method, freq: Optional[str], id_col: str, time_col: str, @@ -1290,6 +1301,9 @@ def _distributed_detect_anomalies( schema=schema, params=dict( client=self, + h=h, + detection_size=detection_size, + threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1310,6 +1324,9 @@ def _distributed_detect_anomalies( def detect_anomalies( self, df: AnyDFType, + h: _PositiveInt, + detection_size: _PositiveInt, + threshold_method: _Threshold_Method = "univariate", freq: Optional[str] = None, id_col: str = "unique_id", time_col: str = "ds", @@ -1338,6 +1355,15 @@ def detect_anomalies( - id_col: Column name in `df` that identifies unique time series. Each unique value in this column corresponds to a unique time series. + h : int + Forecast horizon. + detection_size: int + The length of the sequence where anomalies will be detected starting from the end of the dataset. + threshold_method: str (default='univariate') + The method used to calculate the intervals for anomaly detection. + Use `univariate` to flag anomalies independently for each series in the dataset. + Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series + must have the same length. freq : str Frequency of the data. By default, the freq will be inferred automatically. See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). @@ -1381,6 +1407,9 @@ def detect_anomalies( if not isinstance(df, (pd.DataFrame, pl_DataFrame)): return self._distributed_detect_anomalies( df=df, + h=h, + detection_size=detection_size, + threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1434,6 +1463,9 @@ def detect_anomalies( "sizes": np.diff(processed.indptr), "X": X, }, + "h": h, + "detection_size": detection_size, + "threshold_method": threshold_method, "model": model, "freq": standard_freq, "clean_ex_first": clean_ex_first, @@ -1458,10 +1490,11 @@ def detect_anomalies( id_col=id_col, time_col=time_col, target_col=target_col, + detection_size=detection_size, ) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) + out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) - self._maybe_assign_weights(weights=resp["weights_x"], df=df, x_cols=x_cols) return out def _distributed_cross_validation( From 6940e2a2a84a8d3c23b0e777034b39ba5b63ce0b Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 25 Nov 2024 10:28:14 -0500 Subject: [PATCH 02/38] WIP - Add method for online anomaly detection --- nbs/src/nixtla_client.ipynb | 231 +++++++++++++++++++++++++++++++++--- nixtla/_modidx.py | 4 + nixtla/nixtla_client.py | 229 ++++++++++++++++++++++++++++++++--- 3 files changed, 434 insertions(+), 30 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 25a47e95..b9da9b44 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -171,7 +171,7 @@ "_Loss = Literal[\"default\", \"mae\", \"mse\", \"rmse\", \"mape\", \"smape\"]\n", "_Model = Literal[\"azureai\", \"timegpt-1\", \"timegpt-1-long-horizon\"]\n", "_Finetune_Depth = Literal[1, 2, 3, 4, 5]\n", - "_Threshold_Method = Literal[\"univariate\", \"multivariate\", \"historical\"]\n", + "_Threshold_Method = Literal[\"univariate\", \"multivariate\"]\n", "\n", "_date_features_by_freq = {\n", " # Daily frequencies\n", @@ -586,7 +586,7 @@ " id_col: str,\n", " time_col: str,\n", " target_col: str,\n", - " detection_size: Optional[int]\n", + " detection_size: int,\n", ") -> DataFrame:\n", " times = df[time_col].to_numpy()\n", " targets = df[target_col].to_numpy()\n", @@ -1305,7 +1305,7 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " detection_size=None\n", + " detection_size=None,\n", " )\n", " in_sample_df = ufp.drop_columns(in_sample_df, target_col)\n", " out = ufp.vertical_concat([in_sample_df, out])\n", @@ -1332,6 +1332,211 @@ " def _distributed_detect_anomalies(\n", " self,\n", " df: DistributedDFType,\n", + " freq: Optional[str],\n", + " id_col: str,\n", + " time_col: str,\n", + " target_col: str,\n", + " level: Union[int, float],\n", + " clean_ex_first: bool,\n", + " validate_api_key: bool,\n", + " date_features: Union[bool, list[str]],\n", + " date_features_to_one_hot: Union[bool, list[str]],\n", + " model: _Model,\n", + " num_partitions: Optional[int],\n", + " ) -> DistributedDFType:\n", + " import fugue.api as fa\n", + " \n", + " schema, partition_config = _distributed_setup(\n", + " df=df,\n", + " method='detect_anomalies',\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " level=level,\n", + " quantiles=None,\n", + " num_partitions=num_partitions,\n", + " )\n", + " result_df = fa.transform(\n", + " df,\n", + " using=_detect_anomalies_wrapper,\n", + " schema=schema,\n", + " params=dict(\n", + " client=self,\n", + " freq=freq,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " level=level,\n", + " clean_ex_first=clean_ex_first,\n", + " validate_api_key=validate_api_key,\n", + " date_features=date_features,\n", + " date_features_to_one_hot=date_features_to_one_hot,\n", + " model=model,\n", + " num_partitions=None, \n", + " ),\n", + " partition=partition_config,\n", + " as_fugue=True,\n", + " )\n", + " return fa.get_native_as_df(result_df)\n", + "\n", + " def detect_anomalies(\n", + " self,\n", + " df: AnyDFType,\n", + " freq: Optional[str] = None, \n", + " id_col: str = 'unique_id',\n", + " time_col: str = 'ds',\n", + " target_col: str = 'y',\n", + " level: Union[int, float] = 99,\n", + " clean_ex_first: bool = True,\n", + " validate_api_key: bool = False,\n", + " date_features: Union[bool, list[str]] = False,\n", + " date_features_to_one_hot: Union[bool, list[str]] = False,\n", + " model: _Model = 'timegpt-1',\n", + " num_partitions: Optional[_PositiveInt] = None,\n", + " ) -> AnyDFType:\n", + " \"\"\"Detect anomalies in your time series using TimeGPT.\n", + "\n", + " Parameters\n", + " ----------\n", + " df : pandas or polars DataFrame\n", + " The DataFrame on which the function will operate. Expected to contain at least the following columns:\n", + " - time_col:\n", + " Column name in `df` that contains the time indices of the time series. This is typically a datetime\n", + " column with regular intervals, e.g., hourly, daily, monthly data points.\n", + " - target_col:\n", + " Column name in `df` that contains the target variable of the time series, i.e., the variable we \n", + " wish to predict or analyze.\n", + " Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:\n", + " - id_col:\n", + " Column name in `df` that identifies unique time series. Each unique value in this column\n", + " corresponds to a unique time series.\n", + " freq : str\n", + " Frequency of the data. By default, the freq will be inferred automatically.\n", + " See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases).\n", + " id_col : str (default='unique_id')\n", + " Column that identifies each serie.\n", + " time_col : str (default='ds')\n", + " Column that identifies each timestep, its values can be timestamps or integers.\n", + " target_col : str (default='y')\n", + " Column that contains the target.\n", + " level : float (default=99)\n", + " Confidence level between 0 and 100 for detecting the anomalies.\n", + " clean_ex_first : bool (default=True)\n", + " Clean exogenous signal before making forecasts\n", + " using TimeGPT.\n", + " validate_api_key : bool (default=False)\n", + " If True, validates api_key before sending requests.\n", + " date_features : bool or list of str or callable, optional (default=False)\n", + " Features computed from the dates. \n", + " Can be pandas date attributes or functions that will take the dates as input.\n", + " If True automatically adds most used date features for the \n", + " frequency of `df`.\n", + " date_features_to_one_hot : bool or list of str (default=False)\n", + " Apply one-hot encoding to these date features.\n", + " If `date_features=True`, then all date features are\n", + " one-hot encoded by default.\n", + " model : str (default='timegpt-1')\n", + " Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`. \n", + " We recommend using `timegpt-1-long-horizon` for forecasting \n", + " if you want to predict more than one seasonal \n", + " period given the frequency of your data.\n", + " num_partitions : int (default=None)\n", + " Number of partitions to use.\n", + " If None, the number of partitions will be equal\n", + " to the available parallel resources in distributed environments.\n", + " \n", + " Returns\n", + " -------\n", + " pandas, polars, dask or spark DataFrame or ray Dataset.\n", + " DataFrame with anomalies flagged by TimeGPT.\n", + " \"\"\"\n", + " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", + " return self._distributed_detect_anomalies(\n", + " df=df,\n", + " freq=freq,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " level=level,\n", + " clean_ex_first=clean_ex_first,\n", + " validate_api_key=validate_api_key,\n", + " date_features=date_features,\n", + " date_features_to_one_hot=date_features_to_one_hot,\n", + " model=model,\n", + " num_partitions=num_partitions,\n", + " )\n", + " self.__dict__.pop('weights_x', None)\n", + " model = self._maybe_override_model(model)\n", + " logger.info('Validating inputs...')\n", + " df, _, drop_id, freq = self._run_validations(\n", + " df=df,\n", + " X_df=None,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " validate_api_key=validate_api_key,\n", + " model=model,\n", + " freq=freq,\n", + " )\n", + " standard_freq = _standardize_freq(freq)\n", + " model_input_size, model_horizon = self._get_model_params(model, standard_freq)\n", + "\n", + " logger.info('Preprocessing dataframes...')\n", + " processed, _, x_cols, _ = _preprocess(\n", + " df=df,\n", + " X_df=None,\n", + " h=0,\n", + " freq=standard_freq,\n", + " date_features=date_features,\n", + " date_features_to_one_hot=date_features_to_one_hot,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " )\n", + " if processed.data.shape[1] > 1:\n", + " X = processed.data[:, 1:].T\n", + " logger.info(f'Using the following exogenous features: {x_cols}')\n", + " else:\n", + " X = None\n", + "\n", + " logger.info('Calling Anomaly Detector Endpoint...')\n", + " payload = {\n", + " 'series': {\n", + " 'y': processed.data[:, 0],\n", + " 'sizes': np.diff(processed.indptr),\n", + " 'X': X,\n", + " },\n", + " 'model': model,\n", + " 'freq': standard_freq,\n", + " 'clean_ex_first': clean_ex_first,\n", + " 'level': level,\n", + " }\n", + " with httpx.Client(**self._client_kwargs) as client:\n", + " if num_partitions is None:\n", + " resp = self._make_request_with_retries(\n", + " client, 'v2/anomaly_detection', payload\n", + " )\n", + " else:\n", + " payloads = _partition_series(payload, num_partitions, h=0)\n", + " resp = self._make_partitioned_requests(client, 'v2/anomaly_detection', payloads)\n", + "\n", + " # assemble result\n", + " out = _parse_in_sample_output(\n", + " in_sample_output=resp,\n", + " df=df,\n", + " processed=processed,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " detection_size=None,\n", + " )\n", + " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", + " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", + " return out\n", + " \n", + " def _distributed_detect_anomalies_online(\n", + " self,\n", + " df: DistributedDFType,\n", " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", " threshold_method: _Threshold_Method,\n", @@ -1365,9 +1570,6 @@ " schema=schema,\n", " params=dict(\n", " client=self,\n", - " h=h,\n", - " detection_size=detection_size,\n", - " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1385,7 +1587,7 @@ " )\n", " return fa.get_native_as_df(result_df)\n", "\n", - " def detect_anomalies(\n", + " def detect_anomalies_online(\n", " self,\n", " df: AnyDFType,\n", " h: _PositiveInt,\n", @@ -1403,7 +1605,7 @@ " model: _Model = 'timegpt-1',\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", - " \"\"\"Detect anomalies in your time series using TimeGPT.\n", + " \"\"\"Online anomaly detection in your time series using TimeGPT.\n", "\n", " Parameters\n", " ----------\n", @@ -1469,11 +1671,8 @@ " DataFrame with anomalies flagged by TimeGPT.\n", " \"\"\"\n", " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", - " return self._distributed_detect_anomalies(\n", + " return self._distributed_detect_anomalies_online(\n", " df=df,\n", - " h=h,\n", - " detection_size=detection_size,\n", - " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1520,7 +1719,7 @@ " else:\n", " X = None\n", "\n", - " logger.info('Calling Anomaly Detector Endpoint...')\n", + " logger.info('Calling Online Anomaly Detector Endpoint...')\n", " payload = {\n", " 'series': {\n", " 'y': processed.data[:, 0],\n", @@ -1538,11 +1737,11 @@ " with httpx.Client(**self._client_kwargs) as client:\n", " if num_partitions is None:\n", " resp = self._make_request_with_retries(\n", - " client, 'v2/anomaly_detection', payload\n", + " client, 'v2/online_anomaly_detection', payload\n", " )\n", " else:\n", " payloads = _partition_series(payload, num_partitions, h=0)\n", - " resp = self._make_partitioned_requests(client, 'v2/anomaly_detection', payloads)\n", + " resp = self._make_partitioned_requests(client, 'v2/online_anomaly_detection', payloads)\n", "\n", " # assemble result\n", " out = _parse_in_sample_output(\n", @@ -1552,7 +1751,7 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " detection_size=detection_size\n", + " detection_size=detection_size,\n", " )\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", diff --git a/nixtla/_modidx.py b/nixtla/_modidx.py index a12fd69f..174c9618 100644 --- a/nixtla/_modidx.py +++ b/nixtla/_modidx.py @@ -38,6 +38,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies', 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies_online', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_forecast': ( 'src/nixtla_client.html#nixtlaclient._distributed_forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._get_model_params': ( 'src/nixtla_client.html#nixtlaclient._get_model_params', @@ -60,6 +62,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies', 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient.detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies_online', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.forecast': ( 'src/nixtla_client.html#nixtlaclient.forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.plot': ( 'src/nixtla_client.html#nixtlaclient.plot', diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index dac2801e..06cb5487 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -100,7 +100,7 @@ _Loss = Literal["default", "mae", "mse", "rmse", "mape", "smape"] _Model = Literal["azureai", "timegpt-1", "timegpt-1-long-horizon"] _Finetune_Depth = Literal[1, 2, 3, 4, 5] -_Threshold_Method = Literal["univariate", "multivariate", "historical"] +_Threshold_Method = Literal["univariate", "multivariate"] _date_features_by_freq = { # Daily frequencies @@ -525,7 +525,7 @@ def _parse_in_sample_output( id_col: str, time_col: str, target_col: str, - detection_size: Optional[int], + detection_size: int, ) -> DataFrame: times = df[time_col].to_numpy() targets = df[target_col].to_numpy() @@ -1266,6 +1266,213 @@ def forecast( return out def _distributed_detect_anomalies( + self, + df: DistributedDFType, + freq: Optional[str], + id_col: str, + time_col: str, + target_col: str, + level: Union[int, float], + clean_ex_first: bool, + validate_api_key: bool, + date_features: Union[bool, list[str]], + date_features_to_one_hot: Union[bool, list[str]], + model: _Model, + num_partitions: Optional[int], + ) -> DistributedDFType: + import fugue.api as fa + + schema, partition_config = _distributed_setup( + df=df, + method="detect_anomalies", + id_col=id_col, + time_col=time_col, + target_col=target_col, + level=level, + quantiles=None, + num_partitions=num_partitions, + ) + result_df = fa.transform( + df, + using=_detect_anomalies_wrapper, + schema=schema, + params=dict( + client=self, + freq=freq, + id_col=id_col, + time_col=time_col, + target_col=target_col, + level=level, + clean_ex_first=clean_ex_first, + validate_api_key=validate_api_key, + date_features=date_features, + date_features_to_one_hot=date_features_to_one_hot, + model=model, + num_partitions=None, + ), + partition=partition_config, + as_fugue=True, + ) + return fa.get_native_as_df(result_df) + + def detect_anomalies( + self, + df: AnyDFType, + freq: Optional[str] = None, + id_col: str = "unique_id", + time_col: str = "ds", + target_col: str = "y", + level: Union[int, float] = 99, + clean_ex_first: bool = True, + validate_api_key: bool = False, + date_features: Union[bool, list[str]] = False, + date_features_to_one_hot: Union[bool, list[str]] = False, + model: _Model = "timegpt-1", + num_partitions: Optional[_PositiveInt] = None, + ) -> AnyDFType: + """Detect anomalies in your time series using TimeGPT. + + Parameters + ---------- + df : pandas or polars DataFrame + The DataFrame on which the function will operate. Expected to contain at least the following columns: + - time_col: + Column name in `df` that contains the time indices of the time series. This is typically a datetime + column with regular intervals, e.g., hourly, daily, monthly data points. + - target_col: + Column name in `df` that contains the target variable of the time series, i.e., the variable we + wish to predict or analyze. + Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column: + - id_col: + Column name in `df` that identifies unique time series. Each unique value in this column + corresponds to a unique time series. + freq : str + Frequency of the data. By default, the freq will be inferred automatically. + See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). + id_col : str (default='unique_id') + Column that identifies each serie. + time_col : str (default='ds') + Column that identifies each timestep, its values can be timestamps or integers. + target_col : str (default='y') + Column that contains the target. + level : float (default=99) + Confidence level between 0 and 100 for detecting the anomalies. + clean_ex_first : bool (default=True) + Clean exogenous signal before making forecasts + using TimeGPT. + validate_api_key : bool (default=False) + If True, validates api_key before sending requests. + date_features : bool or list of str or callable, optional (default=False) + Features computed from the dates. + Can be pandas date attributes or functions that will take the dates as input. + If True automatically adds most used date features for the + frequency of `df`. + date_features_to_one_hot : bool or list of str (default=False) + Apply one-hot encoding to these date features. + If `date_features=True`, then all date features are + one-hot encoded by default. + model : str (default='timegpt-1') + Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`. + We recommend using `timegpt-1-long-horizon` for forecasting + if you want to predict more than one seasonal + period given the frequency of your data. + num_partitions : int (default=None) + Number of partitions to use. + If None, the number of partitions will be equal + to the available parallel resources in distributed environments. + + Returns + ------- + pandas, polars, dask or spark DataFrame or ray Dataset. + DataFrame with anomalies flagged by TimeGPT. + """ + if not isinstance(df, (pd.DataFrame, pl_DataFrame)): + return self._distributed_detect_anomalies( + df=df, + freq=freq, + id_col=id_col, + time_col=time_col, + target_col=target_col, + level=level, + clean_ex_first=clean_ex_first, + validate_api_key=validate_api_key, + date_features=date_features, + date_features_to_one_hot=date_features_to_one_hot, + model=model, + num_partitions=num_partitions, + ) + self.__dict__.pop("weights_x", None) + model = self._maybe_override_model(model) + logger.info("Validating inputs...") + df, _, drop_id, freq = self._run_validations( + df=df, + X_df=None, + id_col=id_col, + time_col=time_col, + target_col=target_col, + validate_api_key=validate_api_key, + model=model, + freq=freq, + ) + standard_freq = _standardize_freq(freq) + model_input_size, model_horizon = self._get_model_params(model, standard_freq) + + logger.info("Preprocessing dataframes...") + processed, _, x_cols, _ = _preprocess( + df=df, + X_df=None, + h=0, + freq=standard_freq, + date_features=date_features, + date_features_to_one_hot=date_features_to_one_hot, + id_col=id_col, + time_col=time_col, + target_col=target_col, + ) + if processed.data.shape[1] > 1: + X = processed.data[:, 1:].T + logger.info(f"Using the following exogenous features: {x_cols}") + else: + X = None + + logger.info("Calling Anomaly Detector Endpoint...") + payload = { + "series": { + "y": processed.data[:, 0], + "sizes": np.diff(processed.indptr), + "X": X, + }, + "model": model, + "freq": standard_freq, + "clean_ex_first": clean_ex_first, + "level": level, + } + with httpx.Client(**self._client_kwargs) as client: + if num_partitions is None: + resp = self._make_request_with_retries( + client, "v2/anomaly_detection", payload + ) + else: + payloads = _partition_series(payload, num_partitions, h=0) + resp = self._make_partitioned_requests( + client, "v2/anomaly_detection", payloads + ) + + # assemble result + out = _parse_in_sample_output( + in_sample_output=resp, + df=df, + processed=processed, + id_col=id_col, + time_col=time_col, + target_col=target_col, + detection_size=None, + ) + out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) + out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) + return out + + def _distributed_detect_anomalies_online( self, df: DistributedDFType, h: _PositiveInt, @@ -1301,9 +1508,6 @@ def _distributed_detect_anomalies( schema=schema, params=dict( client=self, - h=h, - detection_size=detection_size, - threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1321,7 +1525,7 @@ def _distributed_detect_anomalies( ) return fa.get_native_as_df(result_df) - def detect_anomalies( + def detect_anomalies_online( self, df: AnyDFType, h: _PositiveInt, @@ -1339,7 +1543,7 @@ def detect_anomalies( model: _Model = "timegpt-1", num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: - """Detect anomalies in your time series using TimeGPT. + """Online anomaly detection in your time series using TimeGPT. Parameters ---------- @@ -1405,11 +1609,8 @@ def detect_anomalies( DataFrame with anomalies flagged by TimeGPT. """ if not isinstance(df, (pd.DataFrame, pl_DataFrame)): - return self._distributed_detect_anomalies( + return self._distributed_detect_anomalies_online( df=df, - h=h, - detection_size=detection_size, - threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1456,7 +1657,7 @@ def detect_anomalies( else: X = None - logger.info("Calling Anomaly Detector Endpoint...") + logger.info("Calling Online Anomaly Detector Endpoint...") payload = { "series": { "y": processed.data[:, 0], @@ -1474,12 +1675,12 @@ def detect_anomalies( with httpx.Client(**self._client_kwargs) as client: if num_partitions is None: resp = self._make_request_with_retries( - client, "v2/anomaly_detection", payload + client, "v2/online_anomaly_detection", payload ) else: payloads = _partition_series(payload, num_partitions, h=0) resp = self._make_partitioned_requests( - client, "v2/anomaly_detection", payloads + client, "v2/online_anomaly_detection", payloads ) # assemble result From 7a529584a91061334f158d5876a367edb9c7d04d Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 25 Nov 2024 15:46:43 -0500 Subject: [PATCH 03/38] WIP - New method for new anomaly detection endpoint --- nbs/src/nixtla_client.ipynb | 57 +++++++++++++++++++++++++++++++---- nixtla/_modidx.py | 10 ++++--- nixtla/nixtla_client.py | 60 +++++++++++++++++++++++++++++++++---- 3 files changed, 111 insertions(+), 16 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index b9da9b44..22a88518 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1534,7 +1534,7 @@ " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", " return out\n", " \n", - " def _distributed_detect_anomalies_online(\n", + " def _distributed_detect_anomalies_realtime(\n", " self,\n", " df: DistributedDFType,\n", " h: _PositiveInt,\n", @@ -1566,10 +1566,13 @@ " )\n", " result_df = fa.transform(\n", " df,\n", - " using=_detect_anomalies_wrapper,\n", + " using=_detect_anomalies_realtime_wrapper,\n", " schema=schema,\n", " params=dict(\n", " client=self,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1587,7 +1590,7 @@ " )\n", " return fa.get_native_as_df(result_df)\n", "\n", - " def detect_anomalies_online(\n", + " def detect_anomalies_realtime(\n", " self,\n", " df: AnyDFType,\n", " h: _PositiveInt,\n", @@ -1605,7 +1608,7 @@ " model: _Model = 'timegpt-1',\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", - " \"\"\"Online anomaly detection in your time series using TimeGPT.\n", + " \"\"\"Real-time anomaly detection in your time series using TimeGPT.\n", "\n", " Parameters\n", " ----------\n", @@ -1671,8 +1674,11 @@ " DataFrame with anomalies flagged by TimeGPT.\n", " \"\"\"\n", " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", - " return self._distributed_detect_anomalies_online(\n", + " return self._distributed_detect_anomalies_realtime(\n", " df=df,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", " freq=freq,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -1719,11 +1725,14 @@ " else:\n", " X = None\n", "\n", + " sizes = np.diff(processed.indptr)\n", + " if not np.any((sizes - detection_size) > 5 * detection_size):\n", + " logger.info('Detection size is large. Using the entire series to compute the anomaly threshold...')\n", " logger.info('Calling Online Anomaly Detector Endpoint...')\n", " payload = {\n", " 'series': {\n", " 'y': processed.data[:, 0],\n", - " 'sizes': np.diff(processed.indptr),\n", + " 'sizes': sizes,\n", " 'X': X,\n", " },\n", " 'h': h,\n", @@ -2254,6 +2263,42 @@ " num_partitions=num_partitions,\n", " )\n", "\n", + "def _detect_anomalies_realtime_wrapper(\n", + " df: pd.DataFrame,\n", + " client: NixtlaClient,\n", + " h: _PositiveInt,\n", + " detection_size: _PositiveInt,\n", + " threshold_method: _Threshold_Method,\n", + " freq: Optional[str],\n", + " id_col: str,\n", + " time_col: str,\n", + " target_col: str,\n", + " level: Union[int, float],\n", + " clean_ex_first: bool,\n", + " validate_api_key: bool,\n", + " date_features: Union[bool, list[str]],\n", + " date_features_to_one_hot: Union[bool, list[str]],\n", + " model: _Model,\n", + " num_partitions: Optional[_PositiveInt],\n", + ") -> pd.DataFrame:\n", + " return client.detect_anomalies_realtime(\n", + " df=df,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", + " freq=freq,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " level=level,\n", + " clean_ex_first=clean_ex_first,\n", + " validate_api_key=validate_api_key,\n", + " date_features=date_features,\n", + " date_features_to_one_hot=date_features_to_one_hot,\n", + " model=model,\n", + " num_partitions=num_partitions,\n", + " )\n", + "\n", "def _cross_validation_wrapper(\n", " df: pd.DataFrame,\n", " client: NixtlaClient,\n", diff --git a/nixtla/_modidx.py b/nixtla/_modidx.py index 174c9618..04e1e15e 100644 --- a/nixtla/_modidx.py +++ b/nixtla/_modidx.py @@ -38,8 +38,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies', 'nixtla/nixtla_client.py'), - 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies_online', - 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies_realtime': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies_realtime', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_forecast': ( 'src/nixtla_client.html#nixtlaclient._distributed_forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._get_model_params': ( 'src/nixtla_client.html#nixtlaclient._get_model_params', @@ -62,8 +62,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies', 'nixtla/nixtla_client.py'), - 'nixtla.nixtla_client.NixtlaClient.detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies_online', - 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient.detect_anomalies_realtime': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies_realtime', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.forecast': ( 'src/nixtla_client.html#nixtlaclient.forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.plot': ( 'src/nixtla_client.html#nixtlaclient.plot', @@ -74,6 +74,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._cross_validation_wrapper': ( 'src/nixtla_client.html#_cross_validation_wrapper', 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client._detect_anomalies_realtime_wrapper': ( 'src/nixtla_client.html#_detect_anomalies_realtime_wrapper', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._detect_anomalies_wrapper': ( 'src/nixtla_client.html#_detect_anomalies_wrapper', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._distributed_setup': ( 'src/nixtla_client.html#_distributed_setup', diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 06cb5487..f95f7cec 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1472,7 +1472,7 @@ def detect_anomalies( out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) return out - def _distributed_detect_anomalies_online( + def _distributed_detect_anomalies_realtime( self, df: DistributedDFType, h: _PositiveInt, @@ -1504,10 +1504,13 @@ def _distributed_detect_anomalies_online( ) result_df = fa.transform( df, - using=_detect_anomalies_wrapper, + using=_detect_anomalies_realtime_wrapper, schema=schema, params=dict( client=self, + h=h, + detection_size=detection_size, + threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1525,7 +1528,7 @@ def _distributed_detect_anomalies_online( ) return fa.get_native_as_df(result_df) - def detect_anomalies_online( + def detect_anomalies_realtime( self, df: AnyDFType, h: _PositiveInt, @@ -1543,7 +1546,7 @@ def detect_anomalies_online( model: _Model = "timegpt-1", num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: - """Online anomaly detection in your time series using TimeGPT. + """Real-time anomaly detection in your time series using TimeGPT. Parameters ---------- @@ -1609,8 +1612,11 @@ def detect_anomalies_online( DataFrame with anomalies flagged by TimeGPT. """ if not isinstance(df, (pd.DataFrame, pl_DataFrame)): - return self._distributed_detect_anomalies_online( + return self._distributed_detect_anomalies_realtime( df=df, + h=h, + detection_size=detection_size, + threshold_method=threshold_method, freq=freq, id_col=id_col, time_col=time_col, @@ -1657,11 +1663,16 @@ def detect_anomalies_online( else: X = None + sizes = np.diff(processed.indptr) + if not np.any((sizes - detection_size) > 5 * detection_size): + logger.info( + "Detection size is large. Using the entire series to compute the anomaly threshold..." + ) logger.info("Calling Online Anomaly Detector Endpoint...") payload = { "series": { "y": processed.data[:, 0], - "sizes": np.diff(processed.indptr), + "sizes": sizes, "X": X, }, "h": h, @@ -2193,6 +2204,43 @@ def _detect_anomalies_wrapper( ) +def _detect_anomalies_realtime_wrapper( + df: pd.DataFrame, + client: NixtlaClient, + h: _PositiveInt, + detection_size: _PositiveInt, + threshold_method: _Threshold_Method, + freq: Optional[str], + id_col: str, + time_col: str, + target_col: str, + level: Union[int, float], + clean_ex_first: bool, + validate_api_key: bool, + date_features: Union[bool, list[str]], + date_features_to_one_hot: Union[bool, list[str]], + model: _Model, + num_partitions: Optional[_PositiveInt], +) -> pd.DataFrame: + return client.detect_anomalies_realtime( + df=df, + h=h, + detection_size=detection_size, + threshold_method=threshold_method, + freq=freq, + id_col=id_col, + time_col=time_col, + target_col=target_col, + level=level, + clean_ex_first=clean_ex_first, + validate_api_key=validate_api_key, + date_features=date_features, + date_features_to_one_hot=date_features_to_one_hot, + model=model, + num_partitions=num_partitions, + ) + + def _cross_validation_wrapper( df: pd.DataFrame, client: NixtlaClient, From 8da44951c3fd525242be22cde3f05197234e8d75 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 26 Nov 2024 11:08:46 -0500 Subject: [PATCH 04/38] WIP - Process output of anomaly v2 to account step size --- nbs/src/nixtla_client.ipynb | 64 +++++++++++++++++++++++++---------- nixtla/nixtla_client.py | 66 ++++++++++++++++++++++++++++--------- 2 files changed, 96 insertions(+), 34 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 22a88518..55872787 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -586,7 +586,6 @@ " id_col: str,\n", " time_col: str,\n", " target_col: str,\n", - " detection_size: int,\n", ") -> DataFrame:\n", " times = df[time_col].to_numpy()\n", " targets = df[target_col].to_numpy()\n", @@ -608,10 +607,6 @@ " 'TimeGPT': in_sample_output['mean'],\n", " }\n", " )\n", - " if detection_size is not None:\n", - " out = (out.groupby(id_col)\n", - " .tail(detection_size)\n", - " .reset_index(drop=True))\n", " return _maybe_add_intervals(out, in_sample_output['intervals']) # type: ignore\n", "\n", "def _restrict_input_samples(level, input_size, model_horizon, h) -> int:\n", @@ -1305,7 +1300,6 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " detection_size=None,\n", " )\n", " in_sample_df = ufp.drop_columns(in_sample_df, target_col)\n", " out = ufp.vertical_concat([in_sample_df, out])\n", @@ -1528,7 +1522,6 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " detection_size=None,\n", " )\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", @@ -1546,6 +1539,10 @@ " target_col: str,\n", " level: Union[int, float],\n", " clean_ex_first: bool,\n", + " step_size: Optional[_PositiveInt],\n", + " finetune_steps: _NonNegativeInt,\n", + " finetune_depth: _Finetune_Depth,\n", + " finetune_loss: _Loss,\n", " validate_api_key: bool,\n", " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", @@ -1579,6 +1576,10 @@ " target_col=target_col,\n", " level=level,\n", " clean_ex_first=clean_ex_first,\n", + " step_size=step_size,\n", + " finetune_steps=finetune_steps,\n", + " finetune_loss=finetune_loss,\n", + " finetune_depth=finetune_depth,\n", " validate_api_key=validate_api_key,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", @@ -1602,6 +1603,10 @@ " target_col: str = 'y',\n", " level: Union[int, float] = 99,\n", " clean_ex_first: bool = True,\n", + " step_size: Optional[_PositiveInt] = None,\n", + " finetune_steps: _NonNegativeInt = 0,\n", + " finetune_depth: _Finetune_Depth = 1,\n", + " finetune_loss: _Loss = 'default',\n", " validate_api_key: bool = False,\n", " date_features: Union[bool, list[str]] = False,\n", " date_features_to_one_hot: Union[bool, list[str]] = False,\n", @@ -1685,6 +1690,10 @@ " target_col=target_col,\n", " level=level,\n", " clean_ex_first=clean_ex_first,\n", + " step_size=step_size,\n", + " finetune_steps=finetune_steps,\n", + " finetune_depth=finetune_depth,\n", + " finetune_loss=finetune_loss,\n", " validate_api_key=validate_api_key,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", @@ -1719,12 +1728,23 @@ " time_col=time_col,\n", " target_col=target_col,\n", " )\n", + " if isinstance(df, pd.DataFrame):\n", + " # in pandas<2.2 to_numpy can lead to an object array if\n", + " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", + " # we thus use the dtype's type as the target dtype\n", + " target_dtype = df.dtypes[target_col].type\n", + " targets = df[target_col].to_numpy(dtype=target_dtype)\n", + " else:\n", + " targets = df[target_col].to_numpy()\n", + " times = df[time_col].to_numpy()\n", + " if processed.sort_idxs is not None:\n", + " targets = targets[processed.sort_idxs]\n", + " times = times[processed.sort_idxs]\n", " if processed.data.shape[1] > 1:\n", " X = processed.data[:, 1:].T\n", " logger.info(f'Using the following exogenous features: {x_cols}')\n", " else:\n", " X = None\n", - "\n", " sizes = np.diff(processed.indptr)\n", " if not np.any((sizes - detection_size) > 5 * detection_size):\n", " logger.info('Detection size is large. Using the entire series to compute the anomaly threshold...')\n", @@ -1742,6 +1762,10 @@ " 'freq': standard_freq,\n", " 'clean_ex_first': clean_ex_first,\n", " 'level': level,\n", + " 'step_size': step_size,\n", + " 'finetune_steps': finetune_steps,\n", + " 'finetune_loss': finetune_loss,\n", + " 'finetune_depth': finetune_depth\n", " }\n", " with httpx.Client(**self._client_kwargs) as client:\n", " if num_partitions is None:\n", @@ -1753,19 +1777,23 @@ " resp = self._make_partitioned_requests(client, 'v2/online_anomaly_detection', payloads)\n", "\n", " # assemble result\n", - " out = _parse_in_sample_output(\n", - " in_sample_output=resp,\n", - " df=df,\n", - " processed=processed,\n", - " id_col=id_col,\n", - " time_col=time_col,\n", - " target_col=target_col,\n", - " detection_size=detection_size,\n", + " idxs = np.array(resp['idxs'], dtype=np.int64)\n", + " sizes = np.array(resp['sizes'], dtype=np.int64)\n", + " out = type(df)(\n", + " {\n", + " id_col: ufp.repeat(processed.uids, sizes),\n", + " time_col: times[idxs],\n", + " target_col: targets[idxs],\n", + " }\n", " )\n", + " out = ufp.assign_columns(out, 'TimeGPT', resp['mean'])\n", + " out_aggregated = out.groupby(['unique_id', 'ds'])['TimeGPT'].median().reset_index()\n", + " out = (out_aggregated.groupby('unique_id')\n", + " .tail(detection_size)\n", + " .reset_index(drop=True))\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", - " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", - " return out\n", + " return _maybe_add_intervals(out, resp['intervals'])\n", "\n", " def _distributed_cross_validation(\n", " self,\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index f95f7cec..8b4529a2 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -525,7 +525,6 @@ def _parse_in_sample_output( id_col: str, time_col: str, target_col: str, - detection_size: int, ) -> DataFrame: times = df[time_col].to_numpy() targets = df[target_col].to_numpy() @@ -543,8 +542,6 @@ def _parse_in_sample_output( "TimeGPT": in_sample_output["mean"], } ) - if detection_size is not None: - out = out.groupby(id_col).tail(detection_size).reset_index(drop=True) return _maybe_add_intervals(out, in_sample_output["intervals"]) # type: ignore @@ -1235,7 +1232,6 @@ def forecast( id_col=id_col, time_col=time_col, target_col=target_col, - detection_size=None, ) in_sample_df = ufp.drop_columns(in_sample_df, target_col) out = ufp.vertical_concat([in_sample_df, out]) @@ -1466,7 +1462,6 @@ def detect_anomalies( id_col=id_col, time_col=time_col, target_col=target_col, - detection_size=None, ) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) @@ -1484,6 +1479,10 @@ def _distributed_detect_anomalies_realtime( target_col: str, level: Union[int, float], clean_ex_first: bool, + step_size: Optional[_PositiveInt], + finetune_steps: _NonNegativeInt, + finetune_depth: _Finetune_Depth, + finetune_loss: _Loss, validate_api_key: bool, date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], @@ -1517,6 +1516,10 @@ def _distributed_detect_anomalies_realtime( target_col=target_col, level=level, clean_ex_first=clean_ex_first, + step_size=step_size, + finetune_steps=finetune_steps, + finetune_loss=finetune_loss, + finetune_depth=finetune_depth, validate_api_key=validate_api_key, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, @@ -1540,6 +1543,10 @@ def detect_anomalies_realtime( target_col: str = "y", level: Union[int, float] = 99, clean_ex_first: bool = True, + step_size: Optional[_PositiveInt] = None, + finetune_steps: _NonNegativeInt = 0, + finetune_depth: _Finetune_Depth = 1, + finetune_loss: _Loss = "default", validate_api_key: bool = False, date_features: Union[bool, list[str]] = False, date_features_to_one_hot: Union[bool, list[str]] = False, @@ -1623,6 +1630,10 @@ def detect_anomalies_realtime( target_col=target_col, level=level, clean_ex_first=clean_ex_first, + step_size=step_size, + finetune_steps=finetune_steps, + finetune_depth=finetune_depth, + finetune_loss=finetune_loss, validate_api_key=validate_api_key, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, @@ -1657,12 +1668,23 @@ def detect_anomalies_realtime( time_col=time_col, target_col=target_col, ) + if isinstance(df, pd.DataFrame): + # in pandas<2.2 to_numpy can lead to an object array if + # the type is a pandas nullable type, e.g. pd.Float64Dtype + # we thus use the dtype's type as the target dtype + target_dtype = df.dtypes[target_col].type + targets = df[target_col].to_numpy(dtype=target_dtype) + else: + targets = df[target_col].to_numpy() + times = df[time_col].to_numpy() + if processed.sort_idxs is not None: + targets = targets[processed.sort_idxs] + times = times[processed.sort_idxs] if processed.data.shape[1] > 1: X = processed.data[:, 1:].T logger.info(f"Using the following exogenous features: {x_cols}") else: X = None - sizes = np.diff(processed.indptr) if not np.any((sizes - detection_size) > 5 * detection_size): logger.info( @@ -1682,6 +1704,10 @@ def detect_anomalies_realtime( "freq": standard_freq, "clean_ex_first": clean_ex_first, "level": level, + "step_size": step_size, + "finetune_steps": finetune_steps, + "finetune_loss": finetune_loss, + "finetune_depth": finetune_depth, } with httpx.Client(**self._client_kwargs) as client: if num_partitions is None: @@ -1695,19 +1721,27 @@ def detect_anomalies_realtime( ) # assemble result - out = _parse_in_sample_output( - in_sample_output=resp, - df=df, - processed=processed, - id_col=id_col, - time_col=time_col, - target_col=target_col, - detection_size=detection_size, + idxs = np.array(resp["idxs"], dtype=np.int64) + sizes = np.array(resp["sizes"], dtype=np.int64) + out = type(df)( + { + id_col: ufp.repeat(processed.uids, sizes), + time_col: times[idxs], + target_col: targets[idxs], + } + ) + out = ufp.assign_columns(out, "TimeGPT", resp["mean"]) + out_aggregated = ( + out.groupby(["unique_id", "ds"])["TimeGPT"].median().reset_index() + ) + out = ( + out_aggregated.groupby("unique_id") + .tail(detection_size) + .reset_index(drop=True) ) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) - out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) - return out + return _maybe_add_intervals(out, resp["intervals"]) def _distributed_cross_validation( self, From 38c993de30b198f9c7e76113034c1df6820ec846 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 26 Nov 2024 14:45:22 -0500 Subject: [PATCH 05/38] WIP - Distributed real time anomaly detection --- nbs/src/nixtla_client.ipynb | 41 ++++++++++++++++++++++++++++++++++--- nixtla/nixtla_client.py | 15 +++++++++++++- 2 files changed, 52 insertions(+), 4 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 55872787..872ff604 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -153,7 +153,18 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#| hide\n", "load_dotenv(override=True)" @@ -798,6 +809,8 @@ " for res, offset in zip(results, offsets)\n", " ]\n", " )\n", + " if 'anomaly_score' in first_res:\n", + " resp['anomaly_score'] = np.hstack([res['anomaly_score'] for res in results])\n", " if first_res[\"intervals\"] is None:\n", " resp[\"intervals\"] = None\n", " else:\n", @@ -1553,7 +1566,7 @@ " \n", " schema, partition_config = _distributed_setup(\n", " df=df,\n", - " method='detect_anomalies',\n", + " method='detect_anomalies_realtime',\n", " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", @@ -2303,6 +2316,10 @@ " target_col: str,\n", " level: Union[int, float],\n", " clean_ex_first: bool,\n", + " step_size: _PositiveInt,\n", + " finetune_steps: _NonNegativeInt,\n", + " finetune_depth: _Finetune_Depth,\n", + " finetune_loss: _Loss,\n", " validate_api_key: bool,\n", " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", @@ -2320,6 +2337,10 @@ " target_col=target_col,\n", " level=level,\n", " clean_ex_first=clean_ex_first,\n", + " step_size=step_size,\n", + " finetune_steps=finetune_steps,\n", + " finetune_depth=finetune_depth,\n", + " finetune_loss=finetune_loss,\n", " validate_api_key=validate_api_key,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", @@ -2389,6 +2410,9 @@ " schema.append('TimeGPT:double')\n", " if method == 'detect_anomalies':\n", " schema.append('anomaly:bool')\n", + " if method == 'detect_anomalies_realtime':\n", + " schema.append('anomaly:bool')\n", + " schema.append('anomaly_score:double')\n", " elif method == 'cross_validation':\n", " schema.append(('cutoff', schema[time_col].type))\n", " if level is not None and quantiles is not None:\n", @@ -2478,7 +2502,18 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "#| hide\n", "nixtla_client.validate_api_key()" diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 8b4529a2..a6a636fc 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -729,6 +729,8 @@ def _make_partitioned_requests( for res, offset in zip(results, offsets) ] ) + if "anomaly_score" in first_res: + resp["anomaly_score"] = np.hstack([res["anomaly_score"] for res in results]) if first_res["intervals"] is None: resp["intervals"] = None else: @@ -1493,7 +1495,7 @@ def _distributed_detect_anomalies_realtime( schema, partition_config = _distributed_setup( df=df, - method="detect_anomalies", + method="detect_anomalies_realtime", id_col=id_col, time_col=time_col, target_col=target_col, @@ -2250,6 +2252,10 @@ def _detect_anomalies_realtime_wrapper( target_col: str, level: Union[int, float], clean_ex_first: bool, + step_size: _PositiveInt, + finetune_steps: _NonNegativeInt, + finetune_depth: _Finetune_Depth, + finetune_loss: _Loss, validate_api_key: bool, date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], @@ -2267,6 +2273,10 @@ def _detect_anomalies_realtime_wrapper( target_col=target_col, level=level, clean_ex_first=clean_ex_first, + step_size=step_size, + finetune_steps=finetune_steps, + finetune_depth=finetune_depth, + finetune_loss=finetune_loss, validate_api_key=validate_api_key, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, @@ -2338,6 +2348,9 @@ def _get_schema( schema.append("TimeGPT:double") if method == "detect_anomalies": schema.append("anomaly:bool") + if method == "detect_anomalies_realtime": + schema.append("anomaly:bool") + schema.append("anomaly_score:double") elif method == "cross_validation": schema.append(("cutoff", schema[time_col].type)) if level is not None and quantiles is not None: From c509c58d53c7516c8a68cab658239ebd0adee64d Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 26 Nov 2024 16:11:46 -0500 Subject: [PATCH 06/38] WIP - Write tests --- nbs/src/nixtla_client.ipynb | 162 +++++++++++++++++++++++++++++++++++- nixtla/nixtla_client.py | 4 +- 2 files changed, 164 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 872ff604..64e145bb 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1800,7 +1800,9 @@ " }\n", " )\n", " out = ufp.assign_columns(out, 'TimeGPT', resp['mean'])\n", - " out_aggregated = out.groupby(['unique_id', 'ds'])['TimeGPT'].median().reset_index()\n", + " out_aggregated = (out.groupby(['unique_id', 'ds'])\n", + " .agg({'TimeGPT': 'median', 'y': 'first'})\n", + " .reset_index())\n", " out = (out_aggregated.groupby('unique_id')\n", " .tail(detection_size)\n", " .reset_index(drop=True))\n", @@ -3430,6 +3432,77 @@ "test_eq(nixtla_client.weights_x['features'].tolist(), ['year', 'month'])" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:__main__:Validating inputs...\n", + "INFO:__main__:Preprocessing dataframes...\n", + "INFO:__main__:Calling Online Anomaly Detector Endpoint...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:__main__:Validating inputs...\n", + "INFO:__main__:Preprocessing dataframes...\n", + "INFO:__main__:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "#| hide\n", + "# Test real-time anomaly detection\n", + "detection_size = 5\n", + "n_series = 2\n", + "n_rows = 320\n", + "\n", + "ds = pd.date_range(start='2023-01-01', periods=n_rows, freq='W')\n", + "x = np.arange(n_rows)\n", + "y = 10 * np.sin(0.1 * x) + 12\n", + "y[315] = 30 # Set anomaly\n", + "\n", + "df = pd.DataFrame({\n", + " 'unique_id': np.repeat(np.arange(1, n_series + 1), n_rows),\n", + " 'ds': np.tile(ds, n_series),\n", + " 'y': np.tile(y, n_series)\n", + "})\n", + "\n", + "def assert_first_rows_anomaly(df: pd.DataFrame) -> None:\n", + " first_rows = df.groupby('unique_id')['anomaly'].first()\n", + " assert first_rows.all(), \"Anomaly not correctly flagged\"\n", + "\n", + "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + " df, \n", + " h=20, \n", + " detection_size=detection_size, \n", + " threshold_method=\"univariate\", \n", + " freq='W-SUN', \n", + " level=99,\n", + ")\n", + "assert len(anomaly_df) == n_series * detection_size\n", + "assert len(anomaly_df.columns) == 8 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score, hi, lo]\n", + "assert_first_rows_anomaly(anomaly_df) # Anomaly is the first entry of each unique_id\n", + "\n", + "multi_anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + " df, \n", + " h=20, \n", + " detection_size=detection_size, \n", + " threshold_method=\"multivariate\", \n", + " freq='W-SUN', \n", + " level=99,\n", + ")\n", + "\n", + "assert len(multi_anomaly_df.columns) == 6 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score]\n", + "assert_first_rows_anomaly(multi_anomaly_df)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -3738,6 +3811,43 @@ " ]\n", " test_eq(cols, exp_cols)\n", "\n", + "def test_realtime_anomalies(\n", + " df: fugue.AnyDataFrame, \n", + " id_col: str = 'unique_id',\n", + " time_col: str = 'ds',\n", + " target_col: str = 'y',\n", + " h=2,\n", + " detection_size=5,\n", + " threshold_method='univariate',\n", + " level=99,\n", + " **anomalies_kwargs\n", + "):\n", + " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", + " df=df, \n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " **anomalies_kwargs,\n", + " )\n", + " anomalies_df = fa.as_pandas(anomalies_df)\n", + " test_eq(fa.as_pandas(df)[id_col].unique(), anomalies_df[id_col].unique())\n", + " cols = anomalies_df.columns.to_list()\n", + " level = anomalies_kwargs.get('level', 99)\n", + " exp_cols = [\n", + " id_col,\n", + " time_col,\n", + " target_col,\n", + " 'TimeGPT',\n", + " 'anomaly',\n", + " 'anomaly_score',\n", + " f'TimeGPT-lo-{level}',\n", + " f'TimeGPT-hi-{level}',\n", + " ]\n", + " test_eq(cols, exp_cols)\n", + "\n", "def test_anomalies_same_results_num_partitions(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", @@ -3769,6 +3879,49 @@ " atol=ATOL,\n", " )\n", "\n", + "def test_anomalies_realtime_same_results_num_partitions(\n", + " df: fugue.AnyDataFrame, \n", + " id_col: str = 'unique_id',\n", + " time_col: str = 'ds',\n", + " target_col: str = 'y',\n", + " h=2,\n", + " detection_size=5,\n", + " threshold_method='univariate',\n", + " level=99,\n", + " **anomalies_kwargs,\n", + "):\n", + " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", + " df=df,\n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", + " level=level,\n", + " num_partitions=1,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " **anomalies_kwargs\n", + " )\n", + " anomalies_df = fa.as_pandas(anomalies_df)\n", + " anomalies_df_2 = nixtla_client.detect_anomalies_realtime(\n", + " df=df, \n", + " h=h,\n", + " detection_size=detection_size,\n", + " threshold_method=threshold_method,\n", + " level=level,\n", + " num_partitions=2,\n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " **anomalies_kwargs\n", + " )\n", + " anomalies_df_2 = fa.as_pandas(anomalies_df_2)\n", + " pd.testing.assert_frame_equal(\n", + " anomalies_df.sort_values([id_col, time_col]).reset_index(drop=True),\n", + " anomalies_df_2.sort_values([id_col, time_col]).reset_index(drop=True),\n", + " atol=ATOL,\n", + " )\n", + "\n", "def test_anomalies_diff_results_diff_models(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", @@ -3809,6 +3962,10 @@ " test_anomalies(df, level=90, num_partitions=1)\n", " test_anomalies_same_results_num_partitions(df)\n", "\n", + "def test_anomalies_realtime_dataframe(df: fugue.AnyDataFrame):\n", + " test_realtime_anomalies(df, num_partitions=1)\n", + " test_anomalies_realtime_same_results_num_partitions(df)\n", + "\n", "def test_anomalies_dataframe_diff_cols(\n", " df: fugue.AnyDataFrame,\n", " id_col: str = 'id_col',\n", @@ -3897,6 +4054,7 @@ "test_forecast_dataframe(spark_df)\n", "test_forecast_dataframe_diff_cols(spark_diff_cols_df)\n", "test_anomalies_dataframe(spark_df)\n", + "test_anomalies_realtime_dataframe(spark_df)\n", "test_anomalies_dataframe_diff_cols(spark_diff_cols_df)\n", "# test exogenous variables\n", "spark_df_x = spark.createDataFrame(df_x).repartition(2)\n", @@ -3937,6 +4095,7 @@ "test_forecast_dataframe(dask_df)\n", "test_forecast_dataframe_diff_cols(dask_diff_cols_df)\n", "test_anomalies_dataframe(dask_df)\n", + "test_anomalies_realtime_dataframe(dask_df)\n", "test_anomalies_dataframe_diff_cols(dask_diff_cols_df)\n", "\n", "# test exogenous variables\n", @@ -3983,6 +4142,7 @@ "test_forecast_dataframe(ray_df)\n", "test_forecast_dataframe_diff_cols(ray_diff_cols_df)\n", "test_anomalies_dataframe(ray_df)\n", + "test_anomalies_realtime_dataframe(ray_df)\n", "test_anomalies_dataframe_diff_cols(ray_diff_cols_df)\n", "\n", "# test exogenous variables\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index a6a636fc..fc4d7f28 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1734,7 +1734,9 @@ def detect_anomalies_realtime( ) out = ufp.assign_columns(out, "TimeGPT", resp["mean"]) out_aggregated = ( - out.groupby(["unique_id", "ds"])["TimeGPT"].median().reset_index() + out.groupby(["unique_id", "ds"]) + .agg({"TimeGPT": "median", "y": "first"}) + .reset_index() ) out = ( out_aggregated.groupby("unique_id") From e3fa7ce503e12bed3aea06c41021c6a714c64f8e Mon Sep 17 00:00:00 2001 From: yibeihu Date: Tue, 26 Nov 2024 23:28:18 -0800 Subject: [PATCH 07/38] change column names --- nbs/src/nixtla_client.ipynb | 54 +++++-------------------------------- nixtla/nixtla_client.py | 12 +++------ 2 files changed, 9 insertions(+), 57 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index bc61d157..7152a935 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -154,18 +154,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "#| hide\n", "load_dotenv(override=True)" @@ -1815,10 +1804,9 @@ " }\n", " )\n", " out = ufp.assign_columns(out, 'TimeGPT', resp['mean'])\n", - " out_aggregated = (out.groupby(['unique_id', 'ds'])\n", - " .agg({'TimeGPT': 'median', 'y': 'first'})\n", - " .reset_index())\n", - " out = (out_aggregated.groupby('unique_id')\n", + " out_aggregated = (out.groupby([id_col, time_col], as_index=False)\n", + " .agg({'TimeGPT': 'median', target_col: 'first'}))\n", + " out = (out_aggregated.groupby(id_col)\n", " .tail(detection_size)\n", " .reset_index(drop=True))\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", @@ -2549,18 +2537,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "True" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "#| hide\n", "nixtla_client.validate_api_key()" @@ -3544,26 +3521,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:__main__:Validating inputs...\n", - "INFO:__main__:Preprocessing dataframes...\n", - "INFO:__main__:Calling Online Anomaly Detector Endpoint...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:__main__:Validating inputs...\n", - "INFO:__main__:Preprocessing dataframes...\n", - "INFO:__main__:Calling Online Anomaly Detector Endpoint...\n" - ] - } - ], + "outputs": [], "source": [ "#| hide\n", "# Test real-time anomaly detection\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 0ae246c0..fa486a21 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1746,16 +1746,10 @@ def detect_anomalies_realtime( } ) out = ufp.assign_columns(out, "TimeGPT", resp["mean"]) - out_aggregated = ( - out.groupby(["unique_id", "ds"]) - .agg({"TimeGPT": "median", "y": "first"}) - .reset_index() - ) - out = ( - out_aggregated.groupby("unique_id") - .tail(detection_size) - .reset_index(drop=True) + out_aggregated = out.groupby([id_col, time_col], as_index=False).agg( + {"TimeGPT": "median", target_col: "first"} ) + out = out_aggregated.groupby(id_col).tail(detection_size).reset_index(drop=True) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) return _maybe_add_intervals(out, resp["intervals"]) From 350ef805cfefbed0c49f0fed20ec4fa6c95f1adb Mon Sep 17 00:00:00 2001 From: yibeihu Date: Wed, 27 Nov 2024 23:50:28 -0800 Subject: [PATCH 08/38] include accumulated anomaly score column in output --- nbs/src/nixtla_client.ipynb | 2 ++ nixtla/nixtla_client.py | 4 ++++ 2 files changed, 6 insertions(+) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 7152a935..f0312050 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1811,6 +1811,8 @@ " .reset_index(drop=True))\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", + " if resp['accumulated_anomaly_score']is not None:\n", + " out = ufp.assign_columns(out, 'accumulated_anomaly_score', resp['accumulated_anomaly_score'])\n", " return _maybe_add_intervals(out, resp['intervals'])\n", "\n", " def _distributed_cross_validation(\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index fa486a21..298086b8 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1752,6 +1752,10 @@ def detect_anomalies_realtime( out = out_aggregated.groupby(id_col).tail(detection_size).reset_index(drop=True) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) + if resp["accumulated_anomaly_score"] is not None: + out = ufp.assign_columns( + out, "accumulated_anomaly_score", resp["accumulated_anomaly_score"] + ) return _maybe_add_intervals(out, resp["intervals"]) def _distributed_cross_validation( From 2de28b8835764e0e0594f4e69404ca78ea516e9b Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 28 Nov 2024 13:13:53 -0500 Subject: [PATCH 09/38] WIP - Accumulated z-scores with num_partitions --- nbs/src/nixtla_client.ipynb | 5 ++++- nixtla/nixtla_client.py | 10 +++++++++- 2 files changed, 13 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index f0312050..dc1309c5 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -812,6 +812,8 @@ " )\n", " if 'anomaly_score' in first_res:\n", " resp['anomaly_score'] = np.hstack([res['anomaly_score'] for res in results])\n", + " if 'accumulated_anomaly_score' in first_res and first_res['accumulated_anomaly_score'] is not None:\n", + " resp['accumulated_anomaly_score'] = np.hstack([res['accumulated_anomaly_score'] for res in results])\n", " if first_res[\"intervals\"] is None:\n", " resp[\"intervals\"] = None\n", " else:\n", @@ -1811,7 +1813,7 @@ " .reset_index(drop=True))\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", - " if resp['accumulated_anomaly_score']is not None:\n", + " if threshold_method == 'multivariate':\n", " out = ufp.assign_columns(out, 'accumulated_anomaly_score', resp['accumulated_anomaly_score'])\n", " return _maybe_add_intervals(out, resp['intervals'])\n", "\n", @@ -2450,6 +2452,7 @@ " if method == 'detect_anomalies_realtime':\n", " schema.append('anomaly:bool')\n", " schema.append('anomaly_score:double')\n", + " schema.append('accumulated_anomaly_score:double')\n", " elif method == 'cross_validation':\n", " schema.append(('cutoff', schema[time_col].type))\n", " if level is not None and quantiles is not None:\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 298086b8..8331e2cb 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -741,6 +741,13 @@ def _make_partitioned_requests( ) if "anomaly_score" in first_res: resp["anomaly_score"] = np.hstack([res["anomaly_score"] for res in results]) + if ( + "accumulated_anomaly_score" in first_res + and first_res["accumulated_anomaly_score"] is not None + ): + resp["accumulated_anomaly_score"] = np.hstack( + [res["accumulated_anomaly_score"] for res in results] + ) if first_res["intervals"] is None: resp["intervals"] = None else: @@ -1752,7 +1759,7 @@ def detect_anomalies_realtime( out = out_aggregated.groupby(id_col).tail(detection_size).reset_index(drop=True) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) - if resp["accumulated_anomaly_score"] is not None: + if threshold_method == "multivariate": out = ufp.assign_columns( out, "accumulated_anomaly_score", resp["accumulated_anomaly_score"] ) @@ -2394,6 +2401,7 @@ def _get_schema( if method == "detect_anomalies_realtime": schema.append("anomaly:bool") schema.append("anomaly_score:double") + schema.append("accumulated_anomaly_score:double") elif method == "cross_validation": schema.append(("cutoff", schema[time_col].type)) if level is not None and quantiles is not None: From 9b3c2aca59a918bc74184a89b3bd7dc0339671b2 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 28 Nov 2024 13:31:04 -0500 Subject: [PATCH 10/38] raise error when num_partitions > 1 for multivariate detection --- action_files/models_performance/main.py | 2 +- nbs/src/nixtla_client.ipynb | 11 +++++++---- nixtla/nixtla_client.py | 18 ++++++++++-------- 3 files changed, 18 insertions(+), 13 deletions(-) diff --git a/action_files/models_performance/main.py b/action_files/models_performance/main.py index 22a631a5..0d20d995 100644 --- a/action_files/models_performance/main.py +++ b/action_files/models_performance/main.py @@ -184,7 +184,7 @@ def evaluate_benchmark_performace(self) -> Tuple[pd.DataFrame, pd.DataFrame]: h=self.h, n_windows=self.n_windows, step_size=self.h, - ).reset_index() + ) total_time = time() - init_time cv_model_df = cv_model_df.rename( columns={value: key for key, value in renamer.items()} diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index dc1309c5..fc6ea7dd 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -812,8 +812,6 @@ " )\n", " if 'anomaly_score' in first_res:\n", " resp['anomaly_score'] = np.hstack([res['anomaly_score'] for res in results])\n", - " if 'accumulated_anomaly_score' in first_res and first_res['accumulated_anomaly_score'] is not None:\n", - " resp['accumulated_anomaly_score'] = np.hstack([res['accumulated_anomaly_score'] for res in results])\n", " if first_res[\"intervals\"] is None:\n", " resp[\"intervals\"] = None\n", " else:\n", @@ -1719,6 +1717,12 @@ " model=model,\n", " num_partitions=num_partitions,\n", " )\n", + " if threshold_method == \"multivariate\" and num_partitions is not None and num_partitions > 1:\n", + " raise ValueError(\n", + " \"Cannot use more than 1 partition for multivariate anomaly detection. \"\n", + " \"Either set threshold_method to univariate \"\n", + " \"or set num_partitions to 1 or None.\"\n", + " )\n", " self.__dict__.pop('weights_x', None)\n", " model = self._maybe_override_model(model)\n", " logger.info('Validating inputs...')\n", @@ -1733,7 +1737,6 @@ " freq=freq,\n", " )\n", " standard_freq = _standardize_freq(freq)\n", - " model_input_size, model_horizon = self._get_model_params(model, standard_freq)\n", "\n", " logger.info('Preprocessing dataframes...')\n", " processed, _, x_cols, _ = _preprocess(\n", @@ -3570,7 +3573,7 @@ " level=99,\n", ")\n", "\n", - "assert len(multi_anomaly_df.columns) == 6 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score]\n", + "assert len(multi_anomaly_df.columns) == 7 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score, accumulated_anomaly_score]\n", "assert_first_rows_anomaly(multi_anomaly_df)" ] }, diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 8331e2cb..37db7119 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -741,13 +741,6 @@ def _make_partitioned_requests( ) if "anomaly_score" in first_res: resp["anomaly_score"] = np.hstack([res["anomaly_score"] for res in results]) - if ( - "accumulated_anomaly_score" in first_res - and first_res["accumulated_anomaly_score"] is not None - ): - resp["accumulated_anomaly_score"] = np.hstack( - [res["accumulated_anomaly_score"] for res in results] - ) if first_res["intervals"] is None: resp["intervals"] = None else: @@ -1662,6 +1655,16 @@ def detect_anomalies_realtime( model=model, num_partitions=num_partitions, ) + if ( + threshold_method == "multivariate" + and num_partitions is not None + and num_partitions > 1 + ): + raise ValueError( + "Cannot use more than 1 partition for multivariate anomaly detection. " + "Either set threshold_method to univariate " + "or set num_partitions to 1 or None." + ) self.__dict__.pop("weights_x", None) model = self._maybe_override_model(model) logger.info("Validating inputs...") @@ -1676,7 +1679,6 @@ def detect_anomalies_realtime( freq=freq, ) standard_freq = _standardize_freq(freq) - model_input_size, model_horizon = self._get_model_params(model, standard_freq) logger.info("Preprocessing dataframes...") processed, _, x_cols, _ = _preprocess( From 12af589df7077c994cf8fd8f9875db43c6791b9d Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 28 Nov 2024 13:52:30 -0500 Subject: [PATCH 11/38] Fix capabilities nb as weight_x is not accessible for anomaly detection --- .../02_anomaly_exogenous.ipynb | 25 ++++++------------- 1 file changed, 8 insertions(+), 17 deletions(-) diff --git a/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb b/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb index 7c0ef5a0..4e556f76 100644 --- a/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb +++ b/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb @@ -48,7 +48,7 @@ "source": [ "# Add exogenous variables\n", "\n", - "To detect anomalies with exogenous variables, load a dataset with the exogenous features as columns. Use the same `detect_anomalies` method and plot the weights of each feature using `weight_x.plot()`." + "To detect anomalies with exogenous variables, load a dataset with the exogenous features as columns and use the same `detect_anomalies` method." ] }, { @@ -141,31 +141,22 @@ "output_type": "stream", "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", "INFO:nixtla.nixtla_client:Inferred freq: H\n", - "INFO:nixtla.nixtla_client:Calling Anomaly Detector Endpoint...\n", - "INFO:nixtla.nixtla_client:Using the following exogenous variables: Exogenous1, Exogenous2, day_0, day_1, day_2, day_3, day_4, day_5, day_6\n" + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Using the following exogenous features: ['Exogenous1', 'Exogenous2', 'day_0', 'day_1', 'day_2', 'day_3', 'day_4', 'day_5', 'day_6']\n", + "INFO:nixtla.nixtla_client:Calling Anomaly Detector Endpoint...\n" ] }, { "data": 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"text/plain": [ - "" + "
" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -177,11 +168,11 @@ "anomalies_df = nixtla_client.detect_anomalies(\n", " df=df,\n", " time_col='ds',\n", - " target_col='y'\n", + " target_col='y',\n", ")\n", "\n", "# Plot weight of exgeonous features\n", - "nixtla_client.weights_x.plot.barh(x='features', y='weights')" + "nixtla_client.plot(df, anomalies_df)" ] }, { From aa022d28f72b4bb4dab09f76c547bb92bb586802 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 28 Nov 2024 14:25:07 -0500 Subject: [PATCH 12/38] Remove the use of weights_x for anomaly detection in capabilities --- .../02_anomaly_exogenous.ipynb | 2 +- .../03_anomaly_detection_date_features.ipynb | 17 ++++------------- 2 files changed, 5 insertions(+), 14 deletions(-) diff --git a/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb b/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb index 4e556f76..347c0a28 100644 --- a/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb +++ b/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb @@ -171,7 +171,7 @@ " target_col='y',\n", ")\n", "\n", - "# Plot weight of exgeonous features\n", + "# Plot anomalies\n", "nixtla_client.plot(df, anomalies_df)" ] }, diff --git a/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb b/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb index 70d76352..9d0940bd 100644 --- a/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb +++ b/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb @@ -137,23 +137,14 @@ }, { "data": { + "image/png": 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"text/plain": [ - "" + "
" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ @@ -170,8 +161,8 @@ " level=99.99,\n", ")\n", "\n", - "# Plot weights of date features\n", - "nixtla_client.weights_x.plot.barh(x='features', y='weights')" + "# Plot anomalies\n", + "nixtla_client.plot(df, anomalies_df_x)" ] }, { From 68556024d5a7b698864634b4f4f6407f01abc389 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 28 Nov 2024 14:29:25 -0500 Subject: [PATCH 13/38] Remove weights_x for anomaly detection in tutorials --- nbs/docs/tutorials/20_anomaly_detection.ipynb | 74 +++++++++---------- 1 file changed, 36 insertions(+), 38 deletions(-) diff --git a/nbs/docs/tutorials/20_anomaly_detection.ipynb b/nbs/docs/tutorials/20_anomaly_detection.ipynb index 8cfa6667..acdf9713 100644 --- a/nbs/docs/tutorials/20_anomaly_detection.ipynb +++ b/nbs/docs/tutorials/20_anomaly_detection.ipynb @@ -232,7 +232,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -306,9 +306,9 @@ " 0\n", " 2008-01-10\n", " 8.281724\n", - " 8.224194\n", - " 9.503593\n", - " 6.944794\n", + " 8.224187\n", + " 9.503586\n", + " 6.944788\n", " False\n", " \n", " \n", @@ -316,9 +316,9 @@ " 0\n", " 2008-01-11\n", " 8.292799\n", - " 8.151521\n", - " 9.430921\n", - " 6.872121\n", + " 8.151533\n", + " 9.430932\n", + " 6.872135\n", " False\n", " \n", " \n", @@ -326,9 +326,9 @@ " 0\n", " 2008-01-12\n", " 8.199189\n", - " 8.127249\n", - " 9.406649\n", - " 6.847849\n", + " 8.127243\n", + " 9.406642\n", + " 6.847845\n", " False\n", " \n", " \n", @@ -336,9 +336,9 @@ " 0\n", " 2008-01-13\n", " 9.996522\n", - " 8.917255\n", - " 10.196655\n", - " 7.637855\n", + " 8.917259\n", + " 10.196658\n", + " 7.637861\n", " False\n", " \n", " \n", @@ -346,9 +346,9 @@ " 0\n", " 2008-01-14\n", " 10.127071\n", - " 9.002296\n", - " 10.281695\n", - " 7.722896\n", + " 9.002326\n", + " 10.281725\n", + " 7.722928\n", " False\n", " \n", " \n", @@ -357,11 +357,11 @@ ], "text/plain": [ " unique_id ds y TimeGPT TimeGPT-hi-99 TimeGPT-lo-99 \\\n", - "0 0 2008-01-10 8.281724 8.224194 9.503593 6.944794 \n", - "1 0 2008-01-11 8.292799 8.151521 9.430921 6.872121 \n", - "2 0 2008-01-12 8.199189 8.127249 9.406649 6.847849 \n", - "3 0 2008-01-13 9.996522 8.917255 10.196655 7.637855 \n", - "4 0 2008-01-14 10.127071 9.002296 10.281695 7.722896 \n", + "0 0 2008-01-10 8.281724 8.224187 9.503586 6.944788 \n", + "1 0 2008-01-11 8.292799 8.151533 9.430932 6.872135 \n", + "2 0 2008-01-12 8.199189 8.127243 9.406642 6.847845 \n", + "3 0 2008-01-13 9.996522 8.917259 10.196658 7.637861 \n", + "4 0 2008-01-14 10.127071 9.002326 10.281725 7.722928 \n", "\n", " anomaly \n", "0 False \n", @@ -400,7 +400,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "As you can see, 0 is assigned to \"normal\" values, as they fall inside the confidence interval. A label of 1 is then assigned to abnormal points.\n", + "As you can see, `False` is assigned to \"normal\" values, as they fall inside the confidence interval. A label of `True` is then assigned to abnormal points.\n", "\n", "We can also plot the anomalies using `NixtlaClient`." ] @@ -412,7 +412,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -432,7 +432,7 @@ "source": [ "## Anomaly detection with exogenous features\n", "\n", - "Previously, we performed anomaly detection without using any exogenous features. Now, it is possible to create features specifically for this scnenario to inform the model in its task of anomaly detection.\n", + "Previously, we performed anomaly detection without using any exogenous features. Now, it is possible to create features specifically for this scenario to inform the model in its task of anomaly detection.\n", "\n", "Here, we create date features that can be used by the model." ] @@ -473,7 +473,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Then, we can plot the weights of each feature to understand its impact on anomaly detection." + "Then, we can plot the detected anomalies where the model now used additional information from exogenous features." ] }, { @@ -483,27 +483,18 @@ "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "" + "
" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" } ], "source": [ - "nixtla_client.weights_x.plot.barh(x='features', y='weights')" + "nixtla_client.plot(df, anomalies_df_x)" ] }, { @@ -549,7 +540,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -562,6 +553,13 @@ "source": [ "nixtla_client.plot(df, anomalies_df)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { From 6bafcfe14dc6a32e4e46d8c3824869ad304f41d2 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 3 Dec 2024 14:38:22 -0500 Subject: [PATCH 14/38] WIP - Support standard freq and add refit to anomaly detection --- nbs/src/nixtla_client.ipynb | 29 ++++++++++++++++++++++++----- nixtla/nixtla_client.py | 12 +++++++++--- 2 files changed, 33 insertions(+), 8 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index c4e34d03..2679bd0e 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -665,7 +665,20 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'Optional' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m#| export\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNixtlaClient\u001b[39;00m:\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 6\u001b[0m api_key: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 11\u001b[0m max_wait_time: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 12\u001b[0m ):\n\u001b[1;32m 13\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124;03m Client to interact with the Nixtla API.\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;124;03m catch these errors, use max_wait_time >> 60. \u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n", + "Cell \u001b[0;32mIn[1], line 6\u001b[0m, in \u001b[0;36mNixtlaClient\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNixtlaClient\u001b[39;00m:\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m----> 6\u001b[0m api_key: \u001b[43mOptional\u001b[49m[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 7\u001b[0m base_url: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 8\u001b[0m timeout: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 9\u001b[0m max_retries: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m,\n\u001b[1;32m 10\u001b[0m retry_interval: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m,\n\u001b[1;32m 11\u001b[0m max_wait_time: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 12\u001b[0m ):\n\u001b[1;32m 13\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124;03m Client to interact with the Nixtla API.\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;124;03m catch these errors, use max_wait_time >> 60. \u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m api_key \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "\u001b[0;31mNameError\u001b[0m: name 'Optional' is not defined" + ] + } + ], "source": [ "#| export\n", "class NixtlaClient:\n", @@ -1591,6 +1604,7 @@ " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", " model: _Model,\n", + " refit: bool,\n", " num_partitions: Optional[int],\n", " ) -> DistributedDFType:\n", " import fugue.api as fa\n", @@ -1628,6 +1642,7 @@ " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", + " refit=refit,\n", " num_partitions=None, \n", " ),\n", " partition=partition_config,\n", @@ -1655,6 +1670,7 @@ " date_features: Union[bool, list[str]] = False,\n", " date_features_to_one_hot: Union[bool, list[str]] = False,\n", " model: _Model = 'timegpt-1',\n", + " refit: bool = False,\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", " \"\"\"Real-time anomaly detection in your time series using TimeGPT.\n", @@ -1742,6 +1758,7 @@ " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", + " refit=refit,\n", " num_partitions=num_partitions,\n", " )\n", " if threshold_method == \"multivariate\" and num_partitions is not None and num_partitions > 1:\n", @@ -1763,20 +1780,19 @@ " model=model,\n", " freq=freq,\n", " )\n", - " standard_freq = _standardize_freq(freq)\n", - "\n", " logger.info('Preprocessing dataframes...')\n", " processed, _, x_cols, _ = _preprocess(\n", " df=df,\n", " X_df=None,\n", " h=0,\n", - " freq=standard_freq,\n", + " freq=freq,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", " )\n", + " standard_freq = _standardize_freq(freq, processed)\n", " if isinstance(df, pd.DataFrame):\n", " # in pandas<2.2 to_numpy can lead to an object array if\n", " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", @@ -1814,7 +1830,8 @@ " 'step_size': step_size,\n", " 'finetune_steps': finetune_steps,\n", " 'finetune_loss': finetune_loss,\n", - " 'finetune_depth': finetune_depth\n", + " 'finetune_depth': finetune_depth,\n", + " 'refit': refit,\n", " }\n", " with httpx.Client(**self._client_kwargs) as client:\n", " if num_partitions is None:\n", @@ -2391,6 +2408,7 @@ " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", " model: _Model,\n", + " refit: bool,\n", " num_partitions: Optional[_PositiveInt],\n", ") -> pd.DataFrame:\n", " return client.detect_anomalies_realtime(\n", @@ -2412,6 +2430,7 @@ " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", + " refit=refit,\n", " num_partitions=num_partitions,\n", " )\n", "\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index b78ef2b5..3d75e513 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1530,6 +1530,7 @@ def _distributed_detect_anomalies_realtime( date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], model: _Model, + refit: bool, num_partitions: Optional[int], ) -> DistributedDFType: import fugue.api as fa @@ -1567,6 +1568,7 @@ def _distributed_detect_anomalies_realtime( date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, + refit=refit, num_partitions=None, ), partition=partition_config, @@ -1594,6 +1596,7 @@ def detect_anomalies_realtime( date_features: Union[bool, list[str]] = False, date_features_to_one_hot: Union[bool, list[str]] = False, model: _Model = "timegpt-1", + refit: bool = False, num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: """Real-time anomaly detection in your time series using TimeGPT. @@ -1681,6 +1684,7 @@ def detect_anomalies_realtime( date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, + refit=refit, num_partitions=num_partitions, ) if ( @@ -1706,20 +1710,19 @@ def detect_anomalies_realtime( model=model, freq=freq, ) - standard_freq = _standardize_freq(freq) - logger.info("Preprocessing dataframes...") processed, _, x_cols, _ = _preprocess( df=df, X_df=None, h=0, - freq=standard_freq, + freq=freq, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, id_col=id_col, time_col=time_col, target_col=target_col, ) + standard_freq = _standardize_freq(freq, processed) if isinstance(df, pd.DataFrame): # in pandas<2.2 to_numpy can lead to an object array if # the type is a pandas nullable type, e.g. pd.Float64Dtype @@ -1760,6 +1763,7 @@ def detect_anomalies_realtime( "finetune_steps": finetune_steps, "finetune_loss": finetune_loss, "finetune_depth": finetune_depth, + "refit": refit, } with httpx.Client(**self._client_kwargs) as client: if num_partitions is None: @@ -2338,6 +2342,7 @@ def _detect_anomalies_realtime_wrapper( date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], model: _Model, + refit: bool, num_partitions: Optional[_PositiveInt], ) -> pd.DataFrame: return client.detect_anomalies_realtime( @@ -2359,6 +2364,7 @@ def _detect_anomalies_realtime_wrapper( date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, + refit=refit, num_partitions=num_partitions, ) From 44bcd37907dcaf977dcb4ae841db3f617f51439c Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 5 Dec 2024 15:04:13 -0500 Subject: [PATCH 15/38] Use FreqType and tests --- nbs/src/nixtla_client.ipynb | 144 ++++++++++++++++++------------------ nixtla/nixtla_client.py | 6 +- 2 files changed, 75 insertions(+), 75 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 2679bd0e..cb5890f9 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1590,7 +1590,7 @@ " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", " threshold_method: _Threshold_Method,\n", - " freq: Optional[str],\n", + " freq: Optional[_Freq],\n", " id_col: str,\n", " time_col: str,\n", " target_col: str,\n", @@ -1656,7 +1656,7 @@ " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", " threshold_method: _Threshold_Method = 'univariate',\n", - " freq: Optional[str] = None, \n", + " freq: Optional[_Freq] = None, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", " target_col: str = 'y',\n", @@ -2394,7 +2394,7 @@ " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", " threshold_method: _Threshold_Method,\n", - " freq: Optional[str],\n", + " freq: Optional[_Freq],\n", " id_col: str,\n", " time_col: str,\n", " target_col: str,\n", @@ -3641,29 +3641,40 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n", + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], "source": [ "#| hide\n", "# Test real-time anomaly detection\n", "detection_size = 5\n", "n_series = 2\n", - "n_rows = 320\n", + "size = 100\n", "\n", - "ds = pd.date_range(start='2023-01-01', periods=n_rows, freq='W')\n", - "x = np.arange(n_rows)\n", + "ds = pd.date_range(start='2023-01-01', periods=size, freq='W')\n", + "x = np.arange(size)\n", "y = 10 * np.sin(0.1 * x) + 12\n", - "y[315] = 30 # Set anomaly\n", + "y = np.tile(y, n_series)\n", + "y[size - 5] = 30\n", + "y[2*size - 1] = 30\n", "\n", "df = pd.DataFrame({\n", - " 'unique_id': np.repeat(np.arange(1, n_series + 1), n_rows),\n", + " 'unique_id': np.repeat(np.arange(1, n_series + 1), size),\n", " 'ds': np.tile(ds, n_series),\n", - " 'y': np.tile(y, n_series)\n", + " 'y': y\n", "})\n", "\n", - "def assert_first_rows_anomaly(df: pd.DataFrame) -> None:\n", - " first_rows = df.groupby('unique_id')['anomaly'].first()\n", - " assert first_rows.all(), \"Anomaly not correctly flagged\"\n", - "\n", "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", " df, \n", " h=20, \n", @@ -3674,7 +3685,8 @@ ")\n", "assert len(anomaly_df) == n_series * detection_size\n", "assert len(anomaly_df.columns) == 8 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score, hi, lo]\n", - "assert_first_rows_anomaly(anomaly_df) # Anomaly is the first entry of each unique_id\n", + "assert anomaly_df['anomaly'].sum() == 2 \n", + "assert anomaly_df['anomaly'].iloc[0] and anomaly_df['anomaly'].iloc[-1]\n", "\n", "multi_anomaly_df = nixtla_client.detect_anomalies_realtime(\n", " df, \n", @@ -3685,8 +3697,13 @@ " level=99,\n", ")\n", "\n", + "assert len(multi_anomaly_df) == n_series * detection_size\n", "assert len(multi_anomaly_df.columns) == 7 # [unique_id, ds, TimeGPT, y, anomaly, anomaly_score, accumulated_anomaly_score]\n", - "assert_first_rows_anomaly(multi_anomaly_df)" + "assert multi_anomaly_df['anomaly'].sum() == 4\n", + "assert (multi_anomaly_df['anomaly'].iloc[0] and \n", + " multi_anomaly_df['anomaly'].iloc[4] and\n", + " multi_anomaly_df['anomaly'].iloc[5] and\n", + " multi_anomaly_df['anomaly'].iloc[9])\n" ] }, { @@ -3997,43 +4014,6 @@ " ]\n", " test_eq(cols, exp_cols)\n", "\n", - "def test_realtime_anomalies(\n", - " df: fugue.AnyDataFrame, \n", - " id_col: str = 'unique_id',\n", - " time_col: str = 'ds',\n", - " target_col: str = 'y',\n", - " h=2,\n", - " detection_size=5,\n", - " threshold_method='univariate',\n", - " level=99,\n", - " **anomalies_kwargs\n", - "):\n", - " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", - " df=df, \n", - " h=h,\n", - " detection_size=detection_size,\n", - " threshold_method=threshold_method,\n", - " id_col=id_col,\n", - " time_col=time_col,\n", - " target_col=target_col,\n", - " **anomalies_kwargs,\n", - " )\n", - " anomalies_df = fa.as_pandas(anomalies_df)\n", - " test_eq(fa.as_pandas(df)[id_col].unique(), anomalies_df[id_col].unique())\n", - " cols = anomalies_df.columns.to_list()\n", - " level = anomalies_kwargs.get('level', 99)\n", - " exp_cols = [\n", - " id_col,\n", - " time_col,\n", - " target_col,\n", - " 'TimeGPT',\n", - " 'anomaly',\n", - " 'anomaly_score',\n", - " f'TimeGPT-lo-{level}',\n", - " f'TimeGPT-hi-{level}',\n", - " ]\n", - " test_eq(cols, exp_cols)\n", - "\n", "def test_anomalies_same_results_num_partitions(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", @@ -4065,41 +4045,60 @@ " atol=ATOL,\n", " )\n", "\n", - "def test_anomalies_realtime_same_results_num_partitions(\n", + "def test_realtime_anomalies(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", " target_col: str = 'y',\n", - " h=2,\n", - " detection_size=5,\n", - " threshold_method='univariate',\n", " level=99,\n", - " **anomalies_kwargs,\n", + " **reatlime_anomalies_kwargs\n", + "):\n", + " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", + " df=df, \n", + " id_col=id_col,\n", + " time_col=time_col,\n", + " target_col=target_col,\n", + " **reatlime_anomalies_kwargs,\n", + " )\n", + " anomalies_df = fa.as_pandas(anomalies_df)\n", + " test_eq(fa.as_pandas(df)[id_col].unique(), anomalies_df[id_col].unique())\n", + " cols = anomalies_df.columns.to_list()\n", + " level = anomalies_kwargs.get('level', 99)\n", + " exp_cols = [\n", + " id_col,\n", + " time_col,\n", + " target_col,\n", + " 'TimeGPT',\n", + " 'anomaly',\n", + " 'anomaly_score',\n", + " f'TimeGPT-lo-{level}',\n", + " f'TimeGPT-hi-{level}',\n", + " ]\n", + " test_eq(cols, exp_cols)\n", + "\n", + "def test_anomalies_realtime_same_results_num_partitions(\n", + " df: fugue.AnyDataFrame, \n", + " id_col: str = 'unique_id',\n", + " time_col: str = 'ds',\n", + " target_col: str = 'y',\n", + " **reatlime_anomalies_kwargs\n", "):\n", " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", " df=df,\n", - " h=h,\n", - " detection_size=detection_size,\n", - " threshold_method=threshold_method,\n", - " level=level,\n", - " num_partitions=1,\n", " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " **anomalies_kwargs\n", + " num_partitions=1,\n", + " **reatlime_anomalies_kwargs\n", " )\n", " anomalies_df = fa.as_pandas(anomalies_df)\n", " anomalies_df_2 = nixtla_client.detect_anomalies_realtime(\n", " df=df, \n", - " h=h,\n", - " detection_size=detection_size,\n", - " threshold_method=threshold_method,\n", - " level=level,\n", - " num_partitions=2,\n", " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " **anomalies_kwargs\n", + " num_partitions=2,\n", + " **reatlime_anomalies_kwargs\n", " )\n", " anomalies_df_2 = fa.as_pandas(anomalies_df_2)\n", " pd.testing.assert_frame_equal(\n", @@ -4149,8 +4148,8 @@ " test_anomalies_same_results_num_partitions(df)\n", "\n", "def test_anomalies_realtime_dataframe(df: fugue.AnyDataFrame):\n", - " test_realtime_anomalies(df, num_partitions=1)\n", - " test_anomalies_realtime_same_results_num_partitions(df)\n", + " test_realtime_anomalies(df, h=20, detection_size=5, threshold_method='univariate', level=99, num_partitions=1)\n", + " test_anomalies_realtime_same_results_num_partitions(df, h=20, detection_size=5, threshold_method='univariate', level=99)\n", "\n", "def test_anomalies_dataframe_diff_cols(\n", " df: fugue.AnyDataFrame,\n", @@ -4275,6 +4274,7 @@ "dask_df = dd.from_pandas(series, npartitions=2)\n", "dask_diff_cols_df = dd.from_pandas(series_diff_cols, npartitions=2)\n", "\n", + "\n", "test_quantiles(dask_df, id_col=\"unique_id\", time_col=\"ds\")\n", "\n", "\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 3d75e513..1f024017 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1516,7 +1516,7 @@ def _distributed_detect_anomalies_realtime( h: _PositiveInt, detection_size: _PositiveInt, threshold_method: _Threshold_Method, - freq: Optional[str], + freq: Optional[_Freq], id_col: str, time_col: str, target_col: str, @@ -1582,7 +1582,7 @@ def detect_anomalies_realtime( h: _PositiveInt, detection_size: _PositiveInt, threshold_method: _Threshold_Method = "univariate", - freq: Optional[str] = None, + freq: Optional[_Freq] = None, id_col: str = "unique_id", time_col: str = "ds", target_col: str = "y", @@ -2328,7 +2328,7 @@ def _detect_anomalies_realtime_wrapper( h: _PositiveInt, detection_size: _PositiveInt, threshold_method: _Threshold_Method, - freq: Optional[str], + freq: Optional[_Freq], id_col: str, time_col: str, target_col: str, From 25c24e389b2608971bba7c8dfda526a0ae3b4e25 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 5 Dec 2024 15:52:37 -0500 Subject: [PATCH 16/38] remove accumulated score from schema --- nbs/src/nixtla_client.ipynb | 2 +- nixtla/nixtla_client.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index cb5890f9..ec07402d 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -2501,7 +2501,7 @@ " if method == 'detect_anomalies_realtime':\n", " schema.append('anomaly:bool')\n", " schema.append('anomaly_score:double')\n", - " schema.append('accumulated_anomaly_score:double')\n", + " # schema.append('accumulated_anomaly_score:double')\n", " elif method == 'cross_validation':\n", " schema.append(('cutoff', schema[time_col].type))\n", " if level is not None and quantiles is not None:\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 1f024017..a40906bc 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -2437,7 +2437,7 @@ def _get_schema( if method == "detect_anomalies_realtime": schema.append("anomaly:bool") schema.append("anomaly_score:double") - schema.append("accumulated_anomaly_score:double") + # schema.append('accumulated_anomaly_score:double') elif method == "cross_validation": schema.append(("cutoff", schema[time_col].type)) if level is not None and quantiles is not None: From dfe7644763409fc1e66fea1fe61d92f47e0ca689 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Thu, 5 Dec 2024 16:41:36 -0500 Subject: [PATCH 17/38] Fix linting --- nbs/src/nixtla_client.ipynb | 31 ++----------------------------- nixtla/nixtla_client.py | 1 - 2 files changed, 2 insertions(+), 30 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index ec07402d..b120c7e2 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -665,20 +665,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'Optional' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m#| export\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNixtlaClient\u001b[39;00m:\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 6\u001b[0m api_key: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 11\u001b[0m max_wait_time: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 12\u001b[0m ):\n\u001b[1;32m 13\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124;03m Client to interact with the Nixtla API.\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;124;03m catch these errors, use max_wait_time >> 60. \u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n", - "Cell \u001b[0;32mIn[1], line 6\u001b[0m, in \u001b[0;36mNixtlaClient\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01mNixtlaClient\u001b[39;00m:\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m----> 6\u001b[0m api_key: \u001b[43mOptional\u001b[49m[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 7\u001b[0m base_url: Optional[\u001b[38;5;28mstr\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 8\u001b[0m timeout: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 9\u001b[0m max_retries: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m,\n\u001b[1;32m 10\u001b[0m retry_interval: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m,\n\u001b[1;32m 11\u001b[0m max_wait_time: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m6\u001b[39m \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m60\u001b[39m,\n\u001b[1;32m 12\u001b[0m ):\n\u001b[1;32m 13\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;124;03m Client to interact with the Nixtla API.\u001b[39;00m\n\u001b[1;32m 15\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;124;03m catch these errors, use max_wait_time >> 60. \u001b[39;00m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m api_key \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "\u001b[0;31mNameError\u001b[0m: name 'Optional' is not defined" - ] - } - ], + "outputs": [], "source": [ "#| export\n", "class NixtlaClient:\n", @@ -2501,7 +2488,6 @@ " if method == 'detect_anomalies_realtime':\n", " schema.append('anomaly:bool')\n", " schema.append('anomaly_score:double')\n", - " # schema.append('accumulated_anomaly_score:double')\n", " elif method == 'cross_validation':\n", " schema.append(('cutoff', schema[time_col].type))\n", " if level is not None and quantiles is not None:\n", @@ -3641,20 +3627,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n", - "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" - ] - } - ], + "outputs": [], "source": [ "#| hide\n", "# Test real-time anomaly detection\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index a40906bc..3f3e4e5b 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -2437,7 +2437,6 @@ def _get_schema( if method == "detect_anomalies_realtime": schema.append("anomaly:bool") schema.append("anomaly_score:double") - # schema.append('accumulated_anomaly_score:double') elif method == "cross_validation": schema.append(("cutoff", schema[time_col].type)) if level is not None and quantiles is not None: From e0fcce888e0ae252aacabf9dc83ed102a23be6cf Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 9 Dec 2024 13:26:43 -0500 Subject: [PATCH 18/38] remove unecessary groupby when assembling results --- nbs/src/nixtla_client.ipynb | 5 ----- nixtla/nixtla_client.py | 4 ---- 2 files changed, 9 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index b120c7e2..8f157c1d 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1840,11 +1840,6 @@ " }\n", " )\n", " out = ufp.assign_columns(out, 'TimeGPT', resp['mean'])\n", - " out_aggregated = (out.groupby([id_col, time_col], as_index=False)\n", - " .agg({'TimeGPT': 'median', target_col: 'first'}))\n", - " out = (out_aggregated.groupby(id_col)\n", - " .tail(detection_size)\n", - " .reset_index(drop=True))\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = ufp.assign_columns(out, 'anomaly_score', resp['anomaly_score'])\n", " if threshold_method == 'multivariate':\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 3f3e4e5b..1e51d7d6 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1787,10 +1787,6 @@ def detect_anomalies_realtime( } ) out = ufp.assign_columns(out, "TimeGPT", resp["mean"]) - out_aggregated = out.groupby([id_col, time_col], as_index=False).agg( - {"TimeGPT": "median", target_col: "first"} - ) - out = out_aggregated.groupby(id_col).tail(detection_size).reset_index(drop=True) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = ufp.assign_columns(out, "anomaly_score", resp["anomaly_score"]) if threshold_method == "multivariate": From 555c7d4d40d90c83ae488943b9e7d8de9417d885 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Tue, 10 Dec 2024 09:01:23 +0800 Subject: [PATCH 19/38] add tutorials for new endpoint --- nbs/assets/machine-1-1.csv | 2777 +++++++++++++++++ .../00_anomaly_detection.ipynb | 49 - .../00_historical_anomaly_detection.ipynb | 43 + .../01_quickstart.ipynb | 4 +- .../02_anomaly_exogenous.ipynb | 0 .../03_anomaly_detection_date_features.ipynb | 2 +- .../04_confidence_levels.ipynb | 2 +- .../00_realtime_anomaly_detection.ipynb | 31 + .../01_quickstart.ipynb | 372 +++ .../02_improve_detection_accuracy.ipynb | 456 +++ ...te_vs_multivariate_anomaly_detection.ipynb | 331 ++ nbs/mint.json | 18 +- nbs/nbdev.yml | 2 +- 13 files changed, 4028 insertions(+), 59 deletions(-) create mode 100644 nbs/assets/machine-1-1.csv delete mode 100644 nbs/docs/capabilities/anomaly-detection/00_anomaly_detection.ipynb create mode 100644 nbs/docs/capabilities/historical-anomaly-detection/00_historical_anomaly_detection.ipynb rename nbs/docs/capabilities/{anomaly-detection => historical-anomaly-detection}/01_quickstart.ipynb (99%) rename nbs/docs/capabilities/{anomaly-detection => historical-anomaly-detection}/02_anomaly_exogenous.ipynb (100%) rename nbs/docs/capabilities/{anomaly-detection => historical-anomaly-detection}/03_anomaly_detection_date_features.ipynb (99%) rename nbs/docs/capabilities/{anomaly-detection => historical-anomaly-detection}/04_confidence_levels.ipynb (99%) create mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb create mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb create mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb create mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb diff --git a/nbs/assets/machine-1-1.csv b/nbs/assets/machine-1-1.csv new file mode 100644 index 00000000..0f69f7b8 --- /dev/null +++ b/nbs/assets/machine-1-1.csv @@ -0,0 +1,2777 @@ +unique_id,ts,y +machine-1-1_y_29,2020-01-31 00:00:00,0.014327 +machine-1-1_y_29,2020-01-31 00:01:00,0.014327 +machine-1-1_y_29,2020-01-31 00:02:00,0.014327 +machine-1-1_y_29,2020-01-31 00:03:00,0.014327 +machine-1-1_y_29,2020-01-31 00:04:00,0.014327 +machine-1-1_y_29,2020-01-31 00:05:00,0.014327 +machine-1-1_y_29,2020-01-31 00:06:00,0.014327 +machine-1-1_y_29,2020-01-31 00:07:00,0.014327 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--- a/nbs/docs/capabilities/anomaly-detection/00_anomaly_detection.ipynb +++ /dev/null @@ -1,49 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "6de758ee-a0d2-4b3f-acff-eed419dd17c5", - "metadata": {}, - "source": [ - "# Anomaly detection" - ] - }, - { - "cell_type": "markdown", - "id": "5d267032-535b-4b7b-b7d3-d2db8f673af6", - "metadata": {}, - "source": [ - "This section provides various recipes for anomaly detection using TimeGPT.\n", - "\n", - "Anomaly detection identifies data points outside normal behavior, helping to spot fraudulent activity, security breaches, or significant outliers.\n", - "\n", - "Anomaly detection involves making predictions and generating a 99% confidence interval. If an observed point falls outside that interval, it is an anomaly.\n", - "\n", - "This section covers:\n", - "\n", - "* [Simple anomaly detection](https://docs.nixtla.io/docs/capabilities-anomaly-detection-quickstart)\n", - "\n", - "* [Anomaly detection with exogenous features](https://docs.nixtla.io/docs/capabilities-anomaly-detection-add_exogenous_variables)\n", - "\n", - "* [Anomaly detection with date features](https://docs.nixtla.io/docs/capabilities-anomaly-detection-add_date_features)\n", - "\n", - "* [Modifying the confidence intervals](https://docs.nixtla.io/docs/capabilities-anomaly-detection-add_confidence_levels)" - ] - }, - { - "cell_type": "markdown", - "id": "af39eb26", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "python3", - "language": "python", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/nbs/docs/capabilities/historical-anomaly-detection/00_historical_anomaly_detection.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/00_historical_anomaly_detection.ipynb new file mode 100644 index 00000000..b719cbf4 --- /dev/null +++ b/nbs/docs/capabilities/historical-anomaly-detection/00_historical_anomaly_detection.ipynb @@ -0,0 +1,43 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6de758ee-a0d2-4b3f-acff-eed419dd17c5", + "metadata": {}, + "source": [ + "# Historical anomaly detection" + ] + }, + { + "cell_type": "markdown", + "id": "5d267032-535b-4b7b-b7d3-d2db8f673af6", + "metadata": {}, + "source": [ + "This section provides various recipes for performing historical anomaly detection using TimeGPT.\n", + "\n", + "Historical anomaly detection identifies data points that deviate from the expected behavior over a given historical time series, helping to spot fraudulent activity, security breaches, or significant outliers.\n", + "\n", + "The process involves generating predictions and constructing a 99% confidence interval. Data points falling outside this interval are considered anomalies.\n", + "\n", + "This section covers:\n", + "\n", + "* [Historical anomaly detection](https://docs.nixtla.io/docs/capabilities-historical-anomaly-detection-quickstart)\n", + "\n", + "* [Historical anomaly detection with exogenous features](https://docs.nixtla.io/docs/capabilities-historical-anomaly-detection-add_exogenous_variables)\n", + "\n", + "* [Historical anomaly detection with date features](https://docs.nixtla.io/docs/capabilities-historical-anomaly-detection-add_date_features)\n", + "\n", + "* [Modifying the confidence intervals](https://docs.nixtla.io/docs/capabilities-historical-anomaly-detection-add_confidence_levels)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "python3", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/nbs/docs/capabilities/anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb similarity index 99% rename from nbs/docs/capabilities/anomaly-detection/01_quickstart.ipynb rename to nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb index 6747e4ff..6de7820a 100644 --- a/nbs/docs/capabilities/anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb @@ -48,7 +48,7 @@ "source": [ "# Quickstart\n", "\n", - "To perform anomaly detection, use the `detect_anomalies` method. Then, plot the anomalies using the `plot` method." + "To perform historical anomaly detection, use the `detect_anomalies` method. Then, plot the anomalies using the `plot` method." ] }, { @@ -176,7 +176,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For an in-depth guide on anomaly detection with TimeGPT, check out our [tutorial](https://docs.nixtla.io/docs/tutorials-anomaly_detection)." + "For an in-depth guide on historical anomaly detection with TimeGPT, check out our [tutorial](https://docs.nixtla.io/docs/tutorials-anomaly_detection)." ] } ], diff --git a/nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb similarity index 100% rename from nbs/docs/capabilities/anomaly-detection/02_anomaly_exogenous.ipynb rename to nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb diff --git a/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb similarity index 99% rename from nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb rename to nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb index 9d0940bd..b1c3b496 100644 --- a/nbs/docs/capabilities/anomaly-detection/03_anomaly_detection_date_features.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb @@ -48,7 +48,7 @@ "source": [ "# Add date features\n", "\n", - "If your dataset lacks exogenous variables, add date features to inform the model for anomaly detection. Use the `date_features` argument. Set it to `True` to extract all possible features, or pass a list of specific features to include." + "If your dataset lacks exogenous variables, add date features to inform the model for historical anomaly detection. Use the `date_features` argument. Set it to `True` to extract all possible features, or pass a list of specific features to include." ] }, { diff --git a/nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb similarity index 99% rename from nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb rename to nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb index 1d822043..f44fae6a 100644 --- a/nbs/docs/capabilities/anomaly-detection/04_confidence_levels.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb @@ -48,7 +48,7 @@ "source": [ "# Add confidence levels\n", "\n", - "Tweak the confidence level used for anomaly detection. By default, if a value falls outside the 99% confidence interval, it is labeled as an anomaly.\n", + "Tweak the confidence level used for historical anomaly detection. By default, if a value falls outside the 99% confidence interval, it is labeled as an anomaly.\n", "\n", "Modify this with the `level` parameter, which accepts any value between 0 and 100, including decimals.\n", "\n", diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb new file mode 100644 index 00000000..56cdfce3 --- /dev/null +++ b/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb @@ -0,0 +1,31 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Realtime Anomaly Detection" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Real-time anomaly detection dynamically identifies anomalies as data streams in, allowing users to specify the number of steps to monitor. This method is well-suited for immediate applications, such as fraud detection, live sensor monitoring, or tracking real-time demand changes. By focusing on recent data and continuously generating forecasts, it enables timely responses to anomalies in critical scenarios.\n", + "\n", + "This section provides various recipes for performing real-time anomaly detection using TimeGPT, offering users the ability to detect outliers and unusual patterns as they emerge, ensuring prompt intervention in time-sensitive situations.\n", + "\n", + "This section covers:\n", + "\n", + "* [Realtime anomaly detection](https://docs.nixtla.io/docs/capabilities-realtime-anomaly-detection-quickstart)\n", + "\n", + "* [How to improve the detection process](https://docs.nixtla.io/docs/capabilities-anomaly-detection-improve_detection_accuracy)\n", + "\n", + "* [Univariate vs. multiseries anomaly detection](https://docs.nixtla.io/docs/capabilities-univariate_vs_multivariate_anomaly_detection)\n" + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb new file mode 100644 index 00000000..5d5b2c18 --- /dev/null +++ b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb @@ -0,0 +1,372 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "!pip install -Uqq nixtla" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "from nixtla.utils import in_colab" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "IN_COLAB = in_colab()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " from nixtla.utils import colab_badge\n", + " from dotenv import load_dotenv" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Introduction to Realtime Anomaly Detectiontion\n", + "In this notebook, we introduce the `detect_anomaly_realtime` method. You'll learn how to quickly start using this new endpoint and understand its key differences from the historical forecast endpoint. The new features include:\n", + "* Have more flexibility and control over the anomaly detection process\n", + "* Conduct univariate/ multivariate anomaly detection\n", + "* Detect Anomaly on stream data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "if not IN_COLAB:\n", + " load_dotenv()\n", + " colab_badge('docs/capabilities/realtime-anomaly-detection/01_quickstart')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from nixtla import NixtlaClient" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nixtla_client = NixtlaClient(\n", + " # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n", + " api_key = 'my_api_key_provided_by_nixtla'\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Dataset\n", + "In this notebook, we use an minute level server machine monitoring time series for demonstration. Here, we use this example simulates a real-world streaming data scenerio, where the goal is to detect anomalies in real time, such as when the server experiences a failure or downtime." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('/Users/yibeihu/nixtla_sdk/nixtla/nbs/assets/machine-1-1.csv', parse_dates=['ts'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We observe that the time series remains stable during the initial period; however, a spike occurs in the last 20 steps, indicating anomalous behavior. Our goal is to capture this abnormal jump as soon as it appears. Let's see how the real-time anomaly detection method performs in this scenario!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "import matplotlib.pyplot as plt\n", + "ax = df.tail(300).plot(x='ts', y='y', color = 'navy', title='Time Series', figsize=(12, 2))\n", + "plt.axvspan('2020-02-01 21:00:00', '2020-02-01 21:02:00', color='orchid', alpha=0.3, label='Anomalous Period')\n", + "plt.axvspan('2020-02-01 21:47:00', '2020-02-01 22:11:00', color='orchid', alpha=0.3)\n", + "ax.legend(['Time Series', 'Anomalous Period'])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Detect anomalies in Realtime\n", + "The `detect_anomaly_realtime` method detect anomalies in a time series leveraging TimeGPT's forecast power. It leverages the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score(its absolute value indicates abnoamlity of the step)\n", + "To make a detection, set the following parameters:\n", + "\n", + "- `df`: A pandas DataFrame containing the time series data.\n", + "- `time_col`: The column that identifies the datestamp.\n", + "- `target_col`: The variable to forecast.\n", + "- `h`: Horizons is the number of steps ahead to make forecast.\n", + "- `freq`: The frequency of the time series in Pandas format.\n", + "- `level`: The confidence level for anomaly detection, default to 99%\n", + "- `detection_size`: The number of steps to analyze for anomaly at the end of time series." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "/Users/yibeihu/anaconda3/envs/test/lib/python3.12/site-packages/utilsforecast/preprocessing.py:131: FutureWarning: 'm' is deprecated and will be removed in a future version, please use 'ME' instead.\n", + " offset = pd.tseries.frequencies.to_offset(freq)\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + }, + { + "data": { + "text/html": [ + "
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unique_idtsyTimeGPTanomalyanomaly_scoreTimeGPT-hi-99TimeGPT-lo-99
95machine-1-1_y_292020-02-01 22:11:000.6060170.481175True8.0122490.5238000.438550
96machine-1-1_y_292020-02-01 22:12:000.0444130.551303True-30.1634460.5939280.508678
97machine-1-1_y_292020-02-01 22:13:000.0386820.538656True-29.7454930.5812810.496031
98machine-1-1_y_292020-02-01 22:14:000.0243550.534585True-30.3652940.5772100.491960
99machine-1-1_y_292020-02-01 22:15:000.0444130.551937True-30.2017270.5945610.509312
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" + ], + "text/plain": [ + " unique_id ts y TimeGPT anomaly \\\n", + "95 machine-1-1_y_29 2020-02-01 22:11:00 0.606017 0.481175 True \n", + "96 machine-1-1_y_29 2020-02-01 22:12:00 0.044413 0.551303 True \n", + "97 machine-1-1_y_29 2020-02-01 22:13:00 0.038682 0.538656 True \n", + "98 machine-1-1_y_29 2020-02-01 22:14:00 0.024355 0.534585 True \n", + "99 machine-1-1_y_29 2020-02-01 22:15:00 0.044413 0.551937 True \n", + "\n", + " anomaly_score TimeGPT-hi-99 TimeGPT-lo-99 \n", + "95 8.012249 0.523800 0.438550 \n", + "96 -30.163446 0.593928 0.508678 \n", + "97 -29.745493 0.581281 0.496031 \n", + "98 -30.365294 0.577210 0.491960 \n", + "99 -30.201727 0.594561 0.509312 " + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "anomaly_online = nixtla_client.detect_anomalies_realtime(df,\n", + " time_col='ts', \n", + " target_col='y', \n", + " freq='m', # Specify the frequency of the data\n", + " h=10, # Specify the forecast horizon\n", + " level=99, # Set the confidence level for anomaly detection\n", + " detection_size=100) # How many steps you want for analyzing anomalies\n", + "anomaly_online.tail()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 📘 In this example, we use a detection size of 100 to illustrate the anomaly detection process. In practice, using a smaller detection size and running the detection more frequently improves granularity and enables more timely identification of anomalies as they occur." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the plot, we observe that both anomalous periods were detected right as they arose. For further ideas on improving detection accuracy and customizing anomaly detection, please proceed to the next sections for exploration." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "plt.figure(figsize=(12, 2))\n", + "plt.plot(anomaly_online['ts'], anomaly_online['y'], label='y', color='navy', alpha=0.8)\n", + "plt.plot(anomaly_online['ts'], anomaly_online['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", + "plt.scatter(anomaly_online.loc[anomaly_online['anomaly'], 'ts'], anomaly_online.loc[anomaly_online['anomaly'], 'y'], color='orchid', label='Anomalies Detected')\n", + "for t in ['2020-02-01 21:00:00', '2020-02-01 21:47:00']:\n", + " plt.axvline(pd.to_datetime(t), color='red', linestyle='--', alpha=0.7, label='Anomaly Flagged' if t == '2020-02-01 21:00:00' else None)\n", + "\n", + "plt.axvspan('2020-02-01 21:00:00', '2020-02-01 21:02:00', color='orchid', alpha=0.3, label='Anomalous Period')\n", + "plt.axvspan('2020-02-01 21:47:00', '2020-02-01 22:11:00', color='orchid', alpha=0.3)\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For an in-depth analysis of the `detect_anomaly_realtime` method, please refer to tutorial." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "python3", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb new file mode 100644 index 00000000..5885d241 --- /dev/null +++ b/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb @@ -0,0 +1,456 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "!pip install -Uqq nixtla" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "from nixtla.utils import in_colab" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "IN_COLAB = in_colab()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " from nixtla.utils import colab_badge\n", + " from dotenv import load_dotenv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "pd.set_option('future.no_silent_downcasting', True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "def plot_anomaly(df, anomaly_df, time_col = 'ts', target_col = 'y'):\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n", + " plt.figure(figsize=(12, 2))\n", + " plt.plot(merged_df[time_col], merged_df[target_col], label='y', color='navy', alpha=0.8)\n", + " plt.plot(merged_df[time_col], merged_df['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", + " plt.scatter(merged_df.loc[merged_df['anomaly'], time_col], merged_df.loc[merged_df['anomaly'], target_col], color='orchid', label='Anomalies Detected')\n", + " plt.legend()\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Improve Detection Accuracy\n", + "\n", + "This notebook shows how to enhance anomaly detection accuracy by controlling the detection process. TimeGPT uses its forecasting power to detect anomalies based on forecast errors. By optimizing forecast parameters and accuracy, you can significantly improve anomaly detection performance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/anomaly-detection/06_improve_detection_accuracy.ipynb)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "if not IN_COLAB:\n", + " load_dotenv()\n", + " colab_badge('docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from nixtla import NixtlaClient" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nixtla_client = NixtlaClient(\n", + " # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n", + " api_key = 'my_api_key_provided_by_nixtla'\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1 Conduct anomaly detection\n", + "After initializing an instance of `NixtlaClient`, let’s explore an example using the Peyton Manning dataset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " unique_id ds y\n", + "2764 0 2015-07-05 6.499787\n", + "2765 0 2015-07-06 6.859615\n", + "2766 0 2015-07-07 6.881411\n", + "2767 0 2015-07-08 6.997596\n", + "2768 0 2015-07-09 7.152269" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv('https://datasets-nixtla.s3.amazonaws.com/peyton-manning.csv',parse_dates = ['ds']).tail(200)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "# Base case for anomaly detection using detect_anomaly_realtime\n", + "anomaly_df = nixtla_client.detect_anomalies_realtime(df,\n", + " freq='D',\n", + " h=14,\n", + " level=90,\n", + " detection_size=100\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_df, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Improving the Anomaly Detection Process\n", + "To enhance anomaly detection, we will explore two approaches: finetuning the model to improve forecast accuracy and adjusting forecast horizons and step sizes to optimize how the time series is segmented and analyzed. These methods help tailor the process to your data for better results." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.1 Finetune TimeGPT\n", + "TimeGPT uses forecast errors for anomaly detection, so improving forecast accuracy reduces noise in the errors, leading to better anomaly detection. You can fine-tune the model using the following parameters:\n", + "* `finetune_steps`: Number of steps for finetuning TimeGPT on new data.\n", + "* `finetune_depth`: Intensity of fine-tuning, with options ranging from 1 to 5.\n", + "* `finetune_loss`: Loss function to be used during the fine-tuning process." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(df,\n", + " freq='D',\n", + " h=14,\n", + " level=90,\n", + " detection_size=100,\n", + " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", + " finetune_depth = 2, # Intensity of finetuning\n", + " finetune_loss = 'mae' # Loss function used during the finetuning process\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_online_ft, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.2 Change forecast horizon and step\n", + "Similar to cross-validation, the anomaly detection method generates forecasts for historical data by splitting the time series into overlapping windows. The way these windows are defined can impact the anomaly detection results. Two key parameters control this process:\n", + "* `h`: Specifies how many steps into the future the forecast is made for each window.\n", + "* `step_size`: Determines the interval between the starting points of consecutive windows." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(df,\n", + " time_col='ds',\n", + " target_col='y',\n", + " freq='D',\n", + " h=2, # Forecast horizon\n", + " step_size = 1, # Step size for moving through the time series data\n", + " level=90, \n", + " detection_size=100\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_df_horizon, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 📘 **Balancing h and step_size depends on your data:** For frequent, short-lived anomalies, use a smaller `h` to focus on short-term predictions and a smaller `step_size` to increase overlap and sensitivity. For smooth trends or long-term patterns, use a larger `h` to capture broader anomalies and a larger `step_size` to reduce noise and computational cost." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "python3", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb new file mode 100644 index 00000000..e1bdee10 --- /dev/null +++ b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -0,0 +1,331 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "!pip install -Uqq nixtla" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "from nixtla.utils import in_colab" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "IN_COLAB = in_colab()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " from nixtla.utils import colab_badge\n", + " from dotenv import load_dotenv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "import matplotlib.pyplot as plt\n", + "\n", + "def plot_anomalies(df, unique_ids, rows, cols):\n", + " fig, axes = plt.subplots(rows, cols, figsize=(12, rows * 2))\n", + " for i, (ax, uid) in enumerate(zip(axes.flatten(), unique_ids)):\n", + " filtered_df = df[df['unique_id'] == uid]\n", + " ax.plot(filtered_df['ts'], filtered_df['y'], color='navy', alpha=0.8, label='y')\n", + " ax.plot(filtered_df['ts'], filtered_df['TimeGPT'], color='orchid', alpha=0.7, label='TimeGPT')\n", + " [ax.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + " ax.set_title(f\"Unique_id: {uid}\", fontsize=8); ax.tick_params(axis='x', labelsize=6)\n", + " fig.legend(loc='upper center', ncol=3, fontsize=8, labels=['y', 'TimeGPT', 'Anomaly'])\n", + " plt.tight_layout(rect=[0, 0, 1, 0.95])\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Univariate vs. Multivariate Anomaly Detection" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this notebook, we’ll show you how to detect anomalies across multiple time series using our new multivariate method. This method is great for situations where you have several sensors or related time series. We’ll also explain how it works differently from our univariate method." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/anomaly-detection/07_univariate_vs_multivariate_anomaly_detection.ipynb)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "if not IN_COLAB:\n", + " load_dotenv()\n", + " colab_badge('docs/capabilities/anomaly-detection/07_univariate_vs_multivariate_anomaly_detection')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "from nixtla import NixtlaClient" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nixtla_client = NixtlaClient(\n", + " # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n", + " api_key = 'my_api_key_provided_by_nixtla'\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Dataset\n", + "In this notebook example from SMD dataset. SMD (Server Machine Dataset) is a benchmark dataset for anomaly detection with multiple time series. It monitors abnormal patterns in server machine data. \n", + "\n", + "Here we use a set of monitoring data from a single server machine(machine-1-1) that has 38 time series. Each time series represents a different metric being monitored, such as CPU usage, memory usage, disk I/O, and network I/O. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "38" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv('/Users/yibeihu/nixtla_sdk/nixtla/nbs/assets/SMD_test.csv', parse_dates=['ts'])\n", + "df.unique_id.nunique()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Univariate vs. Multivariate Method" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.1 Univariate Method\n", + "Univariate anomaly detection analyzes each time series independently, flagging anomalies based on deviations from its historical patterns. This method is effective for detecting issues within a single metric but ignores dependencies across multiple series. As a result, it may miss collective anomalies or flag irrelevant ones in scenarios where anomalies arise from patterns across multiple series, such as system-wide failures, correlated financial metrics, or interconnected processes. That’s when multiseries anomaly detection comes into play" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_online = nixtla_client.detect_anomalies_realtime(df[['ts', 'y', 'unique_id']],\n", + " time_col='ts',\n", + " target_col='y',\n", + " freq='h', \n", + " h=24, \n", + " level=95, \n", + " detection_size=475, \n", + " threshold_method = 'univariate' # Specify the threshold_method as 'univariate'\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display_ids = ['machine-1-1_y_0', 'machine-1-1_y_1', 'machine-1-1_y_6', 'machine-1-1_y_29']\n", + "plot_anomalies(anomaly_online, display_ids, rows=2, cols=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.2 Multivariate Method\n", + "The multivariate anomaly detection method considers multiple time series simultaneously. Instead of treating each series in isolation, it accumulates the anomaly scores for the same time step across all series and determines whether the step is anomalous based on the combined score. This method is particularly useful in scenarios where anomalies are only significant when multiple series collectively indicate an issue. To apply multivariate detection, simply set the parameter `threshold_method` as `multivariate`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_online_multi = nixtla_client.detect_anomalies_realtime(df[['ts', 'y', 'unique_id']],\n", + " time_col='ts',\n", + " target_col='y',\n", + " freq='h',\n", + " h=24,\n", + " level=95,\n", + " detection_size=475,\n", + " threshold_method = 'multivariate' # Specify the threshold_method as 'multivariate'\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomalies(anomaly_online_multi, display_ids, rows=2, cols=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 📘 In multiseries anomaly detection, error scores from all time series are aggregated at each time step, and a threshold is applied to identify significant deviations. If the aggregated error exceeds the threshold, the time step is flagged as anomalous across all series, capturing system-wide patterns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "filtered_df = anomaly_online_multi[anomaly_online_multi['unique_id'] == 'machine-1-1_y_0']\n", + "threshold = np.percentile(filtered_df['accumulated_anomaly_score'], 95)\n", + "plt.figure(figsize=(12, 3))\n", + "plt.plot(filtered_df['ts'], filtered_df['accumulated_anomaly_score'], label='Score', color='navy', alpha=0.8)\n", + "plt.axhline(y=threshold, color='red', linestyle='--', label=f'95% Threshold')\n", + "[plt.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + "plt.title(\"Accumulated Anomaly Scores for machine-1-1\", fontsize=10)\n", + "plt.xlabel(\"Timestamp\"); plt.ylabel(\"Score\"); plt.legend(); plt.tight_layout(); plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "python3", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/mint.json b/nbs/mint.json index c4e158c7..1393b9d3 100644 --- a/nbs/mint.json +++ b/nbs/mint.json @@ -55,12 +55,20 @@ ] }, { - "group": "Anomaly Detection", + "group": "Historical Anomaly Detection", "pages": [ - "docs/capabilities/anomaly-detection/quickstart.html", - "docs/capabilities/anomaly-detection/anomaly_exogenous.html", - "docs/capabilities/anomaly-detection/anomaly_detection_date_features.html", - "docs/capabilities/anomaly-detection/confidence_levels.html" + "docs/capabilities/historical-anomaly-detection/quickstart.html", + "docs/capabilities/historical-anomaly-detection/anomaly_exogenous.html", + "docs/capabilities/historical-anomaly-detection/anomaly_detection_date_features.html", + "docs/capabilities/historical-anomaly-detection/confidence_levels.html" + ] + }, + { + "group": "Realtime Anomaly Detection", + "pages": [ + "docs/capabilities/realtime-anomaly-detection/quickstart.html", + "docs/capabilities/realtime-anomaly-detection/improve_detection_accuracy.html", + "docs/capabilities/realtime-anomaly-detection/univariate_vs_multivariate_anomaly_detection.html" ] } ] diff --git a/nbs/nbdev.yml b/nbs/nbdev.yml index b72003f4..44fe66b9 100644 --- a/nbs/nbdev.yml +++ b/nbs/nbdev.yml @@ -4,6 +4,6 @@ project: website: title: "nixtla" site-url: "https://Nixtla.github.io/nixtla/" - description: "Time series forecasting suite using TimeGPT" + description: "Python SDK for Nixtla API (TimeGPT)" repo-branch: main repo-url: "https://github.com/Nixtla/nixtla/" From 5f7d614bd74185a2ca98dd1e222f887e59304697 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Wed, 11 Dec 2024 06:21:29 +0800 Subject: [PATCH 20/38] changes with Marco' comments --- nbs/assets/SMD_test.csv | 36101 ++++++++++++++++ .../01_quickstart.ipynb | 19 +- .../02_improve_detection_accuracy.ipynb | 51 +- ...te_vs_multivariate_anomaly_detection.ipynb | 65 +- 4 files changed, 36177 insertions(+), 59 deletions(-) create mode 100644 nbs/assets/SMD_test.csv diff --git a/nbs/assets/SMD_test.csv 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a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb index 5d5b2c18..a3b3c411 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb @@ -114,7 +114,7 @@ "metadata": {}, "outputs": [], "source": [ - "df = pd.read_csv('/Users/yibeihu/nixtla_sdk/nixtla/nbs/assets/machine-1-1.csv', parse_dates=['ts'])" + "df = pd.read_csv('../../../assets/machine-1-1.csv', parse_dates=['ts'])" ] }, { @@ -296,13 +296,14 @@ } ], "source": [ - "anomaly_online = nixtla_client.detect_anomalies_realtime(df,\n", - " time_col='ts', \n", - " target_col='y', \n", - " freq='m', # Specify the frequency of the data\n", - " h=10, # Specify the forecast horizon\n", - " level=99, # Set the confidence level for anomaly detection\n", - " detection_size=100) # How many steps you want for analyzing anomalies\n", + "anomaly_online = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " time_col='ts', \n", + " target_col='y', \n", + " freq='m', # Specify the frequency of the data\n", + " h=10, # Specify the forecast horizon\n", + " level=99, # Set the confidence level for anomaly detection\n", + " detection_size=100) # How many steps you want for analyzing anomalies\n", "anomaly_online.tail()\n" ] }, @@ -343,7 +344,7 @@ "plt.plot(anomaly_online['ts'], anomaly_online['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", "plt.scatter(anomaly_online.loc[anomaly_online['anomaly'], 'ts'], anomaly_online.loc[anomaly_online['anomaly'], 'y'], color='orchid', label='Anomalies Detected')\n", "for t in ['2020-02-01 21:00:00', '2020-02-01 21:47:00']:\n", - " plt.axvline(pd.to_datetime(t), color='red', linestyle='--', alpha=0.7, label='Anomaly Flagged' if t == '2020-02-01 21:00:00' else None)\n", + " plt.axvline(pd.to_datetime(t), color='red', linestyle='--', alpha=0.7, label='Anomaly Behavior Captured' if t == '2020-02-01 21:00:00' else None)\n", "\n", "plt.axvspan('2020-02-01 21:00:00', '2020-02-01 21:02:00', color='orchid', alpha=0.3, label='Anomalous Period')\n", "plt.axvspan('2020-02-01 21:47:00', '2020-02-01 22:11:00', color='orchid', alpha=0.3)\n", diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb index 5885d241..c37094c3 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb @@ -253,12 +253,13 @@ ], "source": [ "# Base case for anomaly detection using detect_anomaly_realtime\n", - "anomaly_df = nixtla_client.detect_anomalies_realtime(df,\n", - " freq='D',\n", - " h=14,\n", - " level=90,\n", - " detection_size=100\n", - " )" + "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " freq='D',\n", + " h=14,\n", + " level=90,\n", + " detection_size=100\n", + " )" ] }, { @@ -331,15 +332,16 @@ } ], "source": [ - "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(df,\n", - " freq='D',\n", - " h=14,\n", - " level=90,\n", - " detection_size=100,\n", - " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", - " finetune_depth = 2, # Intensity of finetuning\n", - " finetune_loss = 'mae' # Loss function used during the finetuning process\n", - " )" + "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " freq='D',\n", + " h=14,\n", + " level=90,\n", + " detection_size=100,\n", + " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", + " finetune_depth = 2, # Intensity of finetuning\n", + " finetune_loss = 'mae' # Loss function used during the finetuning process\n", + " )" ] }, { @@ -397,15 +399,16 @@ } ], "source": [ - "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(df,\n", - " time_col='ds',\n", - " target_col='y',\n", - " freq='D',\n", - " h=2, # Forecast horizon\n", - " step_size = 1, # Step size for moving through the time series data\n", - " level=90, \n", - " detection_size=100\n", - " )" + "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " time_col='ds',\n", + " target_col='y',\n", + " freq='D',\n", + " h=2, # Forecast horizon\n", + " step_size = 1, # Step size for moving through the time series data\n", + " level=90, \n", + " detection_size=100\n", + " )" ] }, { diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index e1bdee10..b6ece4e8 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -57,7 +57,10 @@ " filtered_df = df[df['unique_id'] == uid]\n", " ax.plot(filtered_df['ts'], filtered_df['y'], color='navy', alpha=0.8, label='y')\n", " ax.plot(filtered_df['ts'], filtered_df['TimeGPT'], color='orchid', alpha=0.7, label='TimeGPT')\n", - " [ax.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + " # [ax.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + " ax.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", + " filtered_df.loc[filtered_df['anomaly'] == 1, 'y'], \n", + " color='orchid', label='Anomalies Detected')\n", " ax.set_title(f\"Unique_id: {uid}\", fontsize=8); ax.tick_params(axis='x', labelsize=6)\n", " fig.legend(loc='upper center', ncol=3, fontsize=8, labels=['y', 'TimeGPT', 'Anomaly'])\n", " plt.tight_layout(rect=[0, 0, 1, 0.95])\n", @@ -153,7 +156,7 @@ } ], "source": [ - "df = pd.read_csv('/Users/yibeihu/nixtla_sdk/nixtla/nbs/assets/SMD_test.csv', parse_dates=['ts'])\n", + "df = pd.read_csv('../../../SMD_test.csv', parse_dates=['ts'])\n", "df.unique_id.nunique()" ] }, @@ -195,15 +198,16 @@ } ], "source": [ - "anomaly_online = nixtla_client.detect_anomalies_realtime(df[['ts', 'y', 'unique_id']],\n", - " time_col='ts',\n", - " target_col='y',\n", - " freq='h', \n", - " h=24, \n", - " level=95, \n", - " detection_size=475, \n", - " threshold_method = 'univariate' # Specify the threshold_method as 'univariate'\n", - " )" + "anomaly_online = nixtla_client.detect_anomalies_realtime(\n", + " df[['ts', 'y', 'unique_id']],\n", + " time_col='ts',\n", + " target_col='y',\n", + " freq='h', \n", + " h=24, \n", + " level=95, \n", + " detection_size=475, \n", + " threshold_method = 'univariate' # Specify the threshold_method as 'univariate'\n", + " )" ] }, { @@ -213,7 +217,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -232,7 +236,9 @@ "metadata": {}, "source": [ "### 2.2 Multivariate Method\n", - "The multivariate anomaly detection method considers multiple time series simultaneously. Instead of treating each series in isolation, it accumulates the anomaly scores for the same time step across all series and determines whether the step is anomalous based on the combined score. This method is particularly useful in scenarios where anomalies are only significant when multiple series collectively indicate an issue. To apply multivariate detection, simply set the parameter `threshold_method` as `multivariate`." + "The multivariate anomaly detection method considers multiple time series simultaneously. Instead of treating each series in isolation, it accumulates the anomaly scores for the same time step across all series and determines whether the step is anomalous based on the combined score. This method is particularly useful in scenarios where anomalies are only significant when multiple series collectively indicate an issue. To apply multivariate detection, simply set the parameter `threshold_method` as `multivariate`.\n", + "\n", + "We can see that the anomalies detected for each time series are the same as those based on the accumulated error. " ] }, { @@ -252,15 +258,16 @@ } ], "source": [ - "anomaly_online_multi = nixtla_client.detect_anomalies_realtime(df[['ts', 'y', 'unique_id']],\n", - " time_col='ts',\n", - " target_col='y',\n", - " freq='h',\n", - " h=24,\n", - " level=95,\n", - " detection_size=475,\n", - " threshold_method = 'multivariate' # Specify the threshold_method as 'multivariate'\n", - " )" + "anomaly_online_multi = nixtla_client.detect_anomalies_realtime(\n", + " df[['ts', 'y', 'unique_id']],\n", + " time_col='ts',\n", + " target_col='y',\n", + " freq='h',\n", + " h=24,\n", + " level=95,\n", + " detection_size=475,\n", + " threshold_method = 'multivariate' # Specify the threshold_method as 'multivariate'\n", + " )" ] }, { @@ -270,7 +277,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -297,7 +304,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -313,9 +320,15 @@ "plt.figure(figsize=(12, 3))\n", "plt.plot(filtered_df['ts'], filtered_df['accumulated_anomaly_score'], label='Score', color='navy', alpha=0.8)\n", "plt.axhline(y=threshold, color='red', linestyle='--', label=f'95% Threshold')\n", - "[plt.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + "# [plt.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", + "plt.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", + " filtered_df.loc[filtered_df['anomaly'] == 1, 'accumulated_anomaly_score'], \n", + " color='orchid', label='Anomaly Detected', alpha=0.8)\n", "plt.title(\"Accumulated Anomaly Scores for machine-1-1\", fontsize=10)\n", - "plt.xlabel(\"Timestamp\"); plt.ylabel(\"Score\"); plt.legend(); plt.tight_layout(); plt.show()\n" + "plt.xlabel(\"Timestamp\")\n", + "plt.ylabel(\"Score\")\n", + "plt.legend(labels=['Score', '95% Threshold', 'Anomaly Detected'])\n", + "plt.show()\n" ] } ], From 321797fb1776414d00f68444fa491727263e9370 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Wed, 11 Dec 2024 07:59:20 +0800 Subject: [PATCH 21/38] add sdk reference --- ...te_vs_multivariate_anomaly_detection.ipynb | 2 +- nbs/docs/reference/01_nixtla_client.ipynb | 574 +++++++++++++----- nbs/src/nixtla_client.ipynb | 70 ++- nixtla/nixtla_client.py | 62 +- 4 files changed, 481 insertions(+), 227 deletions(-) diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index b6ece4e8..134ad246 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -156,7 +156,7 @@ } ], "source": [ - "df = pd.read_csv('../../../SMD_test.csv', parse_dates=['ts'])\n", + "df = pd.read_csv('../../../assets/SMD_test.csv', parse_dates=['ts'])\n", "df.unique_id.nunique()" ] }, diff --git a/nbs/docs/reference/01_nixtla_client.ipynb b/nbs/docs/reference/01_nixtla_client.ipynb index bfb235e3..a504279b 100644 --- a/nbs/docs/reference/01_nixtla_client.ipynb +++ b/nbs/docs/reference/01_nixtla_client.ipynb @@ -18,6 +18,15 @@ "from nixtla import NixtlaClient" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# pip install nbdev --upgrade" + ] + }, { "cell_type": "code", "execution_count": null, @@ -28,18 +37,21 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient\n", "\n", "> NixtlaClient (api_key:Optional[str]=None, base_url:Optional[str]=None,\n", - "> max_retries:int=6, retry_interval:int=10,\n", + "> timeout:int=60, max_retries:int=6, retry_interval:int=10,\n", "> max_wait_time:int=360)\n", "\n", - "Constructs all the necessary attributes for the NixtlaClient object.\n", + "*Client to interact with the Nixtla API.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| api_key | Optional | None | The authorization api_key interacts with the Nixtla API.
If not provided, it will be inferred by the NIXTLA_API_KEY environment variable. |\n", - "| base_url | Optional | None | Custom base_url. Pass only if provided. |\n", + "| api_key | Optional | None | The authorization api_key interacts with the Nixtla API.
If not provided, will use the NIXTLA_API_KEY environment variable. |\n", + "| base_url | Optional | None | Custom base_url.
If not provided, will use the NIXTLA_BASE_URL environment variable. |\n", + "| timeout | int | 60 | Request timeout in seconds. Set this to `None` to disable it. |\n", "| max_retries | int | 6 | The maximum number of attempts to make when calling the API before giving up.
It defines how many times the client will retry the API call if it fails.
Default value is 6, indicating the client will attempt the API call up to 6 times in total |\n", "| retry_interval | int | 10 | The interval in seconds between consecutive retry attempts.
This is the waiting period before the client tries to call the API again after a failed attempt.
Default value is 10 seconds, meaning the client waits for 10 seconds between retries. |\n", "| max_wait_time | int | 360 | The maximum total time in seconds that the client will spend on all retry attempts before giving up.
This sets an upper limit on the cumulative waiting time for all retry attempts.
If this time is exceeded, the client will stop retrying and raise an exception.
Default value is 360 seconds, meaning the client will cease retrying if the total time
spent on retries exceeds 360 seconds.
The client throws a ReadTimeout error after 60 seconds of inactivity. If you want to
catch these errors, use max_wait_time >> 60. |" @@ -47,18 +59,21 @@ "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient\n", "\n", "> NixtlaClient (api_key:Optional[str]=None, base_url:Optional[str]=None,\n", - "> max_retries:int=6, retry_interval:int=10,\n", + "> timeout:int=60, max_retries:int=6, retry_interval:int=10,\n", "> max_wait_time:int=360)\n", "\n", - "Constructs all the necessary attributes for the NixtlaClient object.\n", + "*Client to interact with the Nixtla API.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| api_key | Optional | None | The authorization api_key interacts with the Nixtla API.
If not provided, it will be inferred by the NIXTLA_API_KEY environment variable. |\n", - "| base_url | Optional | None | Custom base_url. Pass only if provided. |\n", + "| api_key | Optional | None | The authorization api_key interacts with the Nixtla API.
If not provided, will use the NIXTLA_API_KEY environment variable. |\n", + "| base_url | Optional | None | Custom base_url.
If not provided, will use the NIXTLA_BASE_URL environment variable. |\n", + "| timeout | int | 60 | Request timeout in seconds. Set this to `None` to disable it. |\n", "| max_retries | int | 6 | The maximum number of attempts to make when calling the API before giving up.
It defines how many times the client will retry the API call if it fails.
Default value is 6, indicating the client will attempt the API call up to 6 times in total |\n", "| retry_interval | int | 10 | The interval in seconds between consecutive retry attempts.
This is the waiting period before the client tries to call the API again after a failed attempt.
Default value is 10 seconds, meaning the client waits for 10 seconds between retries. |\n", "| max_wait_time | int | 360 | The maximum total time in seconds that the client will spend on all retry attempts before giving up.
This sets an upper limit on the cumulative waiting time for all retry attempts.
If this time is exceeded, the client will stop retrying and raise an exception.
Default value is 360 seconds, meaning the client will cease retrying if the total time
spent on retries exceeds 360 seconds.
The client throws a ReadTimeout error after 60 seconds of inactivity. If you want to
catch these errors, use max_wait_time >> 60. |" @@ -84,20 +99,24 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.validate_api_key\n", "\n", "> NixtlaClient.validate_api_key (log:bool=True)\n", "\n", - "Returns True if your api_key is valid." + "*Returns True if your api_key is valid.*" ], "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.validate_api_key\n", "\n", "> NixtlaClient.validate_api_key (log:bool=True)\n", "\n", - "Returns True if your api_key is valid." + "*Returns True if your api_key is valid.*" ] }, "execution_count": null, @@ -120,70 +139,90 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.plot\n", "\n", - "> NixtlaClient.plot (df:pandas.core.frame.DataFrame,\n", - "> forecasts_df:Optional[pandas.core.frame.DataFrame]=Non\n", - "> e, id_col:str='unique_id', time_col:str='ds',\n", - "> target_col:str='y', unique_ids:Union[List[str],NoneTyp\n", - "> e,numpy.ndarray]=None, plot_random:bool=True,\n", - "> models:Optional[List[str]]=None,\n", - "> level:Optional[List[float]]=None,\n", + "> NixtlaClient.plot (df:Union[pandas.core.frame.DataFrame,utilsforecast.com\n", + "> pat.pl_DataFrame,NoneType]=None, forecasts_df:Union[pa\n", + "> ndas.core.frame.DataFrame,utilsforecast.compat.pl_Data\n", + "> Frame,NoneType]=None, id_col:str='unique_id',\n", + "> time_col:str='ds', target_col:str='y', unique_ids:Unio\n", + "> n[list[str],NoneType,numpy.ndarray]=None,\n", + "> plot_random:bool=True, max_ids:int=8,\n", + "> models:Optional[list[str]]=None,\n", + "> level:Optional[list[Union[int,float]]]=None,\n", "> max_insample_length:Optional[int]=None,\n", - "> plot_anomalies:bool=False, engine:str='matplotlib',\n", - "> resampler_kwargs:Optional[Dict]=None)\n", + "> plot_anomalies:bool=False,\n", + "> engine:Literal['matplotlib','plotly','plotly-\n", + "> resampler']='matplotlib',\n", + "> resampler_kwargs:Optional[dict]=None, ax:Union[Forward\n", + "> Ref('plt.Axes'),numpy.ndarray,ForwardRef('plotly.graph\n", + "> _objects.Figure'),NoneType]=None)\n", "\n", - "Plot forecasts and insample values.\n", + "*Plot forecasts and insample values.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| forecasts_df | Optional | None | DataFrame with columns [`unique_id`, `ds`] and models. |\n", + "| df | Union | None | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| forecasts_df | Union | None | DataFrame with columns [`unique_id`, `ds`] and models. |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| unique_ids | Union | None | Time Series to plot.
If None, time series are selected randomly. |\n", "| plot_random | bool | True | Select time series to plot randomly. |\n", - "| models | Optional | None | List of models to plot. |\n", - "| level | Optional | None | List of prediction intervals to plot if paseed. |\n", + "| max_ids | int | 8 | Maximum number of ids to plot. |\n", + "| models | Optional | None | list of models to plot. |\n", + "| level | Optional | None | list of prediction intervals to plot if paseed. |\n", "| max_insample_length | Optional | None | Max number of train/insample observations to be plotted. |\n", "| plot_anomalies | bool | False | Plot anomalies for each prediction interval. |\n", - "| engine | str | matplotlib | Library used to plot. 'plotly', 'plotly-resampler' or 'matplotlib'. |\n", - "| resampler_kwargs | Optional | None | Kwargs to be passed to plotly-resampler constructor.
For further custumization (\"show_dash\") call the method,
store the plotting object and add the extra arguments to
its `show_dash` method. |" + "| engine | Literal | matplotlib | Library used to plot. 'matplotlib', 'plotly' or 'plotly-resampler'. |\n", + "| resampler_kwargs | Optional | None | Kwargs to be passed to plotly-resampler constructor.
For further custumization (\"show_dash\") call the method,
store the plotting object and add the extra arguments to
its `show_dash` method. |\n", + "| ax | Union | None | Object where plots will be added. |" ], "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.plot\n", "\n", - "> NixtlaClient.plot (df:pandas.core.frame.DataFrame,\n", - "> forecasts_df:Optional[pandas.core.frame.DataFrame]=Non\n", - "> e, id_col:str='unique_id', time_col:str='ds',\n", - "> target_col:str='y', unique_ids:Union[List[str],NoneTyp\n", - "> e,numpy.ndarray]=None, plot_random:bool=True,\n", - "> models:Optional[List[str]]=None,\n", - "> level:Optional[List[float]]=None,\n", + "> NixtlaClient.plot (df:Union[pandas.core.frame.DataFrame,utilsforecast.com\n", + "> pat.pl_DataFrame,NoneType]=None, forecasts_df:Union[pa\n", + "> ndas.core.frame.DataFrame,utilsforecast.compat.pl_Data\n", + "> Frame,NoneType]=None, id_col:str='unique_id',\n", + "> time_col:str='ds', target_col:str='y', unique_ids:Unio\n", + "> n[list[str],NoneType,numpy.ndarray]=None,\n", + "> plot_random:bool=True, max_ids:int=8,\n", + "> models:Optional[list[str]]=None,\n", + "> level:Optional[list[Union[int,float]]]=None,\n", "> max_insample_length:Optional[int]=None,\n", - "> plot_anomalies:bool=False, engine:str='matplotlib',\n", - "> resampler_kwargs:Optional[Dict]=None)\n", + "> plot_anomalies:bool=False,\n", + "> engine:Literal['matplotlib','plotly','plotly-\n", + "> resampler']='matplotlib',\n", + "> resampler_kwargs:Optional[dict]=None, ax:Union[Forward\n", + "> Ref('plt.Axes'),numpy.ndarray,ForwardRef('plotly.graph\n", + "> _objects.Figure'),NoneType]=None)\n", "\n", - "Plot forecasts and insample values.\n", + "*Plot forecasts and insample values.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| forecasts_df | Optional | None | DataFrame with columns [`unique_id`, `ds`] and models. |\n", + "| df | Union | None | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| forecasts_df | Union | None | DataFrame with columns [`unique_id`, `ds`] and models. |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| unique_ids | Union | None | Time Series to plot.
If None, time series are selected randomly. |\n", "| plot_random | bool | True | Select time series to plot randomly. |\n", - "| models | Optional | None | List of models to plot. |\n", - "| level | Optional | None | List of prediction intervals to plot if paseed. |\n", + "| max_ids | int | 8 | Maximum number of ids to plot. |\n", + "| models | Optional | None | list of models to plot. |\n", + "| level | Optional | None | list of prediction intervals to plot if paseed. |\n", "| max_insample_length | Optional | None | Max number of train/insample observations to be plotted. |\n", "| plot_anomalies | bool | False | Plot anomalies for each prediction interval. |\n", - "| engine | str | matplotlib | Library used to plot. 'plotly', 'plotly-resampler' or 'matplotlib'. |\n", - "| resampler_kwargs | Optional | None | Kwargs to be passed to plotly-resampler constructor.
For further custumization (\"show_dash\") call the method,
store the plotting object and add the extra arguments to
its `show_dash` method. |" + "| engine | Literal | matplotlib | Library used to plot. 'matplotlib', 'plotly' or 'plotly-resampler'. |\n", + "| resampler_kwargs | Optional | None | Kwargs to be passed to plotly-resampler constructor.
For further custumization (\"show_dash\") call the method,
store the plotting object and add the extra arguments to
its `show_dash` method. |\n", + "| ax | Union | None | Object where plots will be added. |" ] }, "execution_count": null, @@ -206,90 +245,112 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.forecast\n", "\n", - "> NixtlaClient.forecast (df:pandas.core.frame.DataFrame, h:int,\n", - "> freq:Optional[str]=None, id_col:str='unique_id',\n", + "> NixtlaClient.forecast (df:~AnyDFType, h:Annotated[int,Gt(gt=0)],\n", + "> freq:Union[str,int,pandas._libs.tslibs.offsets.Bas\n", + "> eOffset,NoneType]=None, id_col:str='unique_id',\n", "> time_col:str='ds', target_col:str='y',\n", - "> X_df:Optional[pandas.core.frame.DataFrame]=None,\n", - "> level:Optional[List[Union[int,float]]]=None,\n", - "> quantiles:Optional[List[float]]=None,\n", - "> finetune_steps:int=0, finetune_loss:str='default',\n", - "> clean_ex_first:bool=True,\n", + "> X_df:Optional[~AnyDFType]=None,\n", + "> level:Optional[list[Union[int,float]]]=None,\n", + "> quantiles:Optional[list[float]]=None,\n", + "> finetune_steps:Annotated[int,Ge(ge=0)]=0,\n", + "> finetune_depth:Literal[1,2,3,4,5]=1, finetune_loss\n", + "> :Literal['default','mae','mse','rmse','mape','smap\n", + "> e']='default', clean_ex_first:bool=True,\n", + "> hist_exog_list:Optional[list[str]]=None,\n", "> validate_api_key:bool=False,\n", - "> add_history:bool=False,\n", - "> date_features:Union[bool,List[str]]=False, date_fe\n", - "> atures_to_one_hot:Union[bool,List[str]]=True,\n", - "> model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", + "> add_history:bool=False, date_features:Union[bool,l\n", + "> ist[Union[str,Callable]]]=False, date_features_to_\n", + "> one_hot:Union[bool,list[str]]=False, model:Literal\n", + "> ['azureai','timegpt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Optional[Ann\n", + "> otated[int,Gt(gt=0)]]=None,\n", + "> feature_contributions:bool=False)\n", "\n", - "Forecast your time series using TimeGPT.\n", + "*Forecast your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| h | int | | Forecast horizon. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| X_df | Optional | None | DataFrame with [`unique_id`, `ds`] columns and `df`'s future exogenous. |\n", "| level | Optional | None | Confidence levels between 0 and 100 for prediction intervals. |\n", "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names. |\n", - "| finetune_steps | int | 0 | Number of steps used to finetune learning TimeGPT in the
new data. |\n", - "| finetune_loss | str | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", - "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune learning TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| hist_exog_list | Optional | None | Column names of the historical exogenous features. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", "| add_history | bool | False | Return fitted values of the model. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with TimeGPT forecasts for point predictions and probabilistic
predictions (if level is not None).** |" + "| feature_contributions | bool | False | |\n", + "| **Returns** | **AnyDFType** | | **DataFrame with TimeGPT forecasts for point predictions and probabilistic
predictions (if level is not None).** |" ], "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.forecast\n", "\n", - "> NixtlaClient.forecast (df:pandas.core.frame.DataFrame, h:int,\n", - "> freq:Optional[str]=None, id_col:str='unique_id',\n", + "> NixtlaClient.forecast (df:~AnyDFType, h:Annotated[int,Gt(gt=0)],\n", + "> freq:Union[str,int,pandas._libs.tslibs.offsets.Bas\n", + "> eOffset,NoneType]=None, id_col:str='unique_id',\n", "> time_col:str='ds', target_col:str='y',\n", - "> X_df:Optional[pandas.core.frame.DataFrame]=None,\n", - "> level:Optional[List[Union[int,float]]]=None,\n", - "> quantiles:Optional[List[float]]=None,\n", - "> finetune_steps:int=0, finetune_loss:str='default',\n", - "> clean_ex_first:bool=True,\n", + "> X_df:Optional[~AnyDFType]=None,\n", + "> level:Optional[list[Union[int,float]]]=None,\n", + "> quantiles:Optional[list[float]]=None,\n", + "> finetune_steps:Annotated[int,Ge(ge=0)]=0,\n", + "> finetune_depth:Literal[1,2,3,4,5]=1, finetune_loss\n", + "> :Literal['default','mae','mse','rmse','mape','smap\n", + "> e']='default', clean_ex_first:bool=True,\n", + "> hist_exog_list:Optional[list[str]]=None,\n", "> validate_api_key:bool=False,\n", - "> add_history:bool=False,\n", - "> date_features:Union[bool,List[str]]=False, date_fe\n", - "> atures_to_one_hot:Union[bool,List[str]]=True,\n", - "> model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", + "> add_history:bool=False, date_features:Union[bool,l\n", + "> ist[Union[str,Callable]]]=False, date_features_to_\n", + "> one_hot:Union[bool,list[str]]=False, model:Literal\n", + "> ['azureai','timegpt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Optional[Ann\n", + "> otated[int,Gt(gt=0)]]=None,\n", + "> feature_contributions:bool=False)\n", "\n", - "Forecast your time series using TimeGPT.\n", + "*Forecast your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| h | int | | Forecast horizon. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| X_df | Optional | None | DataFrame with [`unique_id`, `ds`] columns and `df`'s future exogenous. |\n", "| level | Optional | None | Confidence levels between 0 and 100 for prediction intervals. |\n", "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names. |\n", - "| finetune_steps | int | 0 | Number of steps used to finetune learning TimeGPT in the
new data. |\n", - "| finetune_loss | str | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", - "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune learning TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| hist_exog_list | Optional | None | Column names of the historical exogenous features. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", "| add_history | bool | False | Return fitted values of the model. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with TimeGPT forecasts for point predictions and probabilistic
predictions (if level is not None).** |" + "| feature_contributions | bool | False | |\n", + "| **Returns** | **AnyDFType** | | **DataFrame with TimeGPT forecasts for point predictions and probabilistic
predictions (if level is not None).** |" ] }, "execution_count": null, @@ -312,94 +373,118 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.cross_validation\n", "\n", - "> NixtlaClient.cross_validation (df:pandas.core.frame.DataFrame, h:int,\n", - "> freq:Optional[str]=None,\n", + "> NixtlaClient.cross_validation (df:~AnyDFType, h:Annotated[int,Gt(gt=0)],\n", + "> freq:Union[str,int,pandas._libs.tslibs.off\n", + "> sets.BaseOffset,NoneType]=None,\n", "> id_col:str='unique_id', time_col:str='ds',\n", - "> target_col:str='y', level:Optional[List[Un\n", + "> target_col:str='y', level:Optional[list[Un\n", "> ion[int,float]]]=None,\n", - "> quantiles:Optional[List[float]]=None,\n", + "> quantiles:Optional[list[float]]=None,\n", "> validate_api_key:bool=False,\n", - "> n_windows:int=1,\n", - "> step_size:Optional[int]=None,\n", - "> finetune_steps:int=0,\n", - "> finetune_loss:str='default',\n", - "> clean_ex_first:bool=True,\n", - "> date_features:Union[bool,List[str]]=False,\n", - "> date_features_to_one_hot:Union[bool,List[s\n", - "> tr]]=True, model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", - "\n", - "Perform cross validation in your time series using TimeGPT.\n", + "> n_windows:Annotated[int,Gt(gt=0)]=1, step_\n", + "> size:Optional[Annotated[int,Gt(gt=0)]]=Non\n", + "> e,\n", + "> finetune_steps:Annotated[int,Ge(ge=0)]=0,\n", + "> finetune_depth:Literal[1,2,3,4,5]=1, finet\n", + "> une_loss:Literal['default','mae','mse','rm\n", + "> se','mape','smape']='default',\n", + "> refit:bool=True, clean_ex_first:bool=True,\n", + "> hist_exog_list:Optional[list[str]]=None,\n", + "> date_features:Union[bool,list[str]]=False,\n", + "> date_features_to_one_hot:Union[bool,list[s\n", + "> tr]]=False, model:Literal['azureai','timeg\n", + "> pt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Opti\n", + "> onal[Annotated[int,Gt(gt=0)]]=None)\n", + "\n", + "*Perform cross validation in your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| h | int | | Forecast horizon. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| level | Optional | None | Confidence level between 0 and 100 for prediction intervals. |\n", - "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names.. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", - "| n_windows | int | 1 | Number of windows to evaluate. |\n", + "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", + "| n_windows | Annotated | 1 | Number of windows to evaluate. |\n", "| step_size | Optional | None | Step size between each cross validation window. If None it will be equal to `h`. |\n", - "| finetune_steps | int | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", - "| finetune_loss | str | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", - "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning,
and 5 means that the entire model is finetuned. |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| refit | bool | True | Fine-tune the model in each window. If `False`, only fine-tunes on the first window.
Only used if `finetune_steps` > 0. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| hist_exog_list | Optional | None | Column names of the historical exogenous features. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with cross validation forecasts.** |" + "| **Returns** | **AnyDFType** | | **DataFrame with cross validation forecasts.** |" ], "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.cross_validation\n", "\n", - "> NixtlaClient.cross_validation (df:pandas.core.frame.DataFrame, h:int,\n", - "> freq:Optional[str]=None,\n", + "> NixtlaClient.cross_validation (df:~AnyDFType, h:Annotated[int,Gt(gt=0)],\n", + "> freq:Union[str,int,pandas._libs.tslibs.off\n", + "> sets.BaseOffset,NoneType]=None,\n", "> id_col:str='unique_id', time_col:str='ds',\n", - "> target_col:str='y', level:Optional[List[Un\n", + "> target_col:str='y', level:Optional[list[Un\n", "> ion[int,float]]]=None,\n", - "> quantiles:Optional[List[float]]=None,\n", + "> quantiles:Optional[list[float]]=None,\n", "> validate_api_key:bool=False,\n", - "> n_windows:int=1,\n", - "> step_size:Optional[int]=None,\n", - "> finetune_steps:int=0,\n", - "> finetune_loss:str='default',\n", - "> clean_ex_first:bool=True,\n", - "> date_features:Union[bool,List[str]]=False,\n", - "> date_features_to_one_hot:Union[bool,List[s\n", - "> tr]]=True, model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", - "\n", - "Perform cross validation in your time series using TimeGPT.\n", + "> n_windows:Annotated[int,Gt(gt=0)]=1, step_\n", + "> size:Optional[Annotated[int,Gt(gt=0)]]=Non\n", + "> e,\n", + "> finetune_steps:Annotated[int,Ge(ge=0)]=0,\n", + "> finetune_depth:Literal[1,2,3,4,5]=1, finet\n", + "> une_loss:Literal['default','mae','mse','rm\n", + "> se','mape','smape']='default',\n", + "> refit:bool=True, clean_ex_first:bool=True,\n", + "> hist_exog_list:Optional[list[str]]=None,\n", + "> date_features:Union[bool,list[str]]=False,\n", + "> date_features_to_one_hot:Union[bool,list[s\n", + "> tr]]=False, model:Literal['azureai','timeg\n", + "> pt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Opti\n", + "> onal[Annotated[int,Gt(gt=0)]]=None)\n", + "\n", + "*Perform cross validation in your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| h | int | | Forecast horizon. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| level | Optional | None | Confidence level between 0 and 100 for prediction intervals. |\n", - "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names.. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", - "| n_windows | int | 1 | Number of windows to evaluate. |\n", + "| quantiles | Optional | None | Quantiles to forecast, list between (0, 1).
`level` and `quantiles` should not be used simultaneously.
The output dataframe will have the quantile columns
formatted as TimeGPT-q-(100 * q) for each q.
100 * q represents percentiles but we choose this notation
to avoid having dots in column names. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", + "| n_windows | Annotated | 1 | Number of windows to evaluate. |\n", "| step_size | Optional | None | Step size between each cross validation window. If None it will be equal to `h`. |\n", - "| finetune_steps | int | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", - "| finetune_loss | str | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", - "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning,
and 5 means that the entire model is finetuned. |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| refit | bool | True | Fine-tune the model in each window. If `False`, only fine-tunes on the first window.
Only used if `finetune_steps` > 0. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| hist_exog_list | Optional | None | Column names of the historical exogenous features. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with cross validation forecasts.** |" + "| **Returns** | **AnyDFType** | | **DataFrame with cross validation forecasts.** |" ] }, "execution_count": null, @@ -422,72 +507,82 @@ "text/markdown": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.detect_anomalies\n", "\n", - "> NixtlaClient.detect_anomalies (df:pandas.core.frame.DataFrame,\n", - "> freq:Optional[str]=None,\n", + "> NixtlaClient.detect_anomalies (df:~AnyDFType,\n", + "> freq:Union[str,int,pandas._libs.tslibs.off\n", + "> sets.BaseOffset,NoneType]=None,\n", "> id_col:str='unique_id', time_col:str='ds',\n", "> target_col:str='y',\n", "> level:Union[int,float]=99,\n", "> clean_ex_first:bool=True,\n", "> validate_api_key:bool=False,\n", - "> date_features:Union[bool,List[str]]=False,\n", - "> date_features_to_one_hot:Union[bool,List[s\n", - "> tr]]=True, model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", + "> date_features:Union[bool,list[str]]=False,\n", + "> date_features_to_one_hot:Union[bool,list[s\n", + "> tr]]=False, model:Literal['azureai','timeg\n", + "> pt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Opti\n", + "> onal[Annotated[int,Gt(gt=0)]]=None)\n", "\n", - "Detect anomalies in your time series using TimeGPT.\n", + "*Detect anomalies in your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| level | Union | 99 | Confidence level between 0 and 100 for detecting the anomalies. |\n", "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with anomalies flagged with 1 detected by TimeGPT.** |" + "| **Returns** | **AnyDFType** | | **DataFrame with anomalies flagged by TimeGPT.** |" ], "text/plain": [ "---\n", "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", "## NixtlaClient.detect_anomalies\n", "\n", - "> NixtlaClient.detect_anomalies (df:pandas.core.frame.DataFrame,\n", - "> freq:Optional[str]=None,\n", + "> NixtlaClient.detect_anomalies (df:~AnyDFType,\n", + "> freq:Union[str,int,pandas._libs.tslibs.off\n", + "> sets.BaseOffset,NoneType]=None,\n", "> id_col:str='unique_id', time_col:str='ds',\n", "> target_col:str='y',\n", "> level:Union[int,float]=99,\n", "> clean_ex_first:bool=True,\n", "> validate_api_key:bool=False,\n", - "> date_features:Union[bool,List[str]]=False,\n", - "> date_features_to_one_hot:Union[bool,List[s\n", - "> tr]]=True, model:str='timegpt-1',\n", - "> num_partitions:Optional[int]=None)\n", + "> date_features:Union[bool,list[str]]=False,\n", + "> date_features_to_one_hot:Union[bool,list[s\n", + "> tr]]=False, model:Literal['azureai','timeg\n", + "> pt-1','timegpt-1-long-\n", + "> horizon']='timegpt-1', num_partitions:Opti\n", + "> onal[Annotated[int,Gt(gt=0)]]=None)\n", "\n", - "Detect anomalies in your time series using TimeGPT.\n", + "*Detect anomalies in your time series using TimeGPT.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| df | DataFrame | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", - "| freq | Optional | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| freq | Union | None | Frequency of the timestamps. If `None`, it will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", "| id_col | str | unique_id | Column that identifies each serie. |\n", "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", "| target_col | str | y | Column that contains the target. |\n", "| level | Union | 99 | Confidence level between 0 and 100 for detecting the anomalies. |\n", "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts
using TimeGPT. |\n", - "| validate_api_key | bool | False | If True, validates api_key before
sending requests. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True automatically adds most used date features for the
frequency of `df`. |\n", - "| date_features_to_one_hot | Union | True | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", - "| model | str | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are
one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting
if you want to predict more than one seasonal
period given the frequency of your data. |\n", "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal
to the available parallel resources in distributed environments. |\n", - "| **Returns** | **pandas.DataFrame** | | **DataFrame with anomalies flagged with 1 detected by TimeGPT.** |" + "| **Returns** | **AnyDFType** | | **DataFrame with anomalies flagged by TimeGPT.** |" ] }, "execution_count": null, @@ -497,8 +592,151 @@ ], "source": [ "#| echo: false\n", + "from nbdev.showdoc import show_doc\n", "show_doc(NixtlaClient.detect_anomalies, title_level=2)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "---\n", + "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", + "## NixtlaClient.detect_anomalies_realtime\n", + "\n", + "> NixtlaClient.detect_anomalies_realtime (df:~AnyDFType,\n", + "> h:Annotated[int,Gt(gt=0)], detect\n", + "> ion_size:Annotated[int,Gt(gt=0)],\n", + "> threshold_method:Literal['univari\n", + "> ate','multivariate']='univariate'\n", + "> , freq:Union[str,int,pandas._libs\n", + "> .tslibs.offsets.BaseOffset,NoneTy\n", + "> pe]=None, id_col:str='unique_id',\n", + "> time_col:str='ds',\n", + "> target_col:str='y',\n", + "> level:Union[int,float]=99,\n", + "> clean_ex_first:bool=True, step_si\n", + "> ze:Optional[Annotated[int,Gt(gt=0\n", + "> )]]=None, finetune_steps:Annotate\n", + "> d[int,Ge(ge=0)]=0, finetune_depth\n", + "> :Literal[1,2,3,4,5]=1, finetune_l\n", + "> oss:Literal['default','mae','mse'\n", + "> ,'rmse','mape','smape']='default'\n", + "> , validate_api_key:bool=False, da\n", + "> te_features:Union[bool,list[str]]\n", + "> =False, date_features_to_one_hot:\n", + "> Union[bool,list[str]]=False, mode\n", + "> l:Literal['azureai','timegpt-\n", + "> 1','timegpt-1-long-\n", + "> horizon']='timegpt-1',\n", + "> refit:bool=False, num_partitions:\n", + "> Optional[Annotated[int,Gt(gt=0)]]\n", + "> =None)\n", + "\n", + "*Real-time anomaly detection in your time series using TimeGPT.*\n", + "\n", + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| detection_size | Annotated | | The length of the sequence where anomalies will be detected starting from the end of the dataset. |\n", + "| threshold_method | Literal | univariate | The method used to calculate the intervals for anomaly detection.
Use `univariate` to flag anomalies independently for each series in the dataset.
Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series
must have the same length. |\n", + "| freq | Union | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| id_col | str | unique_id | Column that identifies each series. |\n", + "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", + "| target_col | str | y | Column that contains the target. |\n", + "| level | Union | 99 | Confidence level between 0 and 100 for detecting the anomalies. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| step_size | Optional | None | Step size between each cross validation window. If None it will be equal to `h`. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning,
and 5 means that the entire model is finetuned. |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", + "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True, automatically adds most used date features for the frequency of `df`. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| refit | bool | False | Fine-tune the model in each window. If False, only fine-tunes on the first window.
Only used if finetune_steps > 0.e |\n", + "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal to the available parallel resources in distributed environments. |\n", + "| **Returns** | **AnyDFType** | | **DataFrame with anomalies flagged by TimeGPT.** |" + ], + "text/plain": [ + "---\n", + "\n", + "[source](https://github.com/Nixtla/nixtla/blob/main/nixtla/nixtla_client.py#LNone){target=\"_blank\" style=\"float:right; font-size:smaller\"}\n", + "\n", + "## NixtlaClient.detect_anomalies_realtime\n", + "\n", + "> NixtlaClient.detect_anomalies_realtime (df:~AnyDFType,\n", + "> h:Annotated[int,Gt(gt=0)], detect\n", + "> ion_size:Annotated[int,Gt(gt=0)],\n", + "> threshold_method:Literal['univari\n", + "> ate','multivariate']='univariate'\n", + "> , freq:Union[str,int,pandas._libs\n", + "> .tslibs.offsets.BaseOffset,NoneTy\n", + "> pe]=None, id_col:str='unique_id',\n", + "> time_col:str='ds',\n", + "> target_col:str='y',\n", + "> level:Union[int,float]=99,\n", + "> clean_ex_first:bool=True, step_si\n", + "> ze:Optional[Annotated[int,Gt(gt=0\n", + "> )]]=None, finetune_steps:Annotate\n", + "> d[int,Ge(ge=0)]=0, finetune_depth\n", + "> :Literal[1,2,3,4,5]=1, finetune_l\n", + "> oss:Literal['default','mae','mse'\n", + "> ,'rmse','mape','smape']='default'\n", + "> , validate_api_key:bool=False, da\n", + "> te_features:Union[bool,list[str]]\n", + "> =False, date_features_to_one_hot:\n", + "> Union[bool,list[str]]=False, mode\n", + "> l:Literal['azureai','timegpt-\n", + "> 1','timegpt-1-long-\n", + "> horizon']='timegpt-1',\n", + "> refit:bool=False, num_partitions:\n", + "> Optional[Annotated[int,Gt(gt=0)]]\n", + "> =None)\n", + "\n", + "*Real-time anomaly detection in your time series using TimeGPT.*\n", + "\n", + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| df | AnyDFType | | The DataFrame on which the function will operate. Expected to contain at least the following columns:
- time_col:
Column name in `df` that contains the time indices of the time series. This is typically a datetime
column with regular intervals, e.g., hourly, daily, monthly data points.
- target_col:
Column name in `df` that contains the target variable of the time series, i.e., the variable we
wish to predict or analyze.
- id_col:
Column name in `df` that identifies unique time series. Each unique value in this column
corresponds to a unique time series. |\n", + "| h | Annotated | | Forecast horizon. |\n", + "| detection_size | Annotated | | The length of the sequence where anomalies will be detected starting from the end of the dataset. |\n", + "| threshold_method | Literal | univariate | The method used to calculate the intervals for anomaly detection.
Use `univariate` to flag anomalies independently for each series in the dataset.
Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series
must have the same length. |\n", + "| freq | Union | None | Frequency of the data. By default, the freq will be inferred automatically.
See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). |\n", + "| id_col | str | unique_id | Column that identifies each series. |\n", + "| time_col | str | ds | Column that identifies each timestep, its values can be timestamps or integers. |\n", + "| target_col | str | y | Column that contains the target. |\n", + "| level | Union | 99 | Confidence level between 0 and 100 for detecting the anomalies. |\n", + "| clean_ex_first | bool | True | Clean exogenous signal before making forecasts using TimeGPT. |\n", + "| step_size | Optional | None | Step size between each cross validation window. If None it will be equal to `h`. |\n", + "| finetune_steps | Annotated | 0 | Number of steps used to finetune TimeGPT in the
new data. |\n", + "| finetune_depth | Literal | 1 | The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning,
and 5 means that the entire model is finetuned. |\n", + "| finetune_loss | Literal | default | Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. |\n", + "| validate_api_key | bool | False | If True, validates api_key before sending requests. |\n", + "| date_features | Union | False | Features computed from the dates.
Can be pandas date attributes or functions that will take the dates as input.
If True, automatically adds most used date features for the frequency of `df`. |\n", + "| date_features_to_one_hot | Union | False | Apply one-hot encoding to these date features.
If `date_features=True`, then all date features are one-hot encoded by default. |\n", + "| model | Literal | timegpt-1 | Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.
We recommend using `timegpt-1-long-horizon` for forecasting if you want to predict more than one seasonal
period given the frequency of your data. |\n", + "| refit | bool | False | Fine-tune the model in each window. If False, only fine-tunes on the first window.
Only used if finetune_steps > 0.e |\n", + "| num_partitions | Optional | None | Number of partitions to use.
If None, the number of partitions will be equal to the available parallel resources in distributed environments. |\n", + "| **Returns** | **AnyDFType** | | **DataFrame with anomalies flagged by TimeGPT.** |" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#| echo: false\n", + "show_doc(NixtlaClient.detect_anomalies_realtime, title_level=2)" + ] } ], "metadata": { diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 7162a965..8782df85 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1678,7 +1678,8 @@ " refit: bool = False,\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", - " \"\"\"Real-time anomaly detection in your time series using TimeGPT.\n", + " \"\"\"\n", + " Real-time anomaly detection in your time series using TimeGPT.\n", "\n", " Parameters\n", " ----------\n", @@ -1688,59 +1689,66 @@ " Column name in `df` that contains the time indices of the time series. This is typically a datetime\n", " column with regular intervals, e.g., hourly, daily, monthly data points.\n", " - target_col:\n", - " Column name in `df` that contains the target variable of the time series, i.e., the variable we \n", + " Column name in `df` that contains the target variable of the time series, i.e., the variable we\n", " wish to predict or analyze.\n", - " Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column:\n", " - id_col:\n", " Column name in `df` that identifies unique time series. Each unique value in this column\n", " corresponds to a unique time series.\n", " h : int\n", " Forecast horizon.\n", - " detection_size: int\n", + " detection_size : int\n", " The length of the sequence where anomalies will be detected starting from the end of the dataset.\n", - " threshold_method: str (default='univariate')\n", + " threshold_method : str, optional (default='univariate')\n", " The method used to calculate the intervals for anomaly detection.\n", " Use `univariate` to flag anomalies independently for each series in the dataset.\n", " Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series\n", " must have the same length.\n", - " freq : str\n", + " freq : str, optional\n", " Frequency of the data. By default, the freq will be inferred automatically.\n", " See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases).\n", - " id_col : str (default='unique_id')\n", - " Column that identifies each serie.\n", - " time_col : str (default='ds')\n", + " id_col : str, optional (default='unique_id')\n", + " Column that identifies each series.\n", + " time_col : str, optional (default='ds')\n", " Column that identifies each timestep, its values can be timestamps or integers.\n", - " target_col : str (default='y')\n", + " target_col : str, optional (default='y')\n", " Column that contains the target.\n", - " level : float (default=99)\n", + " level : float, optional (default=99)\n", " Confidence level between 0 and 100 for detecting the anomalies.\n", - " clean_ex_first : bool (default=True)\n", - " Clean exogenous signal before making forecasts\n", - " using TimeGPT.\n", - " validate_api_key : bool (default=False)\n", + " clean_ex_first : bool, optional (default=True)\n", + " Clean exogenous signal before making forecasts using TimeGPT.\n", + " step_size : int, optional (default=None)\n", + " Step size between each cross validation window. If None it will be equal to `h`.\n", + " finetune_steps : int (default=0)\n", + " Number of steps used to finetune TimeGPT in the\n", + " new data.\n", + " finetune_depth : int (default=1)\n", + " The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning,\n", + " and 5 means that the entire model is finetuned.\n", + " finetune_loss : str (default='default')\n", + " Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`.\n", + " validate_api_key : bool, optional (default=False)\n", " If True, validates api_key before sending requests.\n", - " date_features : bool or list of str or callable, optional (default=False)\n", - " Features computed from the dates. \n", + " date_features : bool or list of str, optional (default=False)\n", + " Features computed from the dates.\n", " Can be pandas date attributes or functions that will take the dates as input.\n", - " If True automatically adds most used date features for the \n", - " frequency of `df`.\n", - " date_features_to_one_hot : bool or list of str (default=False)\n", + " If True, automatically adds most used date features for the frequency of `df`.\n", + " date_features_to_one_hot : bool or list of str, optional (default=False)\n", " Apply one-hot encoding to these date features.\n", - " If `date_features=True`, then all date features are\n", - " one-hot encoded by default.\n", - " model : str (default='timegpt-1')\n", - " Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`. \n", - " We recommend using `timegpt-1-long-horizon` for forecasting \n", - " if you want to predict more than one seasonal \n", + " If `date_features=True`, then all date features are one-hot encoded by default.\n", + " model : str, optional (default='timegpt-1')\n", + " Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`.\n", + " We recommend using `timegpt-1-long-horizon` for forecasting if you want to predict more than one seasonal\n", " period given the frequency of your data.\n", - " num_partitions : int (default=None)\n", + " refit : bool, optional (default=False)\n", + " Fine-tune the model in each window. If False, only fine-tunes on the first window.\n", + " Only used if finetune_steps > 0.e\n", + " num_partitions : int, optional (default=None)\n", " Number of partitions to use.\n", - " If None, the number of partitions will be equal\n", - " to the available parallel resources in distributed environments.\n", - " \n", + " If None, the number of partitions will be equal to the available parallel resources in distributed environments.\n", + "\n", " Returns\n", " -------\n", - " pandas, polars, dask or spark DataFrame or ray Dataset.\n", + " pandas, polars, dask or spark DataFrame or ray Dataset\n", " DataFrame with anomalies flagged by TimeGPT.\n", " \"\"\"\n", " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 5b044c30..e8a5d2d3 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1615,7 +1615,8 @@ def detect_anomalies_realtime( refit: bool = False, num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: - """Real-time anomaly detection in your time series using TimeGPT. + """ + Real-time anomaly detection in your time series using TimeGPT. Parameters ---------- @@ -1627,57 +1628,64 @@ def detect_anomalies_realtime( - target_col: Column name in `df` that contains the target variable of the time series, i.e., the variable we wish to predict or analyze. - Additionally, you can pass multiple time series (stacked in the dataframe) considering an additional column: - id_col: Column name in `df` that identifies unique time series. Each unique value in this column corresponds to a unique time series. h : int Forecast horizon. - detection_size: int + detection_size : int The length of the sequence where anomalies will be detected starting from the end of the dataset. - threshold_method: str (default='univariate') + threshold_method : str, optional (default='univariate') The method used to calculate the intervals for anomaly detection. Use `univariate` to flag anomalies independently for each series in the dataset. Use `multivariate` to have a global threshold across all series in the dataset. For this method, all series must have the same length. - freq : str + freq : str, optional Frequency of the data. By default, the freq will be inferred automatically. See [pandas' available frequencies](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases). - id_col : str (default='unique_id') - Column that identifies each serie. - time_col : str (default='ds') + id_col : str, optional (default='unique_id') + Column that identifies each series. + time_col : str, optional (default='ds') Column that identifies each timestep, its values can be timestamps or integers. - target_col : str (default='y') + target_col : str, optional (default='y') Column that contains the target. - level : float (default=99) + level : float, optional (default=99) Confidence level between 0 and 100 for detecting the anomalies. - clean_ex_first : bool (default=True) - Clean exogenous signal before making forecasts - using TimeGPT. - validate_api_key : bool (default=False) + clean_ex_first : bool, optional (default=True) + Clean exogenous signal before making forecasts using TimeGPT. + step_size : int, optional (default=None) + Step size between each cross validation window. If None it will be equal to `h`. + finetune_steps : int (default=0) + Number of steps used to finetune TimeGPT in the + new data. + finetune_depth : int (default=1) + The depth of the finetuning. Uses a scale from 1 to 5, where 1 means little finetuning, + and 5 means that the entire model is finetuned. + finetune_loss : str (default='default') + Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. + validate_api_key : bool, optional (default=False) If True, validates api_key before sending requests. - date_features : bool or list of str or callable, optional (default=False) + date_features : bool or list of str, optional (default=False) Features computed from the dates. Can be pandas date attributes or functions that will take the dates as input. - If True automatically adds most used date features for the - frequency of `df`. - date_features_to_one_hot : bool or list of str (default=False) + If True, automatically adds most used date features for the frequency of `df`. + date_features_to_one_hot : bool or list of str, optional (default=False) Apply one-hot encoding to these date features. - If `date_features=True`, then all date features are - one-hot encoded by default. - model : str (default='timegpt-1') + If `date_features=True`, then all date features are one-hot encoded by default. + model : str, optional (default='timegpt-1') Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon`. - We recommend using `timegpt-1-long-horizon` for forecasting - if you want to predict more than one seasonal + We recommend using `timegpt-1-long-horizon` for forecasting if you want to predict more than one seasonal period given the frequency of your data. - num_partitions : int (default=None) + refit : bool, optional (default=False) + Fine-tune the model in each window. If False, only fine-tunes on the first window. + Only used if finetune_steps > 0.e + num_partitions : int, optional (default=None) Number of partitions to use. - If None, the number of partitions will be equal - to the available parallel resources in distributed environments. + If None, the number of partitions will be equal to the available parallel resources in distributed environments. Returns ------- - pandas, polars, dask or spark DataFrame or ray Dataset. + pandas, polars, dask or spark DataFrame or ray Dataset DataFrame with anomalies flagged by TimeGPT. """ if not isinstance(df, (pd.DataFrame, pl_DataFrame)): From d8572c599550f63c55fd8df721f6b5f2674657c4 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Thu, 12 Dec 2024 05:51:35 +0800 Subject: [PATCH 22/38] change tutorials --- .../01_quickstart.ipynb | 88 ++-- ...adjusting_detection_accuracy_process.ipynb | 436 +++++++++++++++++ .../02_improve_detection_accuracy.ipynb | 459 ------------------ ...te_vs_multivariate_anomaly_detection.ipynb | 48 +- nbs/mint.json | 2 +- 5 files changed, 525 insertions(+), 508 deletions(-) create mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb delete mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb index a3b3c411..3a2d24c4 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb @@ -100,6 +100,28 @@ ")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 👍 Use an Azure AI endpoint\n", + "> \n", + "> To use an Azure AI endpoint, set the `base_url` argument:\n", + "> \n", + "> `nixtla_client = NixtlaClient(base_url=\"you azure ai endpoint\", api_key=\"your api_key\")`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " nixtla_client = NixtlaClient()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -177,8 +199,6 @@ "output_type": "stream", "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", - "/Users/yibeihu/anaconda3/envs/test/lib/python3.12/site-packages/utilsforecast/preprocessing.py:131: FutureWarning: 'm' is deprecated and will be removed in a future version, please use 'ME' instead.\n", - " offset = pd.tseries.frequencies.to_offset(freq)\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] @@ -220,55 +240,55 @@ " machine-1-1_y_29\n", " 2020-02-01 22:11:00\n", " 0.606017\n", - " 0.481175\n", + " 0.544625\n", " True\n", - " 8.012249\n", - " 0.523800\n", - " 0.438550\n", + " 18.463266\n", + " 0.553161\n", + " 0.536090\n", " \n", " \n", " 96\n", " machine-1-1_y_29\n", " 2020-02-01 22:12:00\n", " 0.044413\n", - " 0.551303\n", + " 0.570869\n", " True\n", - " -30.163446\n", - " 0.593928\n", - " 0.508678\n", + " -158.933850\n", + " 0.579404\n", + " 0.562333\n", " \n", " \n", " 97\n", " machine-1-1_y_29\n", " 2020-02-01 22:13:00\n", " 0.038682\n", - " 0.538656\n", + " 0.560303\n", " True\n", - " -29.745493\n", - " 0.581281\n", - " 0.496031\n", + " -157.474880\n", + " 0.568839\n", + " 0.551767\n", " \n", " \n", " 98\n", " machine-1-1_y_29\n", " 2020-02-01 22:14:00\n", " 0.024355\n", - " 0.534585\n", + " 0.521797\n", " True\n", - " -30.365294\n", - " 0.577210\n", - " 0.491960\n", + " -150.178240\n", + " 0.530333\n", + " 0.513261\n", " \n", " \n", " 99\n", " machine-1-1_y_29\n", " 2020-02-01 22:15:00\n", " 0.044413\n", - " 0.551937\n", + " 0.467860\n", " True\n", - " -30.201727\n", - " 0.594561\n", - " 0.509312\n", + " -127.848570\n", + " 0.476396\n", + " 0.459325\n", " \n", " \n", "\n", @@ -276,18 +296,18 @@ ], "text/plain": [ " unique_id ts y TimeGPT anomaly \\\n", - "95 machine-1-1_y_29 2020-02-01 22:11:00 0.606017 0.481175 True \n", - "96 machine-1-1_y_29 2020-02-01 22:12:00 0.044413 0.551303 True \n", - "97 machine-1-1_y_29 2020-02-01 22:13:00 0.038682 0.538656 True \n", - "98 machine-1-1_y_29 2020-02-01 22:14:00 0.024355 0.534585 True \n", - "99 machine-1-1_y_29 2020-02-01 22:15:00 0.044413 0.551937 True \n", + "95 machine-1-1_y_29 2020-02-01 22:11:00 0.606017 0.544625 True \n", + "96 machine-1-1_y_29 2020-02-01 22:12:00 0.044413 0.570869 True \n", + "97 machine-1-1_y_29 2020-02-01 22:13:00 0.038682 0.560303 True \n", + "98 machine-1-1_y_29 2020-02-01 22:14:00 0.024355 0.521797 True \n", + "99 machine-1-1_y_29 2020-02-01 22:15:00 0.044413 0.467860 True \n", "\n", " anomaly_score TimeGPT-hi-99 TimeGPT-lo-99 \n", - "95 8.012249 0.523800 0.438550 \n", - "96 -30.163446 0.593928 0.508678 \n", - "97 -29.745493 0.581281 0.496031 \n", - "98 -30.365294 0.577210 0.491960 \n", - "99 -30.201727 0.594561 0.509312 " + "95 18.463266 0.553161 0.536090 \n", + "96 -158.933850 0.579404 0.562333 \n", + "97 -157.474880 0.568839 0.551767 \n", + "98 -150.178240 0.530333 0.513261 \n", + "99 -127.848570 0.476396 0.459325 " ] }, "execution_count": null, @@ -300,11 +320,11 @@ " df,\n", " time_col='ts', \n", " target_col='y', \n", - " freq='m', # Specify the frequency of the data\n", + " freq='min', # Specify the frequency of the data\n", " h=10, # Specify the forecast horizon\n", " level=99, # Set the confidence level for anomaly detection\n", " detection_size=100) # How many steps you want for analyzing anomalies\n", - "anomaly_online.tail()\n" + "anomaly_online.tail()" ] }, { diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb new file mode 100644 index 00000000..60ce9520 --- /dev/null +++ b/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb @@ -0,0 +1,436 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "!pip install -Uqq nixtla" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "from nixtla.utils import in_colab" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide \n", + "IN_COLAB = in_colab()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " from nixtla.utils import colab_badge\n", + " from dotenv import load_dotenv" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "def plot_anomaly(df, anomaly_df, time_col = 'ts', target_col = 'y'):\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left')\n", + " plt.figure(figsize=(12, 2))\n", + " plt.plot(merged_df[time_col], merged_df[target_col], label='y', color='navy', alpha=0.8)\n", + " plt.plot(merged_df[time_col], merged_df['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", + " plt.scatter(merged_df.loc[merged_df['anomaly'] == True, time_col], merged_df.loc[merged_df['anomaly'] == True, target_col], color='orchid', label='Anomalies Detected')\n", + " plt.legend()\n", + " plt.tight_layout()\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Adjusting the Anomaly Detection Process\n", + "\n", + "This notebook explores methods to improve anomaly detection by refining the detection process. TimeGPT leverages its forecasting capabilities to identify anomalies based on forecast errors. By optimizing forecast parameters and accuracy, you can align anomaly detection with specific use cases and improve its effectiveness." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#| echo: false\n", + "if not IN_COLAB:\n", + " load_dotenv()\n", + " colab_badge('docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from nixtla import NixtlaClient" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "nixtla_client = NixtlaClient(\n", + " # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n", + " api_key = 'my_api_key_provided_by_nixtla'\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 👍 Use an Azure AI endpoint\n", + "> \n", + "> To use an Azure AI endpoint, set the `base_url` argument:\n", + "> \n", + "> `nixtla_client = NixtlaClient(base_url=\"you azure ai endpoint\", api_key=\"your api_key\")`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " nixtla_client = NixtlaClient()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1 Conduct anomaly detection\n", + "After initializing an instance of `NixtlaClient`, let’s explore an example using the Peyton Manning dataset." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " unique_id ds y\n", + "2764 0 2015-07-05 6.499787\n", + "2765 0 2015-07-06 6.859615\n", + "2766 0 2015-07-07 6.881411\n", + "2767 0 2015-07-08 6.997596\n", + "2768 0 2015-07-09 7.152269" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv('https://datasets-nixtla.s3.amazonaws.com/peyton-manning.csv',parse_dates = ['ds']).tail(200)\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "# Base case for anomaly detection using detect_anomaly_realtime\n", + "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " freq='D',\n", + " h=14,\n", + " level=80,\n", + " detection_size=150\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_df, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Adjusting the Anomaly Detection Process\n", + "This section explores two key approaches to enhancing anomaly detection: fine-tuning the model to boost forecast accuracy and adjusting forecast horizons and step sizes to optimize time series segmentation and analysis. These strategies allow for a more tailored and effective anomaly detection process." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.1 Finetune TimeGPT\n", + "TimeGPT uses forecast errors for anomaly detection, so improving forecast accuracy reduces noise in the errors, leading to better anomaly detection. You can fine-tune the model using the following parameters:\n", + "* `finetune_steps`: Number of steps for finetuning TimeGPT on new data.\n", + "* `finetune_depth`: Intensity of fine-tuning, with options ranging from 1 to 5.\n", + "* `finetune_loss`: Loss function to be used during the fine-tuning process." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " freq='D',\n", + " h=14,\n", + " level=80,\n", + " detection_size=150,\n", + " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", + " finetune_depth = 2, # Intensity of finetuning\n", + " finetune_loss = 'mae' # Loss function used during the finetuning process\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_online_ft, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2.2 Change forecast horizon and step\n", + "Similar to cross-validation, the anomaly detection method generates forecasts for historical data by splitting the time series into overlapping windows. The way these windows are defined can impact the anomaly detection results. Two key parameters control this process:\n", + "* `h`: Specifies how many steps into the future the forecast is made for each window.\n", + "* `step_size`: Determines the interval between the starting points of consecutive windows." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" + ] + } + ], + "source": [ + "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(\n", + " df,\n", + " time_col='ds',\n", + " target_col='y',\n", + " freq='D',\n", + " h=2, # Forecast horizon\n", + " step_size = 1, # Step size for moving through the time series data\n", + " level=80, \n", + " detection_size=150\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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u3Mlbb73Fjh07UKvVvfxbCIIgCIIgCMLRLxaUMhg0qNVtH3aJoJQgCMe7oz5TSmiSnZ3NsmXLuPfee5k6dSqBQIA+ffowbdo0VCrli7B///6sX7+exx57jPvvv5+ysjL0ej3Dhg3j7rvv5vbbb+/l30IQBEEQBEEQjn5u98H7SYEISgmCIEhyd4+Q6ySn04nVasXhcGCxWFpc5/f72bt3L3379sVgMPTSCgWh54nXviAIgiAIwtFl/fpKbr75C/Lzrcyde1Wb2xQVNXLllR9isej5/vubeniFgiB0Nzkq4yvyEnGGUVs0GPslIKmOrIqr7nKw2E5zIlNKEARBEARBEAShi3k8SvnewTKlkpKUk41OZ4BIJNpumZ8gCEcf9yYntXOrCTvC8cs0Vg1pl2ZgHtV+kOZ4Iz71BEEQBEEQBEEQulisp1R7Tc4BLBZ9vE+twxHokXUJgtD93JucVL5W3iIgBRB2hKl8rRz3JmcvrezII4JSgiAIgiAIgiAIXaypp1T7QSm1WkViopJJJfpKCcKxQY7K1M6tPug2tZ9UI0ePqE5KvUYEpQRBEARBEARBELqYx3PoRucgmp0LwrHGV+SNZ0j5QmHmbCik1OFusU3YHsZX5O2N5R1xRFBKEARBEARBEAShizX1lGo/UwpEUEoQjjURZ1PJ3teFZXy6rZi3Nu4+6HbHMxGUEgRBEARBEARB6GJNPaVEppQgHE/UlqZ5crvqHQAUNbgOut3xTASlBEEQBEEQBEEQulisp1RCwsEzpWIT+ERQShCODcZ+CWisSsCpcH9Qqt7rxx0IxbfR2DQY+yX0yvqONCIoJQiCIAiCIAiC0MViPaXM5o5lSjU2+rp9TYIgdD9JJZF2aQYNvgAN3qapmsX2pmyptEsykFRSbyzviNPpoNTSpUuZMWMG2dnZSJLEp59+2uJ6WZZ56KGHyMrKwmg0cvbZZ1NYWNhV6xUEQRAEQRAEQTjiiZ5SgnD8Mo+y0DhBB+qmwFNxoxuNTUPWrBzMoyy9uLojS6eDUh6Ph9GjR/P888+3ef2TTz7Jv//9b1588UV++uknTCYT5557Ln6/+JA92hUUFPDMM8/E/7+toKRweBYvXowkSdjt9t5eiiAIgiAIgtAFRE8pQTi+Ffk86LP16DJ0aFO0NAxSUfDgABGQOkCng1LTp0/n0Ucf5ZJLLml1nSzLPPPMMzzwwANcdNFFjBo1ijlz5lBRUSGCF/utWLECtVrN+eef39tL+dkqKyuZPn16t92/JEnxH5PJxMCBA5k5cyZr167t9H0dGFDrCiKQJAiCIAiCILSnoz2lmoJSgYNuJwjC0WXr1hoATjk9H1WCmr31LlGy14Yu7Sm1d+9eqqqqOPvss+OXWa1WJkyYwIoVK9q8TSAQwOl0tvg5lr3yyiv85je/YenSpVRUVPT2cn6WzMxM9Hp9tz7Ga6+9RmVlJVu3buX555/H7XYzYcIE5syZ062PKwiCIAiCIAg/R6x871A9pZKSjIDIlBKEY4ksy2zbVgfAxRcPAaCoqJFIJNqbyzoidWlQqqqqCoCMjIwWl2dkZMSvO9Djjz+O1WqN/+Tl5XXlktolR2W8uz241jnw7vYgR+Vuf0y3283777/Pr371K84//3xef/31FtfHMm8WLlzI+PHjSUhIYOLEiezcubPFdi+88AL9+/dHp9MxePBg3nzzzRbXS5LESy+9xAUXXEBCQgJDhw5lxYoV7N69m8mTJ2MymZg4cSJ79uyJ32bPnj1cdNFFZGRkYDabOfHEE/nuu+8O+vscWL5XWlrKlVdeic1mIzk5mYsuuoji4uIWv99JJ52EyWTCZrMxadIkSkpKDvoYNpuNzMxMCgoKmDp1Kh999BHXXXcdd9xxB42NjfHtfvzxR0477TSMRiN5eXnceeedeDweACZPnkxJSQm/+93v4plXHbkdKEHTe++9l7y8PPR6PQMGDOCVV16huLiYKVOmAJCUlIQkScycOROAaDTK448/Tt++fTEajYwePZqPPvqoxe81f/58Bg0ahNFoZMqUKS2eJ0EQBEEQBOHoF2t03tGeUqLRuSAcO0pLnbhcAXQ6Naef3oeEBC3BYISSEkdvL+2I0+vT9+6//34cDkf8p7S0tNsf073JSfHDuyl/fh9Vb1ZQ/vw+ih/ejXtT92ZpffDBBwwZMoTBgwdz/fXX8+qrryLLrYNhf/7zn3n66adZs2YNGo2G2bNnx6/75JNPuOuuu/jDH/7Ali1buPXWW5k1axaLFi1qcR+PPPIIN954Ixs2bGDIkCFce+213Hrrrdx///2sWbMGWZa544474tu73W7OO+88Fi5cyPr165k2bRozZsxg3759HfrdQqEQ5557LomJifzwww8sW7YMs9nMtGnTCAaDhMNhLr74Ys444ww2bdrEihUruOWWW1oEiDrqd7/7HS6Xi2+//RZQAmrTpk3jsssuY9OmTbz//vv8+OOP8d9v7ty55Obm8vDDD1NZWUllZWWHbgdw44038u677/Lvf/+b7du389JLL2E2m8nLy+Pjjz8GYOfOnVRWVvKvf/0LUAKtc+bM4cUXX2Tr1q387ne/4/rrr2fJkiWAEry79NJLmTFjBhs2bOCXv/wl9913X6efB0EQBEEQBOHIJMtyp3tK+f1h/P5wt69NEITut21bLQCDB6ei06kZMCAZgF276ntzWUckTVfeWWZmJgDV1dVkZWXFL6+urmbMmDFt3kav13d7CVhz7k1OKl8rb3V52BGm8rVysmbRbY3HXnnlFa6//noApk2bhsPhYMmSJUyePLnFdn//+98544wzALjvvvs4//zz8fv9GAwGnnrqKWbOnMntt98OwO9//3tWrlzJU089Fc/cAZg1axZXXnklAPfeey+nnHIKDz74IOeeey4Ad911F7NmzYpvP3r0aEaPHh3//0ceeYRPPvmEzz//vEWQpj3vv/8+0WiU//3vf/FA02uvvYbNZmPx4sWMHz8eh8PBBRdcQP/+/QEYOnRop56/mCFDlPTHWHbR448/znXXXcdvf/tbAAYOHMi///1vzjjjDF544QWSk5NRq9UkJibGX6Mdud2+ffv44IMP+Pbbb+Mlqf369YvfPjlZ+WBJT0/HZrMBSmbVY489xnfffccpp5wSv82PP/7ISy+9FL/v/v378/TTTwMwePBgNm/ezBNPPHFYz4cgCEcfOSrjK/IScYZRWzQY+yWIHgOCIAjHEL8/THR/JcahekqZTFrUahWRSBSHw4/BYO6JJQqC0I1i/aSGD08DYNCgFDZtqmbXrnqmTRvQm0s74nRpplTfvn3JzMxk4cKF8cucTic//fRT/AC9N8lRmdq51QfdpvaT6m4p5du5cyerVq3immuuAUCj0XDVVVfxyiuvtNp21KhR8X/Hgns1NcqLevv27UyaNKnF9pMmTWL79u3t3kesnHLkyJEtLvP7/fEeXm63m7vvvpuhQ4dis9kwm81s3769w5lSGzduZPfu3SQmJmI2mzGbzSQnJ+P3+9mzZw/JycnMnDmTc889lxkzZvCvf/0rnrHUWbHssljwa+PGjbz++uvxxzWbzZx77rlEo1H27t170DUf7HYbNmxArVbHA4QdsXv3brxeL+ecc06L+50zZ068XHL79u1MmDChxe2OhPeHIAg9o7eydQVBEISeE+snJUkSRuPB8wAkSRIT+AThGLN1q5IpNWxYU1AKoLBQZEodqNOZUm63m927d8f/P3bwnpycTH5+Pr/97W959NFHGThwIH379uXBBx8kOzubiy++uCvXfVh8RV7CjoOnxIbtYXxFXhIGmLr0sV955RXC4TDZ2dnxy2RZRq/X89xzz2G1WuOXa7VNZ1NigZdotHMN0dq6j4Pd79133823337LU089xYABAzAajVx++eUEg8EOPZ7b7eaEE07g7bffbnVdWpryRnzttde48847+frrr3n//fd54IEH+Pbbbzn55JM79bvFAnB9+/aNP/att97KnXfe2Wrb/Pz8g675YLdr/jrvKLfbDcC8efPIyclpcV1PZgQKgnBk6s1sXUEQhO4gMj/b1ryfVEfaVSQlGaiv94qglCAcA8LhKDt2KE3OR4xIB2DgwFj5XkOvretI1emg1Jo1a1qUif3+978H4KabbuL111/nnnvuwePxcMstt2C32zn11FP5+uuvMRgMXbfqwxRxdqxGu6PbdVQ4HGbOnDk8/fTTTJ06tcV1F198Me+++y633XZbh+5r6NChLFu2jJtuuil+2bJlyxg2bNjPWuOyZcuYOXMml1xyCaAEVzrTfHvcuHG8//77pKenY7G0f0A1duxYxo4dy/33388pp5zCO++80+mg1DPPPIPFYomX1I0bN45t27YxYED7aZA6nY5IJNJqzQe73ciRI4lGoyxZsqTFRMnm9wm0uN9hw4ah1+vZt29fuxlWQ4cO5fPPP29x2cqVK9tduyAIx4YDs3Wr3F6SDHr0GnX8stpPqjGNSBQHdIIgHBXcm5zUzq1ucdJXY9WQdmnGcR9gj2VKHaqfVExTs3MRlBKEo11RUSPBYASzWUdurvJZOGBAMpIkUV/vpaHBR3KysZdXeeTodPne5MmTkWW51U9skpwkSTz88MNUVVXh9/v57rvvGDRoUFev+7CoLR2LwXV0u4768ssvaWxs5Be/+AUjRoxo8XPZZZe1WcLXnj/+8Y+8/vrrvPDCCxQWFvLPf/6TuXPncvfdd/+sNQ4cOJC5c+eyYcMGNm7cyLXXXtup7KzrrruO1NRULrroIn744Qf27t3L4sWLufPOOykrK2Pv3r3cf//9rFixgpKSEhYsWEBhYeEh+0rZ7XaqqqooKSnh22+/5fLLL+edd97hhRdeiPdxuvfee1m+fDl33HEHGzZsoLCwkM8++6xFL6yCggKWLl1KeXk5dXV1HbpdQUEBN910E7Nnz+bTTz+N/04ffPABAH369EGSJL788ktqa2txu90kJiZy991387vf/Y433niDPXv2sG7dOp599lneeOMNAG677TYKCwv54x//yM6dO3nnnXdaTWIUBOHY0zxbt9Th5vYvlvHkjxtbbBPL1j3a9MZEW0EQelcs8/PAKoRY5ufxXpLc0cl7MaJ8TxCOHVu2KK13hg1LQ7X/RKPRqCUvTwlQiRK+lnp9+l5PMvZLQGM9eMBJY1PSjrvSK6+8wtlnn92iRC/msssuY82aNWzatKlD93XxxRfzr3/9i6eeeorhw4fz0ksv8dprr7Vqlt5Z//znP0lKSmLixInMmDGDc889l3HjxnX49gkJCSxdupT8/HwuvfRShg4dyi9+8Qv8fj8Wi4WEhAR27NjBZZddxqBBg7jlllv49a9/za233nrQ+501axZZWVkMGTKEX/3qV5jNZlatWsW1114b32bUqFEsWbKEXbt2cdpppzF27FgeeuihFqWSDz/8MMXFxfTv3z9eTtiR273wwgtcfvnl3H777QwZMoSbb74Zj8cDQE5ODn/729+47777yMjIiAezHnnkER588EEef/xxhg4dyrRp05g3b1683DA/P5+PP/6YTz/9lNGjR/Piiy/y2GOPdfi5FgTh6NQ8C3d7rR1k2FXXeixwV2frdjfRI0sQjj8HZn66gyFCkZYnM7urT+vR4nAzpURQShCOfgc2OY9pKuETQanmJDnWNfoI4XQ6sVqtOByOVmVgfr+fvXv30rdv38MuB2yvn0dM1qyc4z7dWDjydMVrXxCE3uXd7aH8eWV4xCtrdzJvp/LvOZdNxqxvOpOe8+v8Lu9r2F3Ed6ogHJ+af55VubzcNX8FE3LT+f2kkS22O5o+z7ravHm7+MtfFnPyybk899x5h9z+xRfX8L//rePyy4dx332n9sAKBUHoLtdc8zGFhfU89dRUJk8uiF/+yivreOGFNZx33kAefnhK+3dwjDhYbKe54ypTCpQGslmzclplTGlsGrHzLAiCIHSb5tm6pQ53/PJKd1O5Xndk63aX3pxoKwhC72qe0bmt1k4oEmX5vmp8oXC72x1vmjKlRPmeIBxPfL4Qe/YozcxbZ0opE/hEplRLXds86ShhHmXBNCJRTAoRBEEQeoykkki7NIPK18opdXjil1e5fAxMUcq70y7JOGq+i5r3yIrKMn9fsh61pOL+00fHJ01110RbQegpYrJc25r3X63x+ADlc2BzdQMn5aa3ud3xpqmnVMfK95KSYo3Ofd22JkEQut/OnfVEozJpaSbS0lru/wwapASl9u61EwxG0OnUbd3Fcee4/aaQVJLYSRYEQRB6lHmUBdMVARrfD8Yvq3J70dg0pF1ydE2rap4BUeb0sL5COetX4fKSYzG1uZ0gHE3EZLn2xTI/w44w1e6mIMq6ivp4UOpoyvzsDoefKRXotjUJgtD92usnBZCRYSIxUY/LFaC42B4PUh3vjrvyPUEQBEHoTdXGMPpsPdp0HdoULd5hOgoeHHDUHeQ2z4DY09DU1HxHrb3d7QThaCEmyx1cLPMTmjKlADZU1RNrV3s0ZX52h85mSonyPeFoJKbvNok9F+sXlhENRBk6JLXVNpIkiWbnbRB7ioIgCILQg4qKGgHQGNVEozJVHt9ReeDWPFOiqMEVv3xnnYOz+ucAIlNCODo175cWlWWWFlcxIj2JVFPToJHaT6oxjUg8Kt+7XUXp0wo1X/4Qv6zG7aOaAGNn9T/qAu1d7ef0lJJlOV4GLQgxbZUTA71WYiyySZs0fy42LCkn5A6S8lMA90nOVs/FoEEprFtXKYJSzRyVQakjbGCgIHQ78ZoXhGPHnj1KUGrs2EzWrq2krOzozLho3iOrqLHpd9hZZ4//+3jPlBCOTs37pa0sreHfK7YwNjuFByePi28j+qUp9ENNeGwSWoOOfjlWisod7Buv5rTj7IC0LYebKRWJRPF4QpjNHbudcHxoKwCkSlCKnqLeaPyyngoKtTd9N5ZNmjWL4yYw1fy5cPqD8ZLmPjpTm89FrGSvsFAEpWKOqvI9rVY50+D1eg+xpSAcW2Kv+dh7QBCEo1csU+qMMwoAqKvz4vOFenFFh888ykLGTdkUO5umCZY6PPiNsphoKxy1mvdB213vAGBrjZ1wNNrudserqio3sixjtOi4+PrhqPQqVv5U1tvLOiJ0NlNKr9dgNCrbimbnQnPtlRNHvdEWASnomRLj5tmksizT4PW3OoF+vEzfPXAS8e797QyyEhMw65T384HPRVP5XoNIPNjvqMqUUqvV2Gw2amqU5mEJCQkitVU4psmyjNfrpaamBpvNhlotJjQIwtEuFpQaMyYTi0WP0xmgvNzFgAHJvbyyw9OYJBNN02CWtSSZDVQ1eHCeZxYBKeGo1bwP2r79kzKD4Qh7G13xSZkHbne8qqhQSnezsxOZODGPZ55Zydq1lQQCYfT64/v5aQpKdTzjyWYz4POFsNv95OVZD30D4Zh3YNDDFwpT7w2gkkClklBJEmpJIlGnRadpOk7ozhLj5tmkP5ZU8/+Wb2bmuEFcOKRPfJvjJZu0+XMBULj/RMag1Kb374HPRf/+yahUEg6Hn9paL+npx/Zz1BFH3bdFZmYmQDwwJQjHA5vNFn/tC4LQs7pyJLzd7qehQTkDXlBgIzfXwrZttZSVOY/aoNSOHXUADBmVTn6+hXnzCtm8pYZJp+b38soE4fA075e2z9GUBbitxh4PSol+aYry8lhQykzfvjYyMsxUV7tZu7aSiRPzenl1vaupfK/jWe42m4GqSheOGpEpJSiaBz3cgRB3zV9Bo6/1hEaDVs3/m34KGWYj0L1BoeZZoivLlGPyhXvKWwSlDtzuWHXg71hsV74z+iUltrudTqemoMBGUVEjhYX1IijFURiUkiSJrKws0tPTCYWOznIHQegMrVYrMqQEoZd0dRPPWJZUdnYiCQnaFkGpo1UsKDV0aCoDBiQzb14hmzZVH+JWgnDkivVL2/NyCXWepklo22sbuWioctDVm/3SovvLQFRHQL+2WKZUTo4FSZKYNCmPuXO3s3x5qQhKHUamVIrNwDV9+5Kw0kdgqB99tuHQNxKOac2DGe9s2k2jL4BGpUKjlojKSlVFKBrFH4qwqqyGGc0CQ90VFGqeJRrLDCp1eKh0eclKTGhzu2PVgb9juVPJrs21mA663cCByRQVNbJrVz2TJomTeEftK0WtVosDdUEQBKHbdEcTzz17GgDo1y8JgNxc5fZHc1Bq+/b9mVJDUhk2LA2ALVtqiEblI+KgWRAOh3mUBd/kBJgroRz5wfZaO2qrmvRLM3u1PPWRR5bw/ffFvPfeZWRlJR76Bt2oefkewCmn5MaDUse7zmZKRUNRzjCmEjAGCAejOFc5SL1IL1qVHOdiwYyiBiff7Fb2SR6cMpaRGU3Z1Z9uL2bO+kI2Vze0CEp1V1Aolk1aW+VpEbhfU14bf/zjJZu0eWZtJBql0qX0Ac5uFpRq67kYNCiFb77ZQ2FhQ4+u90h1VDU6FwRBEISecGAPh7YcThPPWKZU//4tg1KlpY7DWGXvk2W5qXxvSCr9+iVhMunwekPs3i12tISjW5UmhD5bz0mT80jINOC3Skg3pvVqQMpu9zNvXiEeT5AfftjXa+uIOTAodeKJOajVKvbtc1BefvQG23+uSCSK369kqXQkU0oOyzR+W0eqWk8wGiUQjhCqDRLY5z/kbYVjm7FfAiqLmv+u2YEsy0zqk9EiIAXE/39LTSOR/QMZujMoFMsm3V3f8j2+qqw2/u/jZfpu7LkAqPH4iURltGoVaaamLMe2nouBA5UJfGvWVFBT4+m5BR+hRFBKEARBEA7QvIdDVJb5ZFsxy/a1DFLF+jV0xp49saCUsgPZlCnl+rlL7hUVFS7c7iBarZq+fW2oVBIjRijZUqKETzjaxTIbR0zIZPSELFR6FRs2VvXqmpYsKY6X7x0J77EDg1Jms47Ro5UDtBUrjt8pfF5vU4uRhISDZ0rJEZmGhXUEygOodSo+KilhL0pPKecah5jOdZyTVBLrUr3srHOg16iZOXZQq236JiVi1mnxhyLx6W/dHRQyj7JQPUgCtcSIDOVE27ZaOz7D8Td91zzKQtasHKqjSq+vrMQEVJKExqZp97k44YQs8vOtNDT4uP32ecf9xE0RlBIEQRCEAzTvw/DB5iLe3FDIM8s34w6E2t3uUGRZjgelYuV7eXnKjkplpYtwONrubY9UsdK9gQOT0WqVkvrRo5WhDEfCAbMg/BzNg8hjxyqv6w0bejcotXDh3vi/N27s3feYzxeKD26IBaVAKeEDWDK/CNc6B97dnh4fDR9xKycNeiugE+snpdWq0enabzciR2UaF9UrGVEaicYBaip8PrZ6HUg6iXBDCP/e4/tg9XglR2W8uz1U/FDLi+9vQJui5ZqTBpCS0JSBo0pQKT9SU2Boq9PRY0Gh3XYn+mw9F946gkFj0tCkaSmdpDmuAlIx5lEWgmea0abrGHRKOjm/zqfgwQHtPhd6vYbnnz+P9HQTxcV27rjjK1yu1g3sjxdHbU8pQRAEQegusT4Mq8pq+GBLEQCRqMzKshrO7p/TaruOaGz043D4kSSJggIbAKmpCej1GgKBMJWVrqNuBHjz0r2YUaOULInePmAWhJ+rKSiVRFqaUgazfn3vBaWczgA//dTU566y0kVNjafXJjdVVipTpsxmHRaLPn75mJRkAhUBVlSWsM9cgE6t/lkDIg5H45IGghUBbFOSe2UkfUf6SUVDUexLGpSgkxqSz0nFuEsJZtU6fJhHJuJa68S5xoGhwHhclEIJiuZDVl5Zu4OaQic5KWZm/elEDEn6FtOAQcnuPjXDzdq37RRnR3rkfRaNymzbpuwDjDs7j0YpzKuvrueHH/dx/gWts7mOByX7HKj0KgaelNGhz52srERefPECfvnLz9m5s4677vqa558/D6Ox4xM7jxUiU0oQBEEQ9oudmQzbQ1SG/TyzYgtAvDfAD8VNB6Sd7dcQKwXKyUnEYFCCWZIkkZOjZBgcjc3O2wpKjRiRjiRJlJc741kUgnC0sdv91Ncr5bl9+yYxalQGKpVERYWr1/p/LF1aQiQSpX//ZAYNUvqRbN7ce8HfA0v3QDmYNn3vwabVEghH2FGr9MuLDYhwb+r+z7loIEqwUsk48O3pXIl1VznU5L1QXZDaT6qVgJQKks9KxZBrwGZTvmvsdj+mEYlIBhURRxjf7t75PYSeFxuyEnaEKW50MX+XUgb7y1GDqH+nmqg3QuI4KwkDTEgqCUklkTDAxOlXDUClV7FxYxXBYKTb11la6sDlCqDTqenfP5kzzlAanC9fXtojj38kKimxA8RPPB5M2BHCsdJOUh089/Q0EhP1bNpUzR/+sOC4fP5EUEoQBEEQUHYEix/eTfnz+yh+vZTHv1mHPxRhWHoSf5kyDoDNNQ00+JSDnc72a4g1OY+V7sXESviOtqDUgU3OY8xmXbyRuyjhE45WsfdrdnYiCQlaTCZdvDFtb5XwLVyoZG2edVbfeN+m3sxIjAWlYoH12IAISZIYk7X/uaqsa3GbwxkQ0VmBMj/sf4hAuZ9ooOdLo9vLlJJlGfcWF7WfVxNxhFGZ1KScl4ahjxGgRVBKpVOROFp5bl3rHMiRrn3eQg0hHD/ZifqPvwPgI1XzISuyLPPftUpz85Pz0hm9/z3V3nuooMBGamoCwWCkR757t25VmpoPHZqKRqNi6NA0UlIS8HpDrFtX2e2PfzChuiCByp4fElBSogTh+/RpP+s94otgX9ZIzUdVeDa7cK11Yl7t5/lbJ5NrNbNqVTn33//dUdnS4ecQQSlBEAThuNf8zKQsyzy7citlDg/JCXruPnUk2RYTg1OtIMPKutrD6tfQvBSouaYJfEdXUKq62oPd7ketVjFgQMtJQLESPhGUEo5WsczG5u/X3uwr5fEEWblSKd07++x+8d5tvRmUik3Xy8pSAifNB0SMy1YC1Wsr6lvc5nAGRHSWv6zZwWgE/KU9n7HZlCnVFJSK+CM0fFuHc4UdImDoYyT90gz0WU09gmJBKaczQCQSJWGYGVWCmogrgndX12boOZY34tnkwr7M3qX3Kxy+5u+hnXUOttfY0alVzBrXVA7X3ntIkiROPDEbgNWry1td39W2bKkBYPjwdABUKonTT88HlKzO3hJqCFH7RQ31X9YSKO+5wJTHE6SuTvm79Olja3V9NBjFtc5BzfuVeLe5IQr6XAPaDB1EwOZS8di0E7mmXwGla+tZu6b7/4ZHEhGUEgRBEI5psZK89hruNj8zCTB3WzErS2vQqFTcc+pobAY9KpOK868bijZdx3qT57D6NcQyL2KT92KaJvAdXUGpWJZU//5JrRr5NvWV6t2m0IJwuA6clAkwZkzvBaV++GEfoVCEggIbffva4u+xHTvqCAQ6PnChKx2YKdV88MOYzBRUkkSpw83uekeL23VmQERnybJMYH8QSpep9LnqjUbhTZlSSvleNBCl7tNqAiV+UINloo2kc1JQGVp+dlqtTb25HI4AKo0K85hYtpQTOdw12VIRb4RglZL16y/yEqjo+awSobXm741ypxKEHJqeRJrJ2O52zZ14otLzcvXqim5aYZNYptSIEenxy04/XSnhW7KkpFeGDERDURq/r4P97xP70gaiwZ7JOIplSSUnGzGbW5bthhpD1HxQiWutEzkko03TkXJ+GinT00i7MIPUi9Ix9DNiSzIw9YQ+3H/OOMbkp/XIuo8UIiglCIIgHLOal+RVvVmhlOY9vLtFX5PmZyZ3Nzh5e9NuAH45fjCDUpUU7KgnyjlT+6ExqtmytabTASRZlg9Svqc8xtEalGpeuhcTO2Devr3uuOyNcDSprfWIkfNtaCtTKhaUKixswO0O9uh6mpfuSZJEVpaZ1NQEIpEo27bV9uhaYioqlEbnsZ5SzQc/mPVaTi9Qnq+PtxW3uF1nBkR0VqguRNQXRdJKWE62AeAv9ffYgWnMgZlSvr1eIq4IKrOatAszMA9PRJJal3+r1ap403i7XQkUmYaYUZnVRL0RPDvcXbI+f7EvXuIIStZUV5cHCp3X/L1R61H+/ukmw0G3a278eCVTauvWWrzeUJvbdIVgMMKuXUoWZPOg1Ekn5WAwaKiudlNY2NBtj98ex3I74cYwqgQ16kQ1EXcE50p7jzz2wfpJOVfaifqiqC0aks5KIfWidPTZTX9XXbqe5LNSSb8qi/zJGeSNTEKXpW91P8cyEZQSBEEQjknNS/KaO7DhbvMzjqtKa0CGE3PTmDogt8XtrCptfIdvwYI9nVpLfb0PpzOASiW12mGJZUqVl7uI9vDY9J/jYEGpvDwLNpuBYDDCzp11ra7vCdu21XLbbV+KEsKDWLBgD9Onv82TTy7r7aUcUWRZbjNTKjU1gdxcC7Is9+jryusNsWxZKQBnndUPUEp1ertMtilTSvkMM/ZLQGNtOli+ZFgBSPBTaQ37HEowpbMDIjorliWlzzGgTdWitmogIhMo7dlMoAMzpfz7y61MQ81oU9tufh7TvK8UgKSWSBylBP68O7umhM+3V1mPeYwFlVFFuDGMZ6urS+5bOHzN30PVHuW1nHFAltTB3kPZ2Ynk5FiIRKKsX999fZ0KC+sJhSLYbAaysszxy/V6DSefrOw7LVlS3G2P3xZvoQffLg9IkHRmMrYzkkFS3jM9UcLbXj+pYHVA6XOngpTpaRj7JbQZkAbQJGqwTrCRMiO93W2OVSIoJQiCIBxzDizJs/sDbKtpbLFNrFlo8zOO22rtAJyQ3TrQorZomDZtAABff727U+uJZUnl5lpalbplZppRqSQCgXC8H8HRYPv29oNSvX3AHAiE+dOfFrJmTQUvv7y2xx//aBAOR3nuuVUAfPjhth7pQdIRvmIfrg3OXs3eOlgQuTf6Si1bto9gMEJuroWBA5uCZL3Z7NzlCuByKeVfsYNSSSWRdmlGfJs8q5mTc5Usik/2Z0t1dkBEZ/n3B58aNCHefnsz2jwlwBMLwvSU5plSEX+EwP5pgMa+xoPdDFDKf6Bl9qyxfwKoIdwQIlT387L0Ir5IfDphwhATiScqB9GudU4iHpHZ2puav4dq9gel0s0tXzOHeg819ZXqvhK+WOne8OFprYInsRK+pUv3ddvjHyhkD+FYpuxnJY6zoM8yoM8yYBqhfDbZlzZ2+8CDWKbUgf2kXGuVYFXCQBOaDmaJHm8BKRBBKUEQBOEY1LwkLyrLPLxoPQ98t4atzQJTsWahsTOTwUiEwv29T4altSyxi52ZnDKlAK1WTVFRI7t3dzw1PbbtgU3OATQaVbxR8NFSwldX56W+3otKJcVH0x8odsDcG0Gp//1vXfy5XLWqnMbGnu8pc6SbP78wnukC8OijP+D3905vopiwM0zj93W4Vjt6pQ9QTKx0Ly/P2iqI3Bt9pRYu3As0le45VjRS82ElowcoPUc2bqzu8SBe7LWTlGTEaGxq5m0eZSFrVk482+PS4X0B+KG0Cvk862H14+uoiC9CqDZIVJZ54F8/8MwzK5m7ohCAQKmfaKjnSviaZ0r5i30QBW2KFo1Ve4hbNgUVFi3aG79MZVBjyFeCE97dPy9bKla6p03ToUnUkDDIhDZdhxySca6y/6z7Fn6+2HuoNrB/0u/+8j2NTdOhISs9EZQ6sMl5c6eemo8kSWzfXktNTdc252+LHJZpXFiPHJLRZesxj2l6fhLHW1FbNUS9ERwrGg9yLz9fW5lSgcoAgfIAqMA8tvs++44FIiglCIIgHHOal+StLa+juFE5gFpdVttqu9iZyaIGF6FIFItBR46lZWp87MxkYqKeiROV1PRvvt5NxBMhGowe8oCwvX5SMXl5vd/svKHBx/ff7+3QwW2sdK+gwIbB0PaZv6ZMqZoePWDevbuBOXM2AWCx6IlGZb7/fu8hbnV8CYej/O9/6wC45ZYTSE83UV7u7PWsMudqO+xP1HBvdvVatlR7kzIBxo7NApSDsp7ol+b3h1uU7vlLfHi2uAnbw6TslTEbtDgc/h6f3llernymxvpJNWceZaHgoQHk/DqfU+8awqnnFqDN0vPxms6VPXdWoNwPMpQ0utldZgfgv+9vwksEOSwrJTQ9pHmmVCzAaujbsbLFc87pD8CKFWXxbDSAhEEmAHy7vT+r/1Nscpthf9aWJElYJyaBpNx3oFI0Pe9t+qEmPDbQpusYObsfOb/Op+DBAR0K6sbaDOzaVY/D0T1/y1hQqnk/qZgkm4EJo7LINBpZurj7p/A5VjYSbgihMqpImpLSIotMpVGRtL+Mz1foxV/SPSc7olG5WVDKFr/ctW5/ltRgE5rE7uuldywQQSlBEAThmBMryZNlmbnbmgISG6rq29zOPMpC5VAJ1BJD02zx1Om2zkxOmzYAFaBf66PqnXKq3iin8n9lVL5eRtXbFdR9Xk2ooWV5RXuT92I6M4FPlmWWLy/l6aeXt8h0+TlkWeYPf1jAPfd8G8/KOJjt25XgXlulezHDhqWhVquorfV02ToPJRqV+fvffyASiTJ5cgEzZ44BOt8D7Fg3b94uKipcJCcbufHG0dx//6kAvPXWpvjftqcFqwP4i3wgAWoI1QQJ1fRsM/GYtpqcx+TlWUhONhIMRuLB2e60YkUpPl+IrKxEBvdNwv7j/rP9KpBdEW4aNRCJnp90WVnZcvLegSSVRMIAE4njrNz82xMB+PzzXd1aohwo9ROJRPlqTTGglMFFIlG+2lCCjNyj2XexTKlEvTY+2a4jpXugnLzo1y+JcDjK4sXF8cv1OQZURhVRX/SwR903L91r3pdIl6YjYYgS9HIst7eaUiv0rOpqD9GojCFRS/7kdBIGmDpc9pqSkkC/fknIsszatV3fV8rpDLBvnxJsGT48jYgngv3HBuq+qKH63QoqXyvjhtwCru/bl9BCO66a7nvfheqCeLfv7yM1JQV1grrVNroMPaaRyueU/YcGov6uP5lQU+MhEAij0ajin4mBSj/BigCoaZG9JbRNBKUEQRCEY06sJG9brZ2ddQ40KhVIsM/uptGn7JAf2Cx0e50dfbaeidf0J/OG7HbPTJ52Wh8mZqdjjqhxuZoOmuWQTNQbIVgdpP6bunhvjpZNk9vOlGovKCVHZSUzYquLiDfC5s3V3Hrrl9x551e8++4Wbrnli58V8JFlmWBNgI0fljDWY+JXgwaxbfmhd2IP1uQ8Rq/XxEv43nln82GvsTM+/ngbmzdXk5Cg5Z57JnH22UpT6HXrqo6qfl3dKRyO8sor6wGYOXMMBoOG007rw9Sp/YlGZR55ZCnhcM9OKpNlGcdPdgCMA00kDFAOjt2beqfxcltNzmMkSYqX8HVnI+GY5qV7zp8cRL0R1FYNqRekg0ZikM3C6RkZPd5X6mCZUgcaOzaT0aMzCIUivP32pm5ZjxyV8Zf5KS93sbm6gbw8K//734XodGq+2bSP2lov/n0+5HDPBFtimVJJQQ1EQZOsRWM7dOlezNSpSrbUt98WxS+T1BLGAcp3lnfX4ZVFxUv3UnX4iLBo0d74gA3LeCuSQUW4IYRnW9dM+RMOT+x7PTu77SmNMbIsE6jwU7+glpqPqnCstBOsCXDi+FgJX9f3CoxN+8zNtWAx62n4rg7vdg/BqgARdwSikJ5hRlaB5Iuy4G8bcVR2z/evd8/+rL8CI/qc1lMKYywnWNEkaYj6ojiW27t8HbF+Urm5FtRqFbIs41qr7M8lDDajMYssqUMRQSlBEAThmBMryYtlSZ3ZL5t+ScrB08YqJQuiebPQaFSOH9SdPL2AxHHWds9MakJwwaB8AFZ668mclUPG9dmkX5lJ6sUZSv8Cd4SGBXVEQ1Fqa714PEHUahX5+dZW9wety/ei/giujU5qPqikYUEdFd/VsvDPG/jgz6sp29aITqcmPd1EVZWb2277kqqqjh9AyLKMf5+PxsX1VL9dQd1nNVT9WEe6wYBJoyG1DKKHCErs2KFknA0d2n5QCuDmm8cB8PHH2ykv797yopoaD88+qzTuvuOOk0hPN5GdncjIkRnIsszChUWHuIfuJ0fkXh+73jxL6tJLh8Yvv/vuiVgsenbtquett7oncNAe/14foeogkkbCMt4SP6vtL/ERdnTfWPO2yLLcLLOx7SByT/WVCoUiLF2qlL+cNTIPX6FXyQg4Ixldhp6k05OxWPScmJKCa0fPBhGaHzSHXWHlgHh/YPFAkiQxe/ZYAD76aDtOZ6DN7X6OUG2QoDvEnn2NVHi9/OpX48nPtzJ79liqfD42F9YS8kfw91AJXywoZXYr3yGdnTh4zjlKQP2nn8pblGDFArb+fb7Dyvjw720q3fvLXxbzxz9+Gz9poDKosYxXvqPcG5yH/B4Quk8sE7G9oK8ckfEWeqj7pJr6ebUESvyEG0N4Nruo+6yGc7RpnJ6ezp51XZ/NuXVrU+mea4OTUE0QSa/CNiWZ1AvTybg2i4Jf9WH0nQNxyxFCrjDfPbKJxn1d219KluX4VEtj/6b3VzAY4d///onHHvuBUEh5j0gaCdsZKaAC3x5vvIS1qxzYTypYGVAyEtWQOPrQgXtBBKUEQRCEY1SFIcSWoBOVRuLioX0Ylak05N5sb2xVkrd3byNOZwCjUcvgwW037o5xrrCTmWamzOvlnaW7kCVQG9VorFp0aTpSzk1FMqgI1QWxL25gz24lgJOfb0WrbZ1aDk2ZUu4qP/alDVS9W4lrlYOIK0JRuZ35y4poqPcxIimJeyaO4t27zuWVR6dxYr8MtI4oj965kIr1DfiKfYTtoTZ78cgRGe8uD7UfV9PwTR2+Qq9y1tAbZNW+Gr6tqsQTDqMOQO2P9a1uH9PY6KO6WjkAHjz44EGpE8Zmcf7JfUnX6nnrhQ2EXWEi/gjRUJRoIErEGyHsChOyhwjVBwnWBAhU+vGX+fGX+JSG9a6ONd9+6qnleL0hRoxI5/LLh8Uvjx3c9XYJXzQQpfaTaqrfryTi650JV21lSUUDSk+05GQjf/jDKQC8/PLaeHlGd5MjMs7V+/tujDDz2rubePSZH1Fn6UAG95aeDbZUVbnxekNoNCry8qxEw1E8W10Em008iwWl1qyp7NYMvM2ba/B6Q2Qkm0jbH/8yjUhEl6EHlAOx1FOUbK5RUiINe3vuuWoelHKsaFQOiDe52m3CPXFiHoMGpeDzhXjvvS1dvh5/qZ/SfU52O1wMGpwaz5K88cbR5OVZ2VTTQEmJIx6U6W4eTxC9SoXepXwWd7R0L6ZPHxuDBqUQiURZtKg4frk2VYcmWQsR8BV1riyq+RTAalUgHvB8770tRCJKACphkAl1opqoL6qURQm9ovn760DeQg/V71ViX9xAqD4EGomEYWaSzkzB2D8BSSuRbNAzIS2NM/Wp7PugnECFv8t69MUm753QLw33euVkk21SEgkDTOgy9KhNGiRJYti4DE6/ZxhOOUzIHeb7xzZTX9R12a+hmiARdwRJK2HIU95fdruf22+fx5w5G5k7dzuvvbYhvr0uTRff73Msa+zS7+HiYjugvG+bZ0mZhphRiyypDhFBKUEQBOGY9PrrG1AZ1Zx341BOuG8IZ84ajDZdxy69L56JEbN+vXLEN3JkOmp1+1+N/hIf/hIfSSlGfvI00NDg48MPt7XYRmPVknxOKqiVUomKRcqZyn79bO3eb06OhZE2G5dn5OLY6oKwjDZFS3lqmD/MW8mbRUXsyQgxfkYfBg1OQeuUkdd6ueeMUdw4uD+nGlJY/WIh1fOqqfmwiup3KmlYWBc/mHZvdlH9QSX2JQ2EG0NIWgnTcDMp56fx8t5CPi8ro8+p6awLO5BlmdrVjfGDlwPFdkjz860kJLRfjhLxRKj9qIrr+vfj2r59KShVs/eVEqrfrKDq9XKq5pRT/XYFNe9VUvthFbVzq6n7rIb6L2tp+KqWhgV1NC6sp+6zaiKegwemliwp5vvv96JWq/jzn09D1SzD7eyz+yFJEhs3VseDaT1NlmXsPyjPfdQTwbnS3ivrODBLyrfHS9Wb5TiWNSLLMuedN5CTT84lGIzw5JPLemRNnm1uIs4wqgQV/1u0lRdfXMO8eYV8vUtp7u3b5emWHiDtiZXuFRTYUEWh4es6HMvt1H1ajWNlI9FQlCFDUhk2LA2fL8T/+38rum0tsdKbq8f0J+qNorZoSBzfspw48/RU6tUh1JJE+WeV8bLh7iTLcvygOVOlJ1DSlMnj+LGxzew2SZKYNWsMoARBuroBc8MOJxWVLorcbu6448T4Z4BOp+aeeyay0+mkosJF3VZHj2QrejwhBlgsqFWqTpfuxcQC6t9+2zKgHmt47i3sXNCo+RTAt+ZujV9eVeVmyRIlQCWppfiUMPdGkS0VjcqdykTuKu0FpSKeCPYlDUS9EVQJahLHW8m8JgvbpCSM/RNIOjOFjOuzSTs3jUZ9mKgsU7/LSf28Wuq/qCFQ/vOCU7Iss2VLDTqViiF+E8hgHJjQIlOpuUEj0zjzTyOwyyFC3jCLn9xK7a6uOeERb9jfx4ikkSgpsTNz5qds2FAVn5r6yivr2bWr6SRb4jgLmmQtUX80/r3XFWLlewUFNoIVAYJVAVBLmEeLXlIdJYJSgiAIwjGnrMzJd98p5VqzZo0lYYCJSVcPwGjRUVfvjZfnxMR6w8QyINoSDUWxL1dulzg6kat/OQqA559f3WqnVZ+px3Z6Mm5PkPAuH6NsNs49d0Cb9ytHZPxrnFzYNx+VJOEzy6TMSEczxcoDLy4jIstcddVw/vx/U+h/eS4ZV2VhHp2IJlmLKcPI6NNycKsjFDU4WbS+lFAkStQbwV/kUw6mP6nGudJO1L1/J/ZEKxnXZGOdmESJ28MPP+5DpZKYOXMMKUMsbLbbcToC2Jc2tDlC/aefygA44YSs9p+rQJT6b2qJuCIkphowpxvwhsPsKT5gJLMEaCQkvQpVghp1ohq1VYMmRYs2XYcqQTlj37io4aCNd994YyMA118/koEDW2a6paebGDNG6W0Ve030NM9Wt9JkWU18wpW/tOeaLkPrLCkdEo7ljSCDd7sH7w4PkiRx332nIkkSK1eWdXuD+qg/gmu9ExmZ70srefeDpgPlFz7YgF8nI4dlPD2YsRFrcj64XzL1X9XuL8GQQAbPZjc1H1URLPXzpz8pwc9vvtkTf090VDAY4auvCg9ZxrZqVTkFJhPDE60gge30ZFSalrvukiTRkC/REAjgqvPT8G1dtwcSGhv9+P1hNCoV+t1KBplpVCK6TD1ySFber20Efs46qx8FBTaczgC/+tU87PauCUxFvBGKN9UTjcpY+5s4+eTcFtefckoeQ07OxB0KsXtHfbe/92RZxuMJMsRiQaOWOp0lFRObwrd6dQWNjU1rNg5IAJWSKRK2d7y8NdboPZCi4quvdgNKBhvQInstYUDvZUvV13uprz9y+v+98so6LrjgHf71r5U9+rixz96sLHOLywMVyoRJTbKWjKuzSBxrQWVomYGt0qgw9ktAfaKZ/xYWsmBXGbIKpd/l/FrqvqhpNYylo6qq3DQ0+Dg7OwuzWoM6UY31lLbLnGMGDE3l3IfG0LA/MLXw8S08/sdFfPjhVoqL7YcVGJKjcjxT0Ng/gTVrKpg58zPKypxkZyfy1luXMmVKAZFIlL/+dXG8T6KklpRpfCrl/eDvZLZhe5qX77k3K38701ATalPb2fFCayIoJQiCIBxz5szZSDQqx0tGQDljPm6cEnT66aem5p+yLMczpcaObT8o5VrnJOqOoE5UYx5r4ZJLhjJqVAY+X4gnnvix1Y6VrsDIRxuLkGWZa0YNYHxiEqG6YIvtIp4I9fNq8G73YDCo+bGmhn3pYXQZOh5//Efq67307ZvEnXdOiN9GbdZgOclG+mWZpF+eScENeZz393F8563l+Q3beWTVBpLOSyVxvBV9jh5JK6FJ0mA9LUnZiR1jQaVXvv5ffVUJUpx9dj/y862MGZPJ4qoqapw+Is4wrtWtz2iuWKEcgJ9ySl6bz5MckWn4ro5wvTKiOe2iDEbfNZAXdxfywI/rqBqnJnNmDlmzc8n6RS7Zs3LJujGHzOuyybg6m4wrs0i/NJO0izJIvSANSSsRrAzE0+EP5PeH49lbl13WVLYnh+V4CeCFp/QnNyGB1d/uI9QY6tHJUsGaAM79vXYsJ9kwjVAOMhzLGns0C+HALCnnGgdRfxRJq2SUOFY0EqwOkJtrYfx4JeD49de7u3VNrg1O5ECUwko7/++jdQD86U+nMXFiHuFwlA/X7kFGxrPN3WO9uPbsacSoVnNmQprSK8WgInVGOsnTUpUD9f394tLL4PorRgDwj38sIxjseIbS3/++lAcfXHTQA12vN8TObfWcm52NLcmAaZgZfZa+zW2Hj85g7r591Dl8hGqVsuGuygBoS+yA+ey+2cieKCqzmsRxFpKmJCPpVYRqgzjXtP7sUKkk/u//ziElJYFdu+q57bYvWwRbDlfx6lqqqz1U+Xzc8psT22wM/Ye7T2Gvz4PDGWDDe8XdWkIbCkVRR6GPyYRao8LQt3P9pGJycy0MHZpGNCq3KOFTG9Xoc5Wmzt7CjgVwov5IfArgF6v3EolEGTcuiwceOB2VSmLdusp4RomkluLTwtybXD3WHL6+3stll33A9Glvc8cd8/n66934/R0r3+4OLleAN99U+uu9+eamHhvYAVBZqZzoyslpmWkTm7poyDcgqQ8+je/aa0eitWj5cNteftTale8ejUSoOkjDd/WH9T24dWstgy0WJuSko1ZL2CanxPcnDqbvwCQueHgsjaowRGRyK9W8/ex6Lr/8A6ZPf5vf//4b/vSnhTz00CIefXQpTzzxIy+8sBqXq+3AfbA6QNQbQdKr+HZ9Cb/+9XxcrgAjR2bw+usX069fEvfdd2q8T+Ibb2yI31abqiNxfzagfVnjz84u9fvD8ROTeRmW+N/INNR8sJsJBxBBKUEQBOGYUlfn5YsvdgFKRkhzEyYoZ9BXrmzKbKisdFNT40GtVjFyZEab9xlqCOLZohyIWScmodKoUKkkHnjgdDQaFT/8sC8+JSvm1VfXM3fzXooCHgYOSMa9wUXtJ9XUvFeJY3kj3kIPtZ9WE6xWmoTutgVYWVdHaZmTL7/cxfff70WjUfHII1PQ6w/ekyA7O5EXXzwfk0nHhk3VvP3VdhLHWkg5L53Mm3JIvzwL0xBzi53YkhJ7fM2xsppRozIIRKN8uHOvcrZ/qzt+IAPKWdLiYjsqlcSJJ2a3WocsyzQubiBYEUDSSqRMS0Nj0ZCXZ+XiiwcD8Oxzq5E0EpJaOuhUIVBKIW2nKT1z3BucbWY4bN5cTSQSJT3dFD+rHPFHqJtXEy8BHOk3cU3fvpwctbHvrTJqPqjEs9Pd7cGpqD9C48J6iIKhnxHTcDOJJ1hRmdWEXWG2fFLKQw8t4pZbvqCmpnszEmIBpuuvH4XKGcG7Q3m85HNTMfQzQgQavqsn4okwffpAAL76ane3BTcingiebW5Ky5w8t3AzMvD735/CpZcO5e67J6LVqvl4eSF1Lj9RbwTf7p7JnqgocnJt374ka5RMvdTz09Gl6TDkGUm7PBPz6MT4WfZLU3MZn5dGaamD115b36H7X7ZsH/PmFQLw/ffF7U46XLeuktNS00hLNGJK1ZN4YttDEgBGj87AHgrx1vY9yPvX5lzVfT3BKipcWLVaTklPA8A6wYZKq0Jt1ihZCIBnk6vN92vfvkm8/PIFpKYmsHt3A7fe+iUNDT8vMLXic+XzyphvZMSI9Da3ycgwM+LiPJyhEPu2N7L51aI2M0G7gtsdZEBiIipJQp+iQ5vU+dK9mPZ64iUM3F/Ct9vTofeor0Qp3ZMTVbz7uVJyftNNo0lPN8X7b73/frNsqYH7s6W8ETxtNNGXZZmnnlrOX/6yKN6P6uf65svdXJvVh98OGcKQWj2rXtzFQ1d/xUt/WcGOtT07XRLgww+34fWG4mXq//znilallN0hGIxQW6t83jXPlJJlmcD+Rv0HmzQXYzLpuP32EwF44dW1RIcYyLgyC5VBRcQRxruz8985uzbVMjUri0SzDvNoC/rMtgPlbcnva+OXL57GqCk5DOyXzM1jBtPXmkhdnZelS0tYsGAP8+cX8umnO/jww2288sp6XnppbZv35ds/dc9pjPC3R5YSiUSZOrU/L754PsnJSmZiSkoCf/zjRAD++9918SxYAPNoC9pULXIgiv3HnxfEj/VftFj06OqU6YPadN1hlewez0RQShAEQTimvPvuZkKhCKNGZbTKfJowIQdQDvhimQ2xCVpDh6ZiMLQO/shRGcePjUpgoa8RQ35TKUa/fknxgM6TTy6Ll+Ps2lUfL5UaP7s/6eekYSgwgkYi4o7g2erGvljpC6FJ0pJ2UToJBcrZ9NWrK/i//1sOwG23jWfIkIM3E4/Jy7Ny332TAKVR9ZYtyoSc9gI/r7++AVmWOf30PvGSt379kjCZdOysd+BOUW5nX9pANKgcdKxYofT5GTEincTEljujsizjXGlXpuGoIfmcVLSpuvj1N998AgaDhs2bq+MNdjvC2D+BhGHKjrl9cQMRd8sz57Est3HjspAkibAjRN3nNfGJQLosPaYsI2qLGlcoRE29h4grgmNpIzUfVuEt9HRLcCoWoIu4I6gtGmynJSNJEk5PkBXOetaurWTL5/tYtXAf69ZV8uyzP3X5GmLC4SibNyuvh0kT85TXswzGQSb0WQZspyejSdIS9UZoXFjHlDMK0OnU7N3b2KIfR1fy7vJQUeZi2dZyij0ebr/9RK69diSg9Cu7/vqRRIEPVu8mEpVxb3F1a/YPQNAR4mTZSpJOhynVQOoFaWiTmw4sVBoVlpNspF2cgTZViyoMt580jDMzM3nzjU3xviLtcbuD/P3vP8T/3+UKsGZNRZvbbv+xktFJSdhsyt9HpW1/l71v3yTMZh1Fdheuvkq5iGeTC8/27umFU17u5MzMTBL0GnQ5egzNytMMfYxN79clDW1mIfTpY+Pll2eQnm6iqKiRW2754rAbxteWuqBG+Uw4+9rBB932qhtH0jBAhTccpnBNDTvf2depDLzGRh+FhYd+P3i9IQZbrajVqk5P3TtQLGC0bl0lpavrcK1z4N3tQZ9rQNKriLojBCsOXgYqy3I8qLu+qh6vN0S/fknx0r2rr1Yy/r76ane8pLJFttTG1tlS69dX8d57W5g3Twki/FyyLFO+uAaLVktBHxsnDMpgVHoy4yxJWPdG2Pjv3ez8uLTH+sv5/eF4ZtR9953KlVcOB+Chhxazbl1ltz52VZUbWZYxGDTYbE3Bp3BDiKgviqSR4sMODuXCCwczaFAKbneQF19cg9qkjvcMc61zdiowGwpFCGxwo1erMWTqSRzX+X5JWoOaoTcUMPCUDMaOzOSZa0/l5cenc//9p3L33RO5664J3H77ifFhJZ9/vhO3u2WpoRyV46Wo89YVA3DmmX159NEzW53AmzZtAKef3odwOMrf/rYkHkCV1Pun8akhsM+Pd9vhf1Y27ycVC5a112NLaJ8ISgmCIAhdSpZlSkrsnSpn6QplZU7+8pdF8XT7mTPHtArIDBiQTHKyEb8/zObNypnXWFCqvX5S7o0uJZtJK2E92dbq+lmzxtKnj42GBh/PPbeKcFjpYRCJRDnzzL6cM7U/CQNNJJ+TSuYN2SRPTSVhsAmVWY1xQAKpF6ajsWrJy1MyIdasqcDrDTF2bCY33ji6U8/BtGkDmDq1P9GozIMPLsLrbbvfSGWli/nzlcyZ2Kh2UMprRo1SMg02BZ2oE9VEXBGq31eyu7atUHbGTzmlqWeLLMuEGkO4Vjvw7J+UZjs9udWZ3NTUhHjQ4fnnVxPtRCDIOsGGNkVpTnpgf6nYAcK4cVkEa4PUfVFDxBFGnagmdUY6qRekk3ZJBqopVl4qLOQ/u3ZhmWBVzhY7w9gXN1A7twrPDnergNfhCgYjvHzfclZ+Ucya9ZU8On8tN/3iM66/fi7Tp7/N3/+7go1V9Wg1am6dqOx8f/31nm4LAO3cWYffH8Zi0ZPu0xCqDyHpVVhOUl5zKq2K5HNSkPQqgtVBIlu8nH56HwDmzy/s8vXIsszu7yvZvbuBDY2NzJ49tsXrEJTXZXq6icV7KthX7iDcEMKztfsaDsuyTNn8KsxqDa5ImNwrstFY2z7TrU3RkXphBqZRiaSkGjl7QA5X5ubz3D9WHDRw9q9/raSmxkNuroXzzlOy0b7/fm+r7aKhKIl7lc9P/cAE9NkHz4pQ3rdKlufy4moST9g/YWp5I/6yrm0oDuDf56d/YiJ6owbrKUmtPmetE2xKM2FflIYFtfj2elsFf/Lzrbz00gWkp5soLrZzyy1fdPr1L8syOz8qQyNJBBOg37iDB/AlSeLuv5xGUUqQQDjKtqWV7P28okPBTo8nyE03fcp1181l5866g29rD1BgMqFWSz87KJWdncjgnCR8ZX7m/nUdVW9WUP78Pkoe24NKrzzv7s2ugwbW3eudBCsCRJF541slS+rGG0fH/24jR6YzdGgawWCETz7ZHr9dwkATanPb2VLNy6FefHFtq8BBZxVurCMnrEelkhh0RR5jb+nPWb8exvBpuUQSVcp+xQ81VH9YhWd792e5fvbZDux2PwU5Vk7Lz+BX543ixslDGGxK5MWHlrP7xyqige7JtKusbGpy3vy9FSsL02XpD1m6F6NSSdx9t5It9MknO9i9uwHTUHNTFlwnppt+OXcnGbIOnU7N0CvzO7yGA0kaieRzUtHnGZCikFkmccHJ/bj66hHccMNoZs8ey733TqJfvyS83hCff76zxe0DFQGi/igBory/ULnuF78Y22LASfyxJIn77z+VxEQ927bV8tZbm+LXaZO1JJ6gfAc6VtjjAaXOivWTGpybRKgmCCoRlDocXR6UikQiPPjgg/Tt2xej0Uj//v155JFHuv3sliAIgtC7Kitd/O9/67jkkve57LIPuO++73rscR99dCmXXvo+8+YVEo0qU8ROPTW/1baSJMWzpWIlfAfrJxWo9ONaq+xwWCcmtTnaV6dT8+c/nwbA3Lnbuf/+79i1qx6r1RBvGh2j0qgw9DFiOz2ZzGuySZqSgkqnfBXn5jaddUxI0PK3v01pcyfrYGKNqjMyzJSWOvjnP1tPBotEorz00loikSgnnZTTqtwldnC7YUsVSWemoDKrkf1R3FtcDK4zMLN/fyZmpuNa76T+61qq3qyg9qMq3BuVHWnLyTYSBpjaXN+NN47GYtFTVNTII48saTdo1ur30kgknZWi9JeqCuBYrvQ/8tuDbNqkBBfHZKdQ/2UNUV8UbYqW1BkZLcpmzjyzLyqVxPZddTTYZNKvziLxRCuSXkW4MYzjh0aq361UphQua8RX7D3sg46180uwVsq4XAE+2VXMiq0VbN9ey44ddYRCEYYOTWPUNX05+dRcJgzKZPZZw5BlmeeeW3VYj3cosdf4hNHZuPf35rKcaEVtbGrCqrFqSZqcDBJ4t7m5ZExfJOCbb/Z0KoDYEVsWVVC4uY5AJMLIqbn86lfjW21jNGr5/e9PIRCN8vH6Inz+MM4Vdhwr7Z0+IK2t9Rxy8qJ/rw93iZewLLNW7UTXTkAqRlJLWCfYSDk3jQHDUshMMDLKZWLpW7vazL5ZtaqcTz5RMkoeeuiMeFBq8eLiVs9v1eI68EVxhUIMviinQ79jLKPm9dc34MtVYxyYAFFoXFhHsPrgmTSdIYdlMuuVz6xwnrbN0jRJI5F0pvJ+DdWFaPyunqq3K7D/2ECwOoAckQnVBUl2q/nPr6Zw+8ghXJKQxWf3r+GFu3+kcE11x0rSdnnxFnuJyDKaceZDlgMDaDQq7v/HZDZpXASCYTZ9VUrl97WHvN3TT6+gosJFNCrz2Wc7D7qtv9iHSpJwE/lZpXsA7k1OxgUTISKzfF9TCVvYEca50kHYHSZQ6se+pO1hEN7dnng/vp0aL3urnaSnmzj33P7xbSRJ4uqrlUygDz/c1qIpdFvZUnv2NLBsWSmSJJGZaaax0dfh8tX2bP+0FJUkQYqGlFFWDHlGEkdbGHltAafdO5wP9pWwq9KOo9aH48dG6j6rIVjTda/r5sLhaPzk1m+mjMS1woFrhZ1LBhZw1ZC+nJmcweY3itn3TtlhNww/mPYm78VL93IPXbrX3LhxWZx1Vl+iUVnZJ1BB4nglGOPe6CTSgeyzQCDMio+KUEkS6QMtJOb8vKBLPDCVb4CwTP2COkINTfsDkiRxzTVKBt97721p8Rnp3z91b2N1PZGozPjx2Qwe3H5AOi3NxO9/fzKgBFD/8Y8fWbGilGAwgnlUIglDlSmCjYvr8Zd0vpQ4lik13KY8p/ocQ4vvVqFjujwo9cQTT/DCCy/w3HPPsX37dp544gmefPJJnn322a5+KOEI0djo44475nfL2VRBEI5s0ajM/PmF3Hbbl8yY8S4vvriGsjJlB3jp0pJuTXP3+8P83/8t45JL3ufTT3fEG5u/8cbFPPxw+wGd2GSmn34qx273s3evMhHuwEypiC9C4/cN8TKn2Bjutowbl8UllwwBiDekvffeSfHeBh2Rm2uJH1Tdc8+kVjukHWWx6Pnb3yYjSRKffrqDxYuV9UQiUebN28Xll3/Il18qPbdipYfNjR6tPA+bNtWgS9eTcVUWydPTcJii+EMRskxGbFUyrjUOAqV+5EAUNBK6LD3WU5Mwj2x/3Wazjt/+9mQkSeKLL3Zx9dUfxTPVDkVj1WI7XelX493uoe7zGopf3ccd/Qdx+/DBGLYEkMMy+hw9KRekt5p6Y7MZ4n/7BQv2oNKqSBxjIeOqLBLHW9Gm60BC6bWxzU3jt/VUvVlO7WfVOFc7CFT4O9TwN1DhJ7hSOagIpKn55V8n8K9/TYv/vPfe5bz55iVcdNVQkk9WphadW5DD6ORkVq8o65b3TGy65FnZmcghGW26joQhrV/PhnxjvCQjx6nllqGDSA1qWLO6vNW2h6u01MHXL28jGpUJpqv5wx8nthtMOOusvpx0Ug5LK6v5pkgJIns2u2j8rr7DZScVFS6uvPIjrrrqo3Z7F0XDURw/2fF4QqyqqyOzX8fLUgz5Rvpcl0fqYAtalYq6RfWs/sd26hYrwSBZlvF6Qzz66FIArrxyOOPGZXHCCVkkJuppaPC1eA8EKv3UrlZ6n2zTeElOb/9zp7kLLhjE8OHpeL0hnnnmJ2ynJaPL0iMHZeo+r6Fufg3+Ut/PHgfvWN6IKgDucDheBtQWbZKWtEuVHlwqkxo5EI2/bytfL6P2k2ocPzaiq4ow5YQ8sjMSyTebSaqBtf8u5Os/rKPwg1KCtW0f9EfcYep/rKfR7ufHmhpOnda3w79HQoKW+56ewtqQHb8/zLqPi6n6shrXeif+Eh9hR6jF87RkSXGLbI1vvtlDKNT2gbwclqFQCR6U8vN6ZclRmdq51UzMU04UbKttZFtNI+sq6liwu4x3Nu7m/e93Ynf68e32Yl/aMjAVqFKmqAIkjDDzwjwl0HLNNSPQalt+Pp5zTn+Sk43U1Hji3xkACYNaZ0vFAjZnnlnAffedCsA772w57Gmdvko/kTIlwJR7Tnqrz4P8fCtjz8rljT17+LKoFEknEaoLUvdZDfVf1yqfzV2Y/PD117upqnIzKMNG/wQzSErpvqlvAqPPycWhiVDn9rFtbTW1n9UcViDjYNoKSslhmUCV8l7oSD+pA91118nodGpWrSpn6dISjP0T0KZokUMy7g1tDxFp7sMPtpGvMmLQaxg5PfeQ23eEpJZIPjsVfY4ewnKr3k7nnTcQq9VARYUr/pqUIzK+Yh+RSJQPf1SOO6+7buQhH+uCCwYxeXIBoVCEjz7axm9+8xVnnz2H++9fyHJHHcF0FXJUpmFhXTwjraNimVI5krK/ZxwgsqQOx8E7px6G5cuXc9FFF3H++ecDUFBQwLvvvsuqVd1z9k/offPmFbJyZRl79jQybdqATp/ZFwTh6PXvf//UIh36xBOzmTFjMGvWVPD55zt5/vlV/O9/F3boDHZn1NR4+MMfFrB9e238cW+7bXw8oHIwJ52kZB5s314X723Ur18SVmvTjp4sy816PmmwTrQd8n5/85sJLFlSQkODTynb29+gtqMsFj333TeJQCDC+ecP7NRtDzR+fDY33DCKOXM28sgjS2lo8PHWW5viDTltNgO33HICJ57YOgtjxIh0VCqJykoXNTUe0tNNGHIN/Oip542dO7l68mAMuUYknQpdhg5dhh5tsrbDqfwXXjiYnJxE/vrXJVRUuLj55i+48cZR3HrreHS6g59dNPZLIBqM4tvjJeIKYy/zo5Ik8lMSleDhwASld1M7aznnnH4sX17Ku+9u4bzzBpKdnYhKryJxrIXEsRaigSiBygCBcj/BCj9he5hQTZBQTRD3BkAjoc/UYx5jaXMSWrA2SMOCOuyNfva4XEyaNYRJp/Zp9/dJGGrGu8cL1XDT2IGUlDtY/tJOhj+SjC5N1yXvG1mW2bChmj4mE7lqI0hgndS65CrGPNaCpJFwbXAxKDuJRElD7dxqfGnJGPoaf9aa7HY/9/72W2aYMklM1HP+PcMPus8gSRJ//ONErr76Y179YTvDTsxgkD8Bf4mP+i9qSJ6a2mb2Ykw0KvPXvy6OT3D68MOt3Hpr66ws90YXEXeYokoHP9XV8ccRB+9NdCC1Sc2pvx/Kk79aRIZPQ2hnA2VFDrJzEskdZGPpnkoMTpkBOTZ+/Wul8bBWq+b00/OZN6+QRYv2Mm5cFtFwFPvSRhrtfjbb7eRNTunwGlQqiT/96VRuuOETFizYw0UXDebEs7OUspQiL8HyAA3lATTJWswjEjH2T0DSdO5v6VrjwLPTjd8fZkFFBRfktX4um9NYlEmhieOtBCsDeAs9+It9yCFZ6feWpkObpiM5TUeuOYd9G+pZ8/U+gpUBHHU+1n5Zgn2Hi2FX5JMwxBR/7cmyjP3HRuqqvFR4vTRYo+Tnt98Ivi3JyUZ+99QZ/OuuJZxAEuu+3sewYWno9gdrJI2EPsdAZKCeRx9V+oBdd91IvvlmD3V1XpYvL+WMMwpa3a97iwt5f5ZbpfnnZdH4iryEHWFSTQYGp1rZWefgge/WtNquRPLxpwvH49s/ic92ejIRV5iGb+sgAoYCI5uCDoqL7ZhMOi69dGir+9Dp1Fx66VD+9791vPfelnjmXSxbyvFjI85Vdhx2P199pZR+33TTGIYOTeWkk3JYtaqcZ5/9iccfP7tTv6Msy+z8rIxgMMLeoJfLz2778/KXvxzHvHmFvLeykMnXDqJ/KAFfoYdAqZ9AqR9tihbTqESMfRMOu6wMlM+MN97YqDzmaUNRSRLG/gkkTWl6L8440czM6z7h7GAGqSUJ8K2M5SQrppGJXfKZ3VZQKlAVgIiMyqxGY+v84Xt2diLXXTeS117bwP/7fys55ZQ8LBNs1M+vxbPNjWl4IprEtu/X4wny5TvbuTgth7wCK4mDD++EWVsktYTt9GRqPqoiVB3Eu92DaX9POr1ew2WXDeXVV9fzzjubOfPMvgTKlRNhZXVudtU56NPHxqRJrbPiWz2OJPHEE2ezcmUZS5aUsHRpCXV1Xr77rojvvitCAi7vX8DojGQS9jQSGmvElGtEpZKQJPb/V2LAgGQslqbvflmWKS62k2U0YlZpkLQShj4dPxkpNOnyTKmJEyeycOFCdu1SzsJu3LiRH3/8kenTp7e5fSAQwOl0tvgRji6xs7q1tR62bq3p5dUIgtBT9u1z8O67yrSe2bPH8sUX1/DCCxdw3nkD+dWvlADDxo3VLF9e2qWPu21bLTfe+Anbt9disxl49tnpvPDCBR0KSIGSyt2vXxKyLMebkR+YJeXe6FJS5TUSSWemHrTJcIzFouepp6Zy9dUj+POfTzusndPLLhvGtdeO7JId29tuG8+gQSk4HH4ee+wH9u1zYLUauOOOk/j882vijVsPlJCgZcAAJSMpVhoHSrljIBolf1IaKdPTSD4rBfOIRCV40smDgBNOyOa99y5jxoxByLJyEHDTTZ+2eLz2mIaYST0/nYyrs3m3sZSXCwtxD9eSemE6tjPaD0gBnHvuAIYOTcPh8HP33Qvw+VqWD6r0KowFRmyTkki/IouMa7KwnZGMcWACqgQ1hJXpR/Vf1tC4uJ6ItylbImwP0fB1LT53iMJ6B19WlDO+jaBfc5JKmVBomWClYHgyBq2aVJ+Gna8WUzu3mvpvamn4ro7GxfXYf2jAsaIRf0nnsl2Ki+1EPWFm5OdhNuswDTOja9aAvtWaJAnzKAsZV2eRcnISgWgUb02Aum/rqPmwCudaB6HGjpVdNhcMRvjDH74h2aPCaNAw6oxsErMOfUa5b98kbrpJ6a1237+XUpEfRWVUEaoPUftZDb6i1v2KYt57bwvr1lXG308ffLCt1Yj5sCuMe6OLujofX+7ZhylRFy+t6wydXsPd/5mC9eJ0FnlrWV9bT2FRAysW7kO1J8Cl+fk8eOoYnB/XUvdlDY7ljZw/OJ/RSUnsXV6Lv9yHc6WdiDNMRb2HxVVV8VLjjho8ODX+vv7HP5YRVkHSlBTSr8pSDpi1EuGGEPalDVS+Xkb1+5XUf12LY6Udzw73QUuR3JtduDe4CAYifFNeTonPS3oHs7gklRLgSZqcQsZ12aRfnUXmDdmkTE/DMt6KoY8RbYqO/mdlcdX/TeCUvwxnT3qQ3S4XJcV2GpbUY1/SQHR/WZmv0Eug1E9tvZevysuZPKWgU89TTG6uhdmPnsyn1WV8WbiPj1bsxquNglpCDsv4SrxsfLaQ8QYbwwek8utfn8T06QMA4hMUm4v6I7g3uQgEIvxQU4Mh4eeV7kWcTa/VGUP6oFZJmHVa+tjMnJCdytQBueg1apbvrqKhQAKV8tzYlzRQ/00dsj+KNk2HbUoyb+4/eXT55UMxmdp+/1922VDUahUbNlSxY0dT36yEQSalmX0E9s6v5OKcXE4Zl8OwYWlIksTvfqdkv377bVGHPsObC5T6qS90EpFlzOMS0Wja/q7NykqMB9P+87812E5PIv2KTKWpvkYiVB/CvqiB6g8qf1bm0pIlxezd28igVCsDbBal1O2Aht7Z2YncftdJfFRSwucbivF5Qzh/cmBf2tipxvntqax0xx8nJpa9o882HPb+waxZY0lJSaCszMl7721Bn2NQspQiSsC5PW+/vZkCtZGEBC0FE1JR6bs2fKA2a+LTRZ2r7S2GI1xxxTA0GuU1uW1brfJ5L8ss2l6OjBIo7mgyhFqtYtKkfP70p9OYP/865sy5hNmzxzJsWBoarZq5RSWsL6ujotRJ+aeVPHz399x++zx+9at53Hrrl9xyyxdceOG7LTJb6+t9eL0hhttsGI0aDAXGDu0vCq11+bN23333cfXVVzNkyBC0Wi1jx47lt7/9Ldddd12b2z/++ONYrdb4T15eXlcvSehG0ajcotQgVrYiCELHyLLMli01vPHGhm4fCd/VnntuFZFIlEmT8rj99hPJymragUpLM8Un+nS2qfXBLFiwh1/+8nPq6rz065fEnDmXcMopnf/eiJVxlZcrJ0KaB6UCVYFmfaRsLaZvHcqoURncfffEFllXvUWnU/Poo2diNuuwWPT8+tcn8sUX1zBz5pj4iOv2xJ6P2AGG0xmIT/OLPXc/l8mk4y9/mcz//d852GwGCgvrmT37M2699QtWrSo/ZOAlGpVZv6EKZyjE0FOz0GXoD7mzrtOpeeqpc0hONrJrVz2PPLL0oI+jNmtIGGRSDqavzSLt8kyl/4SkHPzVfFiJe7OLsCtM3Ve1RP1Rqv1+5u7bx7ARaZjN7Qd/YlQ6FeZRFvJuyMU7ysB2h4M9exsJ1QcJ7PPj3+vDV+jFu8ODZ4ubhgV1SubSHm+HeittXFfFxfn5ZCYloEvRxXf+O7Ku4Rfn8YWrkh+qqqlz+Ig4wrjXOan9qIqaj6twrnNgLz/055bPF+Ivf1nExo3VnJCewvDh6aSMtXVoHaAEWM8+ux/hcJTfP7wQxwhts2mB9VS9U4FjRWOLoEpRUWO8R9c990wkOzsRh8PPF1+07AfkXGlHjkRZs7eGQpeLq68eccj3R3sMBg1XXjWc/7x/EZNuH8KCSB1f7Ctlh8OBJTuBpGQjciBKsDKAZ6ubLJeWabk5nGpKoeSDcrzbPfgDYT7dU0JYgrFjszq9httuG09KSgKlpQ5ef30DABqzBuvJNjKuycbXR8OGnTXsK3EQdoYIlPrxbHbh+KGR2o+rqV9QS6i+ZXDKW+jBudIOgCtXxSa7ncxM82Flxqu0KjSJmoO+VwcMTOH+J6ewTnKysLySqmoPvkIvdZ/XEKgM4FhpJxKVmbdrHw3BIGee2fHSvQMNHZrGP16aRoUxxHvbi5j96vcUD46SdmkGJQEvdXVexiYn8+dTxxDY5uG8aUrAcunSkvi01RjXBqU/z5aSOrY5HIwfn33Y6wJQW5oyVybmZ/D+VWcx5/LJ/L/zTuHPk8dy20lDmZCbBmqJ+etKlGweFfh2e4k4wqjMapLPSWVviZ3166tQqSSuumpEu4+Xlmbi7LOV5/Kxx37A4WiaxJd0Vgq6E8yUVTjpazZzy9CB8UDJwIEpXHSRkl349NMrOvx9L0dl6n5soL7ex7qGBqZedPBg8OzZY9Hp1GzaVM2KFWVKSfekJDKvUUqwVUZlGmHDt3W4t3S+lFCWZV57bQMAsyYOQaNWkTDY1ObAg4suGsyJE3L4uqyc97cWIQO+XR7qPqsmUPHzhguUlytrz8oyxy+L9ZMydLKfVHMJCVruuEPJ1HzttQ04nQEST7QBymsmVNc6KG23+3n37c0MtVrp08eGaUjXZUk1ZxpqRpuuQw7KOFY0xi9PSzMxdarS/+z9dzbjL/ZRX+9j5b5qrFbDYZ1AACXzadiwNG6//UTmzLmEpUtn8ubblzLixgLM+Qmk2YzMHjGQ0YPS6d8/mX79kkhNTcDtDvLrX8/nxx/3AUo/KRUwNiMlnlUnHJ4uD0p98MEHvP3227zzzjusW7eON954g6eeeoo33nijze3vv/9+HA5H/Ke0tGvPqAvda9eu+hYTNxYtKhZN7QWhA+x2P++8s5mrrvqImTM/5dlnV3Hj9XPZuLwCf6kPzzY3zlV23JtdBMr9RHw9O8nuUDZurOL77/eiUkncddfJbW5z002jSUjQsmtXPQsXFnX4vuWITKghFD8rDkoA4uWX1/KnPy0kGIxw6qn5vPbaRYfdd+nADISxYzMJu8J4drpp/L4eokpfgIP1kToa9OuXxLx51/L119cza9bYDh9sx5qdb9yoBKVWry4nGpXp2zeJjAzzwW7aaVOm9OWDD67goosGo9GoWLu2kttvn8dNN33aZhPomF27lNHmJpOOgQM7XuaUkWHmiSfORq1WsWDBHubM2djh236xaDd/+fAnIieb0KYpO9DOlXZqPqgk6o6gtmqYX1tBMBplwoTOBe8kSeKym0fyo7uepzdsZaveg/X0JKwTbVgmWEkcbyVhmDme7dL4fT01H1Xh2elu9+y8LMv4VzvJMBgw2XQkT+1Y1l/zNZ01rR/La2t5p7IY2+RkpTGtGuylHpa8vIOv71/Pyzcv5b3n1lNc3HQwEY3KrFlTwV//upipU9/i22+L6GdJZMLIbMxJeox9O77zrlJJPPzwFMaPz8brDfGbe74hON6AeYxF6Vfkj+LZ4qb242qlV9FGB48+tIRgMMLEiXlcfvkwrr9+FKCc9Y+9pgLlfvzFPuz2AB9sLVKCSu1kEHaGWq1i2rQBzHnnEm57ZCL9Lstlyl9GkjUzl7RLMrBNTsY8OhHzEDORVDXlXi9ldg+qBDX7NH6K3G5GjEg7rOCY2azjD384BVCanpeWKgF2rzfEcy+t5toH5/HQ4rXcs+AnNiV4sJ6ahGmkWcmYkCBQ4qd2bjUNC+sJ20P4S3zxvkSmUYmUapSD45yc7jk4jVGpJK69diSr6+v53+adSAaJcH2I+i9rkANRaoN+llfVkJWVyKBBHX//t6WgwMYbb1zMuHFZeL0hfvu7b3jt483c/+FK3isuJn2QBbNei2u1A8v6ABOGZhIOR1mwYE/8PsKuMJ5tbqqq3MzfW0Z6uqnNMrnOMPZLQGNtCkyp2gjkTRmRi0qvfJZp8w3xwJSklUg5NxW1SR1vsH/GGX0Omd12880nYLEok8p++csv4gMCJEli3uYSXi/cQ8ggkWw2UD+/loaF9Th+sjP79KGckpUO5UGWfLy7Q8cC3kIP1XuceENhqhPDh/w7pqYmcNVVyvvzP/9ZHX8MlUFN4lgLGddkx5tWx4cidOKYZPXqCrZtq2VIspWBqVbQSCS20zdNkiQeeOB0EhK0zF1bxBrJjqRXMjjr59VS/1Vtm0GeQwkEwtTXK2WYOTnKY0c8EcINIZBAl9O6bLwzzj9/EP37J+NyBXjjjQ3o0nTxQIrjp9bP1xtvbCBbbSDFaiSjTyL67J/3+O2RVBK205JApQydaJ7tds01I9CrVMhbfPg9IXaVNlLh83HFFcMwGLqmE5FWq2bQoBRmXDyE8x4awwlT8ph4Qi6PX3Yy7755KR98cAWffno1p56aTyAQ5ve//4avviqkpMRBgdlMklmPyqg6rH5fgqLLg1J//OMf49lSI0eO5IYbbuB3v/sdjz/+eJvb6/V6LBZLix/h6LF2bQWgNPnV6dSUljooKmo8xK0E4fhVUmLnvvu+Y9q0t/jnP1dQVNTIiBQbd44ayszMvux8aS9bXy/GsawR90YXzpV26ufXUv1WBVVvlVM/vwbPzu4bix4jh+WDHug+88xPgHK2sF+/pDa3s1oN8QPBF15YQyRy6MbEclSm4ds6aj+uour1cmo+qqTh+zre+MtPfP32DhI1Gq6/bhT//Oe5LUoQZFkm4g7j2+vFucpO4+J6GhbW0bCgjvqva6mbV0PdvBoav6/HsbKRIbpERiUnMcRi4dJBBah+cFPzXiWOpY1EPUpw4WB9d44mJpPukL2aDhQLSu3YUYffH2bFCqXJ9CmndE2W1IGSk408+OAZfPbZ1Vx99Qj0eg3bttVy990LuPvuBW0eWMSydMeMyeh0xsbYsVn88Y/KmOznnlt9yBJTrzfEAw98z2OP/cCyZaX894ONpF6YjvXUJCSDCqIoWQnTUlm2WnmuDiejzGzWMXv2GPyRCM+8vw5NgQHT8ETMo5SeV7ZJSWRck03iCRYkg4qII4xjaSM1H1bi3e1p9Ty5N7owNMhEZRnDRGu7PUMOZvr0/Zkhy0sJpKpIOieV76UG/jF/HVtqlO97S0AFqzx8ee867r/xK554/Ecuuug9brvtS778chc+X4jcXAv3XD0em81AwoDO9zNSstymMmhQCg0NPn7zu28I99eRcXUWydNSlfIiNYTqgmz9cB/nqFK5ZmBf7p85ATkiM2PGICwWPWVlThYvLkaONJ2RX7S3gvpAgEsuGYLN1nUHFZIkMXFiHjfeOBqjUem7pk3VkTDQhOUkG0lnJJMyNZV3i4t5btMOMq7NYsE+Zb8q1vvucJxzTj9OOimHYDDCk08u4/vv93L55R8wZ85GIpEo/fsn441EeOT55ZRKfqwnJ5FyXjrpl2di6KccoPqLvNR8VEXDwjolSD/IhOUkK3uLlSDX4Z4Q6IwLLhiE1WpgbXEt21MCyjACADUsqK5EBqZMKeiSz2mr1cDzz5/HhRcOjp8E8XiCJPVP5NR7h2GbnIzKrCbiinDjwP4MtlhalPC5VjuIhGSW76qixOPhF78Y2+nP3QNJKom0SzMOus05dwwjOdmI3e7np5/KMPZLIP3yTNKvyEKbrCMQCMfXecklhw6SFRTYeOWVC0lPN7F3byOzZ39OcbGdYDDCO+9soS4QIOmCVExDlZMT/iIvnk0u2OnnurEDmJ6djX1BPVUfVR20YXTYHsK1xkl1tZsVtbWce/6ADv0db7pJyfTdsaOuVXWGpJawTkqKZ4N6NrtoXFjfoQEVQLw/5vUnDUKnVWMaZkZtav8zMysrkbvumgDAk6+tJjzRhGm4GdRKZlPtJ9U0fl9P2NHxcueqKmX/LiFBS2Ki8nqPZV5pU3SoDT/vNaVSSfFsqXff3UJNjYfEEyyglghWBOKTGkFpy/L++1sZYbNRUGAjYaAJqRv7BmuTdfFBKfbljUSDUWRZpkBv4u6TRjLMYmXXrga+KixFq1VzxRXDumUdKp2K5HNTURlVygmgxfXIURmDQcNTT03lvPMGEo3KPPjgIt55ZzPDrFaMRq3Sp0/0VT5sXR6U8nq9qFQt71atVhONHt5YZeHItnatclBw2mn58cyD77/f25tLEjpoz54GXn11fav+GsLBbd9ey3//uzY+Ya4zgsEIv/nNV3z3XRHhcFQpG5h9Kg9fPIEpE/JJS0sgGI2ycksFPxVXYxiSgKGvEbVVAxJEfVEC5QEcSxsPKzX9YGRZJlgXxLXBSd28GirnlFH1ZjnO1Q6iB4wLXrhwL5s3V2M0attsGtzcddeNxGo1sG+fo80eHAdyrrQTKN2/IytDqDHExq/KMJaEuaqggKfPP4UrrTnUflRF/de12Jc1Ur+glup3Kql+t5LG7+pxb3ThK/TiL1LOtgVK/QQrAgQrAvj2ePFsdhPY4OaKwX25IDeXk7PTiDjCoAJthg7zOAupF6Sj0h2/fQGyssykpZmIRKJs21YbD0p1VeleezIyzNx990S++OKaeKnG0qUlLFvWOmgUmyg3blznS5xA6Z9yySVDkGWZP/1pYbwJ/IGKihq56aZP+eabPfHg13ffFeFyBzENNZNxRSbWSUmkzUinsMyO0xnAbNYxfHjaYa3riiuGk5FhpqbGw+23z2PlyrIWwSaVXkXiOCvpV2XSkCGzdU8d+3Y0Yl/UQN0n1fEDQf8+H3XLGvD7wyyqqWbYaYf3PBUU2Bg6NI1IJMrbb2/mttu+5Jnnf2JTQyP1/VScfN9Qsk5JwZpkIM1gYDSJpG4Okx3QYjHrueSSIbzyyoV89NblZKuVgE/CkMPLtjObdfz739PJzk6ktNTBXXd9TeHuBgIWpbwo49ps7NkSq3dVIwFnj8pHXuuh+q0KPIsauXfKGC7Jy2PPB2XUf1VLuDGMMxDk3TWFqNWqeBC9J02alB8/qVdY2MDq1UpQqq0hBB0lSRL33XcqWq2aFSvKuOeeb6mp8ZCdncj/+3/n8u67l3H66X0IBiPcc8+38TI0jU1L8lkppF2agb6PAWSURtl9jNhOU4L0sQDu4b7vOsNg0MQPPOd8sJmU89OwTrRhPSuFb5YVA/ys0r0DabVqHnzwdO66awKSJGEwaPjb3yaj0ahJGGgi/dJM9HkGMlJNXJiXh6UqSkmJnWBtEN8eLxWVLr4uLiM7O5ELL+xcs/z2mEdZyJqV0yJjCkBj05A1KwfrWFt8qEasAbnGqo1PH124cC8uV4CsrMQOf3737ZvEq69eRJ8+Nqqr3fziF5/z73//RH290kfs3OkDsJ2aTMr5aSSeYME0KpGEoSb6n5pOLUHcviAVO5QTanXza+ITFKOhKN6dHuo+r6bmwyo89X7K6t1sctjjwe9DsdkMXHutMm3txRfXtMqklSSJxDEWbFOSQa1k3dTPr2m1H3MglyvATz+VM8RiYWC6FUknkTj60IHXSy4ZyoknZhMIhHnkyR9IPNlG+uVZ8Qlsvj1eauZW4yvuWJ+r5k3OY0G6eD+p3K7JUjr11HxGj84gGIzw3/+uVcogT1NOLrrXO/EVKZla//3vOnRRidE5KSQlGUgY1P2laeZxFtQWDVF3BMfyRhoW1NG4sJ7+uTYag0FeWL+djY2NTJ8+gJSU7luPxqwheWoqqCUCJX6cq5X9A41GxV//OplrrlHKYMv3ORlgsZBg1GAccHRn1ve2Lp++N2PGDP7+97+Tn5/P8OHDWb9+Pf/85z+ZPXt2Vz+U0MuiUZn165VmbyeckI3VauCHH/axaFExN998Qi+vTjgYWZZ54IFFFBYq5Zd33jmht5d0RAsGI3z3XREffriNzZtj5UwVvPzyjE7dz9tvb6KiwkV6uolnnj6X1HJlhwmUsogzrs/hzfc38/oLa5D3yMyrruDJJ88hI9lINBQl3BjCV+TDs9mFc4UdtVHdqfr1qio3zzyzkvHjs7n00qGoVBJyRMa52o5vt5eor+XJAzmijAr2bHNhHpmIaXgiEZXMs88qfVpuuGEUqakHf3yTScesWWN45pmVvPzyWqZNG9Du2WPPVheercpZwqSzU1Cnann+sZXs2VxLptHI9NP6kWlNgAhEHGElkNScCjRJWnRpOtQWDZJaavEjyzJRX5SIN0LUFyE9bKF4uYth45NIPiUVXaa+yxt4Hq0kSWLUqHQWLtzL55/vpLrajU6n7pEDUVAyp26//UTC4Shz5mzkP/9ZzcSJefGgkCzLrFunfP8cTt8diE12m8SePY1s2lTNDTd8wpgxGYwencno0RkMH57O4sXFPProUvz+MGlpJh5//CyeeGIZhYX1fP31bq68cjgqgzo+LWjlSiV4d+KJ2ajVh/da0unU3HvvJO6551s2bqzmjjvmM2xYGrNnj+X00/vg9YaYP7+Qjz/ezp49DWgkifEpKdx5wRjM9VA/vxZdjp5QTRCnw8/GxkZ8aap2mxt3xPTpA9i+vTbeo8ho1HL33adw4YWDkSSJgmEpRP0R6tbbKVlag68hyPgRmaTlmbGOs5IwxIx7swuioMvQdapP24FSUxN47rnzmD37M7Zvr+Xaaz8GlElNGRkmnM4AdrufS6cO4rypmfgKPURcEYLlAQanWHFY3US9MnU7nVgser7aqzTwnzFjUJeXpnZEQoKWk0/OZenSEv73v3U0NvowGDSMHJn+s+43P9/KzJmj+e9/16HVqpk5czQzZ45Br1d2/f/618lcf/1cKipc/PWvi3nqqanx95c2RUfK1DSCNQFC9aF4hkRVlZtdu+pRqZQMsJ5w5ZXDmTNnI1u21LB5aw2jR2eycmUZLleA5GRjPKuzq0iSxA03jI4HC3Nzmyo4VHoVyVNT0azSkrSrnlPkNLa9VYxpdDaRSJSF28uo8fv5y80T0Gp/XkZLc+ZRFkwjEvEVeYk4w6gtGoz9mrIypk8fyPvvb2Xx4mK83lCLss+5c7cDcMklQzqVUZqZaeaVVy7kzju/Ytu2Wt57Txlqcu21I+O/mz7bgD67ZWZhUk0qLz27mksMYa7OGUiwPEBdeTW6LD2huiByaH8QSYLdThdz9+3jxAk5h9yXaO6660by/vtbKSpq5KWX1nDbbeNbZVklDDChTlDT8F09weogtZ/XkDI9rd1s0WXLSpEjUc4bkIfRqMU8MhFVB7KSVCqJBx88g6uu+oh16yr56KNtXHnlcJKmpGAemYjjJzvBigCN39URPTUJ0yEC8gdO3pNlOd5PqqtKwyRJ4je/mcAvf/k5n322k+uvH0WfgTZC9SE8m13YlzTw3coS5s7dzoTUVPr2saHPNLTZW6urqTQqbKcmUT+/Nj5NEjX0OTuDh5avo8yrXHbddSO7fS26dD1JZyTT+H09nk0uNFYNpiFKL73f//4UrFYDS98tRCNJGFL1aFO7//k5lnV5UOrZZ5/lwQcf5Pbbb6empobs7GxuvfVWHnrooa5+KKGXFRbW43IFSEjQMnhwijJaWyWxa1c9FRWuHkntFg7Pli01FBbWA8p0oiuvHE5mZs/vjPeGUCjCo48uJRSK8otfjKV//+R2t62t9fDhh9v45JMdNDYqwSONRkUkojT478zrvK7Oy6uvbgDgzltOJGlHBH9dENRgOzU53rto1uyxDByUwp///D0bNlRx442f8K9/TaN//2R06Xq0aTqIyni2umlcUo+kV3W48eVzz62Kj7/95JMd3HvvJPrrTHg27+8ZoZWUncxcZSJLqDGMa62DcEMI11on7i1uNjoacVZ7SUlJ6HBWwRVXDOPttzdTVeXmlVfWccYZBRgMGvR6NXq9BotFT7Q6iGN/I93EE61o8ww8+OD3fPttEWq1isf+eCYnnNUPOSoT8USIuMKEnWEirggqozJaXJOiRdXO5J62nDA5hRN+NajD2x9vRo/OZOHCvcyfr2S4jRmT2WX9GzrqpptG89FH29i1q57vv98bH1O+d68dh8OPXq9h6NDUw75/nU7Nk0+ewy23fMG+fQ6WLSuNZ2WpVFL8LPxJJ+Xw6KNnkpxs5JJLhvDkk8v45JMdXHHFsBYHQ7GgVGf7SR3o9NP78Pnn1/DmmxuZO3dHvJQxP99KTY0nnuGq12tIS0tgZVkdyWV7+cNF4/BsdxMsVzJfSr1eFlZWctXk9psbd8S55/bnmWdWEo3KjBqVwcMPT2lxsA5KX5f0U1JIOykZ7y4Prg3O/We77bg2uWB/OfDhZkk1l59v5bnnzuPpp5dTUuKgocFHIBCOZ7ulp5u4475TsFj0JI6zEKoNEnaElV4z1ZWsWF5GdWqECyYM4e2XdiJJEjfeOPpnr+twnXVWX5YuLYlnmo8bl9UlQY2bbz6BAQOSGTw4tdXfy2LR8+ST5zB79mcsXVrCnDkbmTlzTIttdOl6dOlN2Rk//FACwMiR6V1a5ngwyclGzjtvIJ9+uoM339zE6NGZLFqkPE+TJxccVrP1jmivLF1SSVhPtmEoshD9ykugxE8g3U9ZhYvv9lWQn2897ObLByOpJBLaycQYPjyN3FwLZWVOliwpjmcdFRU1smGD0uB8xozOf9fZbAZefPEC7r57AatWlWMy6bjkkiEHvc0FFwzi/7d353FR1fvjx19nmBn2fUdBcUHFXdzXTMPUJFyi1Gyx+pmZLXbLe72Z7X3bzBbb1CzLLcvd1Ny33FFxSRDEFUEQWYdlYM7vj4lREhQUBui+n48Hj3tlDud8OH2YOed93p/3e+bM/Sw4HM/AZ1ril6UlL95A4SXze5KNq7l5hF0TB2aO2klaQQEvDq7c+XJ2tmXixM68++4O5sw5RHGxyoQJnW4ITNkG2OE1xIcr61IpziwibdVlPO/1LjMovm3bGdq6u9PQ2wWNvQbHVhW/hwkIcGbixM588MEuvvhiH+HhjXFzs0PnpcdzoDeZO69iiM0lc8dVTIZinNq7lLtU8e9BqaKrRkx5JhStgt636uo5tWvnR69eQezYcY4vv9zP++/fg0tnV4rSC7lwOJ1LR5Oxt7FheJfGuLraWbW+pm09O+xDHMmLy0Xvq8e1lwc6dx0jR7fmww//oHv3wJteu1cl+8YOFGWar4Ezd11FNaqoRSrF2UVE+tUnbIAjeVmF1O/i9Y8o91CTqvzq0tnZmRkzZjBjxoyq3rWoZUqW7rVv74eNjQY3Nzs6dPDnwIEktmxJZPRo66fBi4opeXIG5iygr78+wOuv31VzA7KiWbOiLcvINm48zX33hfD00x1LFf9MSEjnxx9jWLcunqK/im37+Dj+tdynBa++upl9+y6yZk1chbMCZ87cR16ekV5t6tE21xGjoRCNnbk+i61f6QuNnj2DmDcvkhdfXM+5c5mMHbuS99/vT9eu9VEUBZdubpjyTeQlGLi6MQ3PQd6lbhzKkpKSw4YN5mLjjo56YmPTeGLsCt7s15EWDTzw6OKOczsXFJtrH6paVx12DezIT8wjOzqT/NRCcg9lMS4khAZtPTGdzqc4WGNZJlAeW1stTz3VwXIBOWfOoVKve9nZ8WRoU9ycbDH62GB/tYjfpuxl8+ZEtFoN77/fnz59GgLmC3OtsxatsxbbO2tsJG6hbVtzBkJJYKa66kndTEldsm+/PchXXx2gb9+G2NhoLEv32rTxueObdy8vB37++QHi4q5w5EgyMTEpHDmSYumG+eSTHfh//y/McvN7771NmDFjD6dOXeHEiVRatjRntBgMRku3wqpY5ujj48hLL3Xn8cfbs3DhUX7++YQl6NKokTvDh7dg0KCmJCfnMHLkr6zbfJonn+lIQEt/sqMzMeWZ+GXLWUyU7i55Ozw9HfjkkwFcuZLH4MFNb5oFptgoOLZwwiHEEUPsteAUYA6iN7K/o7GUaN7ci1mzIgDz51hqai4pKbmkpRlo1coHFxfze6KiKKWCK/0fb8HXa44SsyOD4znmZdh33dWA4OCygxDW0KtXA2xsNJa6e506Vc2bm0aj0K9fo3Jfb97ci5df7s477+zgyy/306qVz007xu3YYe441bt3gyoZX0WNHt2a5ctPsm3bWc6ezbDUEurbt6FVx3G9LsOD+fKHgwzw8ufKlTxWHztLltHIv5/ueNtZkrdLURQGDmzCrFnRrF0bbwlKLVtmvtbr3bsB3t63F1RwcNAxY8a9LFp0jObNvW6ZcenmZsfddzdk/foElq2LY8qUXji1dib/Qr7579BPj6Io7Nt3kaSkbBwd9dx1V8NKj2vYsBbk5xcxffpuvv/+MIWFxbz4YtcbAgM6dx3efwWmiq4Wkbb6Mh7hpa+78q4W4hRfRFt/fzw87XFq61Lp5fsjRoSyYkUssbFpzJt3xLICQdEouPZyR2NvQ87hLLIPZlGcZ8K1m1uZ9YcuXTI/JCwJSpVkSen9bUtdn1WFCRM6s3PneTZtSuTEiVRCQ705aZ/HsaOXcNXpeLVfB5rVd0fRKVX2vl1Rbr3dcWrtjNb9WqfOqKiW+Ps73/HnWWU5tXehKKOIvASDpQtpCV93BxQfRxybydK9OyXrFMRtKylyHhZ27QKm5ALh78UHRe2RnV3A77+bgxMlHXrWrDllyZz6J4uJSbEsP2nf3g+TSWXlylgiIxfx+ed7+eOP8zz33FoefPAXVq+Oo6jIRLt2frz/fn9WrhzJE090wMPDnvvuMz9xXLPmVIU6u5w4kcqqVXHYKArjOjRHNZjQeujwivS9ISBVokEDN+bOvZ8OHfzJzS3kuefWWoKJiqLg1scD2/p2qEaVK+vTKMq4eSHNxYuPU1xsIizMn2XLHiQiohlNnJ3JvGRg174LrIs7T1EZtf8URcG+kQN297iz/Mw5ErNycHDUEeTiSNbuDFIWJpG26jLZh7PMqfnlnI+IiGaEhzcmKMgVX18n3NzssLfX4ajTMiwwkKL8Yg6fS+P1X/fxr5c3sHlzIjqdubBxSUBKWFdIiGeppZbdullnuc7fjR7dGhcXW86ezbBkbZUUOb/dpXt/p9VqCA31ZuTI1rz3Xn/WrBnFqlUjWbt2NE8/3bFUNoaLi60lY6ukq1XJmIqKTAQEON+QlXInPDzsmTChM6tXj+TNN/sya9YQFi8ewYMPtsLZ2ZamTT3p2TMIk0ll3rwjaF20uN/lib6nC8dPpQFVc5569AgiIqJZhW+4FRsFx1AnfKP8cenmhs5Lh0sn10plM1aUXm9DvXoudOjgT3h445tmsDZs6Ebv3g3+WgJqnkePPtquysdUGS4utqUCUXdS5LyyIiObc999IZhM5tpq13dUvp7BYLTUu+rVy7pBqeBgd3r2DEJVzcWF09PzcHLS3zSAVt1sbbW06hXA9wkJfLr9KL+fu0jjxh6W9wZrKwlE7dlzwZI5WPIA7k67AOr1NjzySNsKz8uS461bF4/BYETnqce5rQu2/rYoinkp/cyZ+wEYPLipZUlpZY0a1ZrJk3sAsGDBUT788I8yu7XaOGnxus8Hva8etcDElbWp5J/NQy1SyT6URcJ3Z2hs74Reb4NvZw/LcuzK0GgUxo8319hcvPg4aWkGy2uKouDSyRWX7m6ggOGEuctvWQXYL140Z0r5+5vHYFm6V8GM+Mpo0sSDQYOaAOZM+oMHk3j5vxtZeu4cXr6OtAr2REHBLtihUl1bq4KiKOg8dKWCjIqi0Lt3A8sDB2uOxa23B/aNHdD76rFv6oBzmLlumdf9PviOCkDrZN0s8n8iCUqJ21K6ntS1i92Spx1HjqSQnl6xon7CutaujaegoIjGjT146KFW9O/fCFW9VieoqhkMRrZuPUNCQnq5rd2twWAwMnXqFkwmlUGDmjJrVgRz595P+/Z+FBYW88MPR3juubX88cd5NBqF/v0b8f33kcyeHUG/fo3QXncj1bdvQxwcdFy4kMWRIyk3Pa6qqnz88R8ADBjYhIb3B2DXwB6vIT637ITl6mrHF18MsnT6ePfdHXz6qXkJjWKj4N7f09yWPt98kVVeIU+DwWgJaI0e3eavTme9mTq6K05OevZfTuODj/8gKuoXNm9OLBVYMplUVqw4yfARS5i36U8WnTmD70MBuHZzR++rBxUKkwvI3p9J6rIUUuYncXXLFQyncjEVXgtyabUa3n23H0uXPsiaNaPYuPERtq57hCWvDCK8VzAtO/lRL8KPgYOb0ry5F/7+zkyfHk7PnkE3/w8rqo1OZ2Mp1u3l5UDjxjWTSeLoqLcsK/r2m4NknMhi/7YLmApMtK+mJ6aKouDv71xudkFkpHkJy/r1CRgM5oBwydK96ioG7+xsy6BBTWnf3v+GbIDHH28HwOrVcZYMr5iYFFRVJSjIFQ8P6z7lvp6iVXBq5Yz3UD9Lx66adv1SvY4dA2jV6s7qN1WFkoLdrq52NG3qabXjlhRFDwpyJT09j5UrY8vcbt++ixiNxdSr50JwsJvVxldizBhz9v2JE6mAucFOVdZtuh2DBzclt6iII5fTUYHx4ztW23LCWwkKciU01BuTSWXDhgQ2bUokK6tyBc6rSocO/gQFuWIwGFm/Pv6G1zdtSuT48cvY2+t44on2d3SsBx5oyauv9kZRFH7++TjvvrujzGtNjZ0NHoO8sQ2ygyKV9I1ppCy5RPaBTNIv53HRYOB8AxPuPT1uOyOpR49A2rTxpaCgiO++O3TD604tnXG/2/NaAfZ1qZgKSj8MvHTJHJSqV88FtUilIMUcJK6qelJ/N25cR3Q6G/btu8jEiWspLCymVVc/uo4PQcF8HqxR4Ly2U7QK7nd74hXhi/tdnjh3cMWhiSN6H9v/6aY4VUnCeuK2xMenk5VlrifVvPm1eh6+vk6Ehnpz4kQqW7eeueOnM6JqqarKr7+agxPDh7dAURQmTOjEli1n+OOP8xw4kFSlTx5Lulrt3GlO+bez09KsmSehod6EhHiSn1/E5cvmJRcpKTmkphro0qUer7zSo8rXZn/yyW4uXszCz8+JV14xP1lr3dqXb78dYllTn5ycw6BBTRk1qvVNMx3s7XX06xfMqlVxrF4dd9NU4g0bTnPkSAp2dlqefbYzdj722Na3q/Dvp9fb8MYbdxEY6MI33xzkxx9j2Lv3Ik2belC/vgtBvs40KNbimGkiOzoL1+43Bg5Wr44jJ6eQoCBXS5CnMLkAN1VLh47+GPs4cWJONufPZ/LKKxto08aXF17oiqLAhx/+YbkJCA525+WXu1ueljq1cqY4p4i8s3kUXMin8FIBpjwTefEG8uINaBxtcOvljl3gjTfEhZcLSN9wBZOhGFtnHfWG1KO1mxSJrG3CwgI4dCiZHj0Ca7ReQlRUS3785hBnoq/wwfjNXDqViY1GwXllNjl2WTi1qbrMpIpo396PBg3cOHs2g99/TyAysjl7914Eqr9DYVnatvWjfXs/Dh1KZv78GF58sRuHD5sfHFl7qUNd0LatL2Fh/hw6lMyTT3ao6eEA5mLy0dGX6NKlntUDG3Z2Wh5+uA3vvruDRYuO8dBDrW4Yw/bt5npSvXoF1ch7QYcO/jRv7sXJk+bsv759q67r3u1q186PgABnkpKyadHCmz59rJtB9ncDBzbhxIlU1q6NR/dXZktkZDOrzydFURg6tDmffrqXZctOMnTotXuBoiKTJUtqzJg2VdJBLTKyOTqdhjfe2Mby5SfZtes83brVp3v3QLp0qYezszmzRqPV4HGPFxk7rpIXl4sppxiNo4Yl8WfYfTaFT1+8947GoSjmbKnx49ewdOmfjBnTBn//0lmb9o0c0NhpSP89jcJLBaStuYznAG9sHG3Izy+yPND3dbHnyrpUKFLRONmgdaueW/aAAGdGjGjBwoXHKCwsplOnAN57rz96vQ02KBQbitGXk9EvRFWSoJS4LSVL99q187shlf/uu4M5cSKVLVsSJShVyxw9epmEhHRsbbUMHGhO2Q0MdGX48Bb8/PNxPvtsL99/H1llFzC//XaKnTvPYWOjwdbWBoPByJEjKTfNLjp3LpOgIFdGjqy6zhrbt59l2bKTKIrCG2/chZPTtZoIJenAla2Rcd99IaxaFceGDad5+eXuZaaf5+cX8emnewF47LF2lrpVlb2gVxSFp54Ko359F958cztxcVeIi7u23DLIwYHRTRrRKs+IQ3OnUkU8TSaVBQuOAuZU95L/tjlHzE/jHEIcGdozkAFDmjJv3hF++imGmJgUxo5dYdmHo6OecePCiIpqWSpjDMxp8U4tnXFq6YxarFJ4uYCCC/nkJRgozi4mfV0a9iGOuHZ1s3S2M8TlkrEzHYrN3fI87vG0SlcXUXmPPNIWFxdbBleyEG1VK4ozMMQtgFnFJ1l10hzkbuLhgk2uyqW5F/F/HKsGphRFITKymeWmq1u3+iQmXkWjUWpsSdHjj7fn0KG1LF16krFj21uymSUodSNFUfjkk3tJSzMQFORa08MBzA873n777ho7/qBBTfnii30kJWWzffvZUnV+TCbV8nDJ2vWkSiiKwsMPt+HVVzej19vUSI27ssY0blwYX311gJdf7l7jhY7DwxvzySd7OHbsMsBfBc6b1chYSgqenziRysmTaZYH2EuX/sn585l4eNhXuFlKRQweHIJeb8Nbb20nNTWXlStjWbkyFo1GoU0bX8aObU/37oEoGgW33u7ovXSYjCrnNfnsnp6Cvb2OTp3ufNlsp0716NQpgP37k5g9O5qpU/vcsI1tgB1e9/1V5+qKkbRVKXje682lq+Z6Uh38PDH8fhW1wISiU3Dr7l6tc2vs2Pbs3HkeX19HPv54gGXZvn0jyZAS1iP5ZuK2lBQ5v37pXomSulL79yeVW5ugqhQWFhMdfYmYmJQaXRpWV5Qs4QoPb2R5cgTmQr4ODjpOnEhl48bTVXKstDQDH320G4Cnnw5j69bH+OWXKN58sy8jR7aiU6cA+vRpQFRUSyZO7Mzbb99teWI9Y8Zejh69+bK4ikpPz+Ptt7cD5to019dAuxPt2/vj7+9Mbm4hW7eeKXObH388QkpKDn5+TpalB3di4MCmLFv2IO++249nnulEREQzOnTwJ9tW5UR6BsePp3JxQ0qp5Xfbt5/lwoWsUoEFY3ohBefzQQGn1uaneA4OOp5+uiPLlj1IZOS11tFDhoSwdGkUo0a1viEg9XeKjYKtvx0undzwHuGHY2snUCAvLpfLvyaTfy6PzN1XydhmDkjZNbTHK8JHAlK1mIODjlGjWuPqap1OW2VRTSqpS1Po37gePk7Xsu5Cfa5lBaYuS0G18mfA4MEhaLUajh+/zE8/xZjHFOpt9XoXJbp1q09IiCd5eUZ++imG48fNGY4SlCqbg4Ou1gSkagM7O63lQWLJg4wSJ06kkp6eh6Ojnvbta24+hYc35qmnOvD663dhb187PjcGDw5h9epRtGnjW9NDwdPToVTdp169gko1cbEmd3d7y5LUkoLrBoORWbOiAXjqKfN1Z1W6557GbNz4CDNnDmLUqNYEB7tjMqkcPpzMyy9vsHS2UxQFx5bOOLdzYdsucwZgt271S9VQvBPjx3cCYNWqOEtzir/TeenxivDFxkVLcXYxaasuc/lEBoPr1SMiKBC1wITOR4/3UF/sGlTv8mt3d3uWLXuQr74aXOX/TYSoKMmUEpVmMl0rDtqhw41BqQYN3AgOdicx8So7d57j3nubVPoYV6/msXDhMWxtbfDxccTHxxFvb0e8vBw4cyaD/fsvcuBAEkeOpFBYaK6jExDgzKBBTRk0qKlcaJYhK6uA339PAG4seunhYc+YMW345puDzJy5n759G95RrQZVVfm//9tJdnYBLVp488gjbdFoFBo2dKNhQ7dy2yWrqkpi4lU2bUrkP//ZxPz5w+7oZlhVVd55Zzvp6Xk0aeLBM890uu19/Z1GozB4cFNmz45m9eo4BgwoPc+joy/x3XeHAXjuuS63Xcjz7/z8nPDzK12XxWAw8vxTawguKOLolos4t3LGs6X5b2D+fPPN8vDhLSwX8Tkx5gszu4b2NwSEvL0defXV3jz6aFuMRlO5bbFvRaPV4NrVHbuGDmRsS6c4q4j09WmW1506uODcofy2yEKUyDttoCizCJ2NhgdbNeLzPccBaHldUKooo4i804ZyW6ZXBw8Pe/r0acCmTYksWmQeU00s3SuhKAqPPdaOKVM28cMPRzCZVDw87AkMtO7SRlF3RUW1ZN68I0RHXyIu7gohIebaViVL97p1q1+jdZw0GoVx4zrW2PHrgoEDm1jq2w0fHlqjYxk2rAW//57A2rXxPP98V3788QhXr+YRFORaaklfVdLrbejSpT5dupjfi5OSspk2bQuHDiXz/vs7mTHj3lLXHdu2mef27XQALE+bNr707BnEzp3n+Pbbg+VmQGpdtHhF+JC+Lg1jWiE2B/No4eqKra0W5zAXnNq5lNmhr7rI9ZioSZIpJSotIcFcT8reXkeLFt5lblOSLbV5c2Kl928wGJk4cS3ffXeIr746wBtvbGPChN+IilrC3Xf/wNixK/jqqwPs359EYWExHh72ODjoSErKZvbsaIYNW8zYsStYseKkZE9dZ+3aUxQWFtOkiUeZRV1LCmBfvJhlyai6XRs2nGbr1jNotRpee613xbs1KQpTp/YhMNCV5OQcXntty23/N1RVlU8+2cO2bWfR6Wx4662+VfYUrERJ5tHevRdJTc21fP/06au89NLvGI3F3H13MPfcU73deBwcdLzzyT3EFmaTazCy/ZuTGPOLOXEilUOHktFqNURFtQQw14BKMHeFcWpb/s1qYKDrbQekrmfrZ4v3cF9L1pSiMxdodwlzlQsgUSHFWUWW/98n2J9QH3f8nR0I9XErdztrKbmxKslO7NLFel3TytK/fyMCA10t75vt2/vJ35moMB8fR0v3uIULr2VL7dhRs0v3RMX17RtM/fouhIZ612iQHMyrKQIDzQXPFy48yo8/mh+SPfts51tmXleVgABn/vvf3mi1GnbtOl/qviQpKZv4+HQ0GqXKm6qUdOJbvz6BhIT0crezsbfBc7A3tvVsKcgvIrOwkEQ/I84dXK0akBKipklQSlRaydK9du18y/1QKUnZ3bnzXLmpq2UxGov5179+5+TJNNzd7YmIaEa3bvVp3NjDstzMzc2Ofv2CmTy5B0uWPMD69Q/z++9jeOedu+nePRCNRiEmJoW33trO669vpajoxjb3/2uuL3A+bFiLMm9SHBx0jBsXBsCsWdHk5t7e0surV/P44INdgHmdemW7CDk56Xn/fXORxV27zvPjj0cqPQaTSeWdd3ZYliC8/HL3aulmFBjoStu2vphMKmvXmjvMXL6cy8SJa8nOLqBtW1/eequvVW4KfXwcefi1TuSpxRRkGJn/9n7LkqLw8MaWLmI5x7LBBPoAW/Te+pvtssqUZE35jPDD5wE/7IOlToGoOBuXa1mGGkXhzX5hfHFfd+y02nK3s5bOnesREHBtCWzr1jW7hEejUXjkkWtLhWXpnqiskSNbAbBuXQLp6XkkJ+dw6tQVNBqF7t0Da3h04lYcHHQsXfpgldYHvV0lBc8BvvrqAPn5RbRu7Wt5cG0tDRu6WTq4fvTRbsv17bZtZwDz+2RVL7tu1syLfv2CUVWVzz7bW+rB5d9p9Bo8Bniz05jO9wkJOAfJNZL43yPL90SllRQ5L2vpXolmzTzp2rU+e/Zc4O23t/P11/fd8sPRZFJ5441t7Nt3EXt7HZ9+ei+hoaUzsQoKitDpbG7Yl52dlgEDmjBgQBPS0gysXBnL118f4LffTpGTU8j//V//Ks+SqYz09DwOHEgiLc2AwWAs9dW8uRejRlVdUe+yxMSkcPr0VWxtteUunQO4//7mzJ9/lHPnMpk374hlXXxlfPjhH2Rk5NO0qaelTXllhYR48sorPXj77e3MnLmfhg3d0OlsLAW+T51Kx2Awcv/9zRg5slWp+lhFRSZee20Lv/+egEaj8OqrvYmIqL5Cn/fdF8KRIymsXh3H8OEteP75daSk5NCggRvTpw+osmV7FdGspTcZw4M4sywJ7Vkju+PNT7dHjzbPr6JMI4aT5gsjpzbO5e6numilu564DfaNHNC6ainKNGdCacoI8mrdtDVSlFWjUYiMbM6XX+6na9f6Vnv6fzODB4cwe/YhUlNzLUtYhKio1q19adnSh+PHL7Po68M42WgxFZho08kfN7eaqy0nKq6mg1HXu+++EL78cr/lAfFzz3WukezNsWPbs359AufPZ/Lll/t5+eUe1bJ073pPP92RLVvOsGvXeQYOnI+3tyMtWngRGupNu3Z+hIX5W86FYqNwPOUqRlWlXj1Zci3+9yjq9RVxa4GsrCxcXV3JzMzExUX+KGsbk0nlnnt+JDMzn+++u/+mhR2TkrKJilpCfn4RU6b0umUnvk8+2c38+UexsdHw6af33nHa8fbtZ/n3vzdSWFhMx44BTJ8+4I4K+L355jaioy/RsWOApc2so2PZmSZFRSZiYlLYs+cCf/xx3tLCuDzTpw+okrT4P/9MZdmyk6Sn56HX26DVatDpNMTGXuHkyTQiIprx2ms3dgK53ubNibzyygbs7LQsX/4QXl4Vv9HbsiWRl1/egEajMG/eUEu3lduhqirTpm3lt99O3XQ7R0c9I0e2YtSo1tjZafn3vzeyfftZbGw0vPPO3ZalCNUlJ6eQ8PAfLUsj4+PT8fR0YO7c+y0ZFNakqio7P/qTi0fTOZWVRZG/jkljOpJ/IZ/iv27qtR46vIf5yrIeUWfkxGRxae7Fcl/3f7yeVbvvXa+oyMTKlbH07FlzRYX/7tKlbFJTDbWi+LKoe5Z/FcPUt7bhptMR6OrE0ZR0Hu3WjKff7FZjf2ei7vrPfzayYcNpevduwPTpA2psHPv2XeSZZ9agKApffDGQiRPXYjKprFjxULUFglaujGXBgqOcPn31hnIU997bhKlTe1seXvbvP4+MjHwWLhxeLdn9QtSEisZ2JCglKiU+Pp2HHvoFOzstW7c+dsunwgsWHGX69N04OupZsuSBci/Yf/ophhkz9gDw5pt9b5rNUxkHDybx4ovrMRiMhIZ68/nnA2+rcPahQ5d46qlVpb5nY6OhXTtf2rb1Ize3kCtX8khPz+PKlTxSUnLIzy9d36RZMy8aNnTFwUFn+YqPT2fLljP4+zvz888jbqubTFGRic2bE1m06BgxMTfvWPf995Fl1pO6nqqqPPHESmJiUhg2rAVTpvSq0Di2bTvDlCmbKSgoYuzY9lVSVDwvz8hTT60iLu4KDRq40bSpByEhnoSEeJKTU8icOYcsa/UdHHTUq+fCqVNX0Ott+PDDe+jRo2prBJRnypRNliLy9vY6Zs0ackcBuTtlTCtk/4xYLl7MplUrb1xd/przGtD72OLaww2dh3WW7glRVXJiskhdmmLJmAJzhpT3UF+5URaiiuTEZHF+znnGrdjJ1bwCy/dnDO5GkKtTjQaARd105YqBX3/9kxEjQvHwqN5Ocrfy6qubWbcuHnt7HXl5Rho39mDx4hHVfty8PCNxcVc4cSKV48dT2bDhNMXFJlq08Objj8NxctLTu/dcALZte6zch95C1DUSlPofkJVVwMmTafz5Zyp//plGZmY+//1vb+rXr57zlpVVwPTpu1m9Oo4uXeoxc+bgW/6MyaQyduwKjh27TO/eDfj44/BS2Rkmk8qiRceYPn03AM8/34UxY9pW6bhPnEhl4sS1ZGbm06iRO199NRhPz8ot85gwYQ17916kT58GBAQ4s2vX+VvWynJzs6Nr1/p07x5I1671y/wgzssz8sADS0hOzuHRR9sycWKXCo+puNjEjz/GsHjxcctada1WQ//+jWjf3g+j0YTRWGz53wYN3CrcCfHw4WSefHIlGo3Czz8/QMOGbjfdfuHCo0yfvgdVVenePZCPPgqvsuWSJpNKUZGpzP2ZTCpbt55h9uxo4uKuAObg1CefDCAsLKBKjl8Ru3efZ+LEtWg0CjNm3Fsr6m5k7skg52gWWmcttvXtzF/+dmhsa355kRC3SzWp5J02UJxVhI2LecmeFIMVomqoJpUzb8ZTlFnEL8dPs+CI+WGLr5M9Xw7pgaIoaN20NJzaRP7uRJ2Unp7H8OE/k51tDrhW1UPUyoqOvsTLL28gMzMfDw97xo/vyDvv7MDFxZbNmx+1+niEqC4SlPqHKiwsZs6caNatS+DixawbXg8Pb8y77/ar9H4NBiNXrhioV8/lhrXomZn5zJ9/lEWLjmEwGAGYOrU399/fvEL7TkhIZ/TopRQVmXjvvX7cc09jAM6dy+Stt7Zx6FAyYK578+KL3So99oo4ffoqEyb8RmpqLp071+OLLwZVeM390aMpPP74CmxsNCxf/iD+/uYlWefPZ/LHH+dJSLiKq6stHh72eHo64Olpj5eXA4GBrhU6xvbtZ5k0aT02NhoWLBhG48YeFRrXV1/tZ86cQ4C5NfmIEaEMG9aiUsvtbuall9azbdtZ7rqrIR99FF7mNiaTyvTpu1m06BhgLqI+eXKPCnfbqyqqqrJjxzm2bEkkKqpluV0hq/P4v/xygqAg11pTw0VVVdQCE4qtRpbpCSGEuCVDfC4XZ5prEWblF/LUih0Yi00MbhbEE2HXajPWmxCEQ5PasVRViMpauvRP3n13BwDz5g29oX6ttSQlZTNp0nri469152ve3IuffhpWI+MRojpIUOofKD4+nalTt3Dq1BXL9wICnAkN9aZ+fRe+//4wGo3C8uUPVbiWjcmksmzZn3z66V4MBiO2tloaNXKnSRN3mjb1JC3NwC+/nLAEo5o29eTJJ9tz993BlbrR/eabA8yaFY2Hhz2LFo1g9eo4vv76AIWFxdjb65g4sTMPPBBarTfPZ85kMHr0UgoKivjXv7rz0EOtKvRzzz+/ll27zleoHtPt+te/fmfr1jO0bevLrFkRtwxmJSZeZeTIXykqMjFpUjceeCAUna5qC7knJl7lwQd/wWRSmTMngrZtS3dxyssz8uqrmy2FIp97rgtjxrSRAIgQQghRB2VHZ5L8Y5Ll34tiElgVe453+nekofu160q/MQE4d3CtiSEKccdMJpX33tuBqsKUKb1qtDC8wWDk9de3snlzImDuXv7BB/fU2HiEqGoSlPoHMZlUFi48yhdf7MdoLMbd3Z6XXupG9+6BpVqYPvPMGvbtu8jIka146aXut9zvhQtZvP32dg4cMF+AaDTKDUX4SjRr5sVTT3Wgd+8Gt/XmXVhYzOjRS0lMvIqDg84S5OratT7//W8vS/ZRdVuy5Djvv78Lvd6G+fOHERzsftPt//wzlTFjlqHRKPz6axSBgdVzEZaSksOIEUvIyzPeMgvNZFIZN24Vhw4ll7kksiq98852li07SZs2vsyZE4GqwrFjl9m58xwbNpzm/PlM9Hob3njjLksGnBBCCCHqnuszpW5GMqWEqDomk8rs2dH88MMRJk/uUa0do4WwNglK/UMkJ+fw+utbLYGjXr2CmDq1T5n1iUrq2tjb61izZlSpgNX1TCaVxYuPMXPmfvLzi7C11fLss5144IGWJCVlEx+fbvkqKChi+PBQevUKuuPAR0xMCk88sRJVVXF2tuXFF7syZEiIVTNrVFXluefWsnv3BVq08Gbu3PtvWqy9JINp0KCmvPlm32od2/z5MXzyyR5cXGz59dco3N3LLga5cmUsb765DTs7LUuWPFCtAb3U1FwiIxdTUFBE9+6BnDiRSkZGvuV1V1c7pk8PvyGLSgghhBB1y/U1pcojNaWEqB4mk1qjWVtCVAcJStVx2dkF/PRTDAsWHCMvz4idnZZJk7oxdGjzcoM4qqoycuSvxMen8+yznXnssXY3bJOTU8gLL6zj8GFzHaewMH+mTu1TbcXR/27lylhiY9N47LF2eHvXzFO21NRcHnzwF7KyCnjqqQ6MG9exzO1OnbrCyJG/oigKS5bcutj3nSouNjFmzDLi4q4wZEgI06bddcM2V6+aCzRmZRXwwgtdefjhNtU6JoAvv9zPd98dsvzbyUlP9+6B9OwZRM+eQeUGP4UQQghRt+TEZHFp7sVyX5fue0IIISqqorEdrRXHJCogP7+IxYuP8cMPR8jKMneGaNPGl9dfv4ugoJsvHVMUhTFj2jBt2lYWLTrGqFGtS3UsM5lUXn11M4cPJ+PgoOOFF7oSGdncqlF5c0pqzaalens78u9/92TKlE3MmXOIHj2CaNXK54btSoqI33NPo2oPSAHY2GiYMqUXjz++glWr4lAUhWef7VwqK27GjD1kZRUQEuLJyJEVq4l1px57rB2ZmfnY2+vo3bsBbdr43jS7TAghhBB1k1MbF/wfh9SlKaUyprRuWryH+kpASgghRJWTTKkaZDKpZGTkk5ZmIC3NQEJCOj/9dJQrVwwABAe7M358R/r2bVjhJW5GYzEREYtITc1l2rQ+DBlyLQBUkvGi19swZ06E1TuU1Tb//e8m1q9PICjIlfnzh2Fvr7O8lph4laioX1BVlUWLRtCkScU64lWFb789yLffHgTA2dmW8eM7MmJEKNHRl3j66dUoisLcufeXGUgTQgghhLhTqkkl77SB4qwibFy02DdykCV7QgghKkWW79Vi0dGXePvt7Vy4kFVmYfGAAGfGjQtj4MCmt5XFNG/eET77bC+NGrmzePEIFEVh06bTTJ68EYC33urLwIFN7/j3qOuysgp46KFfuHw5Fzc3Oxo0cKV+fRcCA105dOgSe/depG/fhnz4YbjVxxYTk8L77+8iNjYNgJAQTwwGIxcuZPHAA6FMntzT6mMSQgghhBBCCCEqQoJStZTBYGTEiJ+5fDkXMC+5c3e3w8vLAS8vB3r1CiIysjk6nc0t9lS+7OwCBg9egMFg5LPPBuLt7cDjj68gP7+Ihx9uwwsvdK2qX6fO27//Ii+99LulG+Df/fTTMJo397LyqMxMJpWlS/9k5sz9ZGebl3J6ejrw669RODnpa2RMQgghhBBCCCHErUhNqVpq1qyDXL6cS0CAM99+OwQvL4cqr8/j7GzL0KHNmT//KLNnR5OWZiA/v4guXeoxcWLnKj1WXdepUz3WrXuYs2czuHAhi/Pns7hwwfzVsWNAjQWkADQahREjQunXL5gvvtjHjh3nmDq1twSkhBBCCCGEEEL8I0imlBWdOnWF0aOXYjKpfPrpvfToEVRtx0pOziEiYqFleWC9ei78+ONQ6ZQmhBBCCCGEEEKIalXR2I600LISk0nlvfd2YjKp9OsXXK0BKQA/PyfCwxsDYG+v4+OPwyUgJYQQQgghhBBCiFpDlu9ZyYoVJ4mJScHBQcdLL3W3yjEnTOhEfn4RI0aEWrV7nBBCCCGEEEIIIcStSFDKCtLT8/j8830AjB/fER8fR6sc19/fmY8+sn7nOCGEEEIIIYQQQohbkeV7VvDpp3vIyiogJMSTqKiWNT0cIYQQQgghhBBCiBonQalqduBAEmvWnEJRFKZM6YWNjZxyIYQQQgghhBBCCImQVCOjsZj/+7+dAAwf3oJWrXxqeERCCCGEEEIIIYQQtYMEpaqRVqvhscfa0bixBxMmdKrp4QghhBBCCCGEEELUGoqqqmpND+J6WVlZuLq6kpmZiYuLS00Pp0qYTCoajVLTwxBCCCGEEEIIIYSodhWN7UimlBVIQEoIIYQQQgghhBCiNAlKCSGEEEIIIYQQQgirk6CUEEIIIYQQQgghhLA6bU0P4O9KSlxlZWXV8EiEEEIIIYQQQgghRGWVxHRuVca81gWlsrOzAQgMDKzhkQghhBBCCCGEEEKI25WdnY2rq2u5r9e67nsmk4mkpCScnZ1RFOsWCM/KyiIwMJDz58//Yzr/ibpH5qGoDWQeCmuTOSdqmsxBYW0y50RtIPNQVBdVVcnOziYgIACNpvzKUbUuU0qj0VC/fv0aHYOLi4v8QYoaJ/NQ1AYyD4W1yZwTNU3moLA2mXOiNpB5KKrDzTKkSkihcyGEEEIIIYQQQghhdRKUEkIIIYQQQgghhBBWJ0Gp69ja2jJt2jRsbW1reijif5jMQ1EbyDwU1iZzTtQ0mYPC2mTOidpA5qGoabWu0LkQQgghhBBCCCGE+OeTTCkhhBBCCCGEEEIIYXUSlBJCCCGEEEIIIYQQVidBKSGEEEIIIYQQQghhdRKUEkIIIYQQQgghhBBWVyeCUu+99x6dOnXC2dkZHx8fIiMjiY2NLbVNfn4+EyZMwNPTEycnJ4YPH05KSkqpbZ577jnCwsKwtbWlXbt2NxznzJkzKIpyw9eePXtuOcaZM2fSsGFD7Ozs6NKlC/v27bvlfhVFYcmSJbd3UoRV1fU5CJCcnMyYMWPw8/PD0dGRDh068Ouvv1b+ZIga80+YhwkJCQwdOhRvb29cXFyIioq6YXyi9qjtc2779u0MGTKEgIAAFEVh+fLlN2yjqiqvvfYa/v7+2Nvb079/f06dOlXpcyFqzj9hHi5dupTw8HA8PT1RFIXDhw9X9jQIK6nr881oNDJ58mRat26No6MjAQEBPPLIIyQlJd3W+RA1w1rzEMyfkx999BEhISHY2tpSr1493nnnnVuOccmSJTRv3hw7Oztat27Nb7/9Vup1ed8TFVUnglLbtm1jwoQJ7Nmzhw0bNmA0GgkPDyc3N9eyzYsvvsiqVatYsmQJ27ZtIykpiWHDht2wr7Fjx/Lggw/e9HgbN27k0qVLlq+wsLCbbr948WImTZrEtGnTiI6Opm3btgwYMIDLly8DEBgYWGp/ly5d4o033sDJyYmBAwfexhkR1lbX5yDAI488QmxsLCtXruTo0aMMGzaMqKgoDh06VMmzIWpKXZ+Hubm5hIeHoygKmzdvZteuXRQWFjJkyBBMJtNtnBFR3Wr7nMvNzaVt27bMnDmz3G0++OADPvvsM77++mv27t2Lo6MjAwYMID8//xa/vagt/gnzMDc3l549e/L+++/f4rcVNa2uzzeDwUB0dDRTp04lOjqapUuXEhsbS0RERAV+e1FbWHMePv/888yePZuPPvqIkydPsnLlSjp37nzT8f3xxx+MHDmSJ554gkOHDhEZGUlkZCTHjh2zbCPve6LC1Dro8uXLKqBu27ZNVVVVzcjIUHU6nbpkyRLLNn/++acKqLt3777h56dNm6a2bdv2hu8nJiaqgHro0KFKjadz587qhAkTLP8uLi5WAwIC1Pfee6/cn2nXrp06duzYSh1H1B51cQ46Ojqq8+bNK/VzHh4e6qxZsyp1LFF71LV5uH79elWj0aiZmZmWbTIyMlRFUdQNGzZU6liiZtS2OXc9QF22bFmp75lMJtXPz0/98MMPLd/LyMhQbW1t1YULF972sUTNqmvzsKqPIayrLs+3Evv27VMB9ezZs7d9LFGzqmsenjhxQtVqterJkycrNZ6oqCh18ODBpb7XpUsXddy4cTdsK+974lbqRKbU32VmZgLg4eEBwMGDBzEajfTv39+yTfPmzQkKCmL37t2V3n9ERAQ+Pj707NmTlStX3nTbwsJCDh48WOrYGo2G/v37l3vsgwcPcvjwYZ544olKj03UDnVxDnbv3p3FixeTnp6OyWRi0aJF5Ofnc9ddd1V6fKJ2qGvzsKCgAEVRsLW1tWxjZ2eHRqNh586dlR6fsL7aNOcqIjExkeTk5FLjc3V1pUuXLrc1PlE71LV5KOq2f8J8y8zMRFEU3NzcqmX/ovpV1zxctWoVjRo1YvXq1QQHB9OwYUOefPJJ0tPTb/pzu3fvLnVsgAEDBshnq7gtdS4oZTKZeOGFF+jRowetWrUCzLVy9Hr9DW+0vr6+JCcnV3jfTk5OfPzxxyxZsoQ1a9bQs2dPIiMjb/oBkZaWRnFxMb6+vhU+9pw5c2jRogXdu3ev8NhE7VFX5+DPP/+M0WjE09MTW1tbxo0bx7Jly2jSpEmFxydqj7o4D7t27YqjoyOTJ0/GYDCQm5vLv/71L4qLi7l06VKFxydqRm2bcxVRMobKfEaL2q0uzkNRd/0T5lt+fj6TJ09m5MiRuLi4VOm+hXVU5zw8ffo0Z8+eZcmSJcybN4/vv/+egwcPMmLEiJv+XHJysny2iiqjrekBVNaECRM4duxYtTxV9/LyYtKkSZZ/d+rUiaSkJD788EMiIiLYsWNHqRpQ33zzDX379q3UMfLy8liwYAFTp06tsnEL66qrc3Dq1KlkZGSwceNGvLy8WL58OVFRUezYsYPWrVtX+e8iqlddnIfe3t4sWbKE8ePH89lnn6HRaBg5ciQdOnRAo6lzz0j+59S2OTd69OgqH4eo/WQeCmuq6/PNaDQSFRWFqqp89dVXVTZ2YV3VOQ9NJhMFBQXMmzePkJAQwJxAERYWRmxsLPb29oSGhlq2nzJlClOmTKnycYj/bXUqKPXss8+yevVqtm/fTv369S3f9/Pzo7CwkIyMjFLR4pSUFPz8/O7omF26dGHDhg0AdOzYsVTXAF9fX2xtbbGxsbmh00F5x/7ll18wGAw88sgjdzQuUTPq6hxMSEjgiy++4NixY7Rs2RKAtm3bsmPHDmbOnMnXX399R2MU1lVX5yFAeHg4CQkJpKWlodVqcXNzw8/Pj0aNGt3R+ET1qo1zriJKxpCSkoK/v3+p8ZXXhUjUXnV1Hoq6qa7Pt5KA1NmzZ9m8ebNkSdVR1T0P/f390Wq1loAUQIsWLQA4d+4cffv2LTUPS5YP+vn5Vfj+V4hbqROPplVV5dlnn2XZsmVs3ryZ4ODgUq+HhYWh0+nYtGmT5XuxsbGcO3eObt263dGxDx8+bLmQtbe3p0mTJpYvZ2dn9Ho9YWFhpY5tMpnYtGlTmceeM2cOEREReHt739G4hHXV9TloMBgAbshGsbGxka5ndUhdn4fX8/Lyws3Njc2bN3P58mXpClRL1eY5VxHBwcH4+fmVGl9WVhZ79+694/EJ66nr81DULf+E+VYSkDp16hQbN27E09PzjsYlrM9a87BHjx4UFRWRkJBg+V5cXBwADRo0QKvVlpqHJUGpbt26lTo2wIYNG+SzVdyWOpEpNWHCBBYsWMCKFStwdna2rFV1dXXF3t4eV1dXnnjiCSZNmoSHhwcuLi5MnDiRbt260bVrV8t+4uPjycnJITk5mby8PEvUNzQ0FL1ezw8//IBer6d9+/YALF26lO+++47Zs2ffdHyTJk3i0UcfpWPHjnTu3JkZM2aQm5vL448/Xmq7+Ph4tm/fzm+//VaFZ0dYQ12fg82bN6dJkyaMGzeOjz76CE9PT5YvX86GDRtYvXp1NZwxUR3q+jwEmDt3Li1atMDb25vdu3fz/PPP8+KLL9KsWbMqPluiKtT2OZeTk0N8fLzl34mJiRw+fBgPDw+CgoJQFIUXXniBt99+m6ZNmxIcHMzUqVMJCAggMjKyak+WqDZ1fR4CpKenc+7cOZKSkgDzzSOYsw0ks6B2qevzzWg0MmLECKKjo1m9ejXFxcWW38HDwwO9Xl+Vp0tUE2vNw/79+9OhQwfGjh3LjBkzMJlMTJgwgXvuuadU9tTfPf/88/Tp04ePP/6YwYMHs2jRIg4cOMC3335r2Ube90SF1Vzjv4oDyvyaO3euZZu8vDz1mWeeUd3d3VUHBwd16NCh6qVLl0rtp0+fPmXuJzExUVVVVf3+++/VFi1aqA4ODqqLi4vauXPnUm02b+bzzz9Xg4KCVL1er3bu3Fnds2fPDdv85z//UQMDA9Xi4uLbPheiZvwT5mBcXJw6bNgw1cfHR3VwcFDbtGmjzps3747Oi7Cuf8I8nDx5surr66vqdDq1adOm6scff6yaTKY7Oi+i+tT2Obdly5Yy9/voo49atjGZTOrUqVNVX19f1dbWVu3Xr58aGxtbFadHWMk/YR7OnTu3zG2mTZtWBWdIVKW6Pt8SExPL/R22bNlSRWdJVDdrzUNVVdWLFy+qw4YNU52cnFRfX1/1scceU69cuXLLMf78889qSEiIqtfr1ZYtW6pr1qwp9bq874mKUlRVVcsOVwkhhBBCCCGEEEIIUT3qRE0pIYQQQgghhBBCCPHPIkEpIYQQQgghhBBCCGF1EpQSQgghhBBCCCGEEFYnQSkhhBB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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_anomaly(df, anomaly_df_horizon, time_col = 'ds', target_col = 'y')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 📘 **Balancing h and step_size depends on your data:** For frequent, short-lived anomalies, use a smaller `h` to focus on short-term predictions and a smaller `step_size` to increase overlap and sensitivity. For smooth trends or long-term patterns, use a larger `h` to capture broader anomalies and a larger `step_size` to reduce noise and computational cost." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "python3", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb deleted file mode 100644 index c37094c3..00000000 --- a/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb +++ /dev/null @@ -1,459 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "!pip install -Uqq nixtla" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide \n", - "from nixtla.utils import in_colab" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide \n", - "IN_COLAB = in_colab()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "if not IN_COLAB:\n", - " from nixtla.utils import colab_badge\n", - " from dotenv import load_dotenv" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "pd.set_option('future.no_silent_downcasting', True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "def plot_anomaly(df, anomaly_df, time_col = 'ts', target_col = 'y'):\n", - " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n", - " plt.figure(figsize=(12, 2))\n", - " plt.plot(merged_df[time_col], merged_df[target_col], label='y', color='navy', alpha=0.8)\n", - " plt.plot(merged_df[time_col], merged_df['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", - " plt.scatter(merged_df.loc[merged_df['anomaly'], time_col], merged_df.loc[merged_df['anomaly'], target_col], color='orchid', label='Anomalies Detected')\n", - " plt.legend()\n", - " plt.tight_layout()\n", - " plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Improve Detection Accuracy\n", - "\n", - "This notebook shows how to enhance anomaly detection accuracy by controlling the detection process. TimeGPT uses its forecasting power to detect anomalies based on forecast errors. By optimizing forecast parameters and accuracy, you can significantly improve anomaly detection performance." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/anomaly-detection/06_improve_detection_accuracy.ipynb)" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "if not IN_COLAB:\n", - " load_dotenv()\n", - " colab_badge('docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "from nixtla import NixtlaClient" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "nixtla_client = NixtlaClient(\n", - " # defaults to os.environ.get(\"NIXTLA_API_KEY\")\n", - " api_key = 'my_api_key_provided_by_nixtla'\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1 Conduct anomaly detection\n", - "After initializing an instance of `NixtlaClient`, let’s explore an example using the Peyton Manning dataset." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " unique_id ds y\n", - "2764 0 2015-07-05 6.499787\n", - "2765 0 2015-07-06 6.859615\n", - "2766 0 2015-07-07 6.881411\n", - "2767 0 2015-07-08 6.997596\n", - "2768 0 2015-07-09 7.152269" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_csv('https://datasets-nixtla.s3.amazonaws.com/peyton-manning.csv',parse_dates = ['ds']).tail(200)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", - "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" - ] - } - ], - "source": [ - "# Base case for anomaly detection using detect_anomaly_realtime\n", - "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", - " df,\n", - " freq='D',\n", - " h=14,\n", - " level=90,\n", - " detection_size=100\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_anomaly(df, anomaly_df, time_col = 'ds', target_col = 'y')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Improving the Anomaly Detection Process\n", - "To enhance anomaly detection, we will explore two approaches: finetuning the model to improve forecast accuracy and adjusting forecast horizons and step sizes to optimize how the time series is segmented and analyzed. These methods help tailor the process to your data for better results." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 2.1 Finetune TimeGPT\n", - "TimeGPT uses forecast errors for anomaly detection, so improving forecast accuracy reduces noise in the errors, leading to better anomaly detection. You can fine-tune the model using the following parameters:\n", - "* `finetune_steps`: Number of steps for finetuning TimeGPT on new data.\n", - "* `finetune_depth`: Intensity of fine-tuning, with options ranging from 1 to 5.\n", - "* `finetune_loss`: Loss function to be used during the fine-tuning process." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", - "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" - ] - } - ], - "source": [ - "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(\n", - " df,\n", - " freq='D',\n", - " h=14,\n", - " level=90,\n", - " detection_size=100,\n", - " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", - " finetune_depth = 2, # Intensity of finetuning\n", - " finetune_loss = 'mae' # Loss function used during the finetuning process\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_anomaly(df, anomaly_online_ft, time_col = 'ds', target_col = 'y')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### 2.2 Change forecast horizon and step\n", - "Similar to cross-validation, the anomaly detection method generates forecasts for historical data by splitting the time series into overlapping windows. The way these windows are defined can impact the anomaly detection results. Two key parameters control this process:\n", - "* `h`: Specifies how many steps into the future the forecast is made for each window.\n", - "* `step_size`: Determines the interval between the starting points of consecutive windows." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", - "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" - ] - } - ], - "source": [ - "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(\n", - " df,\n", - " time_col='ds',\n", - " target_col='y',\n", - " freq='D',\n", - " h=2, # Forecast horizon\n", - " step_size = 1, # Step size for moving through the time series data\n", - " level=90, \n", - " detection_size=100\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/mt/bm2h50kj2872xhymzl24djch0000gn/T/ipykernel_21069/2618285972.py:3: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left').fillna({'anomaly': False}).ffill()\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_anomaly(df, anomaly_df_horizon, time_col = 'ds', target_col = 'y')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "> 📘 **Balancing h and step_size depends on your data:** For frequent, short-lived anomalies, use a smaller `h` to focus on short-term predictions and a smaller `step_size` to increase overlap and sensitivity. For smooth trends or long-term patterns, use a larger `h` to capture broader anomalies and a larger `step_size` to reduce noise and computational cost." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "python3", - "language": "python", - "name": "python3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index 134ad246..aa11b41d 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -49,18 +49,23 @@ "outputs": [], "source": [ "#| hide\n", - "import matplotlib.pyplot as plt\n", - "\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", "def plot_anomalies(df, unique_ids, rows, cols):\n", " fig, axes = plt.subplots(rows, cols, figsize=(12, rows * 2))\n", " for i, (ax, uid) in enumerate(zip(axes.flatten(), unique_ids)):\n", " filtered_df = df[df['unique_id'] == uid]\n", " ax.plot(filtered_df['ts'], filtered_df['y'], color='navy', alpha=0.8, label='y')\n", " ax.plot(filtered_df['ts'], filtered_df['TimeGPT'], color='orchid', alpha=0.7, label='TimeGPT')\n", - " # [ax.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", - " ax.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", - " filtered_df.loc[filtered_df['anomaly'] == 1, 'y'], \n", - " color='orchid', label='Anomalies Detected')\n", + " ax.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], filtered_df.loc[filtered_df['anomaly'] == 1, 'y'], color='orchid', label='Anomalies Detected')\n", " ax.set_title(f\"Unique_id: {uid}\", fontsize=8); ax.tick_params(axis='x', labelsize=6)\n", " fig.legend(loc='upper center', ncol=3, fontsize=8, labels=['y', 'TimeGPT', 'Anomaly'])\n", " plt.tight_layout(rect=[0, 0, 1, 0.95])\n", @@ -129,6 +134,28 @@ ")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> 👍 Use an Azure AI endpoint\n", + "> \n", + "> To use an Azure AI endpoint, set the `base_url` argument:\n", + "> \n", + "> `nixtla_client = NixtlaClient(base_url=\"you azure ai endpoint\", api_key=\"your api_key\")`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#| hide\n", + "if not IN_COLAB:\n", + " nixtla_client = NixtlaClient()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -185,13 +212,7 @@ "output_type": "stream", "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] @@ -320,7 +341,6 @@ "plt.figure(figsize=(12, 3))\n", "plt.plot(filtered_df['ts'], filtered_df['accumulated_anomaly_score'], label='Score', color='navy', alpha=0.8)\n", "plt.axhline(y=threshold, color='red', linestyle='--', label=f'95% Threshold')\n", - "# [plt.axvline(ts, color='grey', alpha=0.3) for ts in filtered_df.loc[filtered_df['anomaly'] == 1, 'ts']]\n", "plt.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", " filtered_df.loc[filtered_df['anomaly'] == 1, 'accumulated_anomaly_score'], \n", " color='orchid', label='Anomaly Detected', alpha=0.8)\n", diff --git a/nbs/mint.json b/nbs/mint.json index 1393b9d3..b963d50c 100644 --- a/nbs/mint.json +++ b/nbs/mint.json @@ -67,7 +67,7 @@ "group": "Realtime Anomaly Detection", "pages": [ "docs/capabilities/realtime-anomaly-detection/quickstart.html", - "docs/capabilities/realtime-anomaly-detection/improve_detection_accuracy.html", + "docs/capabilities/realtime-anomaly-detection/adjusting_detection_accuracy_process.html", "docs/capabilities/realtime-anomaly-detection/univariate_vs_multivariate_anomaly_detection.html" ] } From 41a73174ae4b7e96d231c77d95133d1bf635ec06 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Fri, 13 Dec 2024 00:00:50 +0800 Subject: [PATCH 23/38] minor changes in formatting --- .../capabilities/realtime-anomaly-detection/01_quickstart.ipynb | 2 +- .../02_adjusting_detection_accuracy_process.ipynb | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb index 3a2d24c4..ad66261b 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb @@ -377,7 +377,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For an in-depth analysis of the `detect_anomaly_realtime` method, please refer to tutorial." + "For an in-depth analysis of the `detect_anomaly_realtime` method, refer to the tutorial (coming soon)." ] } ], diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb index 60ce9520..0a4a7ada 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb @@ -153,7 +153,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 1 Conduct anomaly detection\n", + "## 1. Conduct anomaly detection\n", "After initializing an instance of `NixtlaClient`, let’s explore an example using the Peyton Manning dataset." ] }, From ea9eb9a472d58e6e3c6cfc2d4f2097a94d3ffd30 Mon Sep 17 00:00:00 2001 From: yibeihu Date: Fri, 13 Dec 2024 16:27:38 +0800 Subject: [PATCH 24/38] change dataset loadng path --- .../realtime-anomaly-detection/01_quickstart.ipynb | 4 ++-- .../03_univariate_vs_multivariate_anomaly_detection.ipynb | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb index ad66261b..26d1508d 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb @@ -136,7 +136,7 @@ "metadata": {}, "outputs": [], "source": [ - "df = pd.read_csv('../../../assets/machine-1-1.csv', parse_dates=['ts'])" + "df = pd.read_csv('https://datasets-nixtla.s3.us-east-1.amazonaws.com/machine-1-1.csv', parse_dates=['ts'])" ] }, { @@ -348,7 +348,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index aa11b41d..eddfcd71 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -183,7 +183,7 @@ } ], "source": [ - "df = pd.read_csv('../../../assets/SMD_test.csv', parse_dates=['ts'])\n", + "df = pd.read_csv('https://datasets-nixtla.s3.us-east-1.amazonaws.com/SMD_test.csv', parse_dates=['ts'])\n", "df.unique_id.nunique()" ] }, From 68767afb7da80c3b090d55c40c6f92169284456d Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 13 Dec 2024 14:56:43 -0500 Subject: [PATCH 25/38] Jose comments --- nbs/src/nixtla_client.ipynb | 195 +++++++++++++++++++----------------- nixtla/_modidx.py | 16 +-- nixtla/nixtla_client.py | 173 +++++++++++++++++--------------- 3 files changed, 204 insertions(+), 180 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 8782df85..1ac2075c 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -172,10 +172,10 @@ "_NonNegativeInt = Annotated[int, annotated_types.Ge(0)]\n", "_Loss = Literal[\"default\", \"mae\", \"mse\", \"rmse\", \"mape\", \"smape\"]\n", "_Model = Literal[\"azureai\", \"timegpt-1\", \"timegpt-1-long-horizon\"]\n", - "_Finetune_Depth = Literal[1, 2, 3, 4, 5]\n", + "_FinetuneDepth = Literal[1, 2, 3, 4, 5]\n", "_Freq = Union[str, int, pd.offsets.BaseOffset]\n", "_FreqType = TypeVar(\"_FreqType\", str, int, pd.offsets.BaseOffset)\n", - "_Threshold_Method = Literal[\"univariate\", \"multivariate\"]\n", + "_ThresholdMethod = Literal[\"univariate\", \"multivariate\"]\n", "\n", "_date_features_by_freq = {\n", " # Daily frequencies\n", @@ -640,7 +640,50 @@ " else:\n", " # we only want to forecast\n", " new_input_size = input_size\n", - " return new_input_size" + " return new_input_size\n", + "\n", + "def _extract_target_array(df, target_col) -> np.ndarray:\n", + " # in pandas<2.2 to_numpy can lead to an object array if\n", + " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", + " # we thus use the dtype's type as the target dtype\n", + " if isinstance(df, pd.DataFrame):\n", + " target_dtype = df.dtypes[target_col].type\n", + " targets = df[target_col].to_numpy(dtype=target_dtype)\n", + " else:\n", + " targets = df[target_col].to_numpy()\n", + " return targets\n", + "\n", + "def _process_exog_features(\n", + " processed_data: np.ndarray,\n", + " x_cols: list[str],\n", + " hist_exog_list: list[str] | None = None,\n", + " logger: logging.Logger | None = None\n", + ") -> tuple[np.ndarray | None, list[int] | None]:\n", + " X = None\n", + " hist_exog = None\n", + " if processed_data.shape[1] > 1:\n", + " X = processed_data[:, 1:].T\n", + " if hist_exog_list is None:\n", + " futr_exog = x_cols\n", + " else:\n", + " missing_hist: set[str] = set(hist_exog_list) - set(x_cols)\n", + " if missing_hist:\n", + " raise ValueError(\n", + " \"The following exogenous features were declared as historic \"\n", + " f\"but were not found in `df`: {missing_hist}.\"\n", + " )\n", + " futr_exog = [c for c in x_cols if c not in hist_exog_list]\n", + " # match the forecast method order [future, historic]\n", + " fcst_features_order = futr_exog + hist_exog_list\n", + " x_idxs = [x_cols.index(c) for c in fcst_features_order]\n", + " X = X[x_idxs]\n", + " hist_exog = [fcst_features_order.index(c) for c in hist_exog_list]\n", + " if futr_exog and logger:\n", + " logger.info(f'Using future exogenous features: {futr_exog}')\n", + " if hist_exog_list and logger:\n", + " logger.info(f'Using historical exogenous features: {hist_exog_list}')\n", + "\n", + " return X, hist_exog" ] }, { @@ -1027,7 +1070,7 @@ " level: Optional[list[Union[int, float]]],\n", " quantiles: Optional[list[float]],\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", " clean_ex_first: bool,\n", " hist_exog_list: Optional[list[str]],\n", @@ -1113,7 +1156,7 @@ " level: Optional[list[Union[int, float]]] = None,\n", " quantiles: Optional[list[float]] = None,\n", " finetune_steps: _NonNegativeInt = 0,\n", - " finetune_depth: _Finetune_Depth = 1,\n", + " finetune_depth: _FinetuneDepth = 1,\n", " finetune_loss: _Loss = 'default',\n", " clean_ex_first: bool = True,\n", " hist_exog_list: Optional[list[str]] = None,\n", @@ -1587,14 +1630,15 @@ " )\n", " out = ufp.assign_columns(out, 'anomaly', resp['anomaly'])\n", " out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id)\n", + " self._maybe_assign_weights(weights=resp[\"weights_x\"], df=df, x_cols=x_cols)\n", " return out\n", " \n", - " def _distributed_detect_anomalies_realtime(\n", + " def _distributed_detect_anomalies_online(\n", " self,\n", " df: DistributedDFType,\n", " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", - " threshold_method: _Threshold_Method,\n", + " threshold_method: _ThresholdMethod,\n", " freq: Optional[_Freq],\n", " id_col: str,\n", " time_col: str,\n", @@ -1603,20 +1647,21 @@ " clean_ex_first: bool,\n", " step_size: Optional[_PositiveInt],\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", - " validate_api_key: bool,\n", + " hist_exog_list: Optional[list[str]],\n", " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", " model: _Model,\n", " refit: bool,\n", + " validate_api_key: bool,\n", " num_partitions: Optional[int],\n", " ) -> DistributedDFType:\n", " import fugue.api as fa\n", " \n", " schema, partition_config = _distributed_setup(\n", " df=df,\n", - " method='detect_anomalies_realtime',\n", + " method='detect_anomalies_online',\n", " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", @@ -1626,7 +1671,7 @@ " )\n", " result_df = fa.transform(\n", " df,\n", - " using=_detect_anomalies_realtime_wrapper,\n", + " using=_detect_anomalies_online_wrapper,\n", " schema=schema,\n", " params=dict(\n", " client=self,\n", @@ -1643,11 +1688,12 @@ " finetune_steps=finetune_steps,\n", " finetune_loss=finetune_loss,\n", " finetune_depth=finetune_depth,\n", - " validate_api_key=validate_api_key,\n", + " hist_exog_list=hist_exog_list,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", " refit=refit,\n", + " validate_api_key=validate_api_key,\n", " num_partitions=None, \n", " ),\n", " partition=partition_config,\n", @@ -1655,12 +1701,12 @@ " )\n", " return fa.get_native_as_df(result_df)\n", "\n", - " def detect_anomalies_realtime(\n", + " def detect_anomalies_online(\n", " self,\n", " df: AnyDFType,\n", " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", - " threshold_method: _Threshold_Method = 'univariate',\n", + " threshold_method: _ThresholdMethod = 'univariate',\n", " freq: Optional[_Freq] = None, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", @@ -1669,17 +1715,18 @@ " clean_ex_first: bool = True,\n", " step_size: Optional[_PositiveInt] = None,\n", " finetune_steps: _NonNegativeInt = 0,\n", - " finetune_depth: _Finetune_Depth = 1,\n", + " finetune_depth: _FinetuneDepth = 1,\n", " finetune_loss: _Loss = 'default',\n", - " validate_api_key: bool = False,\n", + " hist_exog_list: Optional[list[str]] = None,\n", " date_features: Union[bool, list[str]] = False,\n", " date_features_to_one_hot: Union[bool, list[str]] = False,\n", " model: _Model = 'timegpt-1',\n", " refit: bool = False,\n", + " validate_api_key: bool = False,\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", " \"\"\"\n", - " Real-time anomaly detection in your time series using TimeGPT.\n", + " Online anomaly detection in your time series using TimeGPT.\n", "\n", " Parameters\n", " ----------\n", @@ -1726,8 +1773,8 @@ " and 5 means that the entire model is finetuned.\n", " finetune_loss : str (default='default')\n", " Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`.\n", - " validate_api_key : bool, optional (default=False)\n", - " If True, validates api_key before sending requests.\n", + " hist_exog_list : list of str, optional (default=None)\n", + " Column names of the historical exogenous features.\n", " date_features : bool or list of str, optional (default=False)\n", " Features computed from the dates.\n", " Can be pandas date attributes or functions that will take the dates as input.\n", @@ -1752,7 +1799,7 @@ " DataFrame with anomalies flagged by TimeGPT.\n", " \"\"\"\n", " if not isinstance(df, (pd.DataFrame, pl_DataFrame)):\n", - " return self._distributed_detect_anomalies_realtime(\n", + " return self._distributed_detect_anomalies_online(\n", " df=df,\n", " h=h,\n", " detection_size=detection_size,\n", @@ -1767,18 +1814,19 @@ " finetune_steps=finetune_steps,\n", " finetune_depth=finetune_depth,\n", " finetune_loss=finetune_loss,\n", - " validate_api_key=validate_api_key,\n", + " hist_exog_list=hist_exog_list,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", " refit=refit,\n", + " validate_api_key=validate_api_key,\n", " num_partitions=num_partitions,\n", " )\n", " if threshold_method == \"multivariate\" and num_partitions is not None and num_partitions > 1:\n", " raise ValueError(\n", " \"Cannot use more than 1 partition for multivariate anomaly detection. \"\n", " \"Either set threshold_method to univariate \"\n", - " \"or set num_partitions to 1 or None.\"\n", + " \"or set num_partitions to None.\"\n", " )\n", " self.__dict__.pop('weights_x', None)\n", " model = self._maybe_override_model(model)\n", @@ -1806,26 +1854,15 @@ " target_col=target_col,\n", " )\n", " standard_freq = _standardize_freq(freq, processed)\n", - " if isinstance(df, pd.DataFrame):\n", - " # in pandas<2.2 to_numpy can lead to an object array if\n", - " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", - " # we thus use the dtype's type as the target dtype\n", - " target_dtype = df.dtypes[target_col].type\n", - " targets = df[target_col].to_numpy(dtype=target_dtype)\n", - " else:\n", - " targets = df[target_col].to_numpy()\n", + " targets = _extract_target_array(df, target_col)\n", " times = df[time_col].to_numpy()\n", " if processed.sort_idxs is not None:\n", " targets = targets[processed.sort_idxs]\n", " times = times[processed.sort_idxs]\n", - " if processed.data.shape[1] > 1:\n", - " X = processed.data[:, 1:].T\n", - " logger.info(f'Using the following exogenous features: {x_cols}')\n", - " else:\n", - " X = None\n", + " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list, logger)\n", " sizes = np.diff(processed.indptr)\n", - " if not np.any((sizes - detection_size) > 5 * detection_size):\n", - " logger.info('Detection size is large. Using the entire series to compute the anomaly threshold...')\n", + " if np.all(sizes <= 6 * detection_size):\n", + " logger.warn('Detection size is large. Using the entire series to compute the anomaly threshold...')\n", " logger.info('Calling Online Anomaly Detector Endpoint...')\n", " payload = {\n", " 'series': {\n", @@ -1845,6 +1882,7 @@ " 'finetune_loss': finetune_loss,\n", " 'finetune_depth': finetune_depth,\n", " 'refit': refit,\n", + " 'hist_exog': hist_exog,\n", " }\n", " with httpx.Client(**self._client_kwargs) as client:\n", " if num_partitions is None:\n", @@ -1886,7 +1924,7 @@ " n_windows: _PositiveInt,\n", " step_size: Optional[_PositiveInt],\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", " refit: bool,\n", " clean_ex_first: bool,\n", @@ -1954,7 +1992,7 @@ " n_windows: _PositiveInt = 1,\n", " step_size: Optional[_PositiveInt] = None,\n", " finetune_steps: _NonNegativeInt = 0,\n", - " finetune_depth: _Finetune_Depth = 1,\n", + " finetune_depth: _FinetuneDepth = 1,\n", " finetune_loss: _Loss = 'default',\n", " refit: bool = True,\n", " clean_ex_first: bool = True,\n", @@ -2099,14 +2137,7 @@ " )\n", " standard_freq = _standardize_freq(freq, processed)\n", " model_input_size, model_horizon = self._get_model_params(model, standard_freq)\n", - " if isinstance(df, pd.DataFrame):\n", - " # in pandas<2.2 to_numpy can lead to an object array if\n", - " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", - " # we thus use the dtype's type as the target dtype\n", - " target_dtype = df.dtypes[target_col].type\n", - " targets = df[target_col].to_numpy(dtype=target_dtype)\n", - " else:\n", - " targets = df[target_col].to_numpy()\n", + " targets = _extract_target_array(df, target_col)\n", " times = df[time_col].to_numpy()\n", " if processed.sort_idxs is not None:\n", " targets = targets[processed.sort_idxs]\n", @@ -2125,31 +2156,7 @@ " processed = _tail(processed, new_input_size)\n", " times = _array_tails(times, orig_indptr, np.diff(processed.indptr))\n", " targets = _array_tails(targets, orig_indptr, np.diff(processed.indptr))\n", - " if processed.data.shape[1] > 1:\n", - " X = processed.data[:, 1:].T\n", - " if hist_exog_list is None:\n", - " hist_exog = None\n", - " futr_exog = x_cols\n", - " else:\n", - " missing_hist = set(hist_exog_list) - set(x_cols)\n", - " if missing_hist:\n", - " raise ValueError(\n", - " \"The following exogenous features were declared as historic \"\n", - " f\"but were not found in `df`: {missing_hist}.\"\n", - " )\n", - " futr_exog = [c for c in x_cols if c not in hist_exog_list]\n", - " # match the forecast method order [future, historic]\n", - " fcst_features_order = futr_exog + hist_exog_list\n", - " x_idxs = [x_cols.index(c) for c in fcst_features_order]\n", - " X = X[x_idxs]\n", - " hist_exog = [fcst_features_order.index(c) for c in hist_exog_list]\n", - " if futr_exog:\n", - " logger.info(f'Using future exogenous features: {futr_exog}')\n", - " if hist_exog_list:\n", - " logger.info(f'Using historical exogenous features: {hist_exog_list}')\n", - " else:\n", - " X = None\n", - " hist_exog = None\n", + " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list, logger)\n", "\n", " logger.info('Calling Cross Validation Endpoint...')\n", " payload = {\n", @@ -2332,7 +2339,7 @@ " level: Optional[list[Union[int, float]]],\n", " quantiles: Optional[list[float]],\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", " clean_ex_first: bool,\n", " hist_exog_list: Optional[list[str]],\n", @@ -2404,12 +2411,12 @@ " num_partitions=num_partitions,\n", " )\n", "\n", - "def _detect_anomalies_realtime_wrapper(\n", + "def _detect_anomalies_online_wrapper(\n", " df: pd.DataFrame,\n", " client: NixtlaClient,\n", " h: _PositiveInt,\n", " detection_size: _PositiveInt,\n", - " threshold_method: _Threshold_Method,\n", + " threshold_method: _ThresholdMethod,\n", " freq: Optional[_Freq],\n", " id_col: str,\n", " time_col: str,\n", @@ -2418,16 +2425,16 @@ " clean_ex_first: bool,\n", " step_size: _PositiveInt,\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", - " validate_api_key: bool,\n", + " hist_exog_list: Optional[list[str]],\n", " date_features: Union[bool, list[str]],\n", " date_features_to_one_hot: Union[bool, list[str]],\n", " model: _Model,\n", " refit: bool,\n", " num_partitions: Optional[_PositiveInt],\n", ") -> pd.DataFrame:\n", - " return client.detect_anomalies_realtime(\n", + " return client.detect_anomalies_online(\n", " df=df,\n", " h=h,\n", " detection_size=detection_size,\n", @@ -2442,7 +2449,7 @@ " finetune_steps=finetune_steps,\n", " finetune_depth=finetune_depth,\n", " finetune_loss=finetune_loss,\n", - " validate_api_key=validate_api_key,\n", + " hist_exog_list=hist_exog_list,\n", " date_features=date_features,\n", " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", @@ -2464,7 +2471,7 @@ " n_windows: _PositiveInt,\n", " step_size: Optional[_PositiveInt],\n", " finetune_steps: _NonNegativeInt,\n", - " finetune_depth: _Finetune_Depth,\n", + " finetune_depth: _FinetuneDepth,\n", " finetune_loss: _Loss,\n", " refit: bool,\n", " clean_ex_first: bool,\n", @@ -2516,7 +2523,7 @@ " schema.append('TimeGPT:double')\n", " if method == 'detect_anomalies':\n", " schema.append('anomaly:bool')\n", - " if method == 'detect_anomalies_realtime':\n", + " if method == 'detect_anomalies_online':\n", " schema.append('anomaly:bool')\n", " schema.append('anomaly_score:double')\n", " elif method == 'cross_validation':\n", @@ -3751,7 +3758,7 @@ " 'y': y\n", "})\n", "\n", - "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_df = nixtla_client.detect_anomalies_online(\n", " df, \n", " h=20, \n", " detection_size=detection_size, \n", @@ -3764,7 +3771,7 @@ "assert anomaly_df['anomaly'].sum() == 2 \n", "assert anomaly_df['anomaly'].iloc[0] and anomaly_df['anomaly'].iloc[-1]\n", "\n", - "multi_anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + "multi_anomaly_df = nixtla_client.detect_anomalies_online(\n", " df, \n", " h=20, \n", " detection_size=detection_size, \n", @@ -4121,7 +4128,7 @@ " atol=ATOL,\n", " )\n", "\n", - "def test_realtime_anomalies(\n", + "def test_online_anomalies(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", @@ -4129,7 +4136,7 @@ " level=99,\n", " **reatlime_anomalies_kwargs\n", "):\n", - " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", + " anomalies_df = nixtla_client.detect_anomalies_online(\n", " df=df, \n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -4152,14 +4159,14 @@ " ]\n", " test_eq(cols, exp_cols)\n", "\n", - "def test_anomalies_realtime_same_results_num_partitions(\n", + "def test_anomalies_online_same_results_num_partitions(\n", " df: fugue.AnyDataFrame, \n", " id_col: str = 'unique_id',\n", " time_col: str = 'ds',\n", " target_col: str = 'y',\n", " **reatlime_anomalies_kwargs\n", "):\n", - " anomalies_df = nixtla_client.detect_anomalies_realtime(\n", + " anomalies_df = nixtla_client.detect_anomalies_online(\n", " df=df,\n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -4168,7 +4175,7 @@ " **reatlime_anomalies_kwargs\n", " )\n", " anomalies_df = fa.as_pandas(anomalies_df)\n", - " anomalies_df_2 = nixtla_client.detect_anomalies_realtime(\n", + " anomalies_df_2 = nixtla_client.detect_anomalies_online(\n", " df=df, \n", " id_col=id_col,\n", " time_col=time_col,\n", @@ -4223,9 +4230,9 @@ " test_anomalies(df, level=90, num_partitions=1)\n", " test_anomalies_same_results_num_partitions(df)\n", "\n", - "def test_anomalies_realtime_dataframe(df: fugue.AnyDataFrame):\n", - " test_realtime_anomalies(df, h=20, detection_size=5, threshold_method='univariate', level=99, num_partitions=1)\n", - " test_anomalies_realtime_same_results_num_partitions(df, h=20, detection_size=5, threshold_method='univariate', level=99)\n", + "def test_anomalies_online_dataframe(df: fugue.AnyDataFrame):\n", + " test_online_anomalies(df, h=20, detection_size=5, threshold_method='univariate', level=99, num_partitions=1)\n", + " test_anomalies_online_same_results_num_partitions(df, h=20, detection_size=5, threshold_method='univariate', level=99)\n", "\n", "def test_anomalies_dataframe_diff_cols(\n", " df: fugue.AnyDataFrame,\n", @@ -4315,7 +4322,7 @@ "test_forecast_dataframe(spark_df)\n", "test_forecast_dataframe_diff_cols(spark_diff_cols_df)\n", "test_anomalies_dataframe(spark_df)\n", - "test_anomalies_realtime_dataframe(spark_df)\n", + "test_anomalies_online_dataframe(spark_df)\n", "test_anomalies_dataframe_diff_cols(spark_diff_cols_df)\n", "# test exogenous variables\n", "spark_df_x = spark.createDataFrame(df_x).repartition(2)\n", @@ -4357,7 +4364,7 @@ "test_forecast_dataframe(dask_df)\n", "test_forecast_dataframe_diff_cols(dask_diff_cols_df)\n", "test_anomalies_dataframe(dask_df)\n", - "test_anomalies_realtime_dataframe(dask_df)\n", + "test_anomalies_online_dataframe(dask_df)\n", "test_anomalies_dataframe_diff_cols(dask_diff_cols_df)\n", "\n", "# test exogenous variables\n", @@ -4404,7 +4411,7 @@ "test_forecast_dataframe(ray_df)\n", "test_forecast_dataframe_diff_cols(ray_diff_cols_df)\n", "test_anomalies_dataframe(ray_df)\n", - "test_anomalies_realtime_dataframe(ray_df)\n", + "test_anomalies_online_dataframe(ray_df)\n", "test_anomalies_dataframe_diff_cols(ray_diff_cols_df)\n", "\n", "# test exogenous variables\n", diff --git a/nixtla/_modidx.py b/nixtla/_modidx.py index 8d991525..c4aa00af 100644 --- a/nixtla/_modidx.py +++ b/nixtla/_modidx.py @@ -38,8 +38,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies', 'nixtla/nixtla_client.py'), - 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies_realtime': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies_realtime', - 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient._distributed_detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient._distributed_detect_anomalies_online', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._distributed_forecast': ( 'src/nixtla_client.html#nixtlaclient._distributed_forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient._get_model_params': ( 'src/nixtla_client.html#nixtlaclient._get_model_params', @@ -62,8 +62,8 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.detect_anomalies': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies', 'nixtla/nixtla_client.py'), - 'nixtla.nixtla_client.NixtlaClient.detect_anomalies_realtime': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies_realtime', - 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client.NixtlaClient.detect_anomalies_online': ( 'src/nixtla_client.html#nixtlaclient.detect_anomalies_online', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.forecast': ( 'src/nixtla_client.html#nixtlaclient.forecast', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client.NixtlaClient.plot': ( 'src/nixtla_client.html#nixtlaclient.plot', @@ -76,12 +76,14 @@ 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._cross_validation_wrapper': ( 'src/nixtla_client.html#_cross_validation_wrapper', 'nixtla/nixtla_client.py'), - 'nixtla.nixtla_client._detect_anomalies_realtime_wrapper': ( 'src/nixtla_client.html#_detect_anomalies_realtime_wrapper', - 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client._detect_anomalies_online_wrapper': ( 'src/nixtla_client.html#_detect_anomalies_online_wrapper', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._detect_anomalies_wrapper': ( 'src/nixtla_client.html#_detect_anomalies_wrapper', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._distributed_setup': ( 'src/nixtla_client.html#_distributed_setup', 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client._extract_target_array': ( 'src/nixtla_client.html#_extract_target_array', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._forecast_payload_to_in_sample': ( 'src/nixtla_client.html#_forecast_payload_to_in_sample', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._forecast_wrapper': ( 'src/nixtla_client.html#_forecast_wrapper', @@ -104,6 +106,8 @@ 'nixtla.nixtla_client._prepare_level_and_quantiles': ( 'src/nixtla_client.html#_prepare_level_and_quantiles', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._preprocess': ('src/nixtla_client.html#_preprocess', 'nixtla/nixtla_client.py'), + 'nixtla.nixtla_client._process_exog_features': ( 'src/nixtla_client.html#_process_exog_features', + 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._restrict_input_samples': ( 'src/nixtla_client.html#_restrict_input_samples', 'nixtla/nixtla_client.py'), 'nixtla.nixtla_client._retry_strategy': ( 'src/nixtla_client.html#_retry_strategy', diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index e8a5d2d3..e0c33ff3 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -100,10 +100,10 @@ _NonNegativeInt = Annotated[int, annotated_types.Ge(0)] _Loss = Literal["default", "mae", "mse", "rmse", "mape", "smape"] _Model = Literal["azureai", "timegpt-1", "timegpt-1-long-horizon"] -_Finetune_Depth = Literal[1, 2, 3, 4, 5] +_FinetuneDepth = Literal[1, 2, 3, 4, 5] _Freq = Union[str, int, pd.offsets.BaseOffset] _FreqType = TypeVar("_FreqType", str, int, pd.offsets.BaseOffset) -_Threshold_Method = Literal["univariate", "multivariate"] +_ThresholdMethod = Literal["univariate", "multivariate"] _date_features_by_freq = { # Daily frequencies @@ -576,6 +576,51 @@ def _restrict_input_samples(level, input_size, model_horizon, h) -> int: new_input_size = input_size return new_input_size + +def _extract_target_array(df, target_col) -> np.ndarray: + # in pandas<2.2 to_numpy can lead to an object array if + # the type is a pandas nullable type, e.g. pd.Float64Dtype + # we thus use the dtype's type as the target dtype + if isinstance(df, pd.DataFrame): + target_dtype = df.dtypes[target_col].type + targets = df[target_col].to_numpy(dtype=target_dtype) + else: + targets = df[target_col].to_numpy() + return targets + + +def _process_exog_features( + processed_data: np.ndarray, + x_cols: list[str], + hist_exog_list: list[str] | None = None, + logger: logging.Logger | None = None, +) -> tuple[np.ndarray | None, list[int] | None]: + X = None + hist_exog = None + if processed_data.shape[1] > 1: + X = processed_data[:, 1:].T + if hist_exog_list is None: + futr_exog = x_cols + else: + missing_hist: set[str] = set(hist_exog_list) - set(x_cols) + if missing_hist: + raise ValueError( + "The following exogenous features were declared as historic " + f"but were not found in `df`: {missing_hist}." + ) + futr_exog = [c for c in x_cols if c not in hist_exog_list] + # match the forecast method order [future, historic] + fcst_features_order = futr_exog + hist_exog_list + x_idxs = [x_cols.index(c) for c in fcst_features_order] + X = X[x_idxs] + hist_exog = [fcst_features_order.index(c) for c in hist_exog_list] + if futr_exog and logger: + logger.info(f"Using future exogenous features: {futr_exog}") + if hist_exog_list and logger: + logger.info(f"Using historical exogenous features: {hist_exog_list}") + + return X, hist_exog + # %% ../nbs/src/nixtla_client.ipynb 8 class ApiError(Exception): status_code: Optional[int] @@ -955,7 +1000,7 @@ def _distributed_forecast( level: Optional[list[Union[int, float]]], quantiles: Optional[list[float]], finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, clean_ex_first: bool, hist_exog_list: Optional[list[str]], @@ -1042,7 +1087,7 @@ def forecast( level: Optional[list[Union[int, float]]] = None, quantiles: Optional[list[float]] = None, finetune_steps: _NonNegativeInt = 0, - finetune_depth: _Finetune_Depth = 1, + finetune_depth: _FinetuneDepth = 1, finetune_loss: _Loss = "default", clean_ex_first: bool = True, hist_exog_list: Optional[list[str]] = None, @@ -1524,14 +1569,15 @@ def detect_anomalies( ) out = ufp.assign_columns(out, "anomaly", resp["anomaly"]) out = _maybe_drop_id(df=out, id_col=id_col, drop=drop_id) + self._maybe_assign_weights(weights=resp["weights_x"], df=df, x_cols=x_cols) return out - def _distributed_detect_anomalies_realtime( + def _distributed_detect_anomalies_online( self, df: DistributedDFType, h: _PositiveInt, detection_size: _PositiveInt, - threshold_method: _Threshold_Method, + threshold_method: _ThresholdMethod, freq: Optional[_Freq], id_col: str, time_col: str, @@ -1540,20 +1586,21 @@ def _distributed_detect_anomalies_realtime( clean_ex_first: bool, step_size: Optional[_PositiveInt], finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, - validate_api_key: bool, + hist_exog_list: Optional[list[str]], date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], model: _Model, refit: bool, + validate_api_key: bool, num_partitions: Optional[int], ) -> DistributedDFType: import fugue.api as fa schema, partition_config = _distributed_setup( df=df, - method="detect_anomalies_realtime", + method="detect_anomalies_online", id_col=id_col, time_col=time_col, target_col=target_col, @@ -1563,7 +1610,7 @@ def _distributed_detect_anomalies_realtime( ) result_df = fa.transform( df, - using=_detect_anomalies_realtime_wrapper, + using=_detect_anomalies_online_wrapper, schema=schema, params=dict( client=self, @@ -1580,11 +1627,12 @@ def _distributed_detect_anomalies_realtime( finetune_steps=finetune_steps, finetune_loss=finetune_loss, finetune_depth=finetune_depth, - validate_api_key=validate_api_key, + hist_exog_list=hist_exog_list, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, refit=refit, + validate_api_key=validate_api_key, num_partitions=None, ), partition=partition_config, @@ -1592,12 +1640,12 @@ def _distributed_detect_anomalies_realtime( ) return fa.get_native_as_df(result_df) - def detect_anomalies_realtime( + def detect_anomalies_online( self, df: AnyDFType, h: _PositiveInt, detection_size: _PositiveInt, - threshold_method: _Threshold_Method = "univariate", + threshold_method: _ThresholdMethod = "univariate", freq: Optional[_Freq] = None, id_col: str = "unique_id", time_col: str = "ds", @@ -1606,17 +1654,18 @@ def detect_anomalies_realtime( clean_ex_first: bool = True, step_size: Optional[_PositiveInt] = None, finetune_steps: _NonNegativeInt = 0, - finetune_depth: _Finetune_Depth = 1, + finetune_depth: _FinetuneDepth = 1, finetune_loss: _Loss = "default", - validate_api_key: bool = False, + hist_exog_list: Optional[list[str]] = None, date_features: Union[bool, list[str]] = False, date_features_to_one_hot: Union[bool, list[str]] = False, model: _Model = "timegpt-1", refit: bool = False, + validate_api_key: bool = False, num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: """ - Real-time anomaly detection in your time series using TimeGPT. + Online anomaly detection in your time series using TimeGPT. Parameters ---------- @@ -1663,8 +1712,8 @@ def detect_anomalies_realtime( and 5 means that the entire model is finetuned. finetune_loss : str (default='default') Loss function to use for finetuning. Options are: `default`, `mae`, `mse`, `rmse`, `mape`, and `smape`. - validate_api_key : bool, optional (default=False) - If True, validates api_key before sending requests. + hist_exog_list : list of str, optional (default=None) + Column names of the historical exogenous features. date_features : bool or list of str, optional (default=False) Features computed from the dates. Can be pandas date attributes or functions that will take the dates as input. @@ -1689,7 +1738,7 @@ def detect_anomalies_realtime( DataFrame with anomalies flagged by TimeGPT. """ if not isinstance(df, (pd.DataFrame, pl_DataFrame)): - return self._distributed_detect_anomalies_realtime( + return self._distributed_detect_anomalies_online( df=df, h=h, detection_size=detection_size, @@ -1704,11 +1753,12 @@ def detect_anomalies_realtime( finetune_steps=finetune_steps, finetune_depth=finetune_depth, finetune_loss=finetune_loss, - validate_api_key=validate_api_key, + hist_exog_list=hist_exog_list, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, refit=refit, + validate_api_key=validate_api_key, num_partitions=num_partitions, ) if ( @@ -1719,7 +1769,7 @@ def detect_anomalies_realtime( raise ValueError( "Cannot use more than 1 partition for multivariate anomaly detection. " "Either set threshold_method to univariate " - "or set num_partitions to 1 or None." + "or set num_partitions to None." ) self.__dict__.pop("weights_x", None) model = self._maybe_override_model(model) @@ -1747,26 +1797,17 @@ def detect_anomalies_realtime( target_col=target_col, ) standard_freq = _standardize_freq(freq, processed) - if isinstance(df, pd.DataFrame): - # in pandas<2.2 to_numpy can lead to an object array if - # the type is a pandas nullable type, e.g. pd.Float64Dtype - # we thus use the dtype's type as the target dtype - target_dtype = df.dtypes[target_col].type - targets = df[target_col].to_numpy(dtype=target_dtype) - else: - targets = df[target_col].to_numpy() + targets = _extract_target_array(df, target_col) times = df[time_col].to_numpy() if processed.sort_idxs is not None: targets = targets[processed.sort_idxs] times = times[processed.sort_idxs] - if processed.data.shape[1] > 1: - X = processed.data[:, 1:].T - logger.info(f"Using the following exogenous features: {x_cols}") - else: - X = None + X, hist_exog = _process_exog_features( + processed.data, x_cols, hist_exog_list, logger + ) sizes = np.diff(processed.indptr) - if not np.any((sizes - detection_size) > 5 * detection_size): - logger.info( + if np.all(sizes <= 6 * detection_size): + logger.warn( "Detection size is large. Using the entire series to compute the anomaly threshold..." ) logger.info("Calling Online Anomaly Detector Endpoint...") @@ -1788,6 +1829,7 @@ def detect_anomalies_realtime( "finetune_loss": finetune_loss, "finetune_depth": finetune_depth, "refit": refit, + "hist_exog": hist_exog, } with httpx.Client(**self._client_kwargs) as client: if num_partitions is None: @@ -1833,7 +1875,7 @@ def _distributed_cross_validation( n_windows: _PositiveInt, step_size: Optional[_PositiveInt], finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, refit: bool, clean_ex_first: bool, @@ -1901,7 +1943,7 @@ def cross_validation( n_windows: _PositiveInt = 1, step_size: Optional[_PositiveInt] = None, finetune_steps: _NonNegativeInt = 0, - finetune_depth: _Finetune_Depth = 1, + finetune_depth: _FinetuneDepth = 1, finetune_loss: _Loss = "default", refit: bool = True, clean_ex_first: bool = True, @@ -2046,14 +2088,7 @@ def cross_validation( ) standard_freq = _standardize_freq(freq, processed) model_input_size, model_horizon = self._get_model_params(model, standard_freq) - if isinstance(df, pd.DataFrame): - # in pandas<2.2 to_numpy can lead to an object array if - # the type is a pandas nullable type, e.g. pd.Float64Dtype - # we thus use the dtype's type as the target dtype - target_dtype = df.dtypes[target_col].type - targets = df[target_col].to_numpy(dtype=target_dtype) - else: - targets = df[target_col].to_numpy() + targets = _extract_target_array(df, target_col) times = df[time_col].to_numpy() if processed.sort_idxs is not None: targets = targets[processed.sort_idxs] @@ -2072,31 +2107,9 @@ def cross_validation( processed = _tail(processed, new_input_size) times = _array_tails(times, orig_indptr, np.diff(processed.indptr)) targets = _array_tails(targets, orig_indptr, np.diff(processed.indptr)) - if processed.data.shape[1] > 1: - X = processed.data[:, 1:].T - if hist_exog_list is None: - hist_exog = None - futr_exog = x_cols - else: - missing_hist = set(hist_exog_list) - set(x_cols) - if missing_hist: - raise ValueError( - "The following exogenous features were declared as historic " - f"but were not found in `df`: {missing_hist}." - ) - futr_exog = [c for c in x_cols if c not in hist_exog_list] - # match the forecast method order [future, historic] - fcst_features_order = futr_exog + hist_exog_list - x_idxs = [x_cols.index(c) for c in fcst_features_order] - X = X[x_idxs] - hist_exog = [fcst_features_order.index(c) for c in hist_exog_list] - if futr_exog: - logger.info(f"Using future exogenous features: {futr_exog}") - if hist_exog_list: - logger.info(f"Using historical exogenous features: {hist_exog_list}") - else: - X = None - hist_exog = None + X, hist_exog = _process_exog_features( + processed.data, x_cols, hist_exog_list, logger + ) logger.info("Calling Cross Validation Endpoint...") payload = { @@ -2276,7 +2289,7 @@ def _forecast_wrapper( level: Optional[list[Union[int, float]]], quantiles: Optional[list[float]], finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, clean_ex_first: bool, hist_exog_list: Optional[list[str]], @@ -2350,12 +2363,12 @@ def _detect_anomalies_wrapper( ) -def _detect_anomalies_realtime_wrapper( +def _detect_anomalies_online_wrapper( df: pd.DataFrame, client: NixtlaClient, h: _PositiveInt, detection_size: _PositiveInt, - threshold_method: _Threshold_Method, + threshold_method: _ThresholdMethod, freq: Optional[_Freq], id_col: str, time_col: str, @@ -2364,16 +2377,16 @@ def _detect_anomalies_realtime_wrapper( clean_ex_first: bool, step_size: _PositiveInt, finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, - validate_api_key: bool, + hist_exog_list: Optional[list[str]], date_features: Union[bool, list[str]], date_features_to_one_hot: Union[bool, list[str]], model: _Model, refit: bool, num_partitions: Optional[_PositiveInt], ) -> pd.DataFrame: - return client.detect_anomalies_realtime( + return client.detect_anomalies_online( df=df, h=h, detection_size=detection_size, @@ -2388,7 +2401,7 @@ def _detect_anomalies_realtime_wrapper( finetune_steps=finetune_steps, finetune_depth=finetune_depth, finetune_loss=finetune_loss, - validate_api_key=validate_api_key, + hist_exog_list=hist_exog_list, date_features=date_features, date_features_to_one_hot=date_features_to_one_hot, model=model, @@ -2411,7 +2424,7 @@ def _cross_validation_wrapper( n_windows: _PositiveInt, step_size: Optional[_PositiveInt], finetune_steps: _NonNegativeInt, - finetune_depth: _Finetune_Depth, + finetune_depth: _FinetuneDepth, finetune_loss: _Loss, refit: bool, clean_ex_first: bool, @@ -2464,7 +2477,7 @@ def _get_schema( schema.append("TimeGPT:double") if method == "detect_anomalies": schema.append("anomaly:bool") - if method == "detect_anomalies_realtime": + if method == "detect_anomalies_online": schema.append("anomaly:bool") schema.append("anomaly_score:double") elif method == "cross_validation": From f997f42f12b42b77ff5fc4bfa1f67257743cfca3 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 13 Dec 2024 15:01:55 -0500 Subject: [PATCH 26/38] Fix type hinting --- nbs/src/nixtla_client.ipynb | 4 ++-- nixtla/nixtla_client.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 1ac2075c..b516ee10 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -656,8 +656,8 @@ "def _process_exog_features(\n", " processed_data: np.ndarray,\n", " x_cols: list[str],\n", - " hist_exog_list: list[str] | None = None,\n", - " logger: logging.Logger | None = None\n", + " hist_exog_list: Optional[list[str]] = None,\n", + " logger: Optional[logging.Logger] = None\n", ") -> tuple[np.ndarray | None, list[int] | None]:\n", " X = None\n", " hist_exog = None\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index e0c33ff3..c1ccc2e6 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -592,8 +592,8 @@ def _extract_target_array(df, target_col) -> np.ndarray: def _process_exog_features( processed_data: np.ndarray, x_cols: list[str], - hist_exog_list: list[str] | None = None, - logger: logging.Logger | None = None, + hist_exog_list: Optional[list[str]] = None, + logger: Optional[logging.Logger] = None, ) -> tuple[np.ndarray | None, list[int] | None]: X = None hist_exog = None From 0d91509432cbcaac82f3dd436710215c3c2f2428 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 13 Dec 2024 15:05:44 -0500 Subject: [PATCH 27/38] Another type hinting fix --- nbs/src/nixtla_client.ipynb | 2 +- nixtla/nixtla_client.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index b516ee10..8b76a26f 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -658,7 +658,7 @@ " x_cols: list[str],\n", " hist_exog_list: Optional[list[str]] = None,\n", " logger: Optional[logging.Logger] = None\n", - ") -> tuple[np.ndarray | None, list[int] | None]:\n", + ") -> tuple[Optional[np.ndarray], Optional[list[int]]]:\n", " X = None\n", " hist_exog = None\n", " if processed_data.shape[1] > 1:\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index c1ccc2e6..29b59971 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -594,7 +594,7 @@ def _process_exog_features( x_cols: list[str], hist_exog_list: Optional[list[str]] = None, logger: Optional[logging.Logger] = None, -) -> tuple[np.ndarray | None, list[int] | None]: +) -> tuple[Optional[np.ndarray], Optional[list[int]]]: X = None hist_exog = None if processed_data.shape[1] > 1: From 5247808b873829505e84a5d3880b9b205f981e83 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 13 Dec 2024 15:08:22 -0500 Subject: [PATCH 28/38] Adjust _process_exog_features function --- nbs/src/nixtla_client.ipynb | 2 +- nixtla/nixtla_client.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 8b76a26f..b2f4b304 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -658,7 +658,7 @@ " x_cols: list[str],\n", " hist_exog_list: Optional[list[str]] = None,\n", " logger: Optional[logging.Logger] = None\n", - ") -> tuple[Optional[np.ndarray], Optional[list[int]]]:\n", + "):\n", " X = None\n", " hist_exog = None\n", " if processed_data.shape[1] > 1:\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 29b59971..c5aeb526 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -594,7 +594,7 @@ def _process_exog_features( x_cols: list[str], hist_exog_list: Optional[list[str]] = None, logger: Optional[logging.Logger] = None, -) -> tuple[Optional[np.ndarray], Optional[list[int]]]: +): X = None hist_exog = None if processed_data.shape[1] > 1: From 722d3e324eb26ca1ed292ba5924dd47205705f9a Mon Sep 17 00:00:00 2001 From: yibeihu Date: Sat, 14 Dec 2024 04:57:50 +0800 Subject: [PATCH 29/38] change endpoint name --- .../00_online_anomaly_detection.ipynb | 31 +++++++++++++++++ .../01_quickstart.ipynb | 16 ++++----- .../02_adjusting_detection_process.ipynb} | 34 +++++++++++++------ ...te_vs_multivariate_anomaly_detection.ipynb | 12 +++---- .../00_realtime_anomaly_detection.ipynb | 31 ----------------- nbs/mint.json | 8 ++--- 6 files changed, 72 insertions(+), 60 deletions(-) create mode 100644 nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb rename nbs/docs/capabilities/{realtime-anomaly-detection => online-anomaly-detection}/01_quickstart.ipynb (98%) rename nbs/docs/capabilities/{realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb => online-anomaly-detection/02_adjusting_detection_process.ipynb} (99%) rename nbs/docs/capabilities/{realtime-anomaly-detection => online-anomaly-detection}/03_univariate_vs_multivariate_anomaly_detection.ipynb (99%) delete mode 100644 nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb diff --git a/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb b/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb new file mode 100644 index 00000000..ee2f227a --- /dev/null +++ b/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb @@ -0,0 +1,31 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Online Anomaly Detection" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Online anomaly detection dynamically identifies anomalies as data streams in, allowing users to specify the number of steps to monitor. This method is well-suited for immediate applications, such as fraud detection, live sensor monitoring, or tracking real-time demand changes. By focusing on recent data and continuously generating forecasts, it enables timely responses to anomalies in critical scenarios.\n", + "\n", + "This section provides various recipes for performing real-time anomaly detection using TimeGPT, offering users the ability to detect outliers and unusual patterns as they emerge, ensuring prompt intervention in time-sensitive situations.\n", + "\n", + "This section covers:\n", + "\n", + "* [Online anomaly detection](https://docs.nixtla.io/docs/capabilities-online-anomaly-detection-quickstart)\n", + "\n", + "* [How to adjust the detection process](https://docs.nixtla.io/docs/capabilities-online-anomaly-detection-adjusting_detection_process.ipynb)\n", + "\n", + "* [Univariate vs. multiseries anomaly detection](https://docs.nixtla.io/docs/capabilities-online-anomaly-detection-univariate_vs_multivariate_anomaly_detection)\n" + ] + } + ], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb similarity index 98% rename from nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb rename to nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb index 26d1508d..dd9b9daf 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb @@ -46,8 +46,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to Realtime Anomaly Detectiontion\n", - "In this notebook, we introduce the `detect_anomaly_realtime` method. You'll learn how to quickly start using this new endpoint and understand its key differences from the historical forecast endpoint. The new features include:\n", + "# Introduction the Online Anomaly Detectiontion\n", + "In this notebook, we introduce the `detect_anomaly_online` method. You'll learn how to quickly start using this new endpoint and understand its key differences from the historical forecast endpoint. The new features include:\n", "* Have more flexibility and control over the anomaly detection process\n", "* Conduct univariate/ multivariate anomaly detection\n", "* Detect Anomaly on stream data" @@ -75,7 +75,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/realtime-anomaly-detection/01_quickstart')" + " colab_badge('docs/capabilities/online-anomaly-detection/01_quickstart')" ] }, { @@ -176,8 +176,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 2. Detect anomalies in Realtime\n", - "The `detect_anomaly_realtime` method detect anomalies in a time series leveraging TimeGPT's forecast power. It leverages the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score(its absolute value indicates abnoamlity of the step)\n", + "## 2. Detect anomalies in real time\n", + "The `detect_anomaly_online` method detect anomalies in a time series leveraging TimeGPT's forecast power. It leverages the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score(its absolute value indicates abnoamlity of the step)\n", "To make a detection, set the following parameters:\n", "\n", "- `df`: A pandas DataFrame containing the time series data.\n", @@ -316,11 +316,11 @@ } ], "source": [ - "anomaly_online = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_online = nixtla_client.detect_anomalies_online(\n", " df,\n", " time_col='ts', \n", " target_col='y', \n", - " freq='min', # Specify the frequency of the data\n", + " freq='min', # Specify the frequency of the data\n", " h=10, # Specify the forecast horizon\n", " level=99, # Set the confidence level for anomaly detection\n", " detection_size=100) # How many steps you want for analyzing anomalies\n", @@ -377,7 +377,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For an in-depth analysis of the `detect_anomaly_realtime` method, refer to the tutorial (coming soon)." + "For an in-depth analysis of the `detect_anomaly_online` method, refer to the tutorial (coming soon)." ] } ], diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb b/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb similarity index 99% rename from nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb rename to nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb index 0a4a7ada..36df7977 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/02_adjusting_detection_accuracy_process.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb @@ -88,7 +88,7 @@ { "data": { "text/markdown": [ - "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy.ipynb)" + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb)" ], "text/plain": [ "" @@ -102,7 +102,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/realtime-anomaly-detection/02_improve_detection_accuracy')" + " colab_badge('docs/capabilities/online-anomaly-detection/02_adjusting_detection_process')" ] }, { @@ -251,16 +251,22 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n", + "INFO:nixtla.nixtla_client:Validating inputs...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] } ], "source": [ - "# Base case for anomaly detection using detect_anomaly_realtime\n", - "anomaly_df = nixtla_client.detect_anomalies_realtime(\n", + "# Base case for anomaly detection using detect_anomaly_online\n", + "anomaly_df = nixtla_client.detect_anomalies_online(\n", " df,\n", " freq='D',\n", " h=14,\n", @@ -319,13 +325,13 @@ "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] } ], "source": [ - "anomaly_online_ft = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_online_ft = nixtla_client.detect_anomalies_online(\n", " df,\n", " freq='D',\n", " h=14,\n", @@ -377,14 +383,20 @@ "output_type": "stream", "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] } ], "source": [ - "anomaly_df_horizon = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_df_horizon = nixtla_client.detect_anomalies_online(\n", " df,\n", " time_col='ds',\n", " target_col='y',\n", diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb similarity index 99% rename from nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb rename to nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index eddfcd71..8c2d93d5 100644 --- a/nbs/docs/capabilities/realtime-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -94,7 +94,7 @@ { "data": { "text/markdown": [ - "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/anomaly-detection/07_univariate_vs_multivariate_anomaly_detection.ipynb)" + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb)" ], "text/plain": [ "" @@ -108,7 +108,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/anomaly-detection/07_univariate_vs_multivariate_anomaly_detection')" + " colab_badge('docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection')" ] }, { @@ -213,13 +213,13 @@ "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] } ], "source": [ - "anomaly_online = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_online = nixtla_client.detect_anomalies_online(\n", " df[['ts', 'y', 'unique_id']],\n", " time_col='ts',\n", " target_col='y',\n", @@ -273,13 +273,13 @@ "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", - "INFO:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", + "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] } ], "source": [ - "anomaly_online_multi = nixtla_client.detect_anomalies_realtime(\n", + "anomaly_online_multi = nixtla_client.detect_anomalies_online(\n", " df[['ts', 'y', 'unique_id']],\n", " time_col='ts',\n", " target_col='y',\n", diff --git a/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb b/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb deleted file mode 100644 index 56cdfce3..00000000 --- a/nbs/docs/capabilities/realtime-anomaly-detection/00_realtime_anomaly_detection.ipynb +++ /dev/null @@ -1,31 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Realtime Anomaly Detection" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Real-time anomaly detection dynamically identifies anomalies as data streams in, allowing users to specify the number of steps to monitor. This method is well-suited for immediate applications, such as fraud detection, live sensor monitoring, or tracking real-time demand changes. By focusing on recent data and continuously generating forecasts, it enables timely responses to anomalies in critical scenarios.\n", - "\n", - "This section provides various recipes for performing real-time anomaly detection using TimeGPT, offering users the ability to detect outliers and unusual patterns as they emerge, ensuring prompt intervention in time-sensitive situations.\n", - "\n", - "This section covers:\n", - "\n", - "* [Realtime anomaly detection](https://docs.nixtla.io/docs/capabilities-realtime-anomaly-detection-quickstart)\n", - "\n", - "* [How to improve the detection process](https://docs.nixtla.io/docs/capabilities-anomaly-detection-improve_detection_accuracy)\n", - "\n", - "* [Univariate vs. multiseries anomaly detection](https://docs.nixtla.io/docs/capabilities-univariate_vs_multivariate_anomaly_detection)\n" - ] - } - ], - "metadata": {}, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/nbs/mint.json b/nbs/mint.json index b963d50c..57dc5886 100644 --- a/nbs/mint.json +++ b/nbs/mint.json @@ -64,11 +64,11 @@ ] }, { - "group": "Realtime Anomaly Detection", + "group": "Online Anomaly Detection", "pages": [ - "docs/capabilities/realtime-anomaly-detection/quickstart.html", - "docs/capabilities/realtime-anomaly-detection/adjusting_detection_accuracy_process.html", - "docs/capabilities/realtime-anomaly-detection/univariate_vs_multivariate_anomaly_detection.html" + "docs/capabilities/online-anomaly-detection/quickstart.html", + "docs/capabilities/online-anomaly-detection/adjusting_detection_process.html", + "docs/capabilities/online-anomaly-detection/univariate_vs_multivariate_anomaly_detection.html" ] } ] From 1f055cf507873b4193799dafe6c9627528f6a696 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 16 Dec 2024 14:14:44 -0500 Subject: [PATCH 30/38] Remove validate_api_key and adjust tutorials --- .../01_quickstart.ipynb | 49 ++++---- .../02_adjusting_detection_process.ipynb | 113 +++++++++--------- ...te_vs_multivariate_anomaly_detection.ipynb | 85 ++++++------- nbs/src/nixtla_client.ipynb | 6 +- nixtla/nixtla_client.py | 6 +- 5 files changed, 131 insertions(+), 128 deletions(-) diff --git a/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb index dd9b9daf..a0089e00 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb @@ -46,11 +46,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction the Online Anomaly Detectiontion\n", - "In this notebook, we introduce the `detect_anomaly_online` method. You'll learn how to quickly start using this new endpoint and understand its key differences from the historical forecast endpoint. The new features include:\n", - "* Have more flexibility and control over the anomaly detection process\n", - "* Conduct univariate/ multivariate anomaly detection\n", - "* Detect Anomaly on stream data" + "# Introduction to Online Anomaly Detection\n", + "In this notebook, we introduce the `detect_anomalies_online` method. You will learn how to quickly start using this new endpoint and understand its key differences from the historical anomaly detection endpoint. New features include:\n", + "* More flexibility and control over the anomaly detection process\n", + "* Perform univariate and multivariate anomaly detection\n", + "* Detect anomalies on stream data" ] }, { @@ -61,7 +61,7 @@ { "data": { "text/markdown": [ - "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/realtime-anomaly-detection/01_quickstart.ipynb)" + "[![](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Nixtla/nixtla/blob/main/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb)" ], "text/plain": [ "" @@ -85,7 +85,8 @@ "outputs": [], "source": [ "import pandas as pd\n", - "from nixtla import NixtlaClient" + "from nixtla import NixtlaClient\n", + "import matplotlib.pyplot as plt" ] }, { @@ -127,7 +128,7 @@ "metadata": {}, "source": [ "## 1. Dataset\n", - "In this notebook, we use an minute level server machine monitoring time series for demonstration. Here, we use this example simulates a real-world streaming data scenerio, where the goal is to detect anomalies in real time, such as when the server experiences a failure or downtime." + "In this notebook, we use a minute-level time series dataset that monitors server usage. This is a good example of a streaming data scenario, as the task is to detect server failures or downtime." ] }, { @@ -143,7 +144,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We observe that the time series remains stable during the initial period; however, a spike occurs in the last 20 steps, indicating anomalous behavior. Our goal is to capture this abnormal jump as soon as it appears. Let's see how the real-time anomaly detection method performs in this scenario!" + "We observe that the time series remains stable during the initial period; however, a spike occurs in the last 20 steps, indicating an anomalous behavior. Our goal is to capture this abnormal jump as soon as it appears. Let's see how the real-time anomaly detection capability of TimeGPT performs in this scenario!" ] }, { @@ -153,7 +154,7 @@ "outputs": [ { "data": { - "image/png": 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06YIPPvhAeiwjIwMymQybN2/G4MGDodFosHHjRqxbtw5eXl5Wx/n666/Rq1cvaDQaREZG4pVXXkF5eTkAQBAEvPzyywgNDYVarUZwcDCeeuqper7rRERERM7HcnK14pJylJaVN2FrqLk6mJIFAOh9a+WSzbd28oWnuwoFRXocT7tS6/MFQcCT83dg8nPfwWg0ObStLVGrDLwFQUBRkb5JbrWNj28I69evh6+vLw4cOICZM2di2rRpuO+++zBgwAAcPnwYw4YNw0MPPYTi4mIAQG5uLoYOHYqePXvi4MGD2L59O7KzszFu3LgaXyMwMBD79u3DuXPnatxn48aNmD9/Pv7zn/8gNTUVr7/+OubNm4f169db7Tdnzhw8/fTTSE1NtZpwT/TLL79g4sSJePrpp3HixAl8+OGHWLdunRTkf/nll3jnnXfw4Ycf4tSpU9i6dSuioqLq89YREREROR29wYisq0VW25j1pvo4/EdF4B1VGXgrFHL079kWALD30F+1Pn/LjpP4dMsf+HJ7Gg4cy6x1X6qqVZaaFxcb4O5+8+OR66OwcC7c3FQOO350dDReeuklAOal3d544w34+vri0UcfBQDMnz8fK1euxLFjx9C/f3+8//776NmzJ15//XXpGGvXrkVISAhOnjyJTp06VXmNBQsWYOzYsQgPD0enTp0QGxuLESNG4B//+Afkcrm0z9KlSzF27FgA5tntxcB50qRJ0rFmzZol7VOdV155BXPmzJGeExkZiYULF+L555/HggULcP78eQQGBiIuLg4uLi4IDQ1Fv379bvJdJCIiInIOf10uhCAAWo0SGrUSOXmlyMkrRYA7h+aR7YpKDDhx5hoAoG9UkNVjA3q1xY+/pGPvoYuY/lCvap+vNxjx8ru/Svd37ElHbEXATrZplRnvlqx79+7SvxUKBdq0aWOVARaXaLt8+TIA4OjRo9i1a5c0Ztzd3R1dunQBAJw5c6ba1wgKCkJSUhKOHz+Op59+GuXl5Zg0aRKGDx8Ok8mEoqIinDlzBlOnTrU67muvvVblmH369Kn1fI4ePYpXX33V6jiPPvooMjMzUVxcjPvuuw8lJSWIjIzEo48+ii1btkhl6ERERETN3cVs8/judoEeaONtDraZ8SZ7HT15GSaTgGB/dwT5W88TNbCPeZz33kMXa6zOXfv5MaRfzIPMPDQcO/acdWh7W6JWmfF2dXVBYeHcJnttR3JxsT6+TCaz2iar+LSYTOZxGYWFhRg1ahQWL15c5VhBQUFVtlm69dZbceutt+LJJ5/EE088gUGDBmH37t3o2rUrAPPM5zExMVbPUSgUVvfd3NxqfY3CwkK88sor1WbFNRoNQkJCkJaWhp9++gk7d+7Ek08+ibfeegu7d++u8l4QERERNTfiGt4hQZ4oKNID4MzmZL/DJ8wTq1mWmYt6dQuARq3A9dxSpJ29jvahXkjcfx7eOg163xqIgiI93vhwHwBg3syBeO3935By8iouZhWgXaBHo55Hc9YqA2+ZTObQcu/mpFevXvjyyy8RHh4OpbL+3UEMtouKihAQEIDg4GCcPXsWDzzwwE23Ly0tDR06dKhxH61Wi1GjRmHUqFGYPn06unTpguPHj6NXr+pLZYiIiIiaC3EN75BgD2ReNo/1zskva8omUTN0uGL9bsuJ1UQqFwX6RQdjz4ELmL/sFxz/84o0k37XDm3QLsgT13JK0DHcG89M6Ysde9Kx/8gl/LgnHQ+P617leFS9Vhl4U6Xp06dj9erVmDBhAp5//nn4+Pjg9OnT2LRpEz7++OMqGWoAmDZtGoKDgzF06FC0a9cOmZmZeO211+Dn54fY2FgA5rHZTz31FHQ6HYYPH46ysjIcPHgQOTk5mD17ts3tmz9/Pv72t78hNDRUGkN+9OhRpKSk4LXXXsO6detgNBoRExMDV1dXfPbZZ9BqtQgLC2uw94iIiIioqVzMLgQAhAZ5oqzMCAC4nlfSlE2iZuhgRca7TzUZbwAY2Lst9hy4gB8SzSXkvj5aFBbpceL0NZw4bR4b/vKs26BUyhF/ewT2H7mE7b+cZeBtB47xbuWCg4Oxd+9eGI1GDBs2DFFRUZg1axa8vLykidJuFBcXh3379uG+++5Dp06dcO+990Kj0SAhIQFt2rQBADzyyCP4+OOP8cknnyAqKgqDBw/GunXrEBERYVf74uPjsW3bNvz444/o27cv+vfvj3feeUcKrL28vLB69WoMHDgQ3bt3x08//YRvv/1WagcRERFRcyZmvNsFecLHSwOApeZkn+zsQlzIKoBMBvToGlDtPmPjO0OrUaJjuDeWv3wXUn98FKd+fhxLXxyKftFBeOiebhg11FyBOvz2SADA7v3nubSdHWSCo9e3agT5+fnQ6XTIy8uDp6en1WOlpaVIT09HREQENBpNE7WQyH7su0RERK2bscSITp2W4+zFPPyw9j78evAi/vNBEiaPvRXvzL4DHr10UGirVicSWfr6yz8x5h+b0TnCBwe/mVzjfiaTAJmsck6omgiCgFvuWo2/sgvx1cp7cNdt9iXWnInBYMS9T25BWFsdlr98F0x6E0wlRps/W7XFoTdixpuIiIiIyAmZTII0q3lIsCe8dWLGm2O8yXa/HzSvz92nmvHdluRyWZ1BN2AOzIcNMgfbO/ak33wDm9CR1MvYte88NmxJgcnk2Hw0A28iIiIiIid0+XIR9AYT5HIZgv3dpcCbY7zJHmknzWO0u3X0bbBjxleUm+/Yk17jEmTNQcrJKwDMF7muO3gIBwNvIiIiIiIndO58HgAgyM8NLi4K+HiZ1/HO5TreZIfSUvM4bDdtwy21OyQmFGqVAhl/5eH0udwGO25jS0m7Iv37ak6xQ1+LgTcRERERkRM6f8EceIcEmseOstSc6qNMb54NX61quPkA3Fxd0L2LPwDg+J+XG+y4jS3l5FXp31evO7aShIE3EREREZETkgLvIA8AFoE3M95kBzHjrVY17ErSt3QwryJ04vTVOvZ0ToIg4I9TlW2/xow3EREREVHrc76i1LxdYEXg7WkOvItKDFIWk6gu4vrvDZnxBoCuHcxjxlPPXGvQ4zaWC5kFyCuorB65msOMNxERERFRqyOO8Q4JMpea6zzUkMvNs04z60220peJGe+GDrzFjHfzDLzFidVELDUnIiIiImqFLlzIBwCEVGS85XIZvDzVABh4k+3E6giVSwMH3hWzpJ89n4uSUkODHrsxWE6sBnByNSIiIiKiVimvIrgWx3Zb/jungIE32abMQRlv/zau8PHSwGQScDI9p0GP3RjEidWC/d0BsNTcoUx6E4wlxka7mfSmpj7lRhceHo5ly5Y1dTMaXEZGBmQyGY4cOXJTxxkyZAhmzZrVIG0iIiKilkUcm2uZqayc2ZyBN9lG6kcNHHjLZDJpnHdznGDteEWp+eD+oQAcX2resFPbNSMmvQlFKQUwljTexBQKrQJut3pArrLvekdSUhJuu+02DB8+HN99952DWtcyZWRkICIiQrrv4+OD3r17Y/HixejZs2e9jxsSEoLMzEz4+vo2RDOJiIiIqhBLhDXqyp/sPjrzWt45+VxSjGwjLSfWwKXmgHmc968HL+LEqeYVeBeXGHDmnDlLP7hfCP73zQmWmjuKYBRgLDFCppRDrlU4/CZTymEsMUIwCna3dc2aNZg5cyb27NmDS5cuOeDdaPl++uknZGZmYseOHSgsLMTdd9+N3Nzceh1Lr9dDoVAgMDAQSmWrvXZFREREDiaWCFtmvH24pBjZyVGl5gBwi5Txbl4TrJ04fRWCAPj6aNGtYqw6S80dTOYig1wld/hN5iKrV/sKCwuxefNmTJs2DSNHjsS6deusHk9MTIRMJkNCQgL69OkDV1dXDBgwAGlpaVb7rVy5Eu3bt4dKpULnzp3x6aefWr8PMhk+/PBD/O1vf4OrqytuueUWJCUl4fTp0xgyZAjc3NwwYMAAnDlzRnrOmTNnMHr0aAQEBMDd3R19+/bFTz/9VOv5nD9/HqNHj4a7uzs8PT0xbtw4ZGdnS49PnjwZY8aMsXrOrFmzMGTIEOn+//3f/yEqKgparRZt2rRBXFwcioqKan3dNm3aIDAwEH369MGSJUuQnZ2N/fv3AwB+/fVXDBo0CFqtFiEhIXjqqaesjhceHo6FCxdi4sSJ8PT0xGOPPVZtqfnu3bvRr18/qNVqBAUFYc6cOSgvL5ceLyoqwsSJE+Hu7o6goCAsXbq01jYTERFR61a5/nI1peYc4002qm7IQkMR1/L+s5ktKSaO747q5AdfH1cAwLWcEgiC/UlSW9Ur8F6xYgXCw8Oh0WgQExODAwcO1LjvkCFDIJPJqtxGjhwp7TN58uQqjw8fPrw+TWtxPv/8c3Tp0gWdO3fGgw8+iLVr11bbIf79739j6dKlOHjwIJRKJR5++GHpsS1btuDpp5/Gv/71L6SkpODxxx/HlClTsGvXLqtjiMHlkSNH0KVLF/zzn//E448/jrlz5+LgwYMQBAEzZsyQ9i8sLMSIESOQkJCA5ORkDB8+HKNGjcL58+erPReTyYTRo0fj+vXr2L17N3bu3ImzZ89i/PjxNr8fmZmZmDBhAh5++GGkpqYiMTERY8eOtetDotWaS7T0ej3OnDmD4cOH495778WxY8ewefNm/Prrr1bnCQBLlixBdHQ0kpOTMW/evCrH/OuvvzBixAj07dsXR48excqVK7FmzRq89tpr0j7PPfccdu/eja+//ho//vgjEhMTcfjwYZvbTURERK2H0WiCsaJSUl3NGO/rHONNNhAEAXq9Y9bxBioD7/OX8pFf2HyGP4gzmnfr5Adfb3NsYCg3Ic+B52B3nezmzZsxe/ZsrFq1CjExMVi2bBni4+ORlpYGf3//Kvt/9dVX0Ov10v1r164hOjoa9913n9V+w4cPxyeffCLdV6vV9jatRVqzZg0efPBBAOb3KC8vD7t377bKAAPAf/7zHwwePBgAMGfOHIwcORKlpaXQaDRYsmQJJk+ejCeffBIAMHv2bOzbtw9LlizBHXfcIR1jypQpGDduHADghRdeQGxsLObNm4f4+HgAwNNPP40pU6ZI+0dHRyM6Olq6v3DhQmzZsgXffPNNlcAVABISEnD8+HGkp6cjJCQEALBhwwZ069YNv//+O/r27Vvn+5GZmYny8nKMHTsWYWFhAICoqKg6nyfKzc3FwoUL4e7ujn79+uHf//43HnjgAWmCs44dO+K9997D4MGDsXLlSmg05j9uQ4cOxb/+9S/pOBkZGVbH/eCDDxASEoL3338fMpkMXbp0waVLl/DCCy9g/vz5KC4uxpo1a/DZZ5/hzjvvBACsX78e7dq1s7ntRERE1HqIWUoAUKurlprncow32UAMuoGGn1wNMM85EOTvhszLRfjzzDX0iw5u8NdwBHEN76jOftColXB3dUFhsQHXckrg6efikNe0O+P99ttv49FHH8WUKVPQtWtXrFq1Cq6urli7dm21+/v4+CAwMFC67dy5E66urlUCb7VabbWft7d3/c6oBUlLS8OBAwcwYcIEAIBSqcT48eOxZs2aKvt2795d+ndQUBAA4PLlywCA1NRUDBw40Gr/gQMHIjU1tcZjBAQEALAOagMCAlBaWor8fPOakoWFhXj22Wdxyy23wMvLC+7u7khNTa0x452amoqQkBAp6AaArl27wsvLq0pbahIdHY0777wTUVFRuO+++7B69Wrk5NS9fMGAAQPg7u4Ob29vHD16FJs3b0ZAQACOHj2KdevWwd3dXbrFx8fDZDIhPT1den6fPn1qPX5qaipiY2Mhk1UOKRg4cCAKCwtx8eJFnDlzBnq9HjExMdLjPj4+6Ny5s03nTURERK2LOC4XqD7jzVJzsoXVBRwXx8xN1LWZjfMWBAF/VJSa39rJ3HZfb3O5uSPHedsVeOv1ehw6dAhxcXGVB5DLERcXh6SkJJuOsWbNGtx///1wc3Oz2p6YmAh/f3907twZ06ZNw7VrzeN/nCOtWbMG5eXlCA4OhlKphFKpxMqVK/Hll18iLy/Pal8Xl8orM2LwZzLZt3xZdceo7bjPPvsstmzZgtdffx2//PILjhw5gqioKKsKB3vJ5fIqZeMGg0H6t0KhwM6dO/HDDz+ga9euWL58OTp37mwVJFdn8+bNOHr0KHJycnDmzBmMGDECgPniweOPP44jR45It6NHj+LUqVNo37699Pwb+ysRERGRI4kBk0wGKJWVP9m9Obka2cHqAo4DMt5A5QRrqc1kSbGLWQXILSiDUilH50gfAOZJ1gAnCryvXr0Ko9EoZUNFAQEByMrKqvP5Bw4cQEpKCh555BGr7cOHD8eGDRuQkJCAxYsXY/fu3bj77rthNFa/1FdZWRny8/Otbi1NeXk5NmzYgKVLl1YJCoODg/G///3P5mPdcsst2Lt3r9W2vXv3omvXrjfVxr1792Ly5Mm45557EBUVhcDAwCol2De248KFC7hw4YK07cSJE8jNzZXa4ufnh8zMTKvn3bhWtkwmw8CBA/HKK68gOTkZKpUKW7ZsqbWtISEhaN++Pby8vKy29+rVCydOnECHDh2q3FQqVd1vgsW5JSUlWV002Lt3Lzw8PNCuXTu0b98eLi4u0oRuAJCTk4OTJ0/a/BpERETUekgTq7korCrqOMab7CFewFEq5JDL6zfZc13Ecd4nTjWPxOmPv5gTdt06+kKtMlcBtPF2fODdqGshrVmzBlFRUejXr5/V9vvvv1/6d1RUFLp374727dsjMTFRGg9radGiRXjllVcapE2CQYAJ9mWG6/s69ti2bRtycnIwdepU6HQ6q8fuvfderFmzBk888YRNx3ruuecwbtw49OzZE3Fxcfj222/x1Vdf1TkDeV06duyIr776CqNGjYJMJsO8efNqzbLHxcUhKioKDzzwAJYtW4by8nI8+eSTGDx4sFTKPXToULz11lvYsGEDYmNj8dlnnyElJUVac3v//v1ISEjAsGHD4O/vj/379+PKlSu45ZZb6nUOL7zwAvr3748ZM2bgkUcegZubG06cOIGdO3fi/ffft/k4Tz75JJYtW4aZM2dixowZSEtLw4IFCzB79mzI5XK4u7tj6tSpeO6559CmTRv4+/vj3//+N+TyVr+wABEREVVDWkrshiylj5c5QMgt4BhvqpsjlxITdRUD72aS8f5s6x8AgHEju0jbKkvNHbeWt12/+n19faFQKKyWfwKA7OxsBAYG1vrcoqIibNq0CVOnTq3zdSIjI+Hr64vTp09X+/jcuXORl5cn3SwzqLaSKWRQaBUQyk0wlRgdfhPKTVBoFZApbLvStGbNGsTFxVUJugFz4H3w4EEcO3bMpmONGTMG7777LpYsWYJu3brhww8/xCeffFJlgjZ7vf322/D29saAAQMwatQoxMfHo1evXjXuL5PJ8PXXX8Pb2xu333474uLiEBkZic2bN0v7xMfHY968eXj++efRt29fFBQUYOLEidLjnp6e2LNnD0aMGIFOnTrhpZdewtKlS3H33XfX6xy6d++O3bt34+TJkxg0aBB69uyJ+fPnIzjYvokh2rZti++//x4HDhxAdHQ0nnjiCUydOhUvvfSStM9bb72FQYMGYdSoUYiLi8Ntt92G3r1716vdRERE1LKJmUqNyjpP5u1pzngXlRisyoiJquPIpcREXdqbA+/L14odvhb2zUo9fRUHj2dBqZTj/pGViTux1PxaruPaLxPsXKwsJiYG/fr1w/LlywGYx/uGhoZixowZmDNnTo3PW7duHZ544gn89ddfaNOmTa2vcfHiRYSGhmLr1q34+9//Xmeb8vPzodPpkJeXB09PT6vHSktLkZ6ejoiICGmGapFJb4JgdNxabTeSKcxrhhPZora+S0RERC3b77//hX79Pka7AA/88f1U6TekySTAq8c7EATg4tlZaBtRNUlDJEpOzkSvXh8hsI0b0n581GGxSNTwNcj4Kw9frBiD4bdHOuQ1GsKLS3Zj+fpDGHlHe2x6b7S0fdknv2Pe279g/IguWPXiXfDopYNCW/fFitri0BvZ/c7Pnj0bq1evxvr165Gamopp06ahqKhIWmZq4sSJmDt3bpXnrVmzBmPGjKkSdBcWFuK5557Dvn37kJGRgYSEBIwePRodOnSQlrFyFLlKDoVW0Wg3Bt1EREREZAvLMd6W5HIZvCqy3teuO3d2kZqemPF2ZKk5AAwbFA4AWPDOLzAYqp+nq6kZDEZs+ta8ktJD99xq9VhjzGpu9xjv8ePH48qVK5g/fz6ysrLQo0cPbN++XZpw7fz581XGraalpeHXX3/Fjz/+WOV4CoUCx44dw/r165Gbm4vg4GAMGzYMCxcu5FreRERERNQqSSXC1QRMPjoNcvJKcd3Jy3qp6UkXcBwceL84fQD+b3saTpy+hlX/PYKZk5xvOOWOX9Jx5Xox/HxcMey2cKvHGmNW83pNrjZjxgzMmDGj2scSExOrbOvcuXOVJaJEWq0WO3bsqE8ziIiIiIhaJHH8tqaagEkc553DjDfVQZqkz4FjvAGgjZcWrz4zCDMW7MTrH/yGsfGd0DbQw2qfk+nX8ezrP+Nfj/TD4JhQh7anOp9uMU+qNuHvt8DlhvfDt2JW82vOspwYERERERE5Xm2TYklLijHjTXWQSs0dHHgDwENjbkW/6CAUFhsw963dVR6f9/Yv2LXvPDZ8leLwttwo+2oRdvxyFoC5nTeSSs1zi2tMGN+sVhN4O+oNJHIU9lkiIqLWq7ZloLw8zMMxr+dwLW+qXU3L0jmCXC7DsnlxkMtl2PLjSfy0N0N67FRGDn7YfQYAUNIEs/Fv2pYKo1FAn+6B0izslsRS89IyI4pKDA5pQ4sPvF1cXAAAxcWOW5ONyBH0ej0A8zwIRERE1LqIY3Ory3i7asXft44JEKjlaMyMNwBEdfbDtH/2BAA8+/rPKK0Isj/47DDEnJLYtxuLIAjS2t3VZbsBwE3rAo3a/B45akmxeo3xbk4UCgW8vLxw+fJlAICrqytkMtvW0iZqKiaTCVeuXIGrqyuUyhb/MSUiIqIb1BYwadXm3wYlDsrMUcvRmBlv0YvTY/HljjScOZ+LZWt/x6MTemDj139Ijzd2xvvg8Sz8eeYatBol7h3eudp9ZDIZfL1dcTGrAFcZeNdfYGAgAEjBN1FzIJfLERoaygtFRERErVBtpeYaMfBu5MwhNT+NnfEGAE93Nd54fggmP/cdlnx8AOcz81FSWg6FQgajUUCpvnH7rZjtHh3XETqPmlfN8vXWMvC+WTKZDEFBQfD394fBwCuD1DyoVKoqS/MRERFR61Db+stajfknfGkJA2+qXWPNan6jsfGdsOGrFPycdE6aTXzcyFvwv29ONGqpeXGJAf/3w58AgAfHdKt1X3Gc97Vcx8yd0CoCb5FCoeB4WSIiIiJyerWN8a7MeDOhRLWr7QKOI8lkMix5cSj6j90AvcGIYH93PPD3rubAW29stHZ8m3Aa+YV6hLX1xKC+IbXuWzmzuWMy3kynERERERE5mdpKzSvHeDPjTbVrqow3AHQM98bcJ2MBAM89FgMPdxWAqpOrGY0mvLhkN75JONXgbfh0q3npsgdGd4NcXvvwzTYVa3mz1JyIiIiIqJWozFRW/bkuZrwbe3Zoan6aYoy3pWcf6YeJY7rB39cNqaevAqg6udrhP7KxfP0h/PebExg1tEODzW907q887N5/ATKZOfCui6+POeN9nRlvIiIiIqLWQcp4V1tqbt7GydWoLk0xq/mN/H3dAADqigtGZTcE3gWF5iV0r+WU4GR6ToO97opPDwMABvcLRWiwZ537+zo4483Am4iIiIjIydSWqdRwOTGyUVNnvC1JQyRuCLwt7ycl/9Ugr3Uy/TpWbz4KAJg9ta9NzxEDb0et483Am4iIiIjIyUiTq9UyxpuzmlNdaqucaGzqikoNo1FAeblJ2m45SWDS4YYJvF96ew/Ky00YPjgSd8SG2fQcsdScGW8iIiIiolbCpow3S82pDmI/aspSc5F4wQiwznJb9uN9DZDxTtx3Hj8knoVSKcdrs2+3+XnMeBMRERERtTK1zmquYak52caZSs01FoF3aQ2B99kLeci6Uljv1zAaTZj7ViIA4JFx3dE50sfm54qBd0Gxoco49IbAwJuIiIiIyMnUtv6yhsuJkY1qu4DT2GQymdQOq8D7hiB3X/Kler/Gxm9OIOXkVXh5qDFnWqxdz9V5qKV/5+aW1rsNNWHgTURERETkZKQx3tVkKqUx3g7IylHLIvYjZwi8AYsJ1iyy3DdWbtR3gjWDwYg3P9wHAHj2sRi08dLa9XyZTAZXjeOGcTDwJiIiIiJyMrUvJ8aMN9lGGuPtBKXmgMWSYnqjtE3MeAdULDuWdLh+Ge9N21Jx7q98+Pm44tHx0fU6hlbjAgAoLm74YRwMvImIiIiInEztpebmbXq9EUajqcrjRCJnmtUcsMx4Vwa2YuXG0NhQAMDRPy+joMi8tnfivvP4aW9GncctLzdhyer9AICnp/SBq9alXu0TM96OCLyVde9CRERERESNqbaxuVaTVJWWw81N1WjtoubFmWY1BwCNpmrGu7iicqN9qDdCgz1x/lI+Dh7LRPrFPDz96k+Qy2U4/sNUhAZ71njcL374E2cv5KGNtxZTx3Wvd/vEiQuLHTBxITPeREREREROprYSYatlmVhuTrVwtoy3puICgOUYajHjrdUqEdszGAAw/51f8PSrPwEATCYBX+1Iq/GYRqMJb31kznbPnNgb7q71vxBVWWrOMd5ERERERC1ebZNiKRRyuCjNP+O5pBjVxtnGeIsZb8uZzIsrys61aiVie7UFABxJvQwA6N7FDwCwZcfJGo+55ceTOJWRA2+dBo9N6HFT7ZMmV+MYbyIiIiKilq+y1Lz6kaGcYI1s4UzLiQGApqI/W66TLV5k0mpcMKAi8AaA2VP7YuuqeyGXy3D4j2ycvZBb7THXf5kCAHjygZ7wuMlhFyw1JyIiIiJqRaTJ1WrIVEqTVDHjTbVoHhlvMfBW4pYOvlg4exDenR+Hl5++DX5tXDG4XwgA4Ktqst4lpQZp+bF74jvfdPtcOas5EREREVHrIWYEawqYxIx3qQPWG6aWw/ky3uZ2iBcEAIsx3hVB+awpffHwfd0hk8kAAPfEdwIAfLW96jjvpMOXUKY3om2AOzpFeN90+5jxJiIiIiJqJQRBqHU5McBikiqWmlMt6qqcaGzaajLe4kRrlpMGWvp7XEcolXIcT7uCk+nXrR77ed85AMCQ/mFSoH5z7XOyjPeKFSsQHh4OjUaDmJgYHDhwoMZ9161bB5lMZnXTaDRW+wiCgPnz5yMoKAharRZxcXE4depUfZpGRERERNSs6S2WWqopYNKw1JzqYL6AU3vlRGOrrlJDXNNbW8Pa2228tLgjxrzG942TrCXuOw+gcg3wm+XIdbztDrw3b96M2bNnY8GCBTh8+DCio6MRHx+Py5cv1/gcT09PZGZmSrdz585ZPf7mm2/ivffew6pVq7B//364ubkhPj4epaWl9p8REREREVEzZlmGW2PGm5OrUR3Ky00QBPO/nabUXAy89RaBd1ntGW8AGDvcPH77S4tlxa5cL8bRitnPh8Q0TOBdWWruBMuJvf3223j00UcxZcoUdO3aFatWrYKrqyvWrl1b43NkMhkCAwOlW0BAgPSYIAhYtmwZXnrpJYwePRrdu3fHhg0bcOnSJWzdurVeJ0VERERE1FxZzvhcU6ZSK5WaM+NN1bO8gONsGW/LdbzFi0eaWgLvkXe0h4tSjtTT16TJ1PYcuAAA6NbRF/6+bg3SPnFytSZfTkyv1+PQoUOIi4urPIBcjri4OCQlJdX4vMLCQoSFhSEkJASjR4/GH3/8IT2Wnp6OrKwsq2PqdDrExMTUeMyysjLk5+db3YiIiIiIWgIxYHJxkUMur37cKjPeVBfLCzjOMsZbo66YXM1iOIWY8XbV1hx4e+s0mPD3rgCAF95IhMkk4OckcxX1HbFhDdY+p5lc7erVqzAajVYZawAICAhAVlZWtc/p3Lkz1q5di6+//hqfffYZTCYTBgwYgIsXLwKA9Dx7jrlo0SLodDrpFhISYs9pEBERERE5LXH8q7qWDCCXE6O6iBdw5HIZlErnmFP7xoy30WiSgvDaMt4AsGDmQHi6q5B8Ihufbk3BLjHw7t8wZeaWbXCKMd72io2NxcSJE9GjRw8MHjwYX331Ffz8/PDhhx/W+5hz585FXl6edLtw4UIDtpiIiIiIqOmImUpxzePqcDkxqou0lJjaObLdQGVGWVxCrNSiHF4s866Jv68b5k6LBQDMfXM3LmQWwEUpx8De7RqsfU4zuZqvry8UCgWys7OttmdnZyMwMNCmY7i4uKBnz544ffo0AEjPs+eYarUanp6eVjciIiIiopagrqXEAJaaU93EflTbBZzGplZZB97FpZUBrtaGdj4+oQc6RfigoEgPAIjpEQw319oDdntIy4k1dam5SqVC7969kZCQIG0zmUxISEhAbGysTccwGo04fvw4goKCAAAREREIDAy0OmZ+fj72799v8zGJiIiIiFoKWzKVGk6uRnWQhiyonCfwrprxFtuoqHE+A0suLgq8OWeIdL8hy8wBy4y3E8xqPnv2bKxevRrr169Hamoqpk2bhqKiIkyZMgUAMHHiRMydO1fa/9VXX8WPP/6Is2fP4vDhw3jwwQdx7tw5PPLIIwDMM57PmjULr732Gr755hscP34cEydORHBwMMaMGdMwZ0lERERE1EzYMsabGW+qizOWmmtuyHiLY71rW0rsRncOCMcDo7vB3dVFWmasoYgZb0dc0LL78sf48eNx5coVzJ8/H1lZWejRowe2b98uTY52/vx5yOWV8XxOTg4effRRZGVlwdvbG71798Zvv/2Grl27Svs8//zzKCoqwmOPPYbc3Fzcdttt2L59OzQaTQOcIhERERFR82FLqTknV6O6SP3ImQJvTfWBt73l8CsXDsOKV+6CQtGwU5aJM6s7Yox3veoOZsyYgRkzZlT7WGJiotX9d955B++8806tx5PJZHj11Vfx6quv1qc5REREREQthpSptGFyNWa8qSaVGW/nKTWXhkhUBNzSUmJ2Bt4ymQwKRd2l6fbSOsvkakRERERE5Fi2ZCrF9ZAZeFNNbKmcaGxiZltcQkys2KhrKbHGIpWaO2C1AAbeREREREROxJZMpZbLiVEdxH6kcqJSc+0N63hLGW9tw81MfjOcZjkxIiIiIiJyrMrZqGub1ZxjvKl2lZUTzpFNBizWn9ffMMbbSdoolpqXl5tgMBjr2Ns+DLyJiIiIiJyILesvs9Sc6lJWVvcFnMYmBd43TK5m7xhvR3HVVGbeGzrrzcCbiIiIiMiJ2LaONzPeVDvnzHhXTq4mCIIUgNs7q7mjuCjl0qRtDLyJiIiIiFqwykmx6h7jzYw31cQp1/Gu6LeCABjKTSguNQe39qzj7UgymQyuaseM82bgTURERETkRKQx3rXOas6MN9XOGdfx1lpktktKy6W+rtU4x+RqQGVbGHgTEREREbVglbNRcx1vqr/KMd7OkU0GAJWLArKK5bfLyspRLAXeztNGLTPeREREREQtnzS5Wi2ZSi0z3lQHZ8x4y2SyyotGZZYZbycKvB20pBgDbyIiIiIiJ2LLOt4aruNNdbClcqIpaCpmWS8tMzrdGG/AcWt5M/AmIiIiInIitmQqtRWPGQwmGI2mRmkXNS+Vk/Q5T8YbqJzBvLSsXJrVXKt1ojHeao7xJiIiIiJq8SonV6s5C2g5bpfjvKk6zjirOWAxTKKsXFrH25ky3iw1JyIiIiJqBSrHeNe9nBjAcd5UPakfOdH4aaDygpKzTq7GUnMiIiIiolbAlkylXC6DqqKEmBlvqk7lkAXnCWoB64y3VGruRIE3ZzUnIiIiImoFbJ2NWqvlzOZUM2nIgpON8bbOeJv7bm3VHY1Nw8CbiIiIiKjls2WMNwBoNeZJoJjxpuo4/Rjv0srlxFw1zjO5mtgWBt5ERERERC2YLcuJAZUZby4pRtVx1lJz8UKA5eRqzjQOnaXmREREREStAEvNqSE4e8a7rMwoBd6uzhR4c3I1IiIiIqKWz9aASRyLylJzqo54AUelcp6gFrDot2XlKClzvox35azmDfu5YuBNREREROREpIx3HQGThhlvqoWzZrw1FpOrlVRMruZMY7y1ao7xJiIiIiJq8SonV6ur1JyTq1HNbB2y0NikMdSl5SitaKPWicahs9SciIiIiKgVKLOx/FYMEJjxpupIGW8nKzUXLwTk5pdK25yz1JyBNxERERFRi2X75GrMeFPNnD3jnZNXWmWbM+Cs5kRERERErYCtmUouJ0a1sXVZusYmZrdzKjLeLko5lErnCUvF8eYNXUniPGdIRERERNTKlZebYDQKAGzIeLPUnGrhrBlvjco64+2qdZ6J1QAnG+O9YsUKhIeHQ6PRICYmBgcOHKhx39WrV2PQoEHw9vaGt7c34uLiquw/efJkyGQyq9vw4cPr0zQiIiIiomZLzFICdY971bDUnGpRWTnhZIG3xjrw1jhZRt5pSs03b96M2bNnY8GCBTh8+DCio6MRHx+Py5cvV7t/YmIiJkyYgF27diEpKQkhISEYNmwY/vrrL6v9hg8fjszMTOn2v//9r35nRERERETUTIlZSqDuEmFNRSaTGW+6kdFoWTnhXIGtpuJCgJTxdqKJ1QAnmlzt7bffxqOPPoopU6aga9euWLVqFVxdXbF27dpq99+4cSOefPJJ9OjRA126dMHHH38Mk8mEhIQEq/3UajUCAwOlm7e3d/3OiIiIiIiomRKzlHK5rM5xr5xcjWpifQHHuTLeYil3YUVg60wzmgOAVlO5jrcgCA12XLsCb71ej0OHDiEuLq7yAHI54uLikJSUZNMxiouLYTAY4OPjY7U9MTER/v7+6Ny5M6ZNm4Zr167VeIyysjLk5+db3YiIiIiImjt7xuWKk6sx8KYbWQ5ZcLqM9w3tcaYZzYHKCwOCYH0B42bZFXhfvXoVRqMRAQEBVtsDAgKQlZVl0zFeeOEFBAcHWwXvw4cPx4YNG5CQkIDFixdj9+7duPvuu2E0Vn+iixYtgk6nk24hISH2nAYRERERkVMSZyi3JVjSOmj2ZWr+xIBRJgNcXJxrPu0qgbezZbwtVhNoyHLzRj3LN954A5s2bUJiYiI0Go20/f7775f+HRUVhe7du6N9+/ZITEzEnXfeWeU4c+fOxezZs6X7+fn5DL6JiIiIqNkTM5W2lN8y4001sVxKTCaTNXFrrDl74K1UyqFSKaDXG1FcbICPj7ZBjmvX5Q9fX18oFApkZ2dbbc/OzkZgYGCtz12yZAneeOMN/Pjjj+jevXut+0ZGRsLX1xenT5+u9nG1Wg1PT0+rGxERERFRc1efUnOu4003qqyccK7x3UB1gbdzLScGAK6uleO8G4pdgbdKpULv3r2tJkYTJ0qLjY2t8XlvvvkmFi5ciO3bt6NPnz51vs7Fixdx7do1BAUF2dM8IiIiIqJmzTJTWReWmlNNKi/gOFc2GXD+Md5A5driTRZ4A8Ds2bOxevVqrF+/HqmpqZg2bRqKioowZcoUAMDEiRMxd+5caf/Fixdj3rx5WLt2LcLDw5GVlYWsrCwUFhYCAAoLC/Hcc89h3759yMjIQEJCAkaPHo0OHTogPj6+gU6TiIiIiMj52ZOpVGtYak7Vq7yA44wZb+s2iZUbzsTVteGXFLP7LMePH48rV65g/vz5yMrKQo8ePbB9+3ZpwrXz589DLq+M51euXAm9Xo9//OMfVsdZsGABXn75ZSgUChw7dgzr169Hbm4ugoODMWzYMCxcuBBqtfomT4+IiIiIqPkQM5X2jfFmxpusOXPG+8YMt1NmvB1Qal6vs5wxYwZmzJhR7WOJiYlW9zMyMmo9llarxY4dO+rTDCIiIiKiFsW+UnNmvKl6Tp3x1jj/GG+NxglKzYmIiIiIyDHsm1yNY7ypes6c8Xb2Wc0Bx5SaM/AmIiIiInISdmW8uZwY1cCZM94uSjnk8solzm4MxJ2BU0yuRkREREREjmHP5GpippDLidGNnDnjLZPJrCZYc3XKjDcDbyIiIiKiFsu+ydXMwUF5uQnl5SaHtouaF2fOeAPWWW5b+npjY+BNRERERNSC1afUHOA4b7LmzBlvwHomc1cnnFyNpeZERERERC2YPZOrWQZVHOdNlppVxtsJLw5omfEmIiIiImq57BnjLZfLpP2Y8SZLzp7xtgy2XbXO10axTQy8iYiIiIhaIDFTaeu418olxZjxpkrOn/FWWPzbCQNvZryJiIiIiFouezOVlUuKMeNNlewZstAULINt51zHm4E3EREREVGLZW+mUsx4c0kxsmTPJH1NQcPJ1YiIiIiIqKnUP+PNwJsq2bMsXVNw9snVxIx3Q36uGHgTERERETkJMXNt/xhvlppTJWcf421ZXu7qhBcHmPEmIiIiImrB7B2bKwbozHiTJWef1Vytssh4O2HgrXXlrOZERERERC2WvWNzObkaVceeZemagmXGW+uEFwc4uRoRERERUQtmb8aby4lRdZw/423u30qlHC4uzndxgKXmRERE1Or9/HM6+vT5CG++uRcmk9DUzSFqUJWZSma8qf6ayxhvZ8x2A47JeDvnmRIRERFV4/DhTIwevQmFhXocOpSJHTvOYMOGMWjb1rOpm0bUIMSAyf7J1ZjxpkrOnvEWA25nXMMbYOBNRERErdiZM9dx990bUVioR48egTh58hp+/jkd0dGrMHFiNCIjvREZ6Y2ICC+Eh3tJAUl+fhnS03NQWloOb28tvL018PLSVClvFAQBBQV65OaWIienBGVlRkRF+UvHIWoM9peam3/Ocx1vsiQGjM6a8VY7e+Bd8b1fWloOk0mAXC676WM655kSERERVTAaTTh48BIefHALLl8uQnR0AHbvnozMzAL8859f4fDhTLzzzr4qzwsKcodeb8S1ayXVHtfNzQXe3lqo1Qrk5pYiN7cURqN16bparcCAASG4445weHtrAQAyGXDrrf7o37+d02aTqPmq7+RqDZmZo+btyy9P4LffLgAAIiO9m7g11avMeDvnhU0x4w2Yh3G4ualu+pj8a0FEREROp7S0HF9+eQJffHECiYkZyMsrAwCEh3vhhx8egKenGp6eavz228P473+PIyXlMtLTc3H2bA7Ons1BQYEemZmF0vF8fV3h6uqC3NxS5Oebj1VUZEBRUdVgRaVSwNtbA0EALl8uwq5dGdi1K6PKflqtErffHobOndtYZdLFfwNATo45e65WK9GzZyA6dmxTJXNiMBixbdtJJCZmwN/fDZGR3ggJ0aG0tBw5OSXSMcyZ+FKr+506tcHDD/fEkCHhN5WRMRiMuHAhH+npObhwIR8hIZ7o1StIutjQEHJzS5GYmIGffjqL5OQshIXp0Lt3EHr1CkLnzr4IDHRvkKxSc2dvxjs42AMAsHLlQQwZEo4RIzo6rG3OwGg04eLFfJw9a+6r4eFe6N+/HVQq58zsNraUlMuYNGkrAOCZZ/qjd+9gGEuMTduoaoj921nHeFsO9SguZuBNRETUquzffxHz5u3Cb79dQLt2noiM9EaHDj64/fYw3HFHONq0cW3qJt6UnJwSJCdn4euv/8Snnx5DTk6p9JhOp0ZcXCQWL45DUJCHtF2tVmLKlJ5WxxEEAdevlyA9PRcuLnJERnrDw0MtPV5ebkJeXmUAW1ZmrAiYzUGzVquETCaDIAg4efIaEhLSsW/fRSkgKisrR1LSRVy+XIQdO85gx44zNp+ju7sKUVH+aN/eB5GRXigpKceGDUeRnV1Ur/fs998vYePG42jf3ht33hkBhcI8b645aDefX3UXFwBzACMG83l5pRCqmacuPNwLvr6V/UqrVUoXFiwvNLi5uUAmMwfNSqVcej9LSsqxa1c6EhLScehQptVkeL/9dgH/+1+KdF+jUSIiwgsBAe4W/z8qXwOAdCHCzc0Fd9wRgQEDQmocC11ebsKFC3k4ezYHly4VwNXVRWp7SIgObdpopTY7E7Fk3NYx3o891hvffXcKu3ZlYNSo/+G994ZjypSeUhVHeblJ2tfHR4vgYI+bvsBhNJpw6VIBzp7NwfnzeTAYKl9DrCTR6dRISbmMn35KR2JiBkwmAb16BaFXr0BERnpL772Li7m/eHlp4OmplrZfu1aMXbsykJCQjt9//8vqNW7k6uqC228PQ58+QYiIMA85CQ72kPpRWZkR6enmi3KWFTAGg1H6nJSWliMkRCcNVfH1dYW3txYeHqoa+4n4XbBrVzoyMvKk/ikIgtRv/f1dERFhHgLj7++GvLwy5OSUoKBALx1HJgM8PdUWny3zfz081NDrjdKFtoAAd/j41HwxLCenBGPGbEJRkQFDh0bgzTfvsu1/aBNwrch0O2upuVwug0ajRGlpeYNVk8gEobqv2eYlPz8fOp0OeXl58PTk5CpERNT0rlwpwt69FxAR4YWuXf3qvVyKwWDEvn0XsXRpEr7+Oq3G/WQyoEePQPTr11bKInbq1MYq4GxK4g/17Owi6cep+MM9PT0Xf/xhzlhbCg3VYfLkaPztb53Qq1eQFFQ6A0EQ8McfV5CYmIFLlwosMtOl0r8BSD+i8/PLcPRoVo0TYPn7u+Ef/7gFRUUGpKfn4uLF/IpA0TqLLh7Py0sDd3cVdu48g40bj1v9iK8vtVqBiAhvtG3rIf1/aWidO7dBXFwk+vdvh/Pn83DoUCaSkzNx7lxevWao12iU6Ny5DQoK9MjJKUFhYeX7UF5uqvZigsjDQ4WICG+4u9uXydJolAgP1yEy0hs+PlqcO5eH9PRcZGUVwt1dBW9vDXx8tAgNNe8TFqaDXm+sEggLApCdXSi91+Jn49y5PADAqVMzEdFWh4LDeZBrFZCrKvu/SW+CqcQIj146KLQK6PVGTJu2DWvXHqmz/Wq1AuHhXtJ8CJGR3jAYTDh0KBOHD2fiwoU8aV+FovIiipubCvn5ZVL/tgzoG5tKpUBYmA7t2nkiJeUyrlwpdthryeUyKBSVgbe7u0q6SHDy5DWHTmonk6FKHw4P90KvXkFQqxVShU9urvn7xmQSYDQKCAvT4eDBx6SLZsYSY7X9qCllXy3Cg7O/xeR7o/DA6G5N3RyJ5WfLv91SXL9egr//vTP+9reOGDasPcLCvKz2X7jwR8yfH29THMrAm4jIiRQXG3D5chE8PMx/2G8MNEwmAfn5ZRVjUSt/9LRp4wovL410X8z4FRcbpB/o9c3sGI0mZGYWQqmUw9tbU2Xc4fXrJUhONv9gy80trTYDplDIpO06nVrKthiNgjSRVV5emfTDW5zkSrzK7+KisAo4xH/L5bJqS3ENBiPCw70QEeGNkBBPKJXm91GvN+LcubyKEsU8aLWVgY1lYCwGPN7eWphMQrVZDBcXOXJyzD+kS0vLpYzN1avFWLs2GVu3/illaNRqBaKiAhAU5C69ByUlBun5Xl4a6QewSqWQzufIkWzs2XNOCibkchkmTYrGjBn9kJtbirNnc3DsWDYSEtJx4sSVav//+fq6IiLCy2q8mmXmT8yqCYJgkSUttVqayJxxMbepvNyEW2/1R69eQejSxbcicMjFhQt51f4QN5kEZGYW4ty53FozVqLISG/ExLTFxInRuOuuSKcKtm9WebkJaWlX8ccfV6TsW1GRAWPH3oJRozrV++JMUZEeX36ZivT0HGmbuVxeKwVM1X385XIZdDqNFCj6+blZZUJzckpw9Gg2iorM/U8QzN9R4me28nNXZpUREoPMnJwSGI0CBg4MQVxcJIYOjUC7dtX/TjMYjDh/3hzAXr1aLB3f8rVkMpl08eHSpUIkJJy1Gk5QHZVKgYgIL6vS/WvXSpCVVfvzmlq7dp44dWomXASZTYE3YP4ML168F/Pn74LBYIJCYf7/6+Iir3jcnEW+cR6D+lIq5QgP90JYmE6agFAQBBQW6qX/d+3aeSIuLgJ33hkJjUaJQ4cu4dChTKsKDzGjm5NTioKCMmm7RqNEbGwI7rwzAoMHh8HT03wRUS6XoU0bV6mvmkwCUlIuY9eudPz551WcPZuL9PQcZGcXScNKAPNFsMhIbwQGuldbnaFSKaQ+mJGRi+vXS6DX112iHRDghqFDIxAdHQAfHy28vbWQySD9PcrMLEB6eq7Uty2z+5V/C00VFzUq+7vlZHlyuQyenmopwK6Nv78bdux4ED16BErbnDHwdlaWn62//2Mzvv/+lPSYXC7DM8/0x8KFd0CjUeL553diyZJdAN5g4E1Nr6CgDIWFenh5aeo9K6wgCCgpKa9SLqXVKq1+LBsM5j/0llcexS9UsWzwZl6vJpZj8GoqRRG/MMWyocJC86y5eXnWE/m4ublIP+rLy00WPzYgbVcoZFV+jNx4ld/yx5T4emJgYxmsubmppOCirtfLySmp8fzKy00VV/LLaixXrI1aXfkDUa83Slf/r16tvIItBm5eXhrodJo6y+RuDNzMQaP5NSz7ohj85OSUwGAwSX+AtVoXqRS1oKBMOifLcjAvL40U0Jnfz8pgprJ8rdSmP9xFRXopY2LJw0MlBR4mk/kHTU1ZIW9vDSIivGE0mqQxriKlUl5jIGz5x9+SWKZ57lxelc+eGHwLgiCNvaWqOnVqg+zswpt+j9q00WLEiI548cVB6NLFt9p9srIKsWfPORw+bL4IcuRIlkOzQPWhVMoREOAmfU4CA90REWG+QNKpUxv07BnYoGOKqWUTBAF//nkV6em50OnUVcqClUo5/P3dqv1+Ky0tR0aGOcCydzbwgoIyKZC6fr0EYWHm8uTgYA8UFRmQk1OCq1eLkZGRJ5ViazRKeHub/35ZjkX29XVFZKT5MxAc7CH9TQ4N1UGjUdYYMFUXeIvEvxPVlUhblt+LcyKkp+dCJgN69gxEr15B6NDBR/q7YzAYpdLooiKD9FvG21uLoCB3p78wJg4rETP39rD8PWh5UdjywkJoqA7duvk5ZMhCaWk58vJKodEo4eFh/judm1uKI0eycPiwediGuJKD5bAJX1/XKsMUGHjbzvKzJbjIkJR0AQkJ6di586w0YV3Hjj6Ijg7E//3fCQClcGjgvWLFCrz11lvIyspCdHQ0li9fjn79+tW4/xdffIF58+YhIyMDHTt2xOLFizFixAjpcUEQsGDBAqxevRq5ubkYOHAgVq5ciY4dbZscQgy8f/jhONq184enpxpFRZUfCstAo/I1zVdtLbMY1V0ZFq/yWwc5pSgs1MPDQyVlSix/fDtCZVbIHASIAZM58Ky8kllQUIbcXPMXpEIhl64MA0B1WQxbmEzmH9ZioKjVulhdHbyReEX1xsBJrVbAw0MtvbcKhVz6Q+nuXlm+lJ9fmfUymczBU22Bi1giZhl43kilUsDDQ1VnsGbL6xE5mkqlqLMPajRKq89+Tf3fxUVuU5axLkqlHEZjzWWb7dt7o1evIAQGukvfVWKWDAAMBpP0PVpQoIf4p0cmk0nfAzqd2uq71MNDLX3PWV7IsPw+NpkEq/Fw4neTXC6TfvReulQgvZ5CIUdIiCciIrwRGupp9R1vWf5ZVKSXzkMul0mvYZnFMBiM0gUYjUYplZGaTALuuacLHnmkF3r0CITJJCA93ZyZNmfyzPuJY2W9vDQV45FzcPZsLozGygtAERHeGDo0At27B9RrTKa4jFZGRq7Up8TzsxzfLFKrFVLGxtXVRfq+rswKaSEIAo4ezcbhw5k4ffo6goLcK8ppvWqcDMrPzzxhWNu2Hk7/Q53ImdQn8Ca6EQNv29X22dq27SQef3wbLl0qAGBOYrz33h2YPv12xwTemzdvxsSJE7Fq1SrExMRg2bJl+OKLL5CWlgZ/f/8q+//222+4/fbbsWjRIvztb3/Df//7XyxevBiHDx/GrbfeCgBYvHgxFi1ahPXr1yMiIgLz5s3D8ePHceLECWg0dV+dEgNvYA4A+65mkeNVNz6lPhQKmZTdFgTB6seiJbVaIV31MxiM9S6psny92oiz395YWmvJciKfgoKyijFg1hlTy6uoOTklVhlaQYBV2V51Y/4sL2qUl5uQn6+XghxxzJllYCMGa2IQIU5uYv165mBEfI3ayhUty4jt+WFtXd5qvmAkltwGBFTOcGt51T0/v8ymPlV53hopK39joGH5/8/FRS6dd0mJodqMsGU5WE1XwXNySqxKo22ZIEetViAszHze5oy5SbrYZZltF4PRG8u9xYx5enoOFAq5NK5Qo1GipKS8ygRLYoWIOMNzde+nTAa0bespZXJkMpl0gcwymPf3d7M7k0BERHVj4E0NgYG37er6bOXmluKFF3bixx/PYtmyeNxxR7DNldd2B94xMTHo27cv3n//fXPjTCaEhIRg5syZmDNnTpX9x48fj6KiImzbtk3a1r9/f/To0QOrVq2CIAgIDg7Gv/71Lzz77LMAgLy8PAQEBGDdunW4//7762yTGHhHRi5Gfr75h6FY8mmZEb6ROLZPzAiLmWLLclox+LGcXVMMsCxLTeozIYg9zKXDlWVUYinTjWuOWpa6Go2V4xIBSMGaOYthe+bEsrTWPC6xsrS6plJsnU5dMWmHedIScya+tMqkJ2KQU1iol8qXdDqN1SQWnp7qaseoWgaz4vnpdNbVB5bBkOW4odrU9HpEREREjYmBNzUEBt62s/ezZc+QZ7vmb9fr9Th06BDmzp0rbZPL5YiLi0NSUlK1z0lKSsLs2bOttsXHx2Pr1q0AgPT0dGRlZSEuLk56XKfTISYmBklJSdUG3mVlZSgrqwyi8vPzAQDJyU9wjLeT0unMQXFDUirlaNPGtdblc2QyGTw81E4zqy8REREREbU+dl3yuHr1KoxGIwICAqy2BwQEICsrq9rnZGVl1bq/+F97jrlo0SLodDrpFhISYs9pEBERERERETWaZllrMHfuXOTl5Um3CxcuNHWTiIiIiIiIiKplV+Dt6+sLhUKB7Oxsq+3Z2dkIDAys9jmBgYG17i/+155jqtVqeHp6Wt2IiIiIiIiInJFdgbdKpULv3r2RkJAgbTOZTEhISEBsbGy1z4mNjbXaHwB27twp7R8REYHAwECrffLz87F///4aj0lERERERETUXNg1uRoAzJ49G5MmTUKfPn3Qr18/LFu2DEVFRZgyZQoAYOLEiWjbti0WLVoEAHj66acxePBgLF26FCNHjsSmTZtw8OBBfPTRRwDMk1/NmjULr732Gjp27CgtJxYcHIwxY8bY1CZxYnZxkjUiIiIioubOWGJEQVE+ZGVyyJSVK60I5QKEchOEfBkUBs5qTrWrqR9RVfZ+tsT406aFwoR6WL58uRAaGiqoVCqhX79+wr59+6THBg8eLEyaNMlq/88//1zo1KmToFKphG7dugnfffed1eMmk0mYN2+eEBAQIKjVauHOO+8U0tLSbG7PmTNnBAC88cYbb7zxxhtvvPHGG2+88daotzNnztQZs9q9jrczys3Nhbe3N86fPw+dTtfUzSEn1bdvX/z+++9N3Qwih2Nfp9aCfZ1aA/Zzai2aY1/Py8tDaGgocnJy4OXlVeu+dpeaOyO53DxUXafTcaI1qpFCoWD/oFaBfZ1aC/Z1ag3Yz6m1aM59XYxHa92nEdpB5BSmT5/e1E0gahTs69RasK9Ta8B+Tq1FS+/rLaLUPD8/HzqdDnl5ec32KgkRERERERE1H/bEoS0i461Wq7FgwQKo1eqmbgoRERERERG1AvbEoS0i401ERERERETkrFpExpuIiIiIiIjIWTHwJiIiIiIiInIgBt7k9Pbs2YNRo0YhODgYMpkMW7dutXq8sLAQM2bMQLt27aDVatG1a1esWrWqzuMeO3YMgwYNgkajQUhICN58880q+3zxxRfo0qULNBoNoqKi8P333zfUaRFVUVdfz87OxuTJkxEcHAxXV1cMHz4cp06dqvO47OvkTBYtWoS+ffvCw8MD/v7+GDNmDNLS0qz2KS0txfTp09GmTRu4u7vj3nvvRXZ2dp3HrqsfC4KA+fPnIygoCFqtFnFxcTZ9hojsZUs//+ijjzBkyBB4enpCJpMhNzfXpmMnJiaiV69eUKvV6NChA9atW1dlnxUrViA8PBwajQYxMTE4cOBAA5wVUVV19fXr169j5syZ6Ny5M7RaLUJDQ/HUU08hLy+vzmO3tO90Bt7k9IqKihAdHY0VK1ZU+/js2bOxfft2fPbZZ0hNTcWsWbMwY8YMfPPNNzUeMz8/H8OGDUNYWBgOHTqEt956Cy+//DI++ugjaZ/ffvsNEyZMwNSpU5GcnIwxY8ZgzJgxSElJafBzJAJq7+uCIGDMmDE4e/Ysvv76ayQnJyMsLAxxcXEoKiqq8Zjs6+Rsdu/ejenTp2Pfvn3YuXMnDAYDhg0bZtWPn3nmGXz77bf44osvsHv3bly6dAljx46t9bi29OM333wT7733HlatWoX9+/fDzc0N8fHxKC0tddj5UutkSz8vLi7G8OHD8eKLL9p83PT0dIwcORJ33HEHjhw5glmzZuGRRx7Bjh07pH02b96M2bNnY8GCBTh8+DCio6MRHx+Py5cvN+g5EgF19/VLly7h0qVLWLJkCVJSUrBu3Tps374dU6dOrfW4LfI7XSBqRgAIW7ZssdrWrVs34dVXX7Xa1qtXL+Hf//53jcf54IMPBG9vb6GsrEza9sILLwidO3eW7o8bN04YOXKk1fNiYmKExx9//CbOgMg2N/b1tLQ0AYCQkpIibTMajYKfn5+wevXqGo/Dvk7O7vLlywIAYffu3YIgCEJubq7g4uIifPHFF9I+qampAgAhKSmpxuPU1Y9NJpMQGBgovPXWW9Ljubm5glqtFv73v/815CkRVXFjP7e0a9cuAYCQk5NT53Gef/55oVu3blbbxo8fL8THx0v3+/XrJ0yfPl26bzQaheDgYGHRokX1PwEiG9XW10Wff/65oFKpBIPBUOM+LfE7nRlvavYGDBiAb775Bn/99RcEQcCuXbtw8uRJDBs2TNpn8uTJGDJkiHQ/KSkJt99+O1QqlbQtPj4eaWlpyMnJkfaJi4uzeq34+HgkJSU59oSIqlFWVgYA0Gg00ja5XA61Wo1ff/1V2sa+Ts2NWG7o4+MDADh06BAMBoNVn+zSpQtCQ0Ot+mR4eDhefvll6X5d/Tg9PR1ZWVlW++h0OsTExLCvk8Pd2M9tNWTIEEyePFm6X1c/1+v1OHTokNU+crkccXFx7OfUKGzp6+Ka10qlUtrWGr7TGXhTs7d8+XJ07doV7dq1g0qlwvDhw7FixQrcfvvt0j5BQUEIDQ2V7mdlZSEgIMDqOOL9rKysWvcRHydqTGLgMXfuXOTk5ECv12Px4sW4ePEiMjMzpf3Y16k5MZlMmDVrFgYOHIhbb70VgLk/qlQqeHl5We17Y59s3749fH19pft19WPxv+zr1Niq6+e2Cg0NRVBQkHS/pn6en5+PkpISXL16FUajkf2cmoQtff3q1atYuHAhHnvsMavtreE7XVn3LkTObfny5di3bx+++eYbhIWFYc+ePZg+fTqCg4Olq2CLFi1q4lYS3RwXFxd89dVXmDp1Knx8fKBQKBAXF4e7774bgiBI+7GvU3Myffp0pKSkWFVt2CohIcEBLSJqeDfTzzds2OCAFhE5Rl19PT8/HyNHjkTXrl2tsttA6/hOZ+BNzVpJSQlefPFFbNmyBSNHjgQAdO/eHUeOHMGSJUuqlKiIAgMDq8yQK94PDAysdR/xcaLG1rt3bxw5cgR5eXnQ6/Xw8/NDTEwM+vTpU+Nz2NfJWc2YMQPbtm3Dnj170K5dO2l7YGAg9Ho9cnNzrbLedfXJuvqx+N/s7GyrDGJ2djZ69OjRAGdEVFVN/by+aurnnp6e0Gq1UCgUUCgU/E6nRldXXy8oKMDw4cPh4eGBLVu2wMXFpdbjtcTvdJaaU7NmMBhgMBggl1t3ZYVCAZPJVOPzYmNjsWfPHhgMBmnbzp070blzZ3h7e0v73Hj1befOnYiNjW3AMyCyn06ng5+fH06dOoWDBw9i9OjRNe7Lvk7ORhAEzJgxA1u2bMHPP/+MiIgIq8d79+4NFxcXqz6ZlpaG8+fP19on6+rHERERCAwMtNonPz8f+/fvZ1+nBldXP6+vuvq5SqVC7969rfYxmUxISEhgPyeHsKWviyusqFQqfPPNN1bz1dSkRX6nN+nUbkQ2KCgoEJKTk4Xk5GQBgPD2228LycnJwrlz5wRBEITBgwcL3bp1E3bt2iWcPXtW+OSTTwSNRiN88MEH0jHmzJkjPPTQQ9L93NxcISAgQHjooYeElJQUYdOmTYKrq6vw4YcfSvvs3btXUCqVwpIlS4TU1FRhwYIFgouLi3D8+PHGO3lqVerq659//rmwa9cu4cyZM8LWrVuFsLAwYezYsVbHYF8nZzdt2jRBp9MJiYmJQmZmpnQrLi6W9nniiSeE0NBQ4eeffxYOHjwoxMbGCrGxsVbHGTp0qLB8+XLpvi39+I033hC8vLyEr7/+Wjh27JgwevRoISIiQigpKXH8iVOrYks/z8zMFJKTk4XVq1cLAIQ9e/YIycnJwrVr16R9HnroIWHOnDnS/bNnzwqurq7Cc889J6SmpgorVqwQFAqFsH37dmmfTZs2CWq1Wli3bp1w4sQJ4bHHHhO8vLyErKysxjl5alXq6ut5eXlCTEyMEBUVJZw+fdpqn/Lycuk4reE7nYE3OT1xmY0bb5MmTRIEwfyHa/LkyUJwcLCg0WiEzp07C0uXLhVMJpN0jEmTJgmDBw+2Ou7Ro0eF2267TVCr1ULbtm2FN954o8prf/7550KnTp0ElUoldOvWTfjuu+8cearUytXV1999912hXbt2gouLixAaGiq89NJLVsuECQL7Ojm/6vo4AOGTTz6R9ikpKRGefPJJwdvbW3B1dRXuueceITMz0+o4YWFhwoIFC6y21dWPTSaTMG/ePCEgIEBQq9XCnXfeKaSlpTnqVKkVs6WfL1iwoM59Bg8eLP0NEO3atUvo0aOHoFKphMjISKv9RcuXLxdCQ0MFlUol9OvXT9i3b59jTpRavbr6ek2/bQAI6enp0nFaw3e6TBAsZuUhIiIiIiIiogbFMd5EREREREREDsTAm4iIiIiIiMiBGHgTERERERERORADbyIiIiIiIiIHYuBNRERERERE5EAMvImIiIiIiIgciIE3ERERERERkQMx8CYiIiIiIiJyIAbeRERErcyQIUMwa9aspm4GERFRq8HAm4iIiIiIiMiBGHgTERG1IpMnT8bu3bvx7rvvQiaTQSaTITk5GQ888AD8/Pyg1WrRsWNHfPLJJ03dVCIiohZD2dQNICIiosbz7rvv4uTJk7j11lvx6quvAgBeeeUVnDhxAj/88AN8fX1x+vRplJSUNHFLiYiIWg4G3kRERK2ITqeDSqWCq6srAgMDAQB//fUXevbsiT59+gAAwsPDm7CFRERELQ9LzYmIiFq5adOmYdOmTejRoweef/55/Pbbb03dJCIiohaFgTcREVErd/fdd+PcuXN45plncOnSJdx555149tlnm7pZRERELQYDbyIiolZGpVLBaDRabfPz88OkSZPw2WefYdmyZfjoo4+aqHVEREQtD8d4ExERtTLh4eHYv38/MjIy4O7ujvfeew+9e/dGt27dUFZWhm3btuGWW25p6mYSERG1GMx4ExERtTLPPvssFAoFunbtCj8/P6hUKsydOxfdu3fH7bffDoVCgU2bNjV1M4mIiFoMmSAIQlM3goiIiIiIiKilYsabiIiIiIiIyIEYeBMRERERERE5EANvIiIiIiIiIgdi4E1ERERERETkQAy8iYiIiIiIiByIgTcRERERERGRAzHwJiIiIiIiInIgBt5EREREREREDsTAm4iIiIiIiMiBGHgTERERERERORADbyIiIiIiIiIHYuBNRERERERE5ED/Dzbh1aYHlwCVAAAAAElFTkSuQmCC", + "image/png": 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", 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" ] @@ -164,7 +165,6 @@ ], "source": [ "#| echo: false\n", - "import matplotlib.pyplot as plt\n", "ax = df.tail(300).plot(x='ts', y='y', color = 'navy', title='Time Series', figsize=(12, 2))\n", "plt.axvspan('2020-02-01 21:00:00', '2020-02-01 21:02:00', color='orchid', alpha=0.3, label='Anomalous Period')\n", "plt.axvspan('2020-02-01 21:47:00', '2020-02-01 22:11:00', color='orchid', alpha=0.3)\n", @@ -177,15 +177,16 @@ "metadata": {}, "source": [ "## 2. Detect anomalies in real time\n", - "The `detect_anomaly_online` method detect anomalies in a time series leveraging TimeGPT's forecast power. It leverages the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score(its absolute value indicates abnoamlity of the step)\n", - "To make a detection, set the following parameters:\n", + "The `detect_anomalies_online` method detect anomalies in a time series leveraging TimeGPT's forecast power. It uses the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score (its absolute value indicates quantifies the abnormality of the value).\n", + "\n", + "To perfom real-time anomaly detection, set the following parameters:\n", "\n", "- `df`: A pandas DataFrame containing the time series data.\n", "- `time_col`: The column that identifies the datestamp.\n", "- `target_col`: The variable to forecast.\n", - "- `h`: Horizons is the number of steps ahead to make forecast.\n", + "- `h`: Horizon is the number of steps ahead to make forecast.\n", "- `freq`: The frequency of the time series in Pandas format.\n", - "- `level`: The confidence level for anomaly detection, default to 99%\n", + "- `level`: The confidence level for anomaly detection, default is 99%\n", "- `detection_size`: The number of steps to analyze for anomaly at the end of time series." ] }, @@ -286,7 +287,7 @@ " 0.044413\n", " 0.467860\n", " True\n", - " -127.848570\n", + " -127.848560\n", " 0.476396\n", " 0.459325\n", " \n", @@ -307,7 +308,7 @@ "96 -158.933850 0.579404 0.562333 \n", "97 -157.474880 0.568839 0.551767 \n", "98 -150.178240 0.530333 0.513261 \n", - "99 -127.848570 0.476396 0.459325 " + "99 -127.848560 0.476396 0.459325 " ] }, "execution_count": null, @@ -323,7 +324,8 @@ " freq='min', # Specify the frequency of the data\n", " h=10, # Specify the forecast horizon\n", " level=99, # Set the confidence level for anomaly detection\n", - " detection_size=100) # How many steps you want for analyzing anomalies\n", + " detection_size=100 # How many steps you want for analyzing anomalies\n", + ")\n", "anomaly_online.tail()" ] }, @@ -338,7 +340,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "From the plot, we observe that both anomalous periods were detected right as they arose. For further ideas on improving detection accuracy and customizing anomaly detection, please proceed to the next sections for exploration." + "From the plot, we observe that both anomalous periods were detected right as they arose. For further methods on improving detection accuracy and customizing anomaly detection, read our other tutorials on online anomaly detection." ] }, { @@ -348,7 +350,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -377,8 +379,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For an in-depth analysis of the `detect_anomaly_online` method, refer to the tutorial (coming soon)." + "For an in-depth analysis of the `detect_anomalies_online` method, refer to the tutorial (coming soon)." ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] } ], "metadata": { diff --git a/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb b/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb index 36df7977..dcbd2fea 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/02_adjusting_detection_process.ipynb @@ -42,42 +42,13 @@ " from dotenv import load_dotenv" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "def plot_anomaly(df, anomaly_df, time_col = 'ts', target_col = 'y'):\n", - " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left')\n", - " plt.figure(figsize=(12, 2))\n", - " plt.plot(merged_df[time_col], merged_df[target_col], label='y', color='navy', alpha=0.8)\n", - " plt.plot(merged_df[time_col], merged_df['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", - " plt.scatter(merged_df.loc[merged_df['anomaly'] == True, time_col], merged_df.loc[merged_df['anomaly'] == True, target_col], color='orchid', label='Anomalies Detected')\n", - " plt.legend()\n", - " plt.tight_layout()\n", - " plt.show()" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Adjusting the Anomaly Detection Process\n", "\n", - "This notebook explores methods to improve anomaly detection by refining the detection process. TimeGPT leverages its forecasting capabilities to identify anomalies based on forecast errors. By optimizing forecast parameters and accuracy, you can align anomaly detection with specific use cases and improve its effectiveness." + "This notebook explores methods to improve anomaly detection by refining the detection process. TimeGPT leverages its forecasting capabilities to identify anomalies based on forecast errors. By optimizing forecast parameters and accuracy, you can align anomaly detection with specific use cases and improve its accuracy." ] }, { @@ -112,7 +83,26 @@ "outputs": [], "source": [ "import pandas as pd\n", - "from nixtla import NixtlaClient" + "from nixtla import NixtlaClient\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Utility function to plot anomalies\n", + "def plot_anomaly(df, anomaly_df, time_col = 'ts', target_col = 'y'):\n", + " merged_df = pd.merge(df.tail(300), anomaly_df[[time_col, 'anomaly', 'TimeGPT']], on=time_col, how='left')\n", + " plt.figure(figsize=(12, 2))\n", + " plt.plot(merged_df[time_col], merged_df[target_col], label='y', color='navy', alpha=0.8)\n", + " plt.plot(merged_df[time_col], merged_df['TimeGPT'], label='TimeGPT', color='orchid', alpha=0.7)\n", + " plt.scatter(merged_df.loc[merged_df['anomaly'] == True, time_col], merged_df.loc[merged_df['anomaly'] == True, target_col], color='orchid', label='Anomalies Detected')\n", + " plt.legend()\n", + " plt.tight_layout()\n", + " plt.show()" ] }, { @@ -242,6 +232,13 @@ "df.head()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First, let's set a baseline by using only the default parameters of the method." + ] + }, { "cell_type": "code", "execution_count": null, @@ -251,13 +248,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO:nixtla.nixtla_client:Validating inputs...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" @@ -272,7 +263,7 @@ " h=14,\n", " level=80,\n", " detection_size=150\n", - " )" + ")" ] }, { @@ -282,7 +273,7 @@ "outputs": [ { "data": { - "image/png": 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Xrl188MEH7Ny5E7Va3c2/hSAIgiAIgiAc+yJBqdhYDWp1y4ddIiglCMKJ7pjPlBIapKens3z5ch599FEuuOACfD4fPXv2ZOLEiahUyhdhnz592LBhA8899xyPP/44+/btQ6fTMXjwYKZPn84999zTzb+FIAiCIAiCIBz7XK6D95MCEZQSBEGQ5M4eIddOTqcTq9WKw+HAYrE0+ZnX62Xv3r306tWL2NjYblqhIHQ98doXBEEQBEE4tmzYUMrtt39LVpaV2bN/0+I2eXm1XHPN51gsOn7++ZYuXqEgCJ1NDsvU53kIOYOoLRr0vQ1IqqOr4qqzHCy205jIlBIEQRAEQRAEQehgbrdSvnewTKm4OOVko9PpIxQKt1rmJwjCsce12Unl7HKCjmD0Oo1VQ9KVKZiGth6kOdGITz1BEARBEARBEIQOFukp1VqTcwCLRRftU+tw+LpkXYIgdD7XZielM4ubBKQAgo4gpTOLcW12dtPKjj4iKCUIgiAIgiAIgtDBGnpKtR6UUqtVmM1KJpXoKyUIxwc5LFM5u/yg21TOKUcOH1WdlLqNCEoJgiAIgiAIgiB0MLf70I3OQTQ7F4TjTX2eJ5ohVR8IMmtjLkUOV5NtgvYg9Xme7ljeUUcEpQRBEARBEARBEDpYQ0+p1jOlQASlBOF4E3I2lOzNy93HV9vz+WDT7oNudyITQSlBEARBEARBEIQO1tBTSmRKCcKJRG1pmCeXU+0AIK+m7qDbnchEUEoQBEEQBEEQBKGDRXpKGQwHz5SKTOATQSlBOD7oexvQWJWAU+7+oFS1x4vLF4huo7Fp0Pc2dMv6jjYiKCUIgiAIgiAIgtDBIj2lTKa2ZUrV1tZ3+poEQeh8kkoi6coUaup91Hgapmrm2xuypZKuSEFSSd2xvKNOu4NSS5cu5dJLLyU9PR1Jkvjqq6+a/FyWZZ566inS0tLQ6/Wcd9555ObmdtR6BUEQBEEQBEEQjnqip5QgnLhMQy3Ujo4BdUPgKb/WhcamIW1aBqahlm5c3dGl3UEpt9vNsGHDeP3111v8+d///ndeeeUV3nzzTX799VeMRiMXXnghXq/4kD3WZWdn89JLL0X/v6WgpHB4Fi9ejCRJ2O327l6KIAiCIAiC0AFETylBOLHl1bvRpeuISYlBm6Clpr+K7Cf7ioDUAdodlLrooot49tlnueKKK5r9TJZlXnrpJZ544gkuv/xyhg4dyqxZsygpKRHBi/1WrlyJWq3m4osv7u6lHLHS0lIuuuiiTrt/SZKiF6PRSL9+/Zg6dSrr1q1r930dGFDrCCKQJAiCIAiCILSmrT2lGoJSvoNuJwjCsWXbtgoAzjgrC5VBzd7qOlGy14IO7Sm1d+9eysrKOO+886LXWa1WRo8ezcqVK1u8jc/nw+l0Nrkcz2bMmMH999/P0qVLKSkp6e7lHJHU1FR0Ol2nPsbMmTMpLS1l27ZtvP7667hcLkaPHs2sWbM69XEFQRAEQRAE4UhEyvcO1VMqLk4PiEwpQTieyLLM9u1VAEyePBCAvLxaQqFwdy7rqNShQamysjIAUlJSmlyfkpIS/dmBnn/+eaxWa/SSmZnZkUtqlRyW8ex2U7fegWe3Gzksd/pjulwuPv30U+6++24uvvhi3n333SY/j2TeLFy4kJEjR2IwGBgzZgy7du1qst0bb7xBnz59iImJYcCAAbz//vtNfi5JEm+99RaXXHIJBoOBQYMGsXLlSnbv3s348eMxGo2MGTOGPXv2RG+zZ88eLr/8clJSUjCZTIwaNYqffvrpoL/PgeV7RUVFXHPNNdhsNuLj47n88svJz89v8vuddtppGI1GbDYbY8eOpaCg4KCPYbPZSE1NJTs7mwsuuIAvvviCG264gfvuu4/a2trodr/88gtnnnkmer2ezMxMHnjgAdxuNwDjx4+noKCAhx56KJp51ZbbgRI0ffTRR8nMzESn09G3b19mzJhBfn4+EyZMACAuLg5Jkpg6dSoA4XCY559/nl69eqHX6xk2bBhffPFFk9/r+++/p3///uj1eiZMmNDkeRIEQRAEQRCOfZFG523tKSUanQvC8aOoyEldnY+YGDVnndUTg0GL3x+ioMDR3Us76nT79L3HH38ch8MRvRQVFXX6Y7o2O8l/ejfFrxdS9n4Jxa8Xkv/0blybOzdL67PPPmPgwIEMGDCAG2+8kf/973/IcvNg2P/93//xz3/+k7Vr16LRaLj11lujP5szZw4PPvggv//979m6dSt33nkn06ZNY9GiRU3u45lnnuHmm29m48aNDBw4kOuvv54777yTxx9/nLVr1yLLMvfdd190e5fLxaRJk1i4cCEbNmxg4sSJXHrppRQWFrbpdwsEAlx44YWYzWaWLVvG8uXLMZlMTJw4Eb/fTzAYZPLkyZx99tls3ryZlStXcscddzQJELXVQw89RF1dHQsWLACUgNrEiROZMmUKmzdv5tNPP+WXX36J/n6zZ8+mR48ePP3005SWllJaWtqm2wHcfPPNfPzxx7zyyivs2LGDt956C5PJRGZmJl9++SUAu3btorS0lJdffhlQAq2zZs3izTffZNu2bTz00EPceOONLFmyBFCCd1deeSWXXnopGzdu5Le//S2PPfZYu58HQRAEQRAE4egky3K7e0p5vUG83mCnr00QhM63fXslAAMGJBITo6Zv33gAcnKqu3NZRyVNR95ZamoqAOXl5aSlpUWvLy8v55RTTmnxNjqdrtNLwBpzbXZSOrO42fVBR5DSmcWkTaPTGo/NmDGDG2+8EYCJEyficDhYsmQJ48ePb7LdX//6V84++2wAHnvsMS6++GK8Xi+xsbG8+OKLTJ06lXvuuQeAhx9+mFWrVvHiiy9GM3cApk2bxjXXXAPAo48+yhlnnMGTTz7JhRdeCMCDDz7ItGnTotsPGzaMYcOGRf//mWeeYc6cOXzzzTdNgjSt+fTTTwmHw/z3v/+NBppmzpyJzWZj8eLFjBw5EofDwSWXXEKfPn0AGDRoULuev4iBA5X0x0h20fPPP88NN9zA7373OwD69evHK6+8wtlnn80bb7xBfHw8arUas9kcfY225XaFhYV89tlnLFiwIFqS2rt37+jt4+OVD5bk5GRsNhugZFY999xz/PTTT5xxxhnR2/zyyy+89dZb0fvu06cP//znPwEYMGAAW7Zs4YUXXjis50MQhGOPHJapz/MQcgZRWzToextEjwFBEITjiNcbJLy/EuNQPaWMRi1qtYpQKIzD4SU21tQVSxQEoRNF+kmddFISAP37J7B5czk5OdVMnNi3O5d21OnQTKlevXqRmprKwoULo9c5nU5+/fXX6AF6d5LDMpWzyw+6TeWc8k4p5du1axerV6/muuuuA0Cj0fCb3/yGGTNmNNt26NCh0X9HgnsVFcqLeseOHYwdO7bJ9mPHjmXHjh2t3keknHLIkCFNrvN6vdEeXi6Xi+nTpzNo0CBsNhsmk4kdO3a0OVNq06ZN7N69G7PZjMlkwmQyER8fj9frZc+ePcTHxzN16lQuvPBCLr30Ul5++eVoxlJ7RbLLIsGvTZs28e6770Yf12QyceGFFxIOh9m7d+9B13yw223cuBG1Wh0NELbF7t278Xg8nH/++U3ud9asWdFyyR07djB69Ogmtzsa3h+CIHSN7srWFQRBELpOpJ+UJEno9QfPA5AkSUzgE4TjzLZtSqbU4MENQSmA3FyRKXWgdmdKuVwudu/eHf3/yMF7fHw8WVlZ/O53v+PZZ5+lX79+9OrViyeffJL09HQmT57ckes+LPV5HoKOg6fEBu1B6vM8GPoaO/SxZ8yYQTAYJD09PXqdLMvodDpee+01rFZr9HqttuFsSiTwEg63ryFaS/dxsPudPn06CxYs4MUXX6Rv377o9Xquuuoq/H5/mx7P5XJx6qmn8uGHHzb7WVKS8kacOXMmDzzwAPPmzePTTz/liSeeYMGCBZx++unt+t0iAbhevXpFH/vOO+/kgQceaLZtVlbWQdd8sNs1fp23lcvlAmDu3LlkZGQ0+VlXZgQKgnB06s5sXUEQhM4gMj9b1rifVFvaVcTFxVJd7RFBKUE4DgSDYXbuVJqcn3xyMgD9+kXK92q6bV1Hq3YHpdauXdukTOzhhx8G4JZbbuHdd9/lkUcewe12c8cdd2C32xk3bhzz5s0jNja241Z9mELOttVot3W7tgoGg8yaNYt//vOfXHDBBU1+NnnyZD7++GPuuuuuNt3XoEGDWL58Obfcckv0uuXLlzN48OAjWuPy5cuZOnUqV1xxBaAEV9rTfHvEiBF8+umnJCcnY7G0fkA1fPhwhg8fzuOPP84ZZ5zBRx991O6g1EsvvYTFYomW1I0YMYLt27fTt2/raZAxMTGEQqFmaz7Y7YYMGUI4HGbJkiVNJko2vk+gyf0OHjwYnU5HYWFhqxlWgwYN4ptvvmly3apVq1pduyAIx4cDs3XLXB7iYnXoNOrodZVzyjGebBYHdIIgHBNcm51Uzi5vctJXY9WQdGXKCR9gj2RKHaqfVERDs3MRlBKEY11eXi1+fwiTKYYePZTPwr5945EkiepqDzU19cTH67t5lUePdpfvjR8/HlmWm10ik+QkSeLpp5+mrKwMr9fLTz/9RP/+/Tt63YdFbWlbDK6t27XVd999R21tLbfddhsnn3xyk8uUKVNaLOFrzR/+8Afeffdd3njjDXJzc/nXv/7F7NmzmT59+hGtsV+/fsyePZuNGzeyadMmrr/++nZlZ91www0kJiZy+eWXs2zZMvbu3cvixYt54IEH2LdvH3v37uXxxx9n5cqVFBQUMH/+fHJzcw/ZV8put1NWVkZBQQELFizgqquu4qOPPuKNN96I9nF69NFHWbFiBffddx8bN24kNzeXr7/+ukkvrOzsbJYuXUpxcTFVVVVtul12dja33HILt956K1999VX0d/rss88A6NmzJ5Ik8d1331FZWYnL5cJsNjN9+nQeeugh3nvvPfbs2cP69et59dVXee+99wC46667yM3N5Q9/+AO7du3io48+ajaJURCE40/jbN0ih4t7vl3O33/Z1GSbSLbusaY7JtoKgtC9IpmfB1YhRDI/T/SS5LZO3osQ5XuCcPzYulVpvTN4cBKq/Sca9XotmZlKgEqU8DXV7dP3upK+twGN9eABJ41NSTvuSDNmzOC8885rUqIXMWXKFNauXcvmzZvbdF+TJ0/m5Zdf5sUXX+Skk07irbfeYubMmc2apbfXv/71L+Li4hgzZgyXXnopF154ISNGjGjz7Q0GA0uXLiUrK4srr7ySQYMGcdttt+H1erFYLBgMBnbu3MmUKVPo378/d9xxB/feey933nnnQe932rRppKWlMXDgQO6++25MJhOrV6/m+uuvj24zdOhQlixZQk5ODmeeeSbDhw/nqaeealIq+fTTT5Ofn0+fPn2i5YRtud0bb7zBVVddxT333MPAgQO5/fbbcbvdAGRkZPCXv/yFxx57jJSUlGgw65lnnuHJJ5/k+eefZ9CgQUycOJG5c+dGyw2zsrL48ssv+eqrrxg2bBhvvvkmzz33XJufa0EQjk2Ns3B3VNpBhpyq5mOBOzpbt7OJHlmCcOI5MPPT5Q8QCDU9mdlZfVqPFYebKSWCUoJw7DuwyXlEQwmfCEo1JsmRrtFHCafTidVqxeFwNCsD83q97N27l169eh12OWBr/Twi0qZlnPDpxsLRpyNe+4IgdC/PbjfFryvDI2as28XcXcq/Z00Zj0nXcCY9496sDu9r2FnEd6ognJgaf56V1Xl48PuVjO6RzMNjhzTZ7lj6POtoc+fm8Kc/Leb003vw2muTDrn9m2+u5b//Xc9VVw3mscfGdcEKBUHoLNdd9yW5udW8+OIFjB+fHb1+xoz1vPHGWiZN6sfTT09o/Q6OEweL7TR2QmVKgdJANm1aRrOMKY1NI3aeBUEQhE7TOFu3yOGKXl/qaijX64xs3c7SnRNtBUHoXo0zOrdX2gmEwqwoLKc+EGx1uxNNQ6aUKN8ThBNJfX2APXuUZubNM6WUCXwiU6qpjm2edIwwDbVgPNksJoUIgiAIXUZSSSRdmULpzGKKHO7o9WV19fRLUMq7k65IOWa+ixr3yArLMn9dsgG1pOLxs4ZFJ0111kRbQegqYrJcyxr3X61w1wPK58CW8hpO65Hc4nYnmoaeUm0r34uLizQ6r++0NQmC0Pl27aomHJZJSjKSlNR0/6d/fyUotXevHb8/REyMuqW7OOGcsN8UkkoSO8mCIAhClzINtWC82kftp/7odWUuDxqbhqQrjq1pVY0zIPY53WwoUc76ldR5yLAYW9xOEI4lYrJc6yKZn0FHkHJXQxBlfUl1NCh1LGV+dobDz5TyddqaBEHofK31kwJISTFiNuuoq/ORn2+PBqlOdCdc+Z4gCIIgdKdyfRBdug5tcgzaBC2ewTFkP9n3mDvIbZwBsaemoan5zkp7q9sJwrFCTJY7uEjmJzRkSgFsLKsm0q72WMr87AztzZQS5XvCsUhM320QeS42LNxH2Bdm0MDEZttIkiSanbdA7CkKgiAIQhfKy6sFQKNXEw7LlLnrj8kDt8aZEnk1ddHrd1U5OLdPBiAyJYRjU+N+aWFZZml+GScnx5FobBg0UjmnHOPJ5mPyvdtRlD6tUPHdsuh1Fa56yvExfFqfYy7Q3tGOpKeULMvRMmhBiGipnBjothJjkU3aoPFzsXFJMQGXn4RffbhOczZ7Lvr3T2D9+lIRlGrkmAxKHWUDAwWh04nXvCAcP/bsUYJSw4ensm5dKfv2HZsZF417ZOXVNvwOu6rs0X+f6JkSwrGpcb+0VUUVvLJyK8PTE3hy/IjoNqJfmkI3yIjbJqGNjaF3hpW8YgeFI9WceYIdkLbkcDOlQqEwbncAk6lttxNODC0FgFQGpegp7AlHr+uqoFBr03cj2aRp0zhhAlONnwun1x8tae4ZY2zxuYiU7OXmiqBUxDFVvqfVKmcaPB7PIbYUhONL5DUfeQ8IgnDsimRKnX12NgBVVR7q6wPduKLDZxpqIeWWdPKdDdMEixxuvHpZTLQVjlmN+6DtrnYAsK3CTjAcbnW7rnK0lcqUlbmQZRm9JYbJN56ESqdi1a/7unVNR4v2ZkrpdBr0emVb0excaKy1cuKwJ9wkIAVdU2LcOJtUlmVqPN5mJ9BPlOm7B04i3r2/nUGa2YApRnk/H/hcNJTv1YjEg/2OqUwptVqNzWajokJpHmYwGERqq3Bck2UZj8dDRUUFNpsNtVpMaBCEY10kKHXKKalYLDqcTh/FxXX07RvfzSs7PLVxMuEkDSZZS5wplrIaN85JJhGQEo5ZjfugFe6flOkPhthbWxedlHngdl3haCyVKSlRSnfT082MGZPJSy+tYt26Uny+IDrdMXWY0eEaglJtz3iy2WKprw9gt3vJzLQe+gbCce/AoEd9IEi1x4dKApVKQiVJqCUJc4yWGE3DcUJnlhg3zib9paCcf6/YwtQR/blsYM/oNidKNmnj5wIgd/+JjP6JDe/fA5+LPn3iUakkHA4vlZUekpOP7+eoLY65b4vU1FSAaGBKEE4ENpst+toXBKFrdeRIeLvdS02NcgY8O9tGjx4Wtm+vZN8+5zEblNq5swqAgUOTycqyMHduLlu2VjB2XFY3r0wQDk/jfmmFjoYswO0V9mhQqqv7pR2tpTLFxZGglIlevWykpJgoL3exbl0pY8Zkdvl6jiYN5Xttz3K32WIpLa0Tzc6FqMZBD5cvwIPfr6S2vvmExlitmn9fdAYpJj3QuUGhxlmiq/Ypx+QL9xQ3CUoduN3x6sDfMd+ufGf0jjO3ul1MjJrsbBt5ebXk5laLoBTHYFBKkiTS0tJITk4mEDg2yx0EoT20Wq3IkBKEbtLRmQmRLKn0dDMGg7ZJUOpYFQlKDRqUSN++8cydm8vmzeWHuJUgHL0i/dL2vF1AlbshOLCjspbLBykHXV3ZL+3ATInw/nIPVaNqge5qvB7JlMrIsCBJEmPHZjJ79g5WrCgSQanDypTSAWICn9CgcTDjo827qa33oVGp0KglwrJSVREIh/EGQqzeV8GljQJDnRUUapwlGskMKnK4Ka3zkGY2tLjd8erA37HYqWTX9rAYD7pdv37x5OXVkpNTzdix4iTeMftKUavV4kBdEARB6DSdkZmwZ08NAL17xwHQo4dy+2M5KLVjx/5MqYGJDB6cBMDWrRWEwzIq0eRcOEaZhlqoH2+A2RLKkR/sqLSjtqpJvjK1S7OSDiwPef3X7awqquDfk04n2dj5WREH07h8D+CMM3pEg1InusPNlAIRlBIaRIIZeTVOftyt7JM8OWE4Q1Iasqu/2pHPrA25bCmvaRKU6qygUCSbtLLM3SRwv7a4Mvr4J8r03caZtaFwmNI6pQ9weqOgVEvPRf/+Cfz44x5yc2u6dL1Hq2Oq0bkgCIIgdIUDMxNacjhNPCOZUn36NA1KFRU5DmOV3U+W5YbyvYGJ9O4dh9EYg8cTYPdusaMlHNvKNAF06TpOG5+JITUWr1VCujmpy8vkGmc7OL1+Fu8tpT4QZG1xVavbdZUDg1KjRmWgVqsoLHRQXHzsBtuPVCgUxutV/h7tyZSKi1OCjLW1IiglKPS9Dagsat5ZuxNZlhnbM6VJQAqI/v/WilpC+wcydGZQKJJNuru66Xt89b7K6L9PlOm7kecCoMLtJRSW0apVJBljo9u09Fz066dM4Fu7toSKCnfXLfgoJYJSgiAIgnCAxpkJYVlmzvZ8lhc2DVJFMhPaY8+eSFBK2YFsyJSqO9Ild4uSkjpcLj9arZpevWyoVBInn6xkS4kSPuFYF8lsPHl0KsNGp6HSqdi4qazL19E422F1cWV0WtOuKnur23WVA4NSJlMMw4YpB2grV564U/g8noYWIwaDyJQSDp+kklif6GFXlQOdRs3U4f2bbdMrzowpRos3EIpOf+vsoJBpqIXy/hKoJU5OUU60ba+0Ux974k3fNQ21kDYtg/Kw0usrzWxAJUlobJpWn4tTT00jK8tKTU0999wz94SfuCmCUoIgCIJwgMYZB59tyeP9jbm8tGILLl+g1e0ORZblaFAqUr6XmansqJSW1hEMhlu97dEqUrrXr188Wq1SUj9smDKUQQSlhGNd4yDy8OHK63rjxq4PSkXKQwBWFjW8r3ZW2qP/7o5Smfr6QHRwQyQoBUoJH3BCl/BF+klptWpiYtrebkQEpYQIOSzj2e2mZFklb366EW2ClutO60uCoSEDR2VQKRepITC0zenosqDQbrsTXbqOy+48mf6nJKFJ0lI0VnNCBaQiTEMt+M8xoU2Oof8ZyWTcm0X2k31bfS50Og2vvz6J5GQj+fl27rvvB+rqmjewP1GIoJQgCIIgHCCScbB6XwWfbc0DIBSWo1NmDtyuLWprvTgcXiRJIjvbBkBiogGdTkM4LFNaeuxlSzUu3YsYOlTJkti0SQSlhGNbQ1AqjlNOUYJSGzZ0fVAqUh7i8gXYVNpQFlvp9lLtUYIX3VEqU1qqTJkymWKwWHTR6yNNe9esKcHvD3Xpmo4Wh9NPCkRQSlC4NjvJf3o3xa8X8sr//UJFrpNkdEz74ygy7s0i9aZ0Mu7Novcz/en9TH8y7s1i3FV90CbHkJ8e6pKgUDgss327sg8w4rxMzr28LyqdimW/FHb6Yx+tCgodqHQq+p2WgqGv8ZCfyWlpZt588xLi4/Xs2lXFgw/Oo77+xBzkJoJSgiAIgrBf5Mxk0B6gNOjlpZVbAaK9AZblNxyQtjczIVIKlJFhJjZWCWZJkkRGhpJhcCw2O28pKHXyyclIkkRxsTOaRSEIxxq73Ut1tVKe26tXHEOHpqBSSZSU1HVL/w/TUAu7B4UJqyDTaiJ7/7jx3V5Xt5XKHFi6F9GvXzwJCQbq6wNs6oZyRwA5JBNyd984+sOZvAciKCU0DFkJOoLk19bxfY5SBvvbof2p/qicsCeEeYQ1GvSQVBKGvkbO+o0SFNq0qaxLgsFFRQ7q6nzExKjp0yees89WGpyvWFF0wgajCwrsANETj22RlWXltdcmYTbr2Ly5nN//fv4J+fyJoJQgCIIg0PTMZP67RTz/43q8gRCDk+P404QRAGypqKGmXkmvbm9mQqTJeaR0LyJSwnesBaUObHIeYTLFRBu5ixI+4VgVeb+mp5sxGLQYjTHRxrTdUcIHsCKvDF26jkk3D2TUBZlok2MoH6rutlKZSFAqI8NMyBNCDiq9riRJipbwdVdfKfvSGso/LsVX2j3BnZYypbwF9QRq/Ae9nQhKndgaD1mRZZl31inNzU/PTGZYmvL509qQlexsG4mJBvz+UJd8927bpjQ1HzQoEY1GxaBBSSQkGPB4AqxfX9rpj380KihQhtb07Glt1+3690/glVcmotdrWb26mMcf/+mYbOlwJERQShAEQTjhNT4zKcsyr67axj6Hm3iDjunjhpBuMTIg0QoyrKqqPKzMhMalQI01TOA7toJS5eVu7HYvarWKvn2bTgKKlPCJoJRwrIpkNjZ+v3ZnXym328+qVco4+EnXD+K0SdmodCo2b644xC07T2S6Xt9EK+WflFDzc8M0wDFjMgFYvrzr+0oFHQHq93hABs+O7plq1ZAppQSl/BU+auZXUf19ZTR415JIUMrp9BEKnVgHpULTISu7qhzsqLATo1YxbURDc/PWhqxIksSoUekArFlT3Olr3bpV+ew56aRkAFQqibPOUkp3ly4t6PTHP9q43X6qqpS/S8+etnbffsiQFP71rwuIiVGzZEkB69aVdPAKj24iKCUIgiAc1yIleXXrHXh2u5udYWx8ZhJg9vZ8VhVVoFGpeGTcMGyxOlRGFRffMAhtcgwbjO7DykyIZF5EJu9FNEzgO7aCUpEsqT594po18m3oK9U9GSWCcKQOnJQJRPtKdUdQatmyQgKBENnZNnr1skXfYzt3VuHzdU+ZWiRTaoDWBCHwFXgJOpRgzOmn90CtVrFnTw3bt1ce7G46nHuHC/Z/zNcX1BP2d31wpyFTSinfq9+rlDKH68N49rQeKLNaG3pzORyd2/Q45A7i3u46aJBM6FqNh6cUO5XXyaDkOJKM+la3a2zUqAxA6efW2SKZUiefnBy97qyzlBK+JUsKolNCTxSRLKn4eD0mU/vKdiNGjcrghRfO4+mnJzB6dI+OXN5RTwSlBEEQhONW45K8svdLlNK8p3fj2twQAGp8ZnJ3jZMPN+8G4LcjB9A/UUnBDrvDnH9BbzR6NVu3VbQ7gCTL8kHK95THOFaDUo1L9yIiB8w7dlSdkL0RjiWVle4T7uChLVrKlIoEpXJza3C5Dl6G1dEWLlQGLpx7bi8kSSItzURiooFQKNzlQZ+IkhIXJo2GhGBDiZpnl3IgbbHouOiivgDMnLmhy9YU9oeja5C0EgRlvPld39uucaaULDddg3urq9X3nFqtijaN7+wSPvuyWhzLa3GutXfq4wht13h4SqVb+fsnG2MPul1jI0cqmVLbtlXi8XRew2y/P0ROTjXQNCh12mkZxMZqKC93kZtb09rNj0uH00+qJWee2ZNJk/od+YKOMSIoJQiCIByXGpfkNRZ0BCmdWRwNTDU+47i6qAJkGNUjiQv6Nj1LZVVpozt88+fvaddaqqvrcTp9qFRSsx2WSKZUcXEd4Rb6RBytDhaUysy0YLPF4veH2LWrqtnPu8L27ZXcddd3ooTwIObP38NFF33I3/++vLuXclSRZbnFTKnERAM9eliQZblLX1ceTyBaBnfuub0BpVSnu8tkS0rqOCUujlidBkmnHFJ4cj3RbNRbbhmGJEksWpQfDcp3Nk+OG9kvo7ZqMA2z7F9T15fwNc6UCtqDyveMWgmUBWsC+Etaz4Lqir5SIVcQ3z7l/t3bXQTruq8pvNBA39uAxqoEnMrdSiAz5YAsqYMNWUlPN5ORYSEUCrNhQ+f1dcrNrSYQCGGzxZKWZoper9NpOP10Zd9pyZL8Tnv8g5HDMrVLaqj6rgJ/ZdedPDhUPylx8ufgRFBKEARBOO4cWJJn9/rYXtH0oCjSLLTxGcftlXYATk1vHmhRWzRMnKic+Z83b3e71hM5IOvRw9Ks1C011YRKJeHzBaP9CI4FO3a0HpTq7gNmny/IH/+4kLVrS3j77XVd/vjHgmAwzGuvrQbg88+3d0kPkmPFwYLI3dFXavnyQvz+ED16WOjXryFINmxYpEy2699jdXU+PC4/w+LjiY1VYxsbh0qvIuwJ4StSgh29esUxYUI2AO++u7HT1yTLMu7tLmV9CTB3Yz5hWcZf6iPk6tqgS+NMKW+BElzQpcdi6G8EwLW1rtXbxscrQYjOzJ717PZESxwJQd1aR6c9ltB2kkoi6UrlfV2xPyiVbGoalDrUkJWGvlKdV8IXKd076aQkJKnpWiIlfEuXFnba4x+Ma1Md9Tlu/KU+qr4px7nOgRzq/IBQJFOqpX5Snhw3ZR+UULuomlC9yB5viQhKCYIgCMedxiV5YVnm6UUbeOKntWxrFJiKNAuNnJn0h0LkVis75oOTmpbYRc5MTpiQjVarJi+vlt27256aHtn2wCbnABqNirQ0ZaT6sVLCV1Xlobrag0ol0b9/QovbRA6YuyMo9d//ro8+l6tXF1Nb2/XlOy0JB8KEfUdH8+Lvv8+N9gQCePbZZXi9IlsCGkr3MjOtzYLI3dFXauHCvUBD6V7EsGHKWjZtKu/ys/AlJXUMtFiwxsagtWiJ7aVH31cJuETK5wCmTTsFUAL5kcboncVX5CXkCCJrJR55ZQkvvr6KbSU1SsPzPV0b8G+cKRUJSsX21GM8Sckq8RV6CdpbLq+KBBUWLdrbKWuTZRlPjvI3iqynfrenS7NKhNaZhlpIm5ZBpW//pN/95Xsam6ZNQ1a6Iih1YJPzxsaNy0KSJHbsqKSiomuzFP3lPurWK/tx2uQYCINrvZPKr8sJVHfu67ulTClZlqnb4MS+pAbZG6Z+t4eKL8qUjE6ROdWECEoJgiAIx53GJXnriqvIr1UOvtfsq2y2XeTMZF5NHYFQGEtsDBmWpqnxkTOTZrOOMWOU1PRvP9jeavP0A7XWTyoiM7P7m53X1NTz889727SjFCndy862ERvbcm+Lhkypii7d+dq9u4ZZszYDSl+bcFjm55875+CurWRZpn6Ph/JPSin7qATnOgfhQPcFp4LBMP/973oA7rjjVJKTjRQXO0VW2X6tTcoEGD48DVAOyrqiX5rXG2xWuhcxYEACMTFqHA5vl0/vLN7nZHh8PLpYDcaBJiSVhGGAEpTyFtUT8ijPzaBBSZxxRg/CYZlZszZ16prc+7OPdrgcFO4PgH2+cjceT4D63Z4u/RyKZEpZdFoCFX6QlKCUxqpFl6UEGVzbXC3e9vzz+wCwcuU+6uo6vtl5oNJPyBFE0kiYR1rR91O+75yr7eJA+SihG2TEbVMCK0Nu7U3GvVlkP9m3TUNWIm0GcnKqcTg6pwQ0EpRq3E8qIj5ez5AhyvVdOYUv7AtTu6gawqDvayDxsmTizk1AilURrA5Q+VU5desdh9xfO6zHDsuNglI2QMnYdyyvjWYhGgYZ0SZokb1h7EtqqP6hMjoYQhBBKUEQBOE4FCnJk2WZ2dsbAhIby6pb3M401ELpIAnUEoOSbNFshJbOTJ7dPx1fiY/v3t9B6aziFpunH6i1yXsR7ZnAJ8syK1YU8c9/rmiS6XIkZFnm97+fzyOPLIhmZRzMjh1KcK+l0r2IwYOTUKtVVFa6O2ydhxIOy/z1r8sIhcKMH5/N1KmnAO3vAdaRQu4QtQuqqf25GtkbhqCMa72Tis/LlIBmNxwEzp2bQ0lJHfHxem6+eRiPPz4OgA8+2Bz9257IWmpyHpGZaSE+Xo/fH4oGZzvTypVF1NcHSEszM2hQ0/ebVqtm8OAkoOsnXdbmu0jV69HFqjEMVIJR2jhtNDuhcR+nadOGA/DNNzmdVqIcqA3gK/YRCof5z1wlKB0fr2dHrZ2cPdUEavwEq7vuADCSKRVpAq9NikFtULLuTEOUzNj6HHeLmZO9e8fRu3ccwWCYxYvzO3xtkSyp2F56VDEqzKdaQQ3+El+0z5TQvcrL3YTDMrFmLVnjkzH0NR60ZK+xhAQDvXvHIcsy69Z1fF8pp9NHYaESaDnppKQWtzn7bKWEb/bsHZ3acD1ClmXsv9QSqguhNquxjo1DkiT0vQ0kX5VKbLYewlC3zknNgqoOPylUUeHG5wui0ajIyDATDoSp+akKzw43SGAdY8M2Lp7Ey1Mwn2YFjYS/2EfF7HLqNjq7pLzwaCeCUoIgCMJxJ1KSt73Szq4qBxqVCiQotLuorVfOPB/YLHRHlR1duo4x1/Uh9ab0Fs9MujY76b1VIlalosJVz64qZcfswObpjTVtmtxyplRbg1JbtpRz553f8cADP/Dxx1u5445vOyTgs2ZNCVu2KGV2q1cfurfQwZqcR+h0mmgJ30cfbWn3msL+MK7NTrxFbS+9+/LL7WzZUo7BoOWRR8Zy7jm9AFi/vqzL+3VFSmQqvixTynfUYD7VQty5CajNasLuEPZFNVR9U4G/vHNHvzcWDIaZMUOZhjZ16inExmo488yeXHBBH8JhmWeeWUow2H1ZXHJQ7vYSx5aanEdIkhQt4evMRsIRrZXuRUQyEru6r5SqQDnQrI+TUOsbShwj2VKeXQ0B1+HDUxk2LIVAIMSHH27ulPW4t+3PkqpxUFhZR2amlf/+9zJkjcTawkoqKz1dWsIXyZSy1iuHWrE9G/oCxaTp0MRrkYMynl0tZ0tdcIGSLbVgQV6HrksOytTnKZ+pcoaWRYv2ojKqMZ6kBMqcqzsnk0Ron8j3enq6ucX3/aE0lPB1fK/AyLTPHj0sWK3NJwMCTJzYF6Mxhpycau677/tOn1bqyXHjzfOACuLOSUAV0xDiUOvVxJ2XgG18PGgkfIVeqr+t6NA+c5F+Uj16WCAgU/19Jb4CL2gk4s5LiL6/JLWEeZiF5CtTiMnQQVCmbo2Dyq/LT/jyWRGUEgRBEI47kZK8SJbUOb3T6R2n7BRsKlOyIBo3Cw2H5ehB3ekXZWMeYW12ZjLSPF2nUXNahnJ28JeCptkJkebpTa6r9OB2+1GrVWRltTyV5VDle3l5tUyfPp9p075m/fpSYmLUJCcbKStzcddd31FW1vKBTVvNmLE++u+2HNzu3KlknB2YuXGg228fAcCXX+5ocz8ZOSzj3uGi4rNSnL86qPmxivq9hz6YrKhw8+qrSuPu3996Gqq1bqQfHDw46iR6m0ws/OnID+5kWW7TGc2gI0DNj1VKHwlfGG1iDEmTUzCPsO4/c5uGeaQVSSsRqPBT9U0F5Z+V4lxtx1/h69TsqcZZUldeOSh6/fTpY7BYdOTkVPPBB50TODiUcDBM5TfllH9cgr+qe3bQZVlulNnYchC5q/pKBQKhaPnLOfsDrAfqjt5tIXcIw/63s9Sr6UGpvrcBSSsRcgTxlyt/Q0mSuPVWJVvqiy924HR2bBA27A3hyfUQCIaYuWg7AHffPZKsLCu33jqcbQ4HeXm11O2s67KAi9sdIEalQu9RvkNisxuCUpIkYTxZ6eXk3uZqcU3nn6+Uav76a3GHlmB5C+qRfWHUJjXP/mclf/jDAj76aAvmUyxIOhXBmgD1ud03cCNYFxSNoIHS0oag1OEYNSoD6Jy+Utu2tV66F5GSYuKNNy7GbNaxeXM599wzt8Pf9xFBewDnCjuAkvVn0/DKK7/y3HPLCASU15IkSRj6GUm8OAmVXkWgOkDl1xUEOuh7pnE/qbrVDgIVfqRYFYmTktBnN5+UqLFqSbgoCdv4+Gh5YdXX5ThW1XZraX93EkEpQRAE4bhUEhtgq9+JSiMxeVBPhqYqDbm32GubleTt3VuL0+lDr9cyYEDLjbsbN08f11M5KF1eWE4o3LADEWme3likFCgry4pW27RpckQkU6qlvjD//e96rr32CxYvzkelkrjssgHMmfMb3ntvMpmZVkpK6rjrru8Ou6Ho5s3lrFtXilqt7BLk5dUetI9JbW095eVKEGzAgIMHpUaNymD06AyCwTBvvXXofkXefV4q55Tj+KWWcH1YGTMvQ+2iGnwlBz8we/HFFdhkDfeOHMTIgBl/sfI7DEyxcUVmJiyrU5qLtjNNPlgXxLPLTe3iaso/LqX0f/uomV+Fr6x58CjsD+NcbafiyzJlApkazKOsJF6ejDY+JrqdpJEwD7eQfHUa+v5GUEPIEcS1qY6qryso/6gU+/LaDs8YOjBLKgaJuo1Ogo4A8fF6fv/7MwB4++110fKMruRYYSdvQxU7t1VSNb+yWzKmyspceDwBNBoVmZlWQp4QjhW1TV5/kaDU2rWlnZqBt2VLBR5PgLg4fZMDQDkkR8/yRzKl8vJqO+2g70DunS783iAlHg+JfZoeNKtiVMT2Ug7CGjc8HzMmk/79E6ivD/DJJ1s7dj273BCU2VViJ7fGyYABiZx3nhLUufnmYQRtKpz1fvburMVX0kXPkdtPL5MJtUpCbdWgtWmb/NzQx4gqVkXIFcKb3zwbtGdPG/37JxAKhVm0KL/D1hUpq6yzyixdpgQ8P/lkK7IGzKfsz5Za5yDcDdmSwboglV+WUf5JaZPyz+4kh2R8pV7kYNcPEoDDD0qdemoaKpVEfr6dysqOfS4bT947mMGDk3jrrUuwWmPZvr2Su+76Dru9Y8tD5ZCslMYHZWIydAR7arnnnrnMmrWJ2bN3MHPmxibbxyTrSLw8BU2chrAnRNV3FXgLj3wQSn6+HYCeWTbq9w82iD8ngZgUXau3iQTKkq9KRd/XADK4t7io/LKsXRnixwsRlBIEQRCOS+++uxGVXs2kmwdx6mMDOWfaALTJMeTo6jEOabqjt2GDkvEwZEhyNDhzoMbN009JS8Cs0+Lw+vkhd1+r20HDmcrevW2trjUjQwlK1dX5mhxYrlhRxJtvriUcljnnnF58+ulVPPXU2aSkmEhKMvLWW5eQkWFh3z4nd9313WEdIP/vf0qQ4uKL+9GjhwVZlqNNTFsS2SHNyrJiMGhb3S7i/vtHA/DDD7vJza1ucZtQfYjqHyup+aGSYE0AKVaF5QwbqdenKxkGIZmaBVWtntX8ZW4ecbtD3NC7N+MGpkebLidOTiFtXCL+cBi5LkT5/P0ZSescrWYkySEZb1E99uW1lH9aSsUnpdiX1lCf6yHsVs66egvqqf62gqpvKqjP9yCH95fqfV6Ga1MdhEDXI5akK1OVDIRWeoGojWrizo4n9cYM4s5JQN9HyTIJe0J4truw/1Lb4u0OV+MsqSsuH0jNT9XUrXFQNbeSkDvEpEn9OP30Hvj9If7+9+Ud+tiH4slzs/X7IvIL7OSXOMnfVoP9l5ou77kVKd3LzrahCkPNvErc21zUzK+KTksbODCRwYOTqK8P8O9/r+y0tURKb0aNSke1/zUUcgep2H/gXr/HQ1ycPpqBebD3bUeRQzKeHS68viDra2paPGg27u8x5c3zEPYrwQ1JkqKT+D75ZGuHZf+Eg2Hc25X1fLZmNwD33Tcq+nzFxKiZ/sgYdjqdlJTUUbSya3qmud0B+pnNqNUq9I2ypCIkjYRhsJIt5dpa1+LrPJIttWBBx/TEC7mD0Z5RX6xquM+yMhdLlhRgHGyOlhY7f+36Mj7PDhdyQIagjH3x/vd/FweDGpNlmZrF1RR/WUr550qgrKuekyMNSpnNumh5/apV+w6xdds13j9oafLegfr3T+Dtty8hPl5PTk41d975HTU1HRdw8e3zEqhW9hlcfTRMm/Y1GzeWRaemzpixgZycpvsdGrOGxEuV8jk5IFMzvwp3K2W0bRUp3+ufYkX2KifUYtJaD0g1ptariZuQQPzERNRmNaG6EDXzqvCeYP3dRFBKEARBOO7s2+fkp/3lWtOmDcfQ18jYa/uit8RQVe2JludERHrDRDIgWhJpig6gUam4fmhfAD7ctJtKd32L2+XkVPPhh0o/pQsv7NvqfcfGakhKMkbXDmC3e/nLX5YA8JvfnMTf/34+vXo1LSdKTjby5psXk5ZmprDQwV13tW+HLyenml9+KUSlkpg69ZQ29af59VdlB/fUU9Pa9BgDByZywQV9kGWZ115b3eznofoQ1XMr8BV6QQXGISZSrknDdLIZSSMRNyGBmDQdsl+mel7TaTX+Sj/VP1bi/KGaXiYTGT3MJI2II/maNGxnxROTFEOP81JYpXewtKKCsloPYVcI13qnkpH0YQm1i6upz/PgyXVT81MVZe8XUzOvCs92lxJgVIE2JQbTKRYSJiWRNCVFaeysVkrvahdUUzarGPuSGsKeEGqLhvgLE4mfmNgsO6I1qhgV+j4G4s5JIPWmDOLOVbL1vHs9rY6Nb68Ds6T8m1z4S5UAaNgdouanKgjBY4+NQ5IkVq3a12UN6oN1Adb8bw/FJXWsrqpidmEhhfsc1G5zKo1iu1Aks7Fv7zhqF1YT2N8cWw7sPyMfklGpJP74xzNRqSR+/HFP9D3RVn5/iB9+yD1kZlOkv9tppymlOCFXkKrvKgk5gkoG4ZIa/OW+6Pu2s8sJQckY9ToDOH0BcuvqSE01NdtGmxyD2qrZ37+oIVB+7rm9yc624XT6uPvuuR2SNeHaUEfYFSK3qJYt1bWcemoap5/eo8k2Z5yRiXmgCVmW2bmklFAnT02UZZl6t5/eZjMatdSkn1RjxoEmUEOg3I9jeW2zwFRkCt+aNSXU1h75gbwn1wMyBC0q5vyYAygZbKAECiWNhOU0m7LtdpfSENrfNRlTclDGvcuNPxAinKwBCTw73FR9U07Q2XG9f9qjfo+HnMVlrF5dzO4tVdgX11A5pxxvUX2nB8sjn71pac3fX2115plZAMycuTFaxnakyspc1NTUo1arWs0qP1CfPvG8/falJCYa2LOnhquu+oxHH13A559vIz//yCY+Rkr7KzQBpt31Lfv2OUlPN/PBB1cyYUI2oVCYP/95cbM+iSqdioQLk5QeeDI4ltUeUXZepHyvR4zyXtdl6NrcmD4iNlNP0pRUjEPMxKTp0GW0Lah1vBBBKUEQBOG4M2vWJsJhOVoyAsoZ8xEjlKDTr782NP+UZTmaKTV8eOtBqUjz9Ijz+2YwINGKLxjinbU7kWW5SfP0YFDZGQqFwpxzTi8mTMg+6Jp79FDOiO7b50SWZZ57bhnV1R569YrjgQdGt3q7tDQzb711CSkpJvLz7UyfPp9QqG0HEpEsqfPO601WljUalDtYf5qVK5UD8DPOyGzTY4DS30WtVrF8eRHr1zc0h44EpIK1QVRGNUlXpmI9PQ6VrmH3RNJIxJ+fiCZBS7g+TPW8KnzFXmrmV1H1VTme/Hrq6vxss9vJviUL21nxaMyaJo8//vzerK6q4q3cHGzj44ntpUeKkQjXh6nP9VC7sBr74hq8e+uRAzIqgxrDICPxFyaSelMGSZelYBllRZcRizY+BtuZ8aRcm4Zpfx8WOSAjaSUso63KpJ8s/WE1pwWlEaq+twFdz1iQoW5TxwSGGmdJTRraE/f+cfSW021IOhWBCj/25bVkZJgZOVIJOM6bt7tDHvtg5LDM4pd3UFropKy+nnG3DaDX8EQWlZaxJ68Wx8raLm0AG8mUOtOahG+fF0krEX9BIlKs0ofEucYOKMHW3/zmJAD+9rfl+NsR6PjrX5fy5JOLePnlVa1u4/EE2LpVyeo57bQMgq6gktHmDKI2q9FlxkJIpnp+FSMGdk1fKTksU7fBidcbZENNDQlJhmhGQmOSJEWzpTw7Gxqeq1QS//jH+SQkGMjJqeauu747omBL0B7AtcWJ2xPgvbU5hGSZ++8f3eJ777bfj8QVDuJ2+vlp5s7Dfsy2CATCpOn0xKhUaE0aZSJhC9RGZUpYJABjX1zTpLy4Rw8LgwYlEQ7LR1zCJ8sy9fsPupfmlRIKhRkxIo0nnjgLlUpi/fpScnKq0fc2YJsQD2qlIXTVNxVdEhSqz/PgqwuwaFUBVz77HW9v3EVZrRtvpZ/Kr8qVYRFdKOQKUr2kmn37nKyqquKjdbkUljkJ1gSomVdF9Q+VBGo7b6pcaany+RzJoj4c118/hPh4PYWFDj7/fHuHrCuSKd2/fwI6neYQWzfIzrbxzjuXkpFhwen0sXDhXl54YTlXXfUZF130IQ8//CN//ONCnnpqEc8+u5QXXviFN95Yc9BWAnJIxlugtBP481vLqavzMWRICu++O5neveN47LFx0T6J7723sdntJbWE9cw4JWNRBvuSmmbtF9rC6w1G+3rafMpzEpvVciD6UFRaFdbTbSRMSjrsfYhjlQhKCYIgCMeVqioP336rnAWeOvWUJj8bPVo5g944nb201EVFhRu1WsWQISmt3m+keXqESpK4e/Rg1CqJtcVVrCiqaNI8/X//U9LGrdbYaPbJwTT0lXLw3Xc5/PzzXjQaFc88M6HFnb/GZxfT0828+ebFGI0xbN5c3qyPQksKCuzRyV6RsppIxsXWrRUtBrbKylzk59tRqaTodJ+2yMy0MnnyAABefXU1siw3C0glXpyENq7lzKLIWU21WU3IGaT6+0rlIEWCWn2Q/+bmsi7oIKNfy43kzzuvNyqVxNbtldQaQsSfl0jqjRkkXJyEcagZTbwWbaIW0wgLiZNTSLk+Ddu4eGKz9E2m+DSmNqixjLKScl0aceclkHxNGqahFiR123YkZVlm/fpSnnpqEXfc8W2znmDmU5TXQ/1uN8G6Iz8ojASYfnvVUDyrlWw886kWTEPMxJ+bACplRL17q4uLLuoHKCWXnZ0R8P2rW6nKcRIIh8m4OJUrpwxi+vQxbK5zsKaggupKD7U/V3dZf6k9e2o5MzmZdFmnTHI6N4HYnnrizlYm8bm3uKIHyHfdNZKkJCNFRQ5mztzQpvtfvryQuXNzAfj55/xWJx2uX68EDtLTzSSb9VR/V6EEpCwaEi5JJu7cBLRJMcjeMINcemLV6lbftx2lfo+HkCNIfTDE+poaMjJaLy3S99ufTVjpx7GsIQuoV6843n77EhITDezeXXPY5TyyLONYUQshWFdQQY7DyYQJ2a02X05NNZM+WjlBYV9hZ+0HezqtFMvl8tPPorx/jb2NB/3sNw4wETdh//tvtxIgb1yyFinhmz//yEr4ApV+gvYgQWRmzlN6et1yyzCSk43R/luffqpcb+hrJPGSJFQGNcHaAJVfl+MrbZrVJssyL764gj/9adERv+ZkWca9rY6KCjdrKqoJyzLfrcrj97NX8PWS3ezaWknhnJLDChgc7nrsS2soLnBS7HKzwVXL6upqpn+3igK1MknVX+yj6uvOCZb5/SEqK5XftaVMqZA72CRjuDVGYwz33DMKUPoEdkS2XaTJ+aH6SbUkM9PKl19ew4wZl3H33SMZOTKdmBg1VVUeli4tYP78PXz/fS5ffbWTzz/fzowZGw7ai9JX7KWuxsf67eUUudxccEEf3nzzYuLjlYBQQoKBP/xhDADvvLM+mgXbmCRJWMfYlN6OMtQuqm53j6lI/8XUOAMqVxgkpXz/SLQ3y+p4IIJSgiAIwnHl44+3EAiEGDo0pVnm0+jRShnM+vWl0cyGSMnLoEGJxMYe/MyfaaiFtGkZ0YypLKuJKYN7gVri/ZK9hLOVdOucnOpoqdTjD49BtcOLc40DT64bf6W/xZKISFBqzZoS/vGPFYBy0BvpCxERDoSxL62hdOY+yj8tpfbnalxb6kiJieWxR5QdsLffXtdifxk5JBOo8ePJdbPgne0MMJu54sy+ZCeYCXlC9Mq2YTTG4PEE2L27+Q7cypVFgDJ1x2xWfldZlvFX+qlb78C5zoG3qL7FAMLtt59KbKyGLVvKWfZTfrOAlMZ68FI3tVFNwkXK5Bwk0Pc1kHxVKqu8tdT6/YwYkdbqwV98vD5abhgZsS6pJXTpsVhH20iekkrSFalYTrUSkxTTrjOUKq0KfS8DakPLTewPZLd7+eCDzVx11efccce3fP99LuvXl/Lqq7822S4mWaeMjA6Da/ORZUsFg2G2bKnAoFYzQrZASCa2px7TcOU1p8uIxTLaBoDzVztnDlAOFvburW3Wj6Mjff3uNpzrlB16w2lWrp46BFD6ld144xC+Ly5mU24lfnsA+7LO7y8VDsuYa2RGJyZiMMYogclM5QAnNkuPcYhygFi7tIaQK4jRGMP06Upz+Hff3RTtK9Ial8vPX/+6LPr/dXU+1q5teTpWpHTvzJE9lIBUnVIamnhxEhqTBpVWRfwFiahNagyyimv6ZBPwhcjNbf6+7QhyWKZuvRLMLNJ68YfDpKW1HpRS65V+aUhKw/PG5Wk9e9p4++1LSU42kpdXyx13fNvufnjevfX4in34QyFmrFIyn+6+e9RBbzPxnpPwZ2iQZZm9C8vY+V4+IXfbM9xqa+tb7YvXmNvtp+9B+kkdSN/HQPz5iaCRlH51P1ZGJ3BFAkbr15dSXX34QRlPjhL03ml34HD76d07Llq6d+21JwNKEDpSUhmTrCNpcnI08Fn9fWWT8qYNG8r45JOtzJ2rBBGORKDSj7/KT2m5iy21tfz2tyO4445TMSfrmZWzmwU797FxQxlF35YecuBFR3Bvc+Ep8lK4z8Hc4mIefWwc11xzEt5QiIffWUb5ABUx6fv7ES2oom6js0M/m8rKXMiyTGysBputaXAj5A5R8WU5FZ+VUTm7DNeWuoO+hi+7bAD9+yfgcvl58821R7SuQCAUPZE1ZMih+0m1RKNRMWxYKrfdNoI337yExYun8uYbF/PHR8cxffoYHnxwNPfcM4qrrhoMwDff7MLlajlTtn5vPfuKneQ4nZxzTi+effacZifwJk7sy1ln9SQYDPOXvyxpMYAqSRK2M+PQ9zFAGGp+UrKx2yryuX9aL+WknjYpBrW+bfsDQgMRlBIEQRA6lCzLFBTY21XO0hH27XPypz8t4v33lXH2U6ee0iy40LdvPPHxerzeIFu2KKUukaDUwfpJNWYaaiH7qb5k3JtF6k3p3P/qWfQ/PRlHIMBrr61uVrZ3qikOz3YXro1O7ItrqPqqnLL3iin7uIS6DQ07s5mZSpbP2rUleDwBhg9P5eabhzV57ECNn6qvy5WpViGlqXr9Hg/OVXaqvqlgaKmep8efyg3ZvVjy4jYqfqrEucaOfWkNlXPKKH1vH5VfllP2YwXmIplLevRgSmYWlV+WU/5hCRUflDBlWC/UktRiX6lIhtmY0T3wFtRjX1pD+UelVH1VTt06J671TmrmKX2ZKr4sw768FvcOF+4dLvSVYe6//BROiYuj8LNiArWBNgekIjRWLclXp5FybRpxExLQ2LTRcsARIw7e4yrSn+VIMw7awu8P8cc/LuSmm+Y0udx442wuuuhDXnppFQUFdvR6LRdcoKxr3rw9zQJAkWwpzy53uw6eD7RrVxV+b5Br+majV6nR2DTKKOpG7w/jSaZofw3vr04mntkLgO+/zz3sxz2YhT/uofzHCiTAPMDElAeavtZvvXU41kQ9n+TspWifA+/eemp+rOrUUqLCdVWMT0pBrZJIHBOvPB+NWEbZ0CZqkb1hahfXIO8fQDB2bCaBQIi//e2Xgx6cvvzyKioq3PToYWHSJCUb7eef97a47Zo1JehUKs41JhNyhVBbNSRekoTa1HDQpTaoiZ+YhCpGxcBkGxPT01mxvKgDnonm6nd7CDmDqGJVbPcowamDZUqBEmyxjY+Plqc5VjT0j8nKsvLWW5eQnGwkP9/OHXd82+YAaNgfxrHKDsAe6qn1+xk8OIneveMOejuVWsX1z5xGns2PNxBi+y9l5H9Y1CwLqCVut59bbvmKG26Yza5dVQfd1lNSj0mjQVaBLr1tGROxWXoSLkxE0kr4S3xUf1eBa0sdCbKWkUNSCYflaECgvUL1Iep3ewjLMp8sU7KIb755WPT9P2RIMoMGJeH3h5gzZ0f0dmqjhsRLkqMH6/ZltdEMncblUG++ua7VwEFbuLe5cLsDrC2uJKhSys7uuONUvvrqWt58+1IqUsLscjjI32tXBl7UdF45b8AewLnGQXmZiwVFJegTdVx4YR+mTx/DOef0IhAI8dD/LcDeXx0t+6pb41BKLzuoKXtpaUOT8wP3YZyr7cj7T/oEqgM4V9kp/7iE6h8qqd/jafb5o1JJTJ+unKyaM2dniyeb2uqbb3ZFS8DPOadX9PqwP4xra91h/V3UIehZouGMeitTLhzATTcN49Zbh/Poo2Pp3TsOjyfAN9/sanY7OSRj3+WkstLDLqeT224bHh1u0JgkSTz++DjMZh3bt1fywQebW1yHpJKwnR2/f7AKVM+vwlfatkmdkX5Sg+KVfbjYzCPLkjpRdXhQKhQK8eSTT9KrVy/0ej19+vThmWee6fLpKYIgCELXKi2t47//Xc8VV3zKlCmf8dhjP3XZ4z777FKuvPJT5s7NJRyWmTSpH+PGZTXbVpKkaLZUJMDSln5Sze5HJWHoa8Q8woptsIX/e+IsAGbP3sHjj/8ULdt79OEx1OcpqeD6PgZi0nRKpg8QdoWoW+vAuVI5UItkSgEYDFr+8pcJ0Z0sWZZx73RR+fX+7CKDmviJiSRMSsI80kpsTz0qgxpJhpP6JJJlNZEQ1rJ9fjGujXV4drkJVAUgBGglNu+rZpfDQciqIj7LGM0+kgMyo6wJTOvTh33rmx4ghkJh8jZWc0FaGuO8VmrmV+HZ5SbsCSFpJWJ76dH3MyiN3mUI1gTwbHfh+KU2ejnDnMBFmRlofLA1twrjOXFtDkhFqHSq6IF5IBCK9tE51N/vnHN6oVJJ5ORUR9PtO8uqVfuYP38PO3ZUNrns3FlFIBBi0KAk/vjHM5k37waee+7cVhvBx6TpiEmJgZCMa+vhZ0tt2FDG2SkpDEiOQxWjIv78xGZliZIkYR0bR0xKDLIvzOSkHpyVnMySBXsJd3CZ0+bN5Sz8zw4sWi0JPUxMnD6k2TZ6vZaHHz6Dsvp6Zq7ZhdcfxFfkpeLLMurWO9p1AFhZ6aa8/ODTleSQHJ12WKoNYBnRvJeLpJaIOydBCRyU+qhbq7yOHn10HDExatasKWm1D9fq1cXMmaNklDz11NnRoNTixfnNnt+aGiUj56yUFOL1OtRmNYkXJ6M2Ns/k1MZpiT8vkcQkA4OsVsrnVVBR3LEN6uWQTN165Xc1DTNTVKIEpdoyGczQ14jtrP2Bqe0unKvsTQLx77xzKampJgoLHVx//Zc88siCQ2Yj1W1wEnYrmWPfbFMCNY0Pkg9Go1Hxu7+dySqNg1KXhy1ryyj9qgz7LzVKA+tQy6+rf/5zJSUldYTDMl9/3fwguTF/rvKZXxb2IWnannWpS49VesnoVASqlIBD9feV3NqzD/cNGIB3iV2Z9tnOYyrXJidyQGZfnZvNJdUkJxu58MI+0Z9LksS11yr90T7/fHuTklJJI2GbEK+UI4Vk7Mtr2b27muXLi5AkidRUE7W19W0uXz1QqD5E/V4P5eVu1tfUcNZZWVgsShauSiUxYkQaTz55Nt+XlrB5XzWOai/VP1R1SEnzgeSQMvUvHAizak8ZG2prufnmYajVKlQqiWeemcCwYSm4XH4eeHAe/n4xWMfFRUsvq76rOKKTBxGtTd7zl/uo3+0BCeIvSop+XiMrU+hqf1amqR74+hgxIo1zz+1FOCzzr3+tPKxjcp8vyH//q/yNb7ttOHp9w/e2fWkNzpV2Kr8sp+an1qfkHijkCVE9t5JAhR/ZF6ZuTcP3siRJXHedksH3ySdbm31G+oq9lOQ7cQUCpA62MWBA04zyxpKSjDz88OmAEkD9299+YeXKomYnTiOf77rMWGUC5NKaNpX4FhTYUQEZsUo/UV3m4fWTOtG1vUNZG73wwgu88cYbvPfee5x00kmsXbuWadOmYbVaeeCBBzr64YSjQG1tPU8+uYhJk/pFd7IEQTgxhMMy8+bt5ptvdjUrQ1m6tID160sPmcFyuLzeIK+++itffrkjuhM9Zkwmd9556kFHFZ9+eg9++GE3v/5azA03eNm7VzkQbWumVEtGjEjjiisGMmfOzmhD2kcfHYuuMowvKKOJ12Kb0JCZEvaF8ex241xpx73NhRySyRiqnBWVZZlHHhkb3SEN+8LYf6nFu7+fhi4zFtvZ8dH0cF2GclZOlmXC9WFC7hDZvSVeefFXjBVqbh5sYuDJSajjNCzbtI+33t9IUZGy8/fG/w0jeZTy95HDspKN8p0PW0EMqTUaauZXYR5lJVDpJ39pBVNSeqDVqDAbYlCb1cRm6dFl6dGl6Zr0Ugq5Q/grfPjLfYSc+3f89v84NRDP9wt2syo3F+POXTz99ITDfu537KjC7w9hs8WSnW076LY2Wyynn96DFSuKmD9/D7/97YjDesy2iAQ8zzmnF5dfPqDJz1JSTPTtG9/kurvvHsnChXtZsaKoyXtGkiRMp1io+bEKzw4X5mFmVLHtLwsoXF/FqQkJWCw64sYrGWYtkdQScecnUjOvknhZZmxqMiMCITZ/ks+QyzKbZOkcrqIiB88/upjLkzJISDAw7u4BqHUt/07nntuL007LYPXqYmbu3sOD5w/FX+yjbp0TT64H6xhbtLyuNSUlddxww2xkWWb27N9E+40cyL2tjvoaP+5gEHsvWi3h1Fi1WMfFYV9Ug2tTHUF7kJSz4rj99hG8/voa/vGPFbhcfi67bEC0lMTjCfDss0sBuOaakxgxIo1AIITZrKOmpp6NG8uafE6uXVtCpsHA2B4pxGjV2M6KR21s/e+uy4il/1WZlLxSRy9g7b9zOPf3J6FL65gz9p5cN6G6ECq9CsNgEyUl7WvCbOhvVHpALa3FvdVF2K8MhZCDMqagzBv3ncPin/PZubOK8A4vMx5ewYD+CYw7O4v0Pla0STFo4rWoNCoCtQHc+wO02mEGVv1L+d5pa1AKlKD/M/86jztu+4bB5V40W1QMlSQ8O9xIWgldj9j9n22xqGPVLFmS3yRb48cf9/DQQ6ej1Tb/mwRq/FCsZBPlye2f5qWUzaVQv9tNoCZAoCZAkt9AbJ4ayQX5XxbjM0nsswQosruorfVy0UV9GT685e/ZoCuIe7sLGZkP1ypZj9ddd3KztZ9/fh9efvlXKircLF6cHy0bhIa+OxWzy/EX+5i/ohCAc87J5tJLB/C7383jo4+2MmXK4DYFKhvz7HQTDsps3VdNudfLY5f0b7ZNVpaVSZf0Y863ufRMtzDWnEHNvEoSL00+rM/DlshhGedqO4FKP+U1Hr7IySc+Xs9llzV8fut0Gv7974nceuvX5OfbefTRn5gx4zI0Vg01C6sJVPqp+q6CpMkpTYZ1tFdLQSk5LONYruyrGAYYid3fs8g42ETQEcCzy41rUx2uTXVIGgnziKb9FR988HSWLStk9epili4t4Oyzs9u1ps8/305lpZvUVBNXXDEoer23qB7v3vro97t3r/L/kfLwmKSWm/yH3PsHNziUk2zh+hDegnr8lf7obSZN6sdrr62hpKSOxYvzm7zHnbtclJa5yHU6ueHuYS0+RmOXXNKfJUsKWLw4ny++2M4XX2zHYNAyZkwmZ53Vk2HDUpTMNLVE3LkJlH9cSsipnAhpbXpmREGBgx4GA6ZYLSq9Cm1i+060CYoOz5RasWIFl19+ORdffDHZ2dlcddVVXHDBBaxe3XwMtHB8mDs3l1Wr9vHqq6s7/GyqIAhHt1de+ZWnnloUDUiNGpXO009PiO7Ivf766k7JlK2ocHP77d/y6afbCAbDjBqVzowZl/HKKxcdNCAFDePVd+yoYunSAgB6947Daj2yA7j77x8dPeA955xenHdeL9zblYM342BTk4NclU6F6SQztkjPlZ1uwhvcPPboWB5++AwuvrgfIW8I5zoH5Z+VKgEpFVhGW4m/MLHFfgWSJKE2qIlJimH4hVkMvzSLVVVVPP7+Cn4qLOGmP3zHE88toajIgc0WyyOPjGXUqIyG26sk9H0M9JqaybqaGjz1ARy5dVR+UYZ9SQ2OAjdhWcYbryLxkmSSf5OGdUwcsT1imzX3VhvV6HsZsJ4eR/wFicrlfOUy9v6BXPmnERgSYykpqeP227/l1Vd/Paxyz8ale23pAxVpGvzxx1ujO/6dIRKUmjSpH2PHZjW5HBiQAiVj5IorBgLKe6rxe0aXGYs2QYsckHFtO3i2T0tC3hAZ1UpwxHSS6ZA72Gq9msTJKSRemERsaiwaSaJ2g/I6rFlYhWuzE1+xl1B9+/9edruX3z0wjzHmBMxmHcMm9UB/kKCSJEn84Q9jUKtV/LAsj7WSg7hzElAZlIb3NfOqqF1SE+2/c6BwWObPf15MXZ0Pl8vP559va3G7kDdE3QYnFRVullVUMPgQ/VIMfY1YzrCBGrwF9VR+Wc7V5/Rn4MBEnE4fL7ywnEsu+ZgZM9bjdPp47bXVlJTUkZZm5r77TgNAq1Vz1llKNueiRU3Lstb+WsyF6elYbbEYBhnbVAJmGmCi381ZOAIBnBX17P6gEOcaR6uZP20lh2RcG5TMKNMwC6ikJuVFbWUcYFKySlAa6tetduBa78S9uQ51UYBz+2Uw9dzBnNe/B8Pj49FXhln3RT47viyi6usKyt4tpuKLMmrmV0EYYnvqWZWnNHbv3TuOrKyWhxy0Jj5ez0uvXsSq+hre3ZbLtxvzCWpk5IASnLcvqaH8oxKKvy3j3ReVXjw33DCExEQDDoeXFStaLpN0rnUQCoXZ5XTiNxxes2KNRYN5hJX48xJJuSaN7DuzWR3jZGVlJes3lrFzeRmuH6op/L6MH77O4c9/XtLq96xrvRNCUBH0sTK3DKMxhiuvHNRsu5gYdfT6Tz7Z2nxNVi3mUyz4/EEM+UF0KhW33HIKY8dmctppGQQCoWZ98Q5FDsu4d7iw13pZWVJBXJy+1amuv/3tCEIq+M/q7dR6fQTtQarnKZ9Hrq11Spn4Lhee3W58ZT5C9aE273uEXMrwDPdWJXj3yZY9uIJBbrhhSLPpkhaLjldeuQijMYYtW8r5+OMt6NJjSbosOTqIw/5L7RHt97QUlPLschOoDiDpVJhHNn2ta6xaLKfZsJxuA1BK6Tc7m2yTnm7mhhuUjNR//3tVu75v3W5/dHjKHXecGn1O5KCMY4UdAOPJZpKmpKLvawBJ+Vys+qqcqu8qcO90NekzGXQFqfpOCUipTWoSL0lSBiNANPsUlCDglCnKa/Kjj7ZEr5dDMntXVRAMhnGaZMaObZ4VfyBJknjhhfN4+eWJXHnlIBITDXg8AX76KY+nnlrE5Zd/wjnnzOKuu77j1f+sJs/vptZeT86CEtasKWbduhLWry/F6Wxa0ifLMvn5dnqbzej1WnSZhz9590TX4UGpMWPGsHDhQnJylJrlTZs28csvv3DRRRe1uL3P58PpdDa5CMeWyEFBZaU7OpVBEITjX2Ghg48/VnZeb711ON9+ex1vvHEJkyb14+67RxITo2bTpvJWd94P1/btldx88xx27KjEZovl1Vcv4o03LmHYsLZl2yQlGendOw5ZlqPNyI8kSyrCYtHx4osXcO21J/N//3cm/mIfIWcQKUZSdtRaYOhnbJi8lOvhnPgUrrl4IM6Vdso/LsW13onsDSv9ZC5NVqa7tXGH5667RtK/fwIOh5fnnltGYaEDqzWW++47jW++uY5rrjmpxdsZrTqKLQHe3bOHalk54682q1lWXs6bOTmYzrShS4s9oh2vU09N55NPpnDppf2RZZn33tvELbd81e6R9pHvn7aWXl54YV8GDUrC4fAyffp86us7fqR3SUkdhYUOVCqJkSPbPqHw9ttHEBurYevWChYvzo9eH8mWAqX3SktN8g8mf24pOllFXShI30vath5JkojtqafHNWl8XlDApqIqQgEZb149zl8dVH9fSfkHJZR9WEL1j5W4d7kIew9+kOP3h/j9738kxaMh02bi5OHJJIxLOORaevWK45ZblDPhf/7LErZU15J8dSrGIWaQlABH1dflLY5n/+STraxfXxp9rX722Xa83uZlP671TipK3BTU1lEUrm9T1rfpZDNJl6WgsWkIe0I459fw0l1n88h0JcuxtraeN95Yy8UXf8RnnynBsCeeOBODoeEs+rnnKkHSn3/Ob3IQG95Zjy0mBmuKHstptkOuJWLA6FTcI3RssdvZvbsW5wYHVd9VKAfu+y91m5zUbWx02dBwce90NQs2enLchFwhVAY1xkEmKivdBINh1GoVycnGVlbSMuMgkzLNsLcBfT8DhsEmjEPNmEZYMI+0knpWIqfd0JtTf5ONIwnWVFezZHsx4RhJKQmuDRByBkEjYTnDFn2fTJiQ3a51RPToYeHllydSJQWYuXYX981ZTv2psZhGWNAkaJFDMjsWlXBhXCq/H3EyU8cN4rILlNdGZIJiY/5yH74CLz5/iF8qKpr8rY+EpJG4+LqBrKqp4rPyQmpigsTH65k4OIs7B/bH6pJaHGwRtAeiDc4/2aCUlV511SCMxpazV6ZMGYRarWLjxjJ27mzeN8s01MyeMgexKjU3juzP4MHK2PqHHjodSZJYsCCvXZ/h3oJ6wu4QRRV17HI6mTixDxpNy4emaWlmrrxyEHXBIO9s3IUUo0x2dP6qlMA7fqnFsbQW+6Iaqr+tUD6fZhVT+VW5Mgxkax1BV/P3vregnoo55fhLfUhaiQKrn0W7ijGZYqLNtg+Unm7moYeUcrDXX19DYaEDjVVL3DnKd7k3zxN93g9Haakr+jgAYW8I5/5gjXmEpdUm2qYh5mjAyvmrI3pSLGLatOEkJBjYt8/ZYuCxNR9+uAWHw0vPnjYuvrjhs7Fuo1PpM2dUYx5hQRunJW5CAslXpaLvpwSn/KU+HMtqKfuwhJqfqvDkuhsmiZrVJFySrAQ8h1tApZQhNu7xdvXVg9FolNfk9u2VANTvq6e0qA5PMMh5V/dvsZdUS9RqFWPHZvHHP57J99/fwKxZV3DrrcMZPDgJrVYdHTzx/vubeXLGcrZsqWD70lKe+N1P3Hnnd9xxx7dcdtnH0T6kANXV9Xg8AfqYzej1GtFP6gh0eFDqscce49prr2XgwIFotVqGDx/O7373O2644YYWt3/++eexWq3RS2ZmyxFy4egUDsvRgwIgWrYiCELbyLLM1q0VvPfexmYj4Y92r722mlAozNixmdxzz6gmk5iSkozRiT6vv76mw7IolbKrb6iq8tC7dxyzZl3R6pnVgzn99B4AFBcrJ0I6IigFMHRoCtOnj8FqjcW9Q9khNPQzotK2/nWr72Mg7twEUCsj1ys+K8O9zQVBGW1iDHHnKjt5Mcm6dq0lJkbNs8+eg8kUg8Wi4957R/Htt9cxdeophzxYOuWUVGr8fpb6qkm5MZ3YifF8sTEPTygUfe6OlNEYw5/+NJ5//ON8bLZYcnOrufXWr7nzzm9Zvbr4kGeaw2E5unPY1hLRmBg1L754PvHxenJyqnnmmaUdnsn3669KltSQIcmYTC0f/LUkIcHA9dcrZ7Jff31NkylBsb30SrmTL0ztompc2+qUbCX3wbMB6vd6sG9Xzrrnmb3o2nmQPHRYKgGrig9257E7ya/0L+ulR23VgAQhTxB3ngfHUuWgo3peJZ4cd7Ppi/X1Af70p0Xkb6/hrPRUTjopmaSzWs74a8ldd43kvPN6EwyGmT59Prl7a7CebiNhUmRsfZCqr8qbTAfLy6uN9uh65JExpKebcTi8fPtt035AQXsA9w4XRUUOFpeV8ZtrT25zMEGbGEPiFSkYBinBGf8OD2cTx//uPY+X7xrPRSdlkayKwazRMHnyQEaPbvreGT06A71eS3m5ix07lCDAvq019FUbkSSJrEmpzXp/Hcodd49krc/OZ7l7yS92EKjYf+C+/1K2uIrV7+9h25eFONfYqVvriF4cy2op/6iE6u+V7IaQO0Tdxv1ZUqeYkTRSNIsjNdXU5oPBxvS9DcSfm0Dc+ARsY+OwjrZhOdWKebhFuYyw0ndSBrf/Yyx7dV4+3r2XX3R2Uq5PJ/7CRMwjrSRcmEhQC8v3N3VvT+negQYNSuLddyfTo4eFkpI6pv3uO7b6nCRfmco2Wz0/5RYTkMOcOjiF+o11nK9NIttoZOnSgiZZE7Is41ztICzL/JxbTK3f366g9KGce25vVqy4ja/n38A9/x3P2Y+exODRKaQnmZiUkcH6OQXNbuNc5wAZPGaZheuLUKkkfvObk1t9jKQkI+edpzyXzz23DIejaQN4l8fPjF+VvmhnZqfiL1d+/379EqJlyv/858o2f9+7t7sIBMMszC0mJMtc0kLpXmO33jqcmBg1v2wqpiA9hGGwCX0/A7G9DcRmK+WWMelKDzYkkP0ygUq/MgxkpZ2Kj0upnF2Gc50Df6Ufx4paauZXIXvDaBO1JE5O5s3vlIyca645qdXgHcDllw9g9OgM/P4Qf/nLYsJhmZhkHeZT9weFVthbDJS3RfH+nnBpacq0T+c65eSUJl6LcbDpoLc1D7dET2I4ltfiyXEjyzJyUCZWreaBO0di0miYOXNjs6yflkSmxYJSZq5WK59HAXsgmo1lPcPW5HNKY9MSNz6BlGvTMJ9mRROvhdD+DMTFNcokUavSRF9jVrJ4NRZNdLBE3dqGATBJScboMJCPP1b+NlsW7MPrDVIUqGfSxYfXNkalkhg8OIl77hnFrFlXsHTpVD76aApPPXU211xzEr0Gx1MbE8JkjOHC/pn07h1HYqIBl8vPvfd+zy+/KCWsBQV2rFot6RYDKrUUbacgtF+HB6U+++wzPvzwQz766CPWr1/Pe++9x4svvsh7773X4vaPP/44Docjeikq6pypIULnyMmpbjJxY9GifNHUXhDawG738tFHW/jNb75g6tSvePXV1dx44+wmZ2COZps2lfHzz3tRqSQefPD0Fre55ZZhGAxacnKqWbgw74geLxyWefvtdfzxjwvx+0OMG5fFzJmXt7t/RUSk2XlEe5qct0WwLoivUNmhP9ROJIA+20D8eYmw/xhdl6EjYVISiZOT0fc2IB3GwR8oZYlz517PvHk3Mm3a8DYfbA8dqow23rS5HLVezdp1JYTDMr16xZGScujfpz0mTOjFZ59dzeWXD0CjUbFuXSn33DOXW275qsUm0BE5OdV4PAGMxhj69Tt0xk1ESoqJF144D7Vaxfz5e5g1a1Obbqf0JNrBgw/+EA1mtuTXX4sBmgUg2uLmm4dhtcaSn2/nu+9yotc3zpbyFXpxrlAaIJd/pGQDVP9Yia/Y2+T7N+QJYf+lFqfDy6qqKrKGtf05avy4F13UF4Bvlu3GPNwSLSlyjdHz10Ub+PvX61i4ppDCAge1OXXYl9RQ9mExNYuqWbdoH3/+82IuuOADFizI48KMDIYOTiaur3Iw2VYqlcTTT09g5Mh0PJ4A99+v/A106bEkXZlCTIYOOag0KbYvrcFfH+TJJxfh94cYMyaTq64azI03DgWUs/6NX1PO1Q5qa+rZXFZDRdjfagZhq2vTqLCNiyf+gkSkWBWhuhD+Qi+9ZD13jRvMXy4exd8uHM207N7ULqlR+jPtz9jQ6TSMG6cE1RcuzEMOyRT/oGSa1BqC2Pq3//PNZIrh978/g11OJ88sWo8vXa0MIOipY21ZFe8v2sHi3GK+25TPHp8bwwBj9KJNioEw+Ip90QBV2BVCZVJjHKi87yNBqUNN3jtSKpUUDdJ+9NEWiJWIzdJjHm5Blx7LypVF+HxB0tLM9O/f/td2Y9nZNt57bzIjRqTh8QT43e/m8fbb6/jrayv5qbSU0HgzPS5ORZsUgzFWy02D+9JDp28yydNX5MVf5qO03MWPe/aRnGxssUzuSDQOAurSYkmcnILtFCUIYioI4djU8Lnkr/LjzVN6/fyYr5TXn312z0Nmt91++6lYLMqkst/+9tsmAwJmz95Bbo2TMo2fuLhYpUxtf3no3XePxGDQsm1bBQsWHHrCqb/Sj7/ER1WVh3UVVfTpE3/Iv2NiooHf/EZ5f7723jqsY2zEjU8g/twE4s9PJOHCJBIvTibl2nTSpvYg6apU4s5XApkxqTqQlIl1rvVOqr4qV07+AMahZhIvS2FDTiXbt1ei02miJ9VaI0kSTzxxFgaDlk2byvn0UyXzyDTMjG7/51Htoup2T+Tz+YJUVyv9IzMyLASq/Xj2n+CynmFr076AeaQF4xDl/WpfUkPpf/dROnMfZbOKOaXawO+Hn8yliel8OuPQ333vvbcRjyfAgAGJ0eCvLO/vbxVSystjs1suwVabNJiHWUiekkrSlBSMQ82oTGolAHhxcrMehebhFtBI+Mt8+PY1BEQjDc/nz8+jotxF6Qalt1afscnExnZMe2ytVk3//glcdtkAHnlkLDNmXM6tz4xmxIg0rj2rP5/MupKvvrqWceOy8PmCPPzwj/zwQy4FBQ6ldM+gJSZVd0S9xE50Hf7M/eEPf4hmSw0ZMoSbbrqJhx56iOeff77F7XU6HRaLpclFOHasW6d80Y0YkUZMjJqiIgd5ebXdvCpBOHoVFNh57LGfmDjxA/71r5Xk5dUSE6MmLc1MTU09d931HbNn7zj0HXUjWZZ56SWld8Tllw9odQy31RobPRB84421TTI/2iMclnnuuWW8/fY6AG68cSj/+teFBz2LeSgjRqRFywRSUkxNsrw6gmeHC2QluNRaU+kDxWbplZ23q1JJmJSMLuPISuQijMaYZn0xDiUSlNq5swqvN8jKlUr2zxlndEyW1IHi4/U8+eTZfP31tVx77cnodBq2b69k+vT5TJ8+v8WTHZEs3VNOSWl3xsbw4Wn84Q/KmOzXXltzyBJTjyfAE0/8zHPPLWP58iLeemtdi9uFwzKrVytBqcPJKDOZYrj11lMAeOutdfh8DeUm+r5KRp1pmJnYng3ZSrJfxlfopfr7SqrmKNlCckjGvqwG2Rsmr7qOFRUVrTZCPpSLLlLORK9YsY/a2nrCYZlZszZx861fsTqnnFVVVby8fhtP/bSWl3/YxMI1BezeVcPSj3PJnZmPaaufdE0sZ/dNY+LIntgS9NjGxrX7ta1kuV1A//4J1NTUc999P1BTU49aryZhYhLmUy1Kf7ZdblY/t4Mh9QbGZ6byf/eOgTBceml/LBYd+/Y5o2VfvhIv3oJ6CguVLKkrrhiIzXZ4Z7pje+pJuSaN+ImJWM6wYTzZpLyne5nJzLIg1cvU57ixL66h/ONSyj8tpWZ+FZf1y2JYXBw7finDucaOq8xLfSiEZkj7SuMaO//83px2WgbVHh//mreRDWEn015awNNfr+H7fcXk6L3MKynhsY9WUJYcxnZWPLaz4kmanELyNamYR+7PbtjPPNwS7Ru3d68daF8/qcN1ySX9sVqV3nMHZuJH/n/ChOwO+Zy0WmN5/fVJXHbZgOhJELfbz5AhKdw0dRiGfkYSL00mtqee9BQTk7OyWDNPyZaQZRnnGgehsMy3WwpwBYPcdtvwdn/utpekkhh6bU+21TsJBEIU/VhG3f7AVKQ3j7ZnLF/8qGQHNm5Q3ZrsbBszZlxGcrKRvXtrufXWb8jPt+P3h/joIyXw0v+yDFSxaoI1AVxb6pBlmYQEA1OnngLAK6+sbvLZdaCwN0Ttz8qExbXFldQFg1xySb82/R1vuUXJ9N25s+qg1RmSRkIbp0WfrQQyEy9NJuWGdGxnxytBFI2EyqhMsbWOtiGppWhG0OTJA1odiNBYWpqZBx8cDSjfI/v2OZEkCdvZCaj0KoLVAZyr7Ye8n8bKyvZnWBu0mExaHCvtIENsb32besuBEjCzjLZhPKn5CSRJksjOtpGu12Pe6Kd4SWWrfecqK918+qlSenzvvaOi37P1ezz4S3ygkbCOadtnuTY+ButoG6nXpZN0RWqLgxvURg3GQcqa69Y1ZEsNGpTE8OGphEJh3nhmFd66AN5wmIk3DmzT83G4YlJ1aBK0EJRx73ITG6vhxRcvYNKkfoTDMk8+uYiPPtpCb5MJvV4rSveOUIcHpTweDypV07tVq9WEw4d3MCIc3datUw4KzjwzK5p58PPPew92E+EosWdPDf/734YW+2sIrduxo5J33lnHvn3t73/n94e4//4f+OmnPILBMIMGJfHYY+P48ccb+eyzqzj/fKU85bnnlvHcc8sIBI58tHBnWLhwL1u2lKPXa7nzzpEH3faGG4ZgtcZSWOhosQfHoYTDMk8/vYSvvtqJSqWcmfzd704/rLKRxvR6bTTw0tFZUnJIxrNLKSMytCFLqjGNVYs2rvsnt6SlmUhKMhIKhdm+vTIalOqo0r3WpKSYmD59DN9+e120VGPp0oJomU5jGzY0NDk/HFOmDOKKKwYiyzJ//ONCCgsdLW6Xl1fLLbd8xY8/7om+7n76Ka/F0oedO6twOn2YTDGcdFLSYa3r6qtPIiXFREWFm3vumcuqVfuQZRlJktD3NmA5zUb8BYkkX51K5akaPi8rZJvbgaSRCFQHsC+uoeyjEnyFXnzBEJ/n7AWVxJBDNO9uTXa2jUGDkgiFwnz44Rbuuus7XnnlV4LBMOPHZ/Pll9fw5JNnMeDUZFbXVPPy+u38ffkmNpRXo1JLjOqdzF8uGcXD5w4jMcGAebilzYHaA5lMMbzyykWkp5spKnLw4IPzyMmpxlnnwzTcQsJFSTgDAYoLnWSbTNx02gBCS52UvV+MZ4mdeycOIU2v54P3NxMOh3H+asdZ52NJfhmOUDAaRD9cKp2K2Ew9ppPNWM+II+HCJJKvTiP15gziJyZiGmZGmxyjlD46g3gL6unh13FhRjpn6RIoX1WDw+7lp9JSRpyecegHbIUkSTz22Di0WjUrV+7jkUcWUFHhJj3dzL//fSEffzyFs87qid8f4pFHFjR5LUf6uyRPSSXp6lQSJiVFy2qAaAC3s6aqNhYbq+Hqq5W+Ph98sDl6kBoIhFi2LDIB7vBL9w6k1ap58smzePDB0UpftVgNf/nL+GjJUmQyV9opcWhVKob4jOSvq6J+j4dgTYB95U5+LighPd3cZGpbZ9Jo1FhGWVlZWUlFhdJAvnZRNb4iL6hgvauWujofaWnmNn9+9+oVx//+dzk9e9ooL3dx223f8Morv1Jd7SE52cj5F/fFur/XWd0aBxWflmL/pYarzuxLj1Qz5eWuVr/v5bBM7aIaQs4g9aow72/IRaWSosHvQ7HZYqMZdG++ubZdrQHUejWG/kbiz08k7ZYMUq5Li07vrKvzRbNcD1bieKArrhjEqFHp+HxBnn56CeGwjNqoVoaYoPQB9BbUt/n+IpmIPdLNOJbW4i9Vgj+W0bY23wdEJibGkXJTOik3ppN6SwZpt/Yg7bYeDLqnFx6jDDLsnltM1TflBKr9ze7jnXfW4/eHOOWU1OgJqbAvjHOVHQDzKRY0lo7JVIowDTMjaZV+YY2ft8jf3L8/Az0mK5bExMMP3LeFJEmYTlKC757tLuSwjEaj4s9/Hh/N3tpX4CDLaMSg16A7xCRY4eA6PCh16aWX8te//pW5c+eSn5/PnDlz+Ne//sUVV1zR0Q8ldLNwWGbDBqXU6NRT05kwQdkxEH2ljn6yLPPEE4v4z3/WRLNPhNb5/SG+/z6XadO+5qab5vDWW+t4+ukl7b6fDz/cTElJHcnJRj76aArvv38FV101GLNZh16v5bnnzuXee0chSRKzZ+/g7rvnUlPT9p2ZQykrc/HYYz/xxRfbD7vHkzJhR+nTctNNQ0lMPHgJjtEYw7RppwDw9tvr2jXxJRQK89RTi/juuxxUKolnnz2HyZM77szYddedTFycPjr1rKPU53kIe8OoTGpis47NnRRJkhg6VAlifPPNLsrLXcTEqLvkQBSUzKl77hkVLaH4z3+a9iWTZZn165Xvn8PNAFImu41l6NAUXC4/N900hwcf/IH//W8D69aV4PUGmTdvNzffPIe9e2tJSjLy9tuX0q9fAn5/iHnzdje7z8jUvVGj0qMHsu0VE6Pm0UfHotGo2LSpnPvu+75JKaPL5eezz7Zx7bVfctvt3/L+19t4/IMVOEfGYB5pRaVXIXuVE4HFxgBVPh/9+yccUWZhpITv3Xc3sn59KXq9liefPIt//ON8eva0cfnlA3n11UksWHATTz11NuMu6c3YewdyyT9HMvyqbKxJeiQkNHFaTEOPLMMmMdHAa69NwmaLZceOSq6//kvOPXcW48bN5Lr7v+a+2b8wc/du7OkSmSMTkGJVyAEZX5GXU03x3NSnNxMCcez8Xz6BqgD5+xwsr6hg0qS+HV6aGqHSKsEqy2k2ki5PIfWmDBImJWEdG4flFAuBOBU1Ph/5hXbWVVZT4PccdhAxIivLytSpSoN4rVbN7beP4PPPr+bMM3uiUkn8+c/jSU83U1JSx5//vLjF7wStTdskY7OszEVOTjUqlcSYMV3TA/aaa04iJkbN1q0V0Sba69aVUlfnIz5eHz250FEkSeKmm4bx6adX8cknVzWb6iepJTIuTSNgk9BIEsVfleL8VZm4N3vjXryhELffPgKttnOzpBq7aFI/lldW8u2uQkKhMPW7lfIvwwAjn89VekBdccXAdp3MSU01MWPGZQwerAyGiDTGvv76IWi1avT9DUovNTWE6kJ4drhxLbbz+MihXNOzJ4u+brmEr26dUynN0kgsc1fh3d+n8FD7Eo3dcMMQzGYdeXm1vPXW2sNqGyKppCYZPsuXFx3WJEeVSuLJJ89Gr9eyfn0pX3yxHYDYTL0yjAGoWVhN1bcVOFbVKgFMR6DVNZeU1BGrVnN5Wg/qc5Wpu7ZxcWhMhxf8UceqUevVqGJUSGrld9aYtYy4oy/fFxeTX+LEUeSh8qvyaJYdKKWakaz9e+5R9ktlWcaxyk64Xhm+cqSf5S2uV6/GuD8QVLfWSdgXRg7KnHVmT3qkm+lnVn522uU9O/yxW6LvY0AVqyLkCkWDZCqVxMMPn8Fdd40ky2hELUnExuvQ2Do2QHei6fBn79VXX+XJJ5/knnvuoaKigvT0dO68806eeuqpjn4ooZvl5lZTV+fDYNAyYEAC6elmVCqJnJxqSkrquiS1Wzg8W7dWkJurpE5/8slWrrnmJFJTO2dn/GgTCIR49tmlBAJhbrttOH36NB/PHlFZ6ebzz7czZ85OamuVLyONRkUopDT4b8/rvKrKw//+txGA++47rcXeCZIkMW3acPr1S+D//u9nNm4s4+ab5/DyyxMPus62eu211fz0Ux4//ZTHnDk7efTRse3eof/88+0UFztJSDC0Oavg6qsH8+GHWygrczFjxnrOPjub2FgNOp0anU6DxaJrVuYQDIZ58smfWbAgD7VaxXPPnROdVNVRJkzoFQ2md6TIxBvjQNNh94I6GgwblsrChXv5/nvljPcpp6R2WP+GtrrllmF88cV2cnKq+fnnvZx3nvIa2LvXjsPhRafTMGhQ4mHff0yMmr///XzuuONbCgsdLF9eFM3KUqmk6IH6aadl8Oyz5xAfrwQx//735cyZs5Orrx7c5MAmEpQ6nH5SjZ11Vk+++eY63n9/E7Nn74yWMmZlWamocEczXHU6DUlJyjSldz/azPPPn4dpqFkJjPrDrPhOKUc50mzACy/sw0svrSIclhk6NIWnn55Ajx7N2y1YLDouu2xA0yyR03SYhlvw7fMSk6qLloEdiawsK6+9Nol//nMFBQUOamrq8fmC0Wy35GQj1/9xJBaLDlmWCdYG8JX48Jf6SCgwUFnqpnibHW22jW+2F+ANh7n55mFHvK62UulU6DJi0e1PhrJVJ/DvP22B/cfxY8ZkdkhQ4/bbT6Vv33gGDEhs9veyWHT8/e/nc+utX7N0aQGzZm2Kll+1ZtkypZn2kCHJh13m2F7x8XomTerHV1/t5P33NzNsWCqLFikZ+ePHZx9x1mxrWitLByUwlXxRMuve3k1suYbsLCsF5U6WFZWRlWVt0/TGjnTSSUn06GFh2b5yroj10jdgQNJIVMcrwyBUKolLLz14E/GW2GyxvPnmJUyfPp/Vq4sxGmOiJ3EkScI2Lh7LaBv+UqUHkHefl9Sgkex8E5lhmZ1fFzHgkh7R93z9Xg+u/Y3zrePimP37ZQBNJrq1hdms4/77T+O555YxY8YGQiE5ekLvcC1Zkg8ofbfaKz3dzP33n8bf/76c115bzQUX9MFmi8UyykqgWumd5S9TLm6U/QMpVoW+twHDACMxiQ0nDKoLXdzYqxfpsXqkGIm4cxOJ7dHx77VThqeRMNTK/1buRpsaw/gBGdStdiBJsKKskuef/wWAadNOiZ6Mcm2soz7HDZISKOuIz/KWmIaace9wEawNUDarOHr9E6cOY/eeGoxxOvqMOrKgfVtJGgnDQBOujU7cW13oeynBU0mSuO224ZwcMhEu8pF+SvtL0oWmOnzv0mw289JLL/HSSy919F0LR5lI6d7w4amo1SpstlhGjEhj7doSFi3ayw03HFkavNB5Gvcs8vtDvPnmWv785/Hdt6Au9M4766Np5T/9lMcll/TnrrtGNmn+uWdPDe+/v5l583YTDCoZB8nJxv3lPoN44omfWb26mLlzc7j99lPb9Livv76a+voAJ5+czMSJfQ+67bhxWcyaNZmHHvqRwkIHt976DS+8cN4RlU6Vl7tYsEBpNm40xrBrVxW33vo1l102gPvvP424uNYzeuSwjByQqav18um7m9FKUrSpaVvodBpuv31EdAdyxowNTX4uSRKZmRb69o2nX794+vVL4Pvvc1m2uIBMk5FH7zmdQfo4qn+oBJWSdSBpJaT9/9WYNWgTtGhs2k7bSYqQZRnZFybkDROuDyOHZCQ1SBoVkhpCrhCBCj+owTCwc1PLO9uwYUrAMhKY6ax+UgcT6Uv29tvreOONtUyYkI1arYqW7g0dmnzEB++JiQY+++xqcnKq2bSpjM2by9m0qTw6DfO3vx3BHXecGj34nTixLy+9tIrc3Gq2b6/kpJOUnWOPJxDN5OiIMsfkZCO///0Ypk0bzscfb+Gzz7ZHgy69e8cxZcogJk3qR1mZi+uu+5KFC/dSWOggK8uKoZ/y2tvwrJJNdqTTJRMSDPz73xdSXV3PxRf3a3cWmEqriu7Md5SBAxN5553LAOV7rLLSTXm5m6oqDyefnIzFokyrlCQJbXwM2vgYONlM775qXrzxG3qWm+jrjWNtVRXjJ2TTq1frQYjOduaZPVGrVdG+e6NGdczUNpVKOmgwf+DARP7whzH89a/L+M9/1nDyyckHnRgXKZk766yuyVKIuOGGIXz11U6WLCmgoMDepJ9Udzl7QjZ/+9tyAHpXx/Hh2lyCssxdd4087CzJwxUZSPDOO+v5Yn0eL/7fOUhaFa/MXAMof6+kpMP7PjIYtLz00kQ++WQrAwcmNsu4VGlVxGbpic3SYwWCjgChveVIZQHKV9QQH9BgOyseSavCvqQGAOMQM9tq7ZSU1GE0xjB+fHa713XllYPweoP8618reffdjfj9IR566PTDCgz4/aHoyYizz27/WgCuumowX3+9i127qpg1axMPPDAaSS2RMCmJoP3/27vv6KjK7eHj3+mZ9EoKBBIIgYQWCB0EQYRLNSCgiFhQX/SCDQu/yxWxe71iQ7k2bChIUVCkSJHeSwKhp9AJ6aROyiRz3j/GDEQCJCGZJLg/a2W5SM7MeTLZTtlnP3uXYE4rxpxeTHFaMeYMM0qhBdPRPExH89B56TC2ckLroqXpBQ1Zej0aZy3eI3xrdTv/5MldGbftZ97fFEvH25vgdlHh9OpkFv5xEEVRGDMmnH/+swsApoR8W58ytx7ule5vVR1qgxrXzm5k77wEV3T/8Q9wxuCgoVFPL7te8HMKdyIvNofi5CLM6cWoDGoK4vMxxeXTVG2EZkaMDbQqvj6ROjNRbWVNziMjL7+B6dcv6M+k1GlJStVTublFrF1rTU4891wP3ntvJytXxjN+fLsqTbBqiGJjU/j22wOANZkaE5PM8uUn+P33BMaNa0tkZAALFx4u1/Q4IsKPcePa0rdvkK0x9rBhoX8mpeJ59NFON3wTdPRoGr/9Zp2k9fzzPa+6sluSW0JRUiGK2Tq2F4uCRwn8b0p/Fv90hJOns1jw2l7yonLp3rMJeh89el9DlX73RYuOUFpqITLSn7ffHsAnn+xh+fITLF9+go0bT/P445GMGhWGBhWFJwswJeRTcsmMxaxAiUJJiYX4hEzG+TXDqYWeyEvOpCxMQm3UoHHS4BTufN03KSNGtGLfviSOH0+nqKiUoqIS238tFoWzZ7M5ezabDRtO0crVlT6+vnQODyM8zAfPbD352XnXvG8bjXW7idZLjyHAgLFF9afWXclSZLFO9Eopso66r0SLRGOQY6XH3ddXoaFe6PUa25bLHj3ss13nr8aPb8fChYc5cyaLVaviGT68la3JeXW37v2VVqsmPNyH8HAfxo1rh6IoJCfnodWqr/ow5+pqYMCA5qxaFc+yZcdtSano6IuUlFgICHCpsIqoujw9jUye3JUHHujA1q1n8fd3JiLCz/a84+JioHfvpmzbdpZ58w7y0kt9AOtzfUKC9UNgTTxOvXo1ven7qC16vYbGjV1p3PjGj3twsAdh3fzYsuUM+zKsFcMPPhhRyyu8PldXA126BNgq7bp2rX4/qaqKimrNwYMprFgRx/Tpf7B06T04O1+91dNkMrN3r/V932232TcpFRzsYYvxGTM2kplZgLOz/roJtNpmMGjpPyCYn385zo6sdC7mmGjRwtNWzWlvgwe35Msvo9m16zx5OgtOThrbBbibnQKo12sqXUmoddMRek8gs57fzGAa0zzdnfTlqaj/3EarDzDg0sWVORM3AdYqKYOheh9HrVsJ1bzzznYWLDhESYmlwvdYN7J/fxImkxlvb0fCw6vXC1Cttl6se+aZ31m06Aj33dcOb29Ha1Lc489ekaHW1xKlVKHoYhGmE/kUnjFhzjBj3pEFQGmBhYsFBfh1Caj1/pIhIZ4MGRLCypXxfLzqII/3bcPx7Wnc6edPRBd/przQC5VKRVFSIVlb/kwotnexba+rTU7hztYLexbrhVEsCooF/ACNo33fW2mctBiDHSlINJGxJh1LQSn8uftSpVdZ3/9Kk/ObJkkpUS3l+0ldfrN7++1BvPvuDg4eTCEzs6BS0yuEfa1enUBRUQktWnhy771tOXgwhfXrT/Lxx3uYPXtwjZ/PZDKzZ88FAgNdCQ72qLVS+8qsY8aMjVgsCkOGtOS11/px6FAKs2fvJiYmme++O8h331nH46rVKvr3D+b++9vTtu3VJcL9+gXh6Kjj/PkcDh5MuW4VgqIovPfeDgCGDGlpu7+S3BIKTpooPFWAOe3qBpNlRkU0J94xg5TUfNK3ZXDgtJngYHeMwY64dnNH63Ljp3GTyWyrjhs/vj2enkZefrkvUVGt+c9/thEXl8GPcw5wflUKA9o0wdvD2v8FQEEhJSWf06eyKCwuwQI0b+4OJQqluaWU5pZiBgpPFeDQ3GhdUwW9D7RaNW+9dUeFj09mZgEJCZkkJGSScjybkAwDlhILLUM88WrsjM5Th9ZTZ9uvrxQrKGYLFrP1vyVZJZgzzShFFuubuwwzBXH55B3MxbWrG4bA6k+xU0oUMtelW5uNXkFlUKM2qFFpVdbJNaUKyp9fKq0a54iGv31Zp9PQpo0PMTHJeHs70qJF3VSSODnpeeihCGbP3s0Xn+/nthb+7N18HkuRhY43WQF0LSqV6roTGaOiWrNqVTxr1iQydWoPHB11toRCbTWDd3ExXHNb0MMPR7Bt21lWrIjj//2/SBo1ciI2NgVFUWja1E1ei//igQc6sGWLdSta584BFT7P21v//sHs2nUeNzcHu14gKmuKHhubwtmz2SxffsLWVPhKe/ZcwGwupXFjV4KD3e22vjITJrRn27azHD2aBlgH7Nizb1NFhg61biu8mGPt4fTEE53r7D1O06ZuhIf7cPRoGuvWJeLiYiAnp2oNzmtKp07+FHmo+eJEPEFdfAjROGMpsPZZ9OjvxYaNpzlyJBWjUccjj3S8qXONGdMGnU7Dm29uZfHiIxQXlzJ9+m1V+jts3mx9LujTp9lN/f169QqkfXtfYmNT+PrrGF58sVeFx6k0KhyaOODQxAFLoTumBBOmuHxKMswcvZTFT6dPMzSoU7XXURWTJnVm7dqT7NlzgQMHkrnD25c+LQLo09wHc0oRagcNmeszoNQ6AdC1a+X7bd0slVoFamzvR+uSU1tnChJNWEzWi3T6AAOOrZxwCDKi1tq3MvJWJUkpUS0JCZnk5Fj7SbVufbmfh6+vs+1FcdOm0zd9dUbULEVR+Plna3Li7rvDUKlUTJ7chY0bT7Njxzn27Uuq0SuPZVOttm2zlvw7OGhp1cqL8HAfQkO9KCwsITXVuuUiJSWPtDQT3bo15sUXe9X43uwPPtjJhQs5+Pk5294otGvnyxdfDGfr1rP87397SU7OY8iQltx3X7vrVjoYjTruuCOY336LY8WKuOsmpdatO8nBgyk4OGiZPLkLebE5FJz8SyJKBXpfg3VErkb153YwFSq1CkWBjm2c2bHtHDu3nyMxN5dLWYU4x+kwbLlIaZAej0h3mrf0vOZ2uhUr4sjLK6ZpUzd6975c7dC+vS/ffXkX++bEcTEum+LiUo4dTkPlrKHNoCbgo+GTz/dx+HgaxaWlNAv24IXnexDWMQBLQSmWQgulBaUUXSjCdCyPwpMFFJ4txCXCFed2Lqi0N/4bqlQqvLwc8fJypHM7f9KWpWAxleIQbMS9twdqh8p96FAUxbp1LsOMOa2I/GPWSq/MNenoAwy4dnMv17ehUvdpUbi0KYPii0Wo9Co8B3ijddehdlDX+jbB+iIyMoCYmGR69Qqs034JY8e24fvPYzgdncF/n9jAxfhsNGoVLstzyXPIwbl9zVUmVUbHjn40a+bOmTNZrF2bSFRUa9vkJnt/AARr/6+y6s/582N59tkeHDhQM1v3bkUdOvgSGelPTEwyjz5qnw9/NzJ4cAjR0Rfp1q2x3RMbDg5a7r+/PW+9tZWFCw9z771tr1pDWRLvttua1slzQadO/rRu7c3x4+kAtdIPsKoiIvxszeLDwnyq1Y+oJg0eHMLRo2msXp2ATmf9oBwV1cru8aRSqRg5sjUffbSbuXuP88Ub/6DgpAnn9q4oOhVz5li3FU6Y0B4vr5vf1hsV1RqdTs2rr1on9W7ffo4ePZrQs2cg3bo1xsXl2pXliqLYYvtm/36qP1sbPPHESpYuPcaECe2ve3EDQO2gwbmtC85tXTBlFbHo89WAdQKuPQQEuDB6dBg//niY4uJSMhpDh4FNKDlfRObadFR6NUqRBb2vHo++Xn/bvkn6RgbcentgKbRgDHGs1AVhUTXyiIpqKdu6FxHhd9Xe+f79gzl6NI2NG09JUqqeOXQolcTETAwGrW2aUmCgG3ffHcbixUeYPXs3334bVWNvYFatimfbtrNoNGoMBg0mk5mDB639Wq6lrCfKuHFXX6mtri1bzrBs2XFUKhWvvnp7ua0JKpWKPn2aVblHxrBhofz2Wxzr1p3khRd6Vlh+XlhYwkcf7QbgoYci8PV1Jm1XijUhpQK9vwFjc0ccgow33Oo1pJcnqtWOvPbaFrampnKHnx+BTk5wGo6tS+L93Ayee6ePbStRGYtFYcGCQ4C11P2vf9v8/Tk083AhsIcLB1Iz+O6PY5zKyoU9h2zHODnpeWZSV8aObWPbwqjWq+HPC2bGIEecWjuRvSOL4uQicvdlY4rLx72PBwb/ypU0K6UKl/7IwGIqReth7UGh1lf+6pN1oowWrYsWY5AR5/au5B7IIf9IHsVJRaQvS8HY0hG3nh6Vul9FUcjecYnCUwWgAc87vWu1h0J99cADHXB1NVS5EW1NK4kzMdw9gC9Lj/PbcWuSO8TTFU2+wsVvLuD/MHZNTKlUKqKiWvHRR7tZtvQYHfw8STySjlqnJtJOEwr/6uGHOxITs5qlS48zcWJHWzWzJKWuplKp+OCDf5CebqrSpK3aZDTqeOON/nV2/iFDWvLJJ3tISsply5Yz5fr8WCyK7eKSvftJlVGpVNx/f3teemkDer2mTnrcVbSmSZMi+fTTfbzwQs86/8A+cGALPvhgF4cPpwL82eC81Q1uVTuGDQtlzpy9HD2axmlTPq1vt17AXrz4COfOZePpaaz0sJTKGDo0FL1ew+uvbyEtLd/WnkCtVtG+vS8TJ3ascGLksWPppKbmYzTq6NLl5rfNdunSmC5dAti7N4m5c6OZMaNvpW+bcslacefsrL9uIq2mTZzYkW3bzuHr68Ss9wZh1GvJ+D2N4otFKMWlaNy0eAz0rtSFxluZU9jfYyBUXZF6M1EtZU3Or9y6V6as8eTevUnk5V17W1JNKC4uJTr6IrGxKdUecf93UraFa+DA5uVe8B59tBOOjjqOHk1j/fqTNXKu9HQTs2btBODxxyPZtOkhfvppLK+91o9x49rSpUsAffs2Y+zYNjz5ZFfeeKO/7Yr1hx/u5tChayeuqiIzs4A33tgCWHvTXNkD7WZ07OiPv78L+fnFbNp0usJjvv/+ICkpefj5OTNhgvXNl3N7F9x6e+A7PgDvoY1wCnOudO+hwYNbsmzZPUyd2RuvIY3IDFKjd9Xh7ejAQE8/PvjXVpKScsvdZsuWM5w/n1NhYqE41drTAKDRsEYM+1cE//txBFFRl0dHDx8eytKlY7nvvna2hFRFdF56vIb54N7PE7WjhtKcEjJ/T6c4teiat7lSzm5rQqusIqkqCamKqA1q3Lq502iMH8YQ65XYgngTGavTrH2hbiAvJgfTMeuUGY/bvf6WCSmwNrm97752uLnV3e+vWBTSlqYwoEVjGjlf3oYW3ujydsK0ZSnWvhN2NHRoKKpihej15/n8xR2YM8w0NTuQ+eE58mJzbnwHNaxHjyaEhnpRUGDmhx9iOXLEus1JklIVc3TU1ZuEVH3g4KC1XUgsu5BR5ujRNDIzC3By0t/0JMebMXBgCx57rBOvvHI7RmPt9tuprKFDQ1mx4r4qT7KtDV5ejuX6kd12W9NyQ1zsycPDSP/+1mq2Zcus7z1NJjNffhkNwGOPdar0sJTKuvPOFqxf/wBz5gzhvvvaERzsgcVinUD4wgvrrnp/BJen7vXo0eSqKcDV9cQT1ubgv/0WZxtOURll67P39HIPDyPLlt3Dp58OxdFRh0qrwvNOb/T+BjSuWrwGeaOpZNW6ENUllVKiyiwWxdZktlMFV4SbNXMnONiDU6cusW3b2RtOGqvIpUsF/PjjYQwGDY0aOdGokRM+Pk54ezty+nQWe/deYN++JA4eTLE14Q0IcGHIkJYMGdJS3mhWICeniLVrrfOm/1rB5ulpZMKE9nz++X7mzNlLv35BN9WrQVEU/vOfbeTmFhEW5sMDD3RArVYRFOROUJD7NfuiKIrCqVOX+OOPU/zrX38wf/6om/owrCgKb765hczMAkJCPG1TRGqCWq1i6NCWzJ0bzYoVcQwaVD7Oo6Mv8vXXBwB46qlutkqqm51A5efnjJ/f5as1lhIL6Zsy2LP0FD1KvHjx2bV8OneYLek4f751JPzdd4eVexOvWBSyt2dZ1xTqZGuc7uPjxEsv9eHBBztgNluuOxb7r1QqFY4hTjg0M3JpfQZF5wvJWJOO9/BG6Nyv/ebTFJ9P/hFrI3OP273QXufYqtK6aPHo54VTuDMZa9IxpxaTsTIVzyE+13yTlX8sj9z9f46t7umBsXnNTg0TVVNw0kRJdgk6jZp72jbn411HAGhzRVKqJMvao80xxH4fwPTnzXTUu7GzNJWVcdYqkgh/T0qyS+qseuuhhyKYPv0PvvvuIBaLgqenkcBA+25tFA3X2LFtmDfvINHRF4mLyyA01Nrbqmx7U48eTeq0j5NarWLSpM51dv6GYPDgEFt/u7vvDq/TtYwaFcbatYmsXp3A00935/vvD3LpUgFNm7oxcmTt7KTQ6zV069aEbt2slXRJSbnMnLmRmJhk3nlnGx9++I9yFW1l/aSqMwHwWtq397U15v/ii/2VroCsq6RUmSsfF7VBjfewRiiKUucVgOLvQSqlRJUlJlr7SRmNOsLCKp5SUVYttWHDqSrfv8lk5sknV/P11zF8+uk+Xn11M5Mnr2Ls2CX07/8dEyf+yqef7mPv3iSKi0vx9DTi6KgjKSmXuXOjGTVqERMn/sqvvx6X6qkrrF4dT3FxKSEhnhU2dS1rgH3hQo6toqq61q07yaZNp9Fq1bz8cp9Kj0dWqVTMmNGXwEA3kpPzePnljdX+GyqKwgcf7GLz5jPodBpef71fjV0FK1NWebR79wXS0vJt3z958hLPPbcWs7mU/v2DufPO2pvGo9aq8bndm3bd/fF0cqBlkZFp09ZTUmLh6NE0YmKS0WrVjB3bptztTCfyraNt9aoKG1cGBrpVKSFVbk06NR4DvND56FEKLWSsTqM0r6TCY83pxWRtuwSAcydXHJrVTkNmva8B72E+qI1qzBlmMlakUZpfWn4tl8xc2pRB9vbL63EKl3Ltulaaczl2+gb7E97IA38XR8IbuV/zuNpWVr11Z8ifW4j+fJrq4He5QXVdVG8NGNCcwEA32/Nmx45+8oFCVFqjRk626XE//ni5Wmrr1rrduicqr1+/YJo0cSU83KdO+ttdKTLSn8BAN0wmMz/+eIjvv7deJJsypet1K69rUkCAC//+dx+0WjXbt58r97kkKSmXhIRM1GpVuX6bNeGJJ6zJ0zVrEklMzKzUbS5ezLOtub6Q1w9hL5KUElVWtnUvIsL3mi8qZSW727adrVLpqtlcyvPPr+X48XQ8PIyMGNGKHj2a0KKFp63yw93dgTvuCGbatF4sWTKGNWvuZ+3aCbz5Zn969gxErVYRG5vC669v4ZVXNlFSUon57be4KxucjxoVVuGLjKOjjkmTIgH48sto8vOrt/Xy0qUC/vvf7YB1n3pVpwg5O+t5550B6PUatm8/x/ffH6zyGiwWhTff3GrbgvDCCz1rZZpRYKAbHTr4YrEorF6dAEBqaj5PPrma3NwiOnTw5fXX+9X6i7pKq8J/sC9t2voQ7uFO9vFc3nprKz/8YH0DOHBgi3Jj7S2FpeTss/5/6RLpVuntg1Wh1qnxHOSNxk2LJa+UjN/TsBReTgKVZJnJ2pZJ2vJUKFEwBDrg0ql2Kzp0nnq8hjVC7aih5JKZ9JWplOaVUJxqbeiZ9lMyBfEmUMAx3LnW1yMqR+N6uahbrVLx2h2RfDKsJw5a7TWPq21l1Vvt/TxtWwoddBpCvS8neMuqt+xJrVbxwAOX+7TI1j1RVePGtQXg998TycwsIDk5j/j4DNRqVYU9eUT94uioY+nSe2q0P2h1lTU8B/j0030UFpbQrp2v7cK1vQQFufPQQxEAzJq10/b+tmzrXkSEH66uNdvDqVUrb+64IxhFUZg9e3e5C5fXcuGCtULbXk3OhahPZPueqLKyJucVbd0r06qVF927N2HXrvO88cYWPvts2A1fHC0WhVdf3cyePRcwGnV89NE/CA8vX4lVVFSCTqe56r4cHLQMGhTCoEEhpKebWL78BJ99to9Vq+LJyyvmP/8ZUONVMlWRmVnAvn1JpKebMJnM5b5at/aucPxyTYqNTeHkyUsYDNprbp0DuOuu1syff4izZ7OZN++gbV98Vbz77g6ysgpp2dKLhx+OqNZ6Q0O9ePHFXrzxxhbmzNlLUJA7Op2GuLgM4uIyiI/PxGQyc9ddrRg3rm25/lglJRZefnkja9cmolareOmlPowYUXuNPocNC+XgwRRWrIjj7rvDePrp30lJyaNZM3fef39QhQ3Qa4PeR49fb2+KC0sxmc18vSqR/BJr5cj48eXjK2d/DkqhBa2nrlYrgTRGDV6DfUj/LZWSSyVkrE3HNdKN/CN5FJ4tsFWX6P0MePSzz1QXnbsO72E+1uqt7BJSf0pGMf+5EBU4BBlx7uCK3qdqk/pE7TE2d0TrpqUk2xrP6griROuutes2y7KqLLVKxYAWASw4mEiEnxdatbrC4+xp6NBQ5s6NIS0t37aFRYjKatfOlzZtGnHkSCoLPzuAs0aLpchC+y7+uLv/PXvrNTR1nYy60rBhofzvf3ttF4ifeqprnVTfTJzYkTVrEjl3Lps5c/YyZVQE63+Ox1JkoW8tVQA+/nhnNm48zfbt5xg8eD4+Pk6EhXkTHu5DRIQfkZH+5R6Lskqpxo3lgpj4+5GklKgSaz8p60Sf6zWMVqlUTJ9+G2PHLiE6+iK//HL8hpP4PvpoF7//noBGo+bdd++8KiEFVOoDvre3IxMndiQkxJP/+7/1bNlyhqeeWs377w+6qaaKr722mejoi3TuHGAbM+vkVPEH15ISC7GxKezadZ4dO87ZRhhXZNWqeJo0ca2Rsvhjx9JYtuw4mZkF6PUatFo1Op2aEycyABg0qEW5yXN/pdWqmTKlKy++uI758w8xZkwbvL0r/0Fv48ZTtmTQzJl9b6r3xF13tSI6+iKrVsXz3HNrKzzmiy/2M3/+IcaNa8t997XDwUFr+5trNGrefLO/bStCbbnzzha8++4OTp68xCOPLCchIRMvL0c+/niw3ZtDu0S44nu2gDZFJQwyFbD07Fk6dw6gVStv2zHF6cWYjlnf+Lj1dEdVy29etS5avP7hQ/qKVMwpxWSsSrP9zKGZEad2Luj99HZ9k6p10+E9rBHpq6yJKTTgGOKEU3uX6/a+EnVDpVbhM8qXi99cuOYxPiN9az2Wr3RlVVZUWBAuBj2dA7yve5y96PUa5s4dTlqaqdpbcMXf28juzYled44fPz9IoJsz5tRiwjMdyIvNsWufNNHweXoa6dcviHXrTtKnTzM6dqyb6aR6vYZ//as3jz+8nB8+iqZ5tMLebRdQFIXm0Qp57Ws+toODPXjppT4sWHCIkycvkZaWT1pavq1H2z/+EcKMGX1sn23KekpJpZT4O1IpilKvmu7k5OTg5uZGdnY2rq7ywlffJCRkcu+9P+HgoGXTpoduuCd8wYJDvP/+Tpyc9CxZMuaaU0B++CGWDz/cBcBrr/W7bjVPVezfn8Szz67BZDITHu5T7URBTMxFHnvst3Lf02jURET40qGDH/n5xWRkFJCZWUBGRgEpKXkUFpa/Qt6qlTdBQW44OupsXwkJmWzceBp/fxcWLx5drWkyJSUWNmw4xcKFh4mNvf7Eum+/jaqwn9SVFEXhkUeWExubwqhRYUyfflul1rF582mmT99AUVEJEyd2rJGm4gUFZh577Dfi4jJo1sydli09CQ31IjTUi7y8Yr76Ksa2V9/RUUfjxq7Ex2eg12t499076dWrZnsEXMv06X/YmsgbjTq+/HI4rVtf/QHVHsyXzKQtS+b0ySzmxcQz6Y0edOzoj6IoKGaFjN/TMKcUY2zhiEf/mt/SeC3FKUVkrEpDUcAx1BGntnWfACotLKXwVAEOgQ5onOUaTX2XF5tD2tIUW8UUWCukfEb62v2DsmJROP1aQrm1/JXWXUvQjBC7JsuEuFl5sTmc++ock37dxqWCy9NTPxzag6Zuzvg/3FgSU6JKMjJM/PzzMUaPDsfTs3b6RlZGXmwOLz72O1tPJ2PQaigqKSXQzZmPhvYAqNXYLigwExeXwdGjaRw5ksa6dScpLbUQFubDe+8NxNlZT58+3wCwefND17zoLURDU9ncjiSlGrCcnCKOH0/n2LE0jh1LJzu7kH//uw9NmtTO45aTU8T77+9kxYo4unVrzJw5Q294G4tFYeLEXzl8OJU+fZrx3nsDy1VEWCwKCxce5v33dwLw9NPdmDChQ42u++jRNJ58cjXZ2YU0b+7Bp58Oxcurats8Jk9eye7dF+jbtxkBAS5s337uhr2y3N0d6N69CT17BtK9e5MKX4gLCsyMGbOE5OQ8HnywA08+2a3SayottfD997EsWnTEtlddq1UzYEBzOnb0w2y2YDaX2v7brJl7pSchHjiQzKOPLketVrF48RiCgtyve/yPPx7i/fd3oSgKPXsGMmvWwBrbLmmxKJSUWCq8P4tFYdOm08ydG01cnLUazNFRxwcfDLpuJV9N27nzHE8+uRq1WsWHH/6jzvtu5MXmkLM7G3QqdG46SgtLsRRYoNT6dK/SqWg0xg+Nk30TMaUFpajUKtQGaWcoqkexKBScNFGaU4LG1bplr66SPnmxOdet3pIP76KhuTLZ+tORkyw4aL3Y4uts5H/De6FSqSTZKhqksthOT8nnyRU7yC+2XlC4u00w4ztY3xvbM7ajoy/ywgvryM4uxNPTyBNPdObNN7fi6mpgw4YHa/38QtiLJKVuUcXFpXz1VTS//55oa4h3pYEDW/DWW3dU+X5NJjMZGSYaN3a9ai96dnYh8+cfYuHCw5hMZgBmzOjDXXe1rtR9JyZmMn78UkpKLLz99h3ceWcLAM6ezeb11zcTE2PdDjh+fDuefbZHlddeGSdPXmLy5FWkpeXTtWtjPvlkSKX33B86lMLDD/+KRqPml1/uwd/fOhXj3Llsduw4R2LiJdzcDHh6GvHycsTLy4i3tyOBgW6VOseWLWeYOnUNGo2aBQtG0aKFZ6XW9emne/nqqxjAWh49enQ4o0aFVWm73fU899waNm8+w+23BzFr1sAKj7FYFN5/fycLFx4GrE3Up03rVelpezVFURS2bj3Lxo2nGDu2zTWnQtbm+X/66ShNm7rVix4uikUhY2UaxclFV/1MpVPh2t0dp9ZSHi7EzapP1VtC3CxTQj4X5lgn7eUUFvPYr1sxl1oY2qopj0Re7s3YeHJTHEMqrnwXoj66MrbXJJzn8z3W4T//HdSVEK/LAyrsGdtJSblMnbqGhITL0/lat/bmhx9G2eX8QthDZXM7sl+hAUlIyGTGjI3Ex2fYvhcQ4EJ4uA9Nmrjy7bcHWL/+JFOmdK30OFGLRWHZsmN89NFuTCYzBoOW5s09CAnxoGVLL9LTTfz001FbMqplSy8efbSjbbpeZbRo4cnDD0fw5ZfRvPvuDiIjA1ixIo7PPttHcXEpRqOOJ5/sypgx4VV7QKqgrEJq/Pil7NlzgcWLj3DvvW0rddu5c6MBGDq0pS0hBdbJa/fc43atm1Vanz7NuP32IDZtOs1bb23lyy9H3DCZderUJb77zjqVburUHowZE35T/ZsqMmVKV7ZuPcumTac5eDCZDh3KT3EqKDDz0ksb2LzZujf+qae6MWFC+zppYKlSqejTp1mdjatWqVSMGdOmTs5dEZVahedAbwrPFaDWq1EbNagd1KiNatR2GsMsxN+Bc3tXnNq61JvqLSFuxpWN+V0d9IwMC+K3E2e5o3nANY8ToiG4MmbvbNGYk5k5KAo093S95nG1LSDAha+/votXXtnEhg2nbN8T4u9IKqUaAItF4ccfD/HJJ3sxm0vx8DDy3HM96NkzsNwI03/+cyV79lxg3Li2PPdczxve7/nzObzxxhb27bNO01OrVVgsFYdDq1bePPZYJ/r0aVatqR7FxaWMH7+UU6cu4eiosyW5undvwr//fVu5ZE9tWrLkCO+8sx29XsP8+aMIDr5+E9hjx9KYMGEZarWKn38eS2DgzSehKpKSksfo0UsoKDDfsArNYlGYNOk3YmKSK9wSWZPefHMLy5Ydp317X776agSKAocPp7Jt21nWrTvJuXPZ6PUaXn31dlsFnBBCCCEaniurSa5HKqVEQ1OfY9tiUZg7N5rvvjvItGm9anVitBD2Jtv3bhHJyXm88somW+LottuaMmNG3wr7E5X1tTEadaxceV+5hNWVLBaFRYsOM2fOXgoLSzAYtEyZ0oUxY9qQlJRLQkKm7auoqIS77w7nttua3nTiIzY2hUceWY6iKLi4GHj22e4MHx5q18oaRVF46qnV7Nx5nrAwH7755q7rNmt//vm1bNp0miFDWvLaa/1qdW3z58fywQe7cHU18PPPY/HwqLgZ5PLlJ3jttc04OGhZsmRMrSb00tLyiYpaRFFRCT17BnL0aBpZWYW2n7u5OfD++wOvqqISQgghRMMiDfzFraohxLbFolTrwr8Q9ZkkpRq43NwifvghlgULDlNQYMbBQcvUqT0YObL1NZM4iqIwbtzPJCRkMmVKVx56KOKqY/Lyinnmmd85cMDaxyky0p8ZM/rWWnP0v1q+/AQnTqTz0EMR+PjUzVW2tLR87rnnJ3JyinjssU5MmtS5wuPi4zMYN+5nVCoVS5bcuNn3zSottTBhwjLi4jIYPjyUmTNvv+qYS5cKuPvuxeTkFPHMM925//72tbomgP/9by9ffx1j+7ezs56ePQPp3bspvXs3vWbyUwghhBANizTwF7cqiW0h7E+SUg1UYWEJixYd5rvvDpKTY21S3L69L6+8cjtNm95469jKlXHMnLkJb29Hli8fV25imcWiMHXqGrZtO4ujo45nnulOVFTrv2VWfu3aRKZP/wO1WsXXX99F27aNrjrm//5vPevXn6x28/jqOHw4lYcf/hVFURgxohVTpnQtVxU3c+ZGVq6MJzTUi++/H2mXhuImk5mPPtqF0aijT59mtG/ve93qMiGEEEI0XNLAX9yqJLaFsC9JSjUAFotCVlYh6ekm0tNNJCZm8sMPh8jIMAEQHOzBE090pl+/oEpvcTObSxkxYiFpafnMnNmX4cMv70suq3jR6zV89dUIu08oq2/+/e8/WLMmkaZN3Zg/fxRGo872s1OnLjF27E8oisLChaMJCancRLya8MUX+/nii/0AuLgYeOKJzoweHU509EUef3wFKpWKb76pOJEmhBBCCHGzFIsiDfzFLUliWwj7kaRUPRYdfZE33tjC+fM5FTYWDwhwYdKkSAYPblmtKqZ58w4ye/Zumjf3YNGi0ahUKv744yTTpq0H4PXX+zF4cMub/j0aupycIu699ydSU/Nxd3egWTM3mjRxJTDQjZiYi+zefYF+/YJ4992Bdl9bbGwK77yznRMn0gEIDfXCZDJz/nwOY8aEM21ab7uvSQghhBBCCCGEqAxJStVTJpOZ0aMXk5qaD1hHyXt4OODt7Yi3tyO33daUqKjW6HSaG9zTteXmFjF06AJMJjOzZw/Gx8eRhx/+lcLCEu6/vz3PPNO9pn6dBm/v3gs899xa2zTAv/rhh1G0bu1t51VZWSwKS5ceY86cveTmWrdyenk58vPPY3F21tfJmoQQQgghhBBCiBupbG5Ha8c1CeDLL/eTmppPQIALX3wxHG9vxxrvz+PiYmDkyNbMn3+IuXOjSU83UVhYQrdujXnyya41eq6GrkuXxvz++/2cOZPF+fM5nDuXw/nz1q/OnQPqLCEFoFarGD06nDvuCOaTT/awdetZZszoIwkpIYQQQgghhBC3BKmUsqP4+AzGj1+KxaLw0Uf/oFevprV2ruTkPEaM+NG2PbBxY1e+/36kTEoTQgghhBBCCCFErapsbkdGaNmJxaLw9tvbsFgU7rgjuFYTUgB+fs4MHNgCAKNRx3vvDZSElBBCCCGEEEIIIeoN2b5nJ7/+epzY2BQcHXU891xPu5xz8uQuFBaWMHp0uF2nxwkhhBBCCCGEEELciCSl7CAzs4CPP94DwBNPdKZRIye7nNff34VZs+w/OU4IIYQQQgghhBDiRmT7nh189NEucnKKCA31YuzYNnW9HCGEEEIIIYQQQog6J0mpWrZvXxIrV8ajUqmYPv02NBp5yIUQQgghhBBCCCEkQ1KLzOZS/vOfbQDcfXcYbds2quMVCSGEEEIIIYQQQtQPkpSqRVqtmoceiqBFC08mT+5S18sRQgghhBBCCCGEqDdUiqIodb2IK+Xk5ODm5kZ2djaurq51vZwaYbEoqNWqul6GEEIIIYQQQgghRK2rbG5HKqXsQBJSQgghhBBCCCGEEOVJUkoIIYQQQgghhBBC2J0kpYQQQgghhBBCCCGE3WnregF/VdbiKicnp45XIoQQQgghhBBCCCGqqiync6M25vUuKZWbmwtAYGBgHa9ECCGEEEIIIYQQQlRXbm4ubm5u1/x5vZu+Z7FYSEpKwsXFBZXKvg3Cc3JyCAwM5Ny5c7fM5D/R8EgcivpA4lDYm8ScqGsSg8LeJOZEfSBxKGqLoijk5uYSEBCAWn3tzlH1rlJKrVbTpEmTOl2Dq6ur/A8p6pzEoagPJA6FvUnMibomMSjsTWJO1AcSh6I2XK9Cqow0OhdCCCGEEEIIIYQQdidJKSGEEEIIIYQQQghhd5KUuoLBYGDmzJkYDIa6Xor4G5M4FPWBxKGwN4k5UdckBoW9ScyJ+kDiUNS1etfoXAghhBBCCCGEEELc+qRSSgghhBBCCCGEEELYnSSlhBBCCCGEEEIIIYTdSVJKCCGEEEIIIYQQQtidJKWEEEIIIYQQQgghhN01iKTU22+/TZcuXXBxcaFRo0ZERUVx4sSJcscUFhYyefJkvLy8cHZ25u677yYlJaXcMU899RSRkZEYDAYiIiKuOs/p06dRqVRXfe3ateuGa5wzZw5BQUE4ODjQrVs39uzZc8P7ValULFmypHoPirCrhh6DAMnJyUyYMAE/Pz+cnJzo1KkTP//8c9UfDFFnboU4TExMZOTIkfj4+ODq6srYsWOvWp+oP+p7zG3ZsoXhw4cTEBCASqXil19+ueoYRVF4+eWX8ff3x2g0MmDAAOLj46v8WIi6cyvE4dKlSxk4cCBeXl6oVCoOHDhQ1YdB2ElDjzez2cy0adNo164dTk5OBAQE8MADD5CUlFStx0PUDXvFIVhfJ2fNmkVoaCgGg4HGjRvz5ptv3nCNS5YsoXXr1jg4ONCuXTtWrVpV7ufyvCcqq0EkpTZv3szkyZPZtWsX69atw2w2M3DgQPLz823HPPvss/z2228sWbKEzZs3k5SUxKhRo666r4kTJ3LPPfdc93zr16/n4sWLtq/IyMjrHr9o0SKmTp3KzJkziY6OpkOHDgwaNIjU1FQAAgMDy93fxYsXefXVV3F2dmbw4MHVeESEvTX0GAR44IEHOHHiBMuXL+fQoUOMGjWKsWPHEhMTU8VHQ9SVhh6H+fn5DBw4EJVKxYYNG9i+fTvFxcUMHz4ci8VSjUdE1Lb6HnP5+fl06NCBOXPmXPOY//73v8yePZvPPvuM3bt34+TkxKBBgygsLLzBby/qi1shDvPz8+nduzfvvPPODX5bUdcaeryZTCaio6OZMWMG0dHRLF26lBMnTjBixIhK/PaivrBnHD799NPMnTuXWbNmcfz4cZYvX07Xrl2vu74dO3Ywbtw4HnnkEWJiYoiKiiIqKorDhw/bjpHnPVFpSgOUmpqqAMrmzZsVRVGUrKwsRafTKUuWLLEdc+zYMQVQdu7cedXtZ86cqXTo0OGq7586dUoBlJiYmCqtp2vXrsrkyZNt/y4tLVUCAgKUt99++5q3iYiIUCZOnFil84j6oyHGoJOTkzJv3rxyt/P09FS+/PLLKp1L1B8NLQ7XrFmjqNVqJTs723ZMVlaWolKplHXr1lXpXKJu1LeYuxKgLFu2rNz3LBaL4ufnp7z77ru272VlZSkGg0H58ccfq30uUbcaWhzW9DmEfTXkeCuzZ88eBVDOnDlT7XOJulVbcXj06FFFq9Uqx48fr9J6xo4dqwwdOrTc97p166ZMmjTpqmPleU/cSIOolPqr7OxsADw9PQHYv38/ZrOZAQMG2I5p3bo1TZs2ZefOnVW+/xEjRtCoUSN69+7N8uXLr3tscXEx+/fvL3dutVrNgAEDrnnu/fv3c+DAAR555JEqr03UDw0xBnv27MmiRYvIzMzEYrGwcOFCCgsLuf3226u8PlE/NLQ4LCoqQqVSYTAYbMc4ODigVqvZtm1bldcn7K8+xVxlnDp1iuTk5HLrc3Nzo1u3btVan6gfGlociobtVoi37OxsVCoV7u7utXL/ovbVVhz+9ttvNG/enBUrVhAcHExQUBCPPvoomZmZ173dzp07y50bYNCgQfLaKqqlwSWlLBYLzzzzDL169aJt27aAtVeOXq+/6onW19eX5OTkSt+3s7Mz7733HkuWLGHlypX07t2bqKio675ApKenU1paiq+vb6XP/dVXXxEWFkbPnj0rvTZRfzTUGFy8eDFmsxkvLy8MBgOTJk1i2bJlhISEVHp9ov5oiHHYvXt3nJycmDZtGiaTifz8fJ5//nlKS0u5ePFipdcn6kZ9i7nKKFtDVV6jRf3WEONQNFy3QrwVFhYybdo0xo0bh6ura43et7CP2ozDkydPcubMGZYsWcK8efP49ttv2b9/P6NHj77u7ZKTk+W1VdQYbV0voKomT57M4cOHa+Wqure3N1OnTrX9u0uXLiQlJfHuu+8yYsQItm7dWq4H1Oeff06/fv2qdI6CggIWLFjAjBkzamzdwr4aagzOmDGDrKws1q9fj7e3N7/88gtjx45l69attGvXrsZ/F1G7GmIc+vj4sGTJEp544glmz56NWq1m3LhxdOrUCbW6wV0j+dupbzE3fvz4Gl+HqP8kDoU9NfR4M5vNjB07FkVR+PTTT2ts7cK+ajMOLRYLRUVFzJs3j9DQUMBaQBEZGcmJEycwGo2Eh4fbjp8+fTrTp0+v8XWIv7cGlZSaMmUKK1asYMuWLTRp0sT2fT8/P4qLi8nKyiqXLU5JScHPz++mztmtWzfWrVsHQOfOnctNDfD19cVgMKDRaK6adHCtc//000+YTCYeeOCBm1qXqBsNNQYTExP55JNPOHz4MG3atAGgQ4cObN26lTlz5vDZZ5/d1BqFfTXUOAQYOHAgiYmJpKeno9VqcXd3x8/Pj+bNm9/U+kTtqo8xVxlla0hJScHf37/c+q41hUjUXw01DkXD1NDjrSwhdebMGTZs2CBVUg1Ubcehv78/Wq3WlpACCAsLA+Ds2bP069evXByWbR/08/Or9OdfIW6kQVyaVhSFKVOmsGzZMjZs2EBwcHC5n0dGRqLT6fjjjz9s3ztx4gRnz56lR48eN3XuAwcO2N7IGo1GQkJCbF8uLi7o9XoiIyPLndtisfDHH39UeO6vvvqKESNG4OPjc1PrEvbV0GPQZDIBXFWNotFoZOpZA9LQ4/BK3t7euLu7s2HDBlJTU2UqUD1Vn2OuMoKDg/Hz8yu3vpycHHbv3n3T6xP209DjUDQst0K8lSWk4uPjWb9+PV5eXje1LmF/9orDXr16UVJSQmJiou17cXFxADRr1gytVlsuDsuSUj169Ch3boB169bJa6uolgZRKTV58mQWLFjAr7/+iouLi22vqpubG0ajETc3Nx555BGmTp2Kp6cnrq6uPPnkk/To0YPu3bvb7ichIYG8vDySk5MpKCiwZX3Dw8PR6/V899136PV6OnbsCMDSpUv5+uuvmTt37nXXN3XqVB588EE6d+5M165d+fDDD8nPz+fhhx8ud1xCQgJbtmxh1apVNfjoCHto6DHYunVrQkJCmDRpErNmzcLLy4tffvmFdevWsWLFilp4xERtaOhxCPDNN98QFhaGj48PO3fu5Omnn+bZZ5+lVatWNfxoiZpQ32MuLy+PhIQE279PnTrFgQMH8PT0pGnTpqhUKp555hneeOMNWrZsSXBwMDNmzCAgIICoqKiafbBErWnocQiQmZnJ2bNnSUpKAqwfHsFabSCVBfVLQ483s9nM6NGjiY6OZsWKFZSWltp+B09PT/R6fU0+XKKW2CsOBwwYQKdOnZg4cSIffvghFouFyZMnc+edd5arnvqrp59+mr59+/Lee+8xdOhQFi5cyL59+/jiiy9sx8jznqi0uhv8V3lAhV/ffPON7ZiCggLln//8p+Lh4aE4OjoqI0eOVC5evFjufvr27Vvh/Zw6dUpRFEX59ttvlbCwMMXR0VFxdXVVunbtWm7M5vV8/PHHStOmTRW9Xq907dpV2bVr11XH/Otf/1ICAwOV0tLSaj8Wom7cCjEYFxenjBo1SmnUqJHi6OiotG/fXpk3b95NPS7Cvm6FOJw2bZri6+ur6HQ6pWXLlsp7772nWCyWm3pcRO2p7zG3cePGCu/3wQcftB1jsViUGTNmKL6+vorBYFDuuOMO5cSJEzXx8Ag7uRXi8JtvvqnwmJkzZ9bAIyRqUkOPt1OnTl3zd9i4cWMNPUqittkrDhVFUS5cuKCMGjVKcXZ2Vnx9fZWHHnpIycjIuOEaFy9erISGhip6vV5p06aNsnLlynI/l+c9UVkqRVGUitNVQgghhBBCCCGEEELUjgbRU0oIIYQQQgghhBBC3FokKSWEEEIIIYQQQggh7E6SUkIIIYQQQgghhBDC7iQpJYQQQgghhBBCCCHsTpJSQgghhBBCCCGEEMLuJCklhBBCCCGEEEIIIexOklJCCCGEEEIIIYQQwu4kKSWEEEIIIYQQQggh7E6SUkIIIYQQQgghhBDC7iQpJYQQQgghhBBCCCHsTpJSQgghhBBCCCGEEMLuJCklhBBCCCGEEEIIIezu/wO3yNjmprNLDQAAAABJRU5ErkJggg==", + "image/png": 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", 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" ] @@ -300,17 +291,23 @@ "metadata": {}, "source": [ "## 2. Adjusting the Anomaly Detection Process\n", - "This section explores two key approaches to enhancing anomaly detection: fine-tuning the model to boost forecast accuracy and adjusting forecast horizons and step sizes to optimize time series segmentation and analysis. These strategies allow for a more tailored and effective anomaly detection process." + "This section explores two key approaches to enhancing anomaly detection: \n", + "\n", + "1. fine-tuning the model to boost forecast accuracy\n", + "2. adjusting forecast horizon and step sizes to optimize time series segmentation and analysis. \n", + "\n", + "These strategies allow for a more tailored and effective anomaly detection process." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### 2.1 Finetune TimeGPT\n", + "### 2.1 Fine-tune TimeGPT\n", "TimeGPT uses forecast errors for anomaly detection, so improving forecast accuracy reduces noise in the errors, leading to better anomaly detection. You can fine-tune the model using the following parameters:\n", + "\n", "* `finetune_steps`: Number of steps for finetuning TimeGPT on new data.\n", - "* `finetune_depth`: Intensity of fine-tuning, with options ranging from 1 to 5.\n", + "* `finetune_depth`: Level of fine-tuning controlling the quantity of parameters being fine-tuned (see our [in-depth tutorial](https://docs.nixtla.io/docs/tutorials-controlling_the_level_of_fine_tuning))\n", "* `finetune_loss`: Loss function to be used during the fine-tuning process." ] }, @@ -340,7 +337,7 @@ " finetune_steps = 10, # Number of steps for fine-tuning TimeGPT on new data\n", " finetune_depth = 2, # Intensity of finetuning\n", " finetune_loss = 'mae' # Loss function used during the finetuning process\n", - " )" + ")" ] }, { @@ -350,7 +347,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -363,14 +360,24 @@ "plot_anomaly(df, anomaly_online_ft, time_col = 'ds', target_col = 'y')" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the plot above, we can see that fewer anomalies were detected by the model, since the fine-tuning process helps TimeGPT better forecast the series." + ] + }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2 Change forecast horizon and step\n", - "Similar to cross-validation, the anomaly detection method generates forecasts for historical data by splitting the time series into overlapping windows. The way these windows are defined can impact the anomaly detection results. Two key parameters control this process:\n", + "Similar to cross-validation, the anomaly detection method generates forecasts for historical data by splitting the time series into multiple windows. The way these windows are defined can impact the anomaly detection results. Two key parameters control this process:\n", + "\n", "* `h`: Specifies how many steps into the future the forecast is made for each window.\n", - "* `step_size`: Determines the interval between the starting points of consecutive windows." + "* `step_size`: Determines the interval between the starting points of consecutive windows.\n", + "\n", + "Note that when `step_size` is smaller than `h`, then we get overlapping windows. This can make the detection process more robust, as TimeGPT will see the same time step more than once. However, this comes with a computational cost, since the same time step will be predicted more than once." ] }, { @@ -383,13 +390,7 @@ "output_type": "stream", "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", - "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", "WARNING:nixtla.nixtla_client:Detection size is large. Using the entire series to compute the anomaly threshold...\n", "INFO:nixtla.nixtla_client:Calling Online Anomaly Detector Endpoint...\n" ] @@ -405,7 +406,7 @@ " step_size = 1, # Step size for moving through the time series data\n", " level=80, \n", " detection_size=150\n", - " )" + ")" ] }, { @@ -415,7 +416,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] diff --git a/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index 8c2d93d5..7e367c9c 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -42,36 +42,6 @@ " from dotenv import load_dotenv" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#| hide\n", - "def plot_anomalies(df, unique_ids, rows, cols):\n", - " fig, axes = plt.subplots(rows, cols, figsize=(12, rows * 2))\n", - " for i, (ax, uid) in enumerate(zip(axes.flatten(), unique_ids)):\n", - " filtered_df = df[df['unique_id'] == uid]\n", - " ax.plot(filtered_df['ts'], filtered_df['y'], color='navy', alpha=0.8, label='y')\n", - " ax.plot(filtered_df['ts'], filtered_df['TimeGPT'], color='orchid', alpha=0.7, label='TimeGPT')\n", - " ax.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], filtered_df.loc[filtered_df['anomaly'] == 1, 'y'], color='orchid', label='Anomalies Detected')\n", - " ax.set_title(f\"Unique_id: {uid}\", fontsize=8); ax.tick_params(axis='x', labelsize=6)\n", - " fig.legend(loc='upper center', ncol=3, fontsize=8, labels=['y', 'TimeGPT', 'Anomaly'])\n", - " plt.tight_layout(rect=[0, 0, 1, 0.95])\n", - " plt.show()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -83,7 +53,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "In this notebook, we’ll show you how to detect anomalies across multiple time series using our new multivariate method. This method is great for situations where you have several sensors or related time series. We’ll also explain how it works differently from our univariate method." + "In this notebook, we show how to detect anomalies across multiple time series using the multivariate method. This method is great for situations where you have several sensors or related time series. We also explain how it works differently from the univariate method." ] }, { @@ -119,9 +89,30 @@ "source": [ "import numpy as np\n", "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", "from nixtla import NixtlaClient" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Utility function to plot anomalies\n", + "def plot_anomalies(df, unique_ids, rows, cols):\n", + " fig, axes = plt.subplots(rows, cols, figsize=(12, rows * 2))\n", + " for i, (ax, uid) in enumerate(zip(axes.flatten(), unique_ids)):\n", + " filtered_df = df[df['unique_id'] == uid]\n", + " ax.plot(filtered_df['ts'], filtered_df['y'], color='navy', alpha=0.8, label='y')\n", + " ax.plot(filtered_df['ts'], filtered_df['TimeGPT'], color='orchid', alpha=0.7, label='TimeGPT')\n", + " ax.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], filtered_df.loc[filtered_df['anomaly'] == 1, 'y'], color='orchid', label='Anomalies Detected')\n", + " ax.set_title(f\"Unique_id: {uid}\", fontsize=8); ax.tick_params(axis='x', labelsize=6)\n", + " fig.legend(loc='upper center', ncol=3, fontsize=8, labels=['y', 'TimeGPT', 'Anomaly'])\n", + " plt.tight_layout(rect=[0, 0, 1, 0.95])\n", + " plt.show()" + ] + }, { "cell_type": "code", "execution_count": null, @@ -163,7 +154,7 @@ "## 1. Dataset\n", "In this notebook example from SMD dataset. SMD (Server Machine Dataset) is a benchmark dataset for anomaly detection with multiple time series. It monitors abnormal patterns in server machine data. \n", "\n", - "Here we use a set of monitoring data from a single server machine(machine-1-1) that has 38 time series. Each time series represents a different metric being monitored, such as CPU usage, memory usage, disk I/O, and network I/O. " + "Here, we use a set of monitoring data from a single server machine(machine-1-1) that has 38 time series. Each time series represents a different metric being monitored, such as CPU usage, memory usage, disk I/O, and network I/O. " ] }, { @@ -199,7 +190,7 @@ "metadata": {}, "source": [ "### 2.1 Univariate Method\n", - "Univariate anomaly detection analyzes each time series independently, flagging anomalies based on deviations from its historical patterns. This method is effective for detecting issues within a single metric but ignores dependencies across multiple series. As a result, it may miss collective anomalies or flag irrelevant ones in scenarios where anomalies arise from patterns across multiple series, such as system-wide failures, correlated financial metrics, or interconnected processes. That’s when multiseries anomaly detection comes into play" + "Univariate anomaly detection analyzes each time series independently, flagging anomalies based on deviations from its historical patterns. This method is effective for detecting issues within a single metric but ignores dependencies across multiple series. As a result, it may miss collective anomalies or flag irrelevant ones in scenarios where anomalies arise from patterns across multiple series, such as system-wide failures, correlated financial metrics, or interconnected processes. That’s when multivariate anomaly detection comes into play." ] }, { @@ -228,7 +219,7 @@ " level=95, \n", " detection_size=475, \n", " threshold_method = 'univariate' # Specify the threshold_method as 'univariate'\n", - " )" + ")" ] }, { @@ -238,7 +229,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -257,9 +248,9 @@ "metadata": {}, "source": [ "### 2.2 Multivariate Method\n", - "The multivariate anomaly detection method considers multiple time series simultaneously. Instead of treating each series in isolation, it accumulates the anomaly scores for the same time step across all series and determines whether the step is anomalous based on the combined score. This method is particularly useful in scenarios where anomalies are only significant when multiple series collectively indicate an issue. To apply multivariate detection, simply set the parameter `threshold_method` as `multivariate`.\n", + "The multivariate anomaly detection method considers multiple time series simultaneously. Instead of treating each series in isolation, it accumulates the anomaly scores for the same time step across all series and determines whether the step is anomalous based on the combined score. This method is particularly useful in scenarios where anomalies are only significant when multiple series collectively indicate an issue. To apply multivariate detection, simply set the `threshold_method` parameter to `multivariate`.\n", "\n", - "We can see that the anomalies detected for each time series are the same as those based on the accumulated error. " + "We can see that the anomalies detected for each time series occur at the same time step since they rely on the accumulated error across all series." ] }, { @@ -288,7 +279,7 @@ " level=95,\n", " detection_size=475,\n", " threshold_method = 'multivariate' # Specify the threshold_method as 'multivariate'\n", - " )" + ")" ] }, { @@ -298,7 +289,7 @@ "outputs": [ { "data": { - "image/png": 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44Yfx9ttvY/Xq1fjf//1ffO1rXyv4vakURxxxBOrq6vDqq68CAD755BP09fXhtNNOy/mc9vZ2zJw50/x91qxZaG9vH/N9JQiCIIiJBMVQFEMVG0MRBFE81F5HEJMQjuPMn9lFur6+HnPmzMGuXbvQ0tKStvzrr7+Om2++GQDQ0tKCs88+u6DtPP3001i5ciUOP/xwAICqqgXvYyAQwJo1a8yM3yGHHIITTjjB/PvZZ5+ddz++8IUvoKamBgBw2GGHwW63w+v1AgCWLl2K7du3AwB27dqFiy++GB0dHRBFEYODg9i1axemTZuGd999F6+88oq5zoaGBvPn8847Dy6XCwBw1FFHYefOnVn3g2VA2c9//OMfAQDPPPMM1q5di6OPPtpcdnBwENFoFE6ns7A3qUL84Ac/wJ/+9Cd84QtfwO23347vfve7accIQRAEQRAGFENRDGWFYiiCGHtIdCKICUxDQwMGBgZQXV1tPtbf34/Gxkbzd4fDYf4sCAIURRl1vdaLqSiKaYFQLBYzf9Z1HT/72c9w5ZVXlvoScm53NDJfV67X+dWvfhW/+c1vcMEFFwAwSqutr6HQ9ed633Itp+s6vvGNb+DXv/71iOdccMEF2LFjBwAjWK2rq8u5H8Usm4vzzz8fP/7xj/HJJ5/g2WefNYPjXMyYMSOtxL+trQ0zZswoersEQRAEMVGhGMqAYqj8FBtDEQRRPNReRxATmGXLluGvf/2r+fv999+POXPmYMqUKUWt59RTT8Xdd98NwPAmePbZZ82/zZs3D6tWrYKqqohEImkl0ueeey7uuOMODA4OAgBkWcYnn3xS0DZ9Ph+WLl2K+++/HwCwceNGvPvuu0XtdyEMDQ2ZWbQHH3wQQ0NDAACPx4OTTjoJt9xyi7lsX19fxbZ79tln48EHHzTb0jRNw6pVqwAATzzxBNasWYM1a9aMGgAVs2wuRFHEt7/9bZx99tk477zz0gLsbHz5y1/GAw88gHA4jHg8jrvvvhtf/epXS9o2QRAEQUxEKIYaHYqhio+hCIIoHhKdCGICc9ttt6GrqwuLFy/GkiVL8NBDD+Hxxx8vej1/+MMf8MEHH2DRokW49NJL8dnPftb82/nnn4+pU6di4cKFOOuss7B06VLzbxdffDG++c1v4pRTTsGhhx6KJUuW4I033ih4u/fffz/+9re/4eCDD8b//M//4KSTTjL/NpofQTGv7YILLsDSpUvxySefpFXsPPDAA1i1ahUOOuggLFmyBH/605/K3h7jxBNPxO9+9zucd955OPTQQ3HQQQfhkUceybpsJBLBtGnT8OUvfxmbNm3CtGnT8LOf/azsZa1861vfQmdnJ6666qpRlz355JNx4YUX4pBDDsHChQvx+c9/HmedddaozyMIgiCIyQLFUIW9Noqhiouhtm7dimnTpuGaa67BK6+8gmnTpuHPf/7zqM8jiE8znG616ycI4lPBj370I3g8HnP6CjH5eeKJJ/CXv/ylYINTgiAIgiCKh2Ko/Q+KoQhibCFPJ4IgiEnOaaedhm3btuGpp54a710hCIIgCIKYNFAMRRBjD1U6EQRRNDfccAOWL18+4vEnn3wSc+fOHYc92v+58847s5a2//GPf8SJJ5444nHr1Bsr3/jGN3D11VePxS4SBEEQBDEKFEPteyiGIojxhUQngiAIgiAIgiAIgiAIouKQkThBEARBEARBEARBEARRcUh0IgiCIAiCIAiCIAiCICrOpDAS1zQNe/fuhdfrBcdx4707BEEQBEHsJ+i6jmAwiKlTp4Ln969cHMVPBEEQBEGMBcXET5NCdNq7dy+mT58+3rtBEARBEMR+yp49ezBt2rTx3o2KQvETQRAEQRBjSSHx06QQnbxeLwDjBfl8vnHeG4IgiPFB13REd0WgBhUIXhHO2S5wPFUvEEQ5BAIBTJ8+3Yw19icofiIIgqD4iSDGgmLip6JFp7fffhs33XQTPv74Y3R1deGpp57Cueeem/c5b731Fq655hps3LgR06dPx//8z/9kHUOZC1YS7vP5KGgiCOJTSWhdAH3Le6H4FfOxaFUIDec3wbOYzosEUS5j3X5G8RNBEMS+h+InghhbComfijYvCIfDOPTQQ3H77bcXtPyuXbtw5pln4pRTTsGaNWvwwx/+EJdffjleeeWVYjdNEATxqSS0LoCuezrTAiYAUPwKuu7pRGhdYJz2jCCIQqH4iSAIYt9C8RNBTAyKrnQ6/fTTcfrppxe8/B133IHZs2fjlltuAQAsXLgQ7777Lm699VYsW7as2M0TBEF8qtA1HT2PduVdpu+pHrgP9lKpOEFMYCh+IgiC2HdQ/EQQE4cxH9OyYsUKnHrqqWmPLVu2DCtWrMj5nHg8jkAgkPaPIAji08jgq/3QIhoAIKGq+MfaHVixpydtGWVYQbQ1Mh67RxDEGEHxE0EQROlY4ycA2DHgx52rtiCckM3HKH4iiH3DmItO3d3daGpqSnusqakJgUAA0Wg063NuvPFGVFVVmf9o8gpBEJ9GdE3H8L8Gzd9vfnc9nty4C39YsXHEsmpAGfEYQRCTF4qfCIIgSiMzfkooKn78ykd4cdsevN3WnbYsxU8EMfaMuehUCj/72c/g9/vNf3v27BnvXSIIgtjnRFsj0KJGlq4zEMaqzj4ARvCUieCbFMNICYIYQyh+IgiCSI+fAOCFbalzoaJpactS/EQQY8+Yf8uam5vR05PeCtLT0wOfzwen05n1OXa7HXa7fax3jSAIYkJjzb71hlKVDR67lLYc7+LhnOPaZ/tFEMTYQ/ETQRBEaWRWL328t9/8WeBTNRcUPxHEvmHMK52OPfZYvP7662mPvfrqqzj22GPHetMEQRCTGmv2LSynAihd19OWqz6plkwwCWI/g+IngiCI0sisXhqKxs2fNS0VQ1H8RBD7hqJFp1AohDVr1mDNmjUAjJG+a9asQXt7OwCjtPvSSy81l//2t7+N1tZW/PjHP8aWLVvw5z//GY899hiuvvrqyrwCgiCI/RTnHBfEKiNwCidSopNqEZ14F4/az9fv830jCKI4KH4iCILYN1jjJwAYillEJxgxFMVPBLHvKFp0WrVqFZYuXYqlS5cCAK655hosXboU1113HQCgq6vLDKAAYPbs2XjhhRfw6quv4tBDD8Utt9yCO++8k8b9EgRBjALHc2g43zAStk5bsSTp0HThFMrSEcQkgOIngiCIfYM1forKCmJyygtTTQZRFD8RxL6D0zP7NCYggUAAVVVV8Pv98Pl84707BEEQ+5TQugBu+snbWL66FQAgCTye/PdlaDivCZ7FdE4kiHLYn2OM/fm1EQRBjEZoXQBr7mnFdx5623zs0mMPwHduOJbiJ4Iok2JiDLLrJwiCmOB4FvsgHe+D1GEDVB28xGPWtfMoQ0cQBEEQBJEDz2IfnBc3QnrNiJ8gcKg9q4EEJ4LYx5DoRBAEMQkIhRLg7amOaBKcCIIgCIIgcqNrOjrXD5mCE2/noU38Jh+C2O8g0YkgCGISEAjE037XNB08CU8EQRAEQRAjCK0LoG95D7Z/uAfyQNIXU+AQbY+O744RxKeQoo3ECYIgiH1PKJRI+9068pcgCIIgCIIwCK0LoOueTih+BUNRS9JO1TH43hBC6wLjt3ME8SmERCeCIIhJQLZKJ4IgCIIgCCKFrunoW95j/p4mOgHQdB19T/VApziKIPYZJDoRBEFMAjJFJ1XVxmlPCIIgCIIgJibR1ggUv2L+PhwzKsWrHDYAgK7rUIYVRFsj47J/BPFphEQngiCICY6maggMxKBFVGhxQ2xSVcrQEQRBEARBWFEDStrvcUUFALgkw8pYTRqJZy5HEMTYQUbiBEEQE5jQugB2P9KJeLel0kngEFjnh+e4hvHbMYIgCIIgiAmG4Eu/vVWSIpNNMGotWFdd5nIEQYwdVOlEEAQxQWFGmMP9xqQVgU2rU3XsfWBv0UaYuqYjsiOM4Go/IjvC5GdAEARBEMR+hXOOC2JVSlBSknYENkEAYHg6idUinHNc47J/BPFphCRegiCICYjVCDOcMErAPTYJ/ngC0FNGmO6DveCYGJUHNjrY6nMgVoloOL8JnsW+sXkRBEEQBEEQ+xCO59BwfhO67ukEAChaZqWTjobzmgqKnQiCqAxU6UQQBDEBsRphRmTjf5ckgocRJGlFGGFaRwdbUfwKuu7ppNHBBEEQBEHsN3gW+zDlshaIVSIULVnpJPKAwMF9mI+SbQSxjyHRiSAIYgJiNbhkJpgOUTBb7LQCjTAzRwdng0YHEwRBEASxP+FZ7MOs6+ZBmG6HVCeh7oga2KfaIdRL471rBPGpg0QngiCICYjV4DJh+hHw4DlDdGLTV0YzwswcHfzhnl5c/8bHGIzEzMfGanQweUgRBEEQBDFecDwH3caBdwnwTnECADSKRQhin0OeTgRBEBMQZoSp+BUkVKPSySYIpuikaYUZYWZWQv32nbUAgLtWb8N/nbA453LlQh5SBEEQBEGMN7JsJO4cDuO2t1TRSdd0RFsjUAMKBJ8Rf5EvFEEUBolOBEEQExCrEaZsqXQSmOikoyAjzFyVUEPReEHLlQLzkMqEeUhNuQwkPBEEQRAEMebIspG4s9uN6XVqMqYqBkqkEUR5UHsdQRDEBIUZYSp243ebwIPjAAgc6i9oLCjQyRwdzND1VKavkqODyUOKIAiCIIiJAqt0sttLq3SiYSwEUT4kOhEEQUxgPIt98J3VAKnRhpql1XDOcMI+1Q7HfHdBz2cVU5lYY65Kjg7O9JB6dP1O/PKt1eb0GGDsPKQIgiAIgiAYmqablU2pSqfCRafMRNrW/mEMWDwxAUqkEUQhkOhEEAQxwZEVFbydh2+WCzavMXWlmEyddXQwQ4PhCTXlspaKloZbvaEUTcOj61vxyd4BbOkbzrkcQRAEQRBEpVGUVMKrlEonayJt11AQP/vnSlzx9Dvp26BEGkGMCnk6EQRBTHDiceZHIEIQktPrisjUAYbw5D7YC+lJG6DqcMx3Yda18ypugmn1hurwh82fHaKQczmCIAiCIIhKw/ycgNKMxK0Jsq39wwUtVwnItJzY36ConyAIYoITixnBjM0mgOeZ6FS8ESbHc+DtRoEr7xbGJIBRQ6nAq3UoaP5sjfEq6SFFEARBEASRDebnBJRmJG5NkHFc7pip0sNYyLSc2N+g9jqCIIgJTjxuBB4OhwhBME7bpY78ZehjYD+gazr6n+41f28dTJlrapYN1p9TOQ8pgiAIgiCIbLBKJ57nIIrFx0/WYSyCRXTSxmgYC5mWE/srJDoRBEFMcBKJ1LjfVKVTeapRKZVSo5FpIm6tdFItAZrgSW+1IwiCIAiCqDSs0kmSSoufrMNYrKJTXEm17VVqGEumaXkoIadNGgbItJyYvJDoRBAEMcFhnk42m2B6OpVb6VTu87OR6WnQEUh5OlmzgmQiThAEQRDEWMOMxCWJL7lSnA1j4d2phFlUUSs+jMWauFvbNYBLn3gL/1i3I20ZMi0nJiskOhEEQUxwmKeT3S6ambqJKDplehpYM4HW7ZGJOEEQBEEQYw1rr7NWOpUS/3gW+1BzfiOkRhukOgnVX2vCrGvnjdn037tXbwMALN/Ylnc5gpgskOhEEAQxwWHtdVZPJ+sY4FIYC08nq/eBruuQLS18rL2OTMQJgiAIgtgXpNrr+LIGsQBAPKGCt/PgXQLQJI3p9F+3LXdyjhJ3xGSERCeCIIgJDjMSL7e9zvqcsfB0snofyFr6+pnoVCnvA4IgCIIgiHywSidR5C3xU2nrYglAAIhE5LL3LRNr4s4tZReWKHFHTFZIdCIIgpjgME8nq5F4KaITC75KfX4hMO8D1Z1+eeHdfEW9DwiCIAiCIPKR3Ui8xEqneKqtLRqtfIubNXFnrXSyVo1T4o6YrFB9HkEQxAQnJTqJZQVNLPgCxk50AgzhqblpBqTnbYCqAwKHhounkuBEEARBEMQ+I5uReKnTf1ksBgDRaOUrnQCWuAOca7eYj/ljCTS3eNBwXhPFUcSkhUQngiCICqNrOqKtEagBBYLPKIUuJzPFsmt2e3ntdfui0snclqKBt6eqnVQa8UsQBEEQxD6kUkbiQHql01i01zE8i31wHl8FqbcHWlyDssSBxlOnwDXPPWbbJIixhkQngiCIChJaF0Df8h5z7C0AiFUiGs4vPUOVvdKpFNEpVelk9SYYC6wZQWDsRS6CIAiCmMxUOmFFpBuJs6Rdqe111rhpLNrrrIQ6opAHZUDVsfuNXjRvLz+WJIjxhEQngiCIChFaF0DXPZ0jHlf8Crru6cSUy1BSsJBe6cTKw0tpr0sFTJmiUKWJxdIDsrEwLicIgiCI/YGxSFgRmUbiRvxUeqXT2BqJM0LrAhhc4zfsCQAMxeIAyo8lCWI8ISNxgiCICqBrOvqW9+Rdpnd5N/QSgh1rpVN57XUp4SceV6DrY1d9lFlJVaqHAkEQBEHsz7CElVVwAlIiQ2hdYJz2bPJjrXSaDO11LJZMqKkYajAST1um76mekmJJghhPSHQiCIKoANHWSFrA+NDaHfjOs+8iEEuYj6l+FYOv9he1Xl3X0yqdymuvUzN+H7vqI2twBlClE0EQBEFkkpmw8scSULT06yWJDKWTMhIvL34C0iudMqu5KwWLJROWmIlVOjGUYQXR1siYbJ8gxgoSnQiCICqAGkgPQJ7YuAs9oSie29qe9vjgy/1FZS2twpBR6VR6eXimyJQpDFUS8nQiCIIgiPxYE1bdoQguW/4v/OzVlWnLkMhQOikjcb6sSnEgvYJ7rCqdWCxpFZ0C8ZHbyow5CWKiQ6ITQRBEBRB82S3y/LEENvcNp7WyFZO1tApD1kqncqfXGeseO1+nkZVOJDoRBEEQhBWrePB+ey8AYOfAyMQUiQylkWqvs1Y6lVZ5ba1uGivRicWScSX/tOFcMSdBTFRIdCIIgqgAzjkuiFUjg4DXdnbiv19diQ86es3HislaMmGI4ziIIl9W0DSelU7UXkcQBEEQ6VjFAynPpLpPk8igazoiO8IIrvYjsiNcVmtheqVTeUbi6dPrxkZ0YrFk3OLppGT4b4rVxmRDgphMfHrOYARBEGMIx3NoOL8p6/Q6APhwTy+Ond5k/l5o1jIeU6DFNdgFAdGdEcvIX6p0IgiCIIjJDBMZFL8CgU/VAqiaZv7+aRIZKj3FL1ul00SeXsdiycTdqURd5v42nNcELo9ASRATEap0IgiCqBCexT7Unlaf9W8clx4gFJK1DK0LYMdNOyH3JoBBBZ23tyP43jC0qEqeTgRBEAQxyWEiAwAIFiEhIqeuz/XnNE54kaES1UljMcUvZSTOV8BIPLVf0ejYxU+exT6gTgSSSUZFN16DWC1iymUtJYlvBDHeUKUTQRBEBan9fD38K4ZHPC5YRKdCspYs+IoMG9PvbMmycCR0yP0ywrvCRe/beFY6scCPIAiCIIgUnsU+TLkMwC9TldLhhAKv3QYA6H+6FxzPTVixoRLVSZlT/LLR91QP3Ad7ixLgUu11QtlG4taYaSxFJ13XIQs67FPtRqX7HCdavjcDzjmuCS8+EkQuqNKJIAjCQrnZOo7n0HBe44jHrRnM0UqjrcGXnPRCsgkCAIBPilf+Vf6i9y2z0snqT1BpqNKJIAiCIArDs9gHabHH/D1kqXQqp9JnrKlUdZJ1it9wLI4fvfwhXtq2J32dJUzxY3FPuZ6YQHrMFA4nSlpHIVhjNd7Og6sS4ZrnJsGJmNRQpRNBEJMKXdMRbY1ADSgQfGJFMz+V8hJwHuSFVC9BHlKAZBk3Bw5itYiG80ZflzX4SiTNJFmlE3upctgIvlzz3AXvV2alk3USS6XJFLTISJwgCIIgsqNrOvo/HDR/7wtHMbPKA0lI1QeUUukzlmRWJ3UFI+gNRXHolDroug6O49DzaFdB+2z1uXxqUxtaBwNoHQzg9AXTcy5XCJU0ErdWcI9lpXhmbEaV4sT+AIlOBEFMGiptMJm57mwm4CxbN+UyFLyNREIF7xRgdwrQ4hqg6qg5vgazrp1XULBoDaoSSbFGMkWnZHm4Xkrwte88nTKDJjISJwiCIIjsRFsjiIZS5tQ3vbMOC+qr8JsvHGU+xip9ikk2jSXWBBkA/O6dtdg9HILHJkHgOfz+9GNQAzsGX+1H3bKGvOuy+lwqeUShYqf4VcpIXNf1tGTa2FaKU/xE7H9Qex1BEJOCsTCYZGRm69Z2D2AoGk9bpu+pnoLb2awVRbydB+8S4GyyF5ydTA++kgFTcooN84bSNL3o4CszW7ZvgybK1BEEQRBENtSAgriSfk3e1u/Pulw5VMLwO9e+7B4OAQBCCRn+WAJb+ocBAMNvD466HTbFDwCckmA+rump5wlVQtFT/CplJJ4ZL8XjCnR9bMQgqnQi9keo0okgiAlPpiik6Tp0XU8bL1xO2bk1W/fWri7834oNOKC+CjeWmGHMJubwReyXdYRyytMpvdJJd3AFBV/WdsTgnnQvhLEsD2fvAc9z0DSdPJ0IgiAIIgeCT0Q8S3JG1bS0WKfYZJOVSleLj7YvHJJJsog2avzEpvh13dMJh5gSncIJ2TRU12Ud4Q3BovY1m5F4KUmwbD6VqqpDFCvf6pi5LUraEfsDVOlEEMSExyoK6bqOn/zzI1zz0gdpGbBSDCYZ6V4CuwAAW8vIMGa2sQFAMQkx6whlJjqJyaCTiVfuxaMLbKF1AbTdsAOdt7ej+4G96HulD/G9cWhRI6DZF0biLpcEgMrDCYIgCCIXzjkuyMLI62TEYiheyOTbXIxFtbhzjgu8M3UraRPSbytZpTZQWPxkTPFrgWYRcoZiKcNuLaIVta+6piPcE4MWUaH2J2CNmIpNhMWiMrS4Bi2iGrYJGLsYiqb/EvsjJDoRBDHhsQYr/ngCOwcC2OMPYzijBa7UsvNEXyqo2RtMCVeZpdOFZhizBSKZJt6jMseBvwZ3YWVfP4CUp5PoFCDVS5Cm2PM+PTPAfG93N/6xdgeg6pD7ZWhRdUxFJ1YenhKdJk7QVMn2AoIgCIIoF47nIMweeV0PJ1JxzWiTb3ORWS2ejWIsBBgcz6H6M7XGNnTd9KCcVeMFkO7NVGj85D7Yi4SeiheGoyOnxBWyryzpNrTKD3lARuDVQXTc3GYm3YoRnULrAtj5252QexPghlXIvQnE98YxsHqo4HUUw8hKJ4pRiMkPtdcRBDHhsQYrA5GU0KSUKApZ0TUd/veHkuuOQbUEIoG4jCqHUdZdTIYxm5hTrMDzf//3Id5a0wEAkBptqF7sQ8v3ZqD+BT/4B7ryijiZAebG3iHc8t76tGXkIQWJfdBe53ROrEqnsTSjJwiCIIhSUT08pLrk5NtkLBKSlYIn3+aCVYsPRmK4b812bOgZwrePWogjW1Lm3qWalNd+vh7Dbw8iFkyZoLskIxZjlU7FxE/R1ghiFkP137+/Ht87ahGOnFb4vloHw6h6yhdTD6qQ+2VI9YWLTmxdEb8hftlEAZoOKKqGjvs7UeNzVDx2YEk7UeShKNqEq3QayynSxP4LVToRBDHhsRpMDkRi5uOyRXgptezcuHAaAsmWjJY667Z8x1QXdFHVdR2h0MjMXLaWu3xs3Nhn/szbeXhmuOCa54YoGqftfCJO5kSZh9btGLmQqiO8N1rUPuUiW+UQy9S53YboNBE8ncbSjJ4gCIIgyiGwNwp5OCU4AUCUV1F/TmNZwgarAn92SzveaevGUDSOVZ19OZcrBo7n0HThFCQswkim6FRMhZYaUBBXUwmxQCyBG99eU/C+ZibdlGSsJPI82C7IQwqUAqrPretKWPw1WRthQlVLqhAbjYlcKZ5p29B5ezvabthB8RMxKlTpRBDEhMdqMNlvqXRKWC7EpZadWwOXSCI9iBmIxDHHqByHrcFW0PquueYVvPNO+4jHR2uvy8wc9feF0/5usxnGmkIy2Mkn4mQGY3sD2b2u4pZsYqnkqhwK9xiCltOZDD7HOVNXaHtBqWb0BEEQBFEqoXUBDG8JAhkJpVAwge779oLjuZKFJ1YFvjeYiiuiWWKSUk3KPYt9qP5KI/A0B04D7MnkmObgMOWylqL2O9GXQLyAeCHXvmYm3WRWbSVw5iAWqDrCO8NwLc4f11nXlUhOFrQJglERLxsxaKkVYvlgnk4ejw2BQHzc4yeGtYLMCkvcTbkMVDFO5IQqnQiCmBQwg8khLVVFFFdUiNVi0UGNFWvgklDTg7B+S6VTIcGY3x/Du+/uyfq3fO112TJHezcMm94DgDHuF4Bl5G/2IETXdChBS8ClavDHRlZeAYBaZtohX+WQf3sIWlQ1M3WlVjr19IRw9dUv46OPRgY6xZAZiL67uxu/e2ctohaT1nLM6AmCIAiiFFhSJK6MjBOYp1M5FTWsWrw7lKputhqUA+WZlAOANM8F+1Q7vNOdqF5SBanRhpovFlehxewO4mr+JF2+fc1MupmiE8+nRCcAieHRk27WdbHKerul0omtu1Q/0VxkDmKZCKLTWPmCEZ8eSHQiCGLS4Fnsg3K4C1KjDVKdhJovNWLWtfPKyqxYW/cSGUIOE50KDcY+/rhrhPk4I1d7XS7hxmr4DVgrnZIjiLNc2Jl41f90r/nYYIbZOpCcMCNw0L3CiL8Viq7p6Hm0y/x9U+8Qdgyk2hMTqgZ5SIHDYby3pZaH//Snr+Odd9rx3e++UPK+AiODwt+/tx4f7OnFM1t2511uIqOqGl58cTu6u0PjvSsEQRBEibCkSGYMAqREp3KSIhzPoe7cRvTkEZ1KrRZnsOocZ5UNnhku8HYeSpHXfWZ3kE18s5LP7iAzQcgSSy5JTBOdOM/o8U96UpK11wnmYBf2WKkVYrlg7XXMnmAieGJaE3earuO5LbvROpjeUkeJOyIfJYlOt99+O2bNmgWHw4Gjjz4aH330Uc5l7733XnAcl/bP4XCUvMMEQUwOxmpCWG9vGLydB+8SwDVKZbdCsdY9YGSlExNsCg3GVq7MXY2Trb0uM3PEAq2EJeCSh4yLvCQZAVKq0imjBD+HeGWt1mI4JRFStVh09sz6mfY8shdaxHh+dzCCa1//GDe8+Qm0pOiWUDVA1WFLbr7QoMm6jfC2ENau7DJHFJdzDOUKCocyRLlKB49jyeOPb8J1172Jr3zl8fHeFYIgCKJEWLKDxQCnzZ+G6VVGu1Y4IY9YrhSiUwSgRgCSiSsmOpVbLc5g1Tl2u2hWZhcbY7DXlym+MZGHkc/uwJpIBFJthGmik8DBPsM56v5Y18Wqr2pdNnhshhgkq1rZFWLZCIeN6nSv15hmqKpazoTmvsJ67L23uwf3rN6GH738Yd7lCMJK0aLTo48+imuuuQY///nPsXr1ahx66KFYtmwZent7cz7H5/Ohq6vL/Ld79+6cyxIEMfkZS6PBnp6UJ0HmWNlSYa17ajKOYRPrBuT4qMGYrukIbwuh/8VevPvcLmix7EFWtkona+ZobfcALnrsDTyxsRW9YYtQpOrQ4hrs9tyeTvnKnpkZOgtgASOAk4cVhDoKz0hlfqbBlanP8vXWvYaBekI2jUNZ8OzgjP0upNIpcxt7/7IHcl8C8oAMtU8u6xjKDESzMRbB41jy3nuGd1gkUr43F7HvoMQdQRBWWLKDCRtfOmg2jp7WCAAIWyqSykmKdHQEwDsF2KfaITXaoDaKaPnejLKrxRms0sluF8yBJ6N5WWZivg/J+OGA+ipjPapmJrSsy2XDmkgEUuKaM5m44zgOUo2Ytr5C1hVXVHjtEs5fOBtfOXiOuV/lVohlo73dqBqfObPKfGy8h7FY3/M9/lR1dWaydjIl7oh9S9Gi0+9//3tcccUVuOyyy7Bo0SLccccdcLlcuPvuu3M+h+M4NDc3m/+amppyLksQxORF13QMvNI3ZhPCFEVDb69VdKpcRsWz2AfP52ohNdowZWE1pEYbhANdeYOx0LoAWq/dhr1/2YMdz3SibfsQ5L4E4p2xND8mILunkzUj9M/tHQCAh9buRGcgnLGgnqXSKSXiZPoVPb25DT94YQVueW8d2pPBwewar/n3mKwCqo6h1f6CPo+cLYAAVE3DG617zd9lVcNgNI64ooLjODS1eACMHjBl20bA4kXV4nOXdQxlBqLZGIvgcSwZq5L7t9/ejauvfhmBwMjWTKI8KHFHEEQmzjkuwMsbBtUA7IIAd7KahokmQpVQVlKko8O4bk6d6gVv5xEXdbjmuSt2zWNJQIdDNOOVYqf2suQQE9/OP2i2+TfWqldIcoglEnmfYApYLlGEWC3C0WQH7xQKFnHYuhQ70OxxguOMqimHXYT7czVjYpzd3m58VnPn1pqPjbevkzVxZ21T3D2cEqAmW+KO2LcUJTolEgl8/PHHOPXUU1Mr4HmceuqpWLFiRc7nhUIhzJw5E9OnT8c555yDjRs35t1OPB5HIBBI+0cQxMQmtC6AXb/YjsGX+83HgvEEXtvZmZYJKcdo8E9/+igtc1apSifr+ng7j5oZbvB2HnKei3xoXQAv37gOD324HZ/s7cf6nqHUHzWk+TEB2YMva0aoxZeqRPr7x1syFuRGeDpZBYfMcublm9qwxx/Ce7t78NQm4wa13p2qjmCZU0XTRv08rFVUuq7jrV1dppAFAKu7BtJa1GRNM/v8p9W4UTPbM2J/820jFJfxzx0dCMVl7BoKmstYy+tLPYZY8GiteNJ0vWLtBfuCeFzB449vRG9veEzGKKuqZk5gfPrpLaM/gSgKStwRBJEJx3PwnlFn/m4TebhtxnWKtdfpso7whmDW5xcCE50OPLDeWG84UdGWrVSlk1hypRNLDrHpdd6k8AakWu4KTQ55FvvQcM0M0wN07n/Mxqxr50HyMJ/Jwl+7Z7EP3jProVUJsFVJsFWJmD2nGsI0ezEvryB0Xcfu3cMAgLlza8zHx9vXyZq4G4qlYr6dFl+nyZa4I/YtRdXA9ff3Q1XVEQFPU1MTtmzJHpwecMABuPvuu7F48WL4/X7cfPPNOO6447Bx40ZMmzYt63NuvPFG/OIXvyhm1wiCGEdyjVH99rPvISorkFUNpy+YDgAlj5cNhRJ46KH1AIwWM1XVKlrpBKSPqQVyB0y6pmPv43tx49tr0/yXMpGHFNidLOM3cjmWOVL8CqzhxGDEUmEicODtvEV0Gtlel1nOLFvECBZU1jlTotOsag92DQULGvdrraLaORTE/63YAJck4qbTjsYUrwuv7Uz/3GVVM8WiRYc1QUgGn/kEEus2Xt6xBw+t3Yk7PtqMeXUpEUi2CJfljCj2LPbBdoAL0pM2QNXhPbIKs66dN2kCpd/85l0899w2vPlmW9nl9pqmIxqVYbMJiERkVFU58P77qemLzASeqAwscfezn/3MfKyYxJ2maTjssMPw61//GgcddFDWZePxOOLx1PmDknYEMTkQ57kg1UtQhxRIfEp0CiWNxLWIVtZY+oEBw0R81qxqY32ajmhUMSeklUvK00kwPZ2KrXQCkq+tUQT2cHDZRHAcB13XoXo4TLmkuORQJKqAt/OQJAHVi4zn5RvGko94QoVo4yG6ROgJFVOdzrxTiUtleDhmVhnPnp0Snca70glgiTtgeMVa87HWwSDEahEN5zVNisQdMX6M+fS6Y489FpdeeimWLFmCz3zmM1i+fDkaGhrw17/+Nedzfvazn8Hv95v/9uzJPoKcIIjxJ5efUH84Zk4NaRtOz86VYjQ4OBiFpulwuSScdtpcAJWvdGIBREp0yn6Rj7ZGEBuSswpOsyxtbMyPybpuK9bMkapl35ZUYwSeLIhj7XXWgCnTr4j5Kn3lkDnmY/UuB35/+jG45NB5+OKBM5PLGevI93lY/8ba3SKygt+9sxbb+v1Y1WlUtnHJcmtZ1dA6FAR4YOnp082MZ74snXUbe/yp1sIdA6kb5kxjUaWAcce5iCUr2niXALG2fDP6fclzz20DAHz0UWfZmc8f/OAlnHHGQ/jKV57A6af/Ax991In77ksFk+NtXLq/kS9x193dnfU5LHH3zDPP4MEHH4SmaTjuuOPQ0dGRdfkbb7wRVVVV5r/p06dX/HUQBFF5YjHF8FySBHAcB5fEKp3Sr8+lVvqGQsb1u6HBZSav2GOVgE1cM0QnI0lWqlAii4B9qh2zvjUDnikOSI02NF01o2hRgxlysylwQPYYqhBiMQUCz0PgOXA8h6kuV8UTn0DKz6m52QOn0xLXTQDRCTCEp8Rcm1lBttMTw4z/nkuCEzEqRYlO9fX1EAQBPT3pN5g9PT1obm4uaB2SJGHp0qXYsWNHzmXsdjt8Pl/aP4IgJiaZfkLvtHXjf15bhac2t5mP1bvSjW9LMRpkwZHXa4fdnjSbrHilU6bolF3UUgOKKewAwGfnTEWVw4bFzbU4Ymp92rJs8pqcIyPGWr40mxEIHTqlDnNqvfjhqYtN7wEAZqVTNk8nq3il67rpC3Ha/Gm44KDZOLChGgc31WBWjRfnHzQbLhYQaqOP+7X+TbUEabuHQ7jpnbVwigKOaKmHz56c5pJsrxPcAhYuaigowLNuwy2lfm7yOHHeolnmeq30Pd1bsj8YC46B7GLgROLDDzvwrW89g02b+tL2tanJU7botGJFB8LhBPbs8SORUPHd776ANWtS4sdEf28+DRSbuKOkHUFMTmIxBVpcgy15a8Y8ncJyeoKl1LH0waBRPePz2U0RppKik7W9rtTpdYARK7B11Sz0wVVnB2/nkSiyVQ8AwmHjvXO7U9PussVQhRCPKxA4DrzAQRA4THO5oEYrf43cvTtlIs5xXMn7O5b09UfMxN3ewTD+9Tb5DBKjU5ToZLPZcPjhh+P11183H9M0Da+//jqOPfbYgtahqirWr1+PKVOmFLenBEFMSDKrZG59fz029Q7hpW2pmx2rQMO7+JKMBlm5sc9nNye5VbrSiYkRo1U6CT7RrBICB3zv6EW45/zP4PrPHg6vPb1UXQ2pkHsTCGwL5RRJPIt98JxSA6nRhqPOmomHn/sK/u2Bz8BVk/ILYJnDXKXhTLyCV0g9h+fxtSXz8OvPHwmnRcwR+WTpewHjfp1zXODdyQBST/os2CXUuey4/IgD8cPjDsYPjj3YXGdMUdEXjoF3Cpg1q9rc33zBp7VSS01W11y0eC7+cvYJ+Mxs41qRWemkhdWSTcWjUdny89iO93333Xa8805pAdmePX5873svYu3aHtx112ps2JAym5461TMmQSjPc2aATqJTZdkXiTtK2hHE5CQWUwBVh100ruGu5P/RLGJLKdXiwWAqccdiHFYJVAmsRuKlejoB6dcdh0M0E27WeE8NK1Bjo687W6VTNouCQojFkqITz4HnjH+egaJWURBdXUZnQEuLce5m7+VEqXRSVQ1DQ0ar5nnnHQgApvUFQeSj6Pa6a665Bn//+99x3333YfPmzfjOd76DcDiMyy67DABw6aWXpvkV3HDDDfjnP/+J1tZWrF69Gpdccgl2796Nyy+/vHKvgiCIcaOQqiXZcnGvPqm2pHYmJjp5vTaz0qnSN8Uj2+uyr985xwXdbbwGkePN1jIAZsCYbd35RBJV1cHbeXjmuM2JMkxcA7JVOo0MmDyLfWj5yWyz7Hnmd2ei+dKWEcsxU25FG33cL8dzaLzAuCFmlU4zqjy49YxjcVBjDQ6bWg+3TYItuc5ATDZ9qDweW0EBnrVSi/lRMRGLrVdWNQxGYiPGHJfSamAVmioZdGcSicj44Q9fxtVXv4JIpPh2wMcf32T+vG5dL+68c7X5ezyull3pZD1ub7rp87j33nPx3HMX4cwz5wNIfR90XU+bGkmUBiXuCILIRTRqXDvtyWue9TqdSSnV4kx08nhsZowzNpVOQsnT64D0SmSHQzS9Bdn61aiK3ie60fdkz6iVRqzSib1eIH8MNdp+CRxnttcBQHWAq3gbOttnn89IOhZiUbAvYVYXPM/h/PMXAki1BBJEPooWnS688ELcfPPNuO6667BkyRKsWbMGL7/8sulR0N7ejq6uLnP5oaEhXHHFFVi4cCHOOOMMBAIBvP/++1i0aFHlXgVBEONGpp9QNljQxLt41H6+Pu+yuUi119lMMcYanFSCzPa6XJkljudQfZrxOkQhXbBxitnfCybY5BJJmMDlUXhoye0yocn6MxNxclW5KKpmlj1XLfTBu2TkxLYWrxs1bjv4afaC+vC9S6pQdXKNWd0l8Bw8Ngkeu2SOzmVG5YF4AlK1kZ202YSs0/aywSq19GSboZgM6mxJ8SmuqLj86Xdwy3vpGbVSWg32VaWTNaAvRdyyPn9oKIqPPkqZtsdiStoxUErgyzSn7373SJx88iwcfHAjmpo8I0xg//jHj3DGGf/As89uLXobRDqUuCMIIht+fxy8nYfPkxQbLBXJ1vN7qWPpWXud12uzVDqV7o2YScpIvLxKJxbX2WwCeD41uZclQaI7I9ATOrSICv97QznXA+SqdCq1vU5NttfxCLk0yJoGQQFCa4NI9MRHX0GBsOs+2+dKVDrpmo7IjjCCq/2I7AiXPEEaAPr7jXirrs6F2lonAOPYJQ9IYjRKGk1z1VVX4aqrrsr6t7feeivt91tvvRW33nprKZshCGISwPEc6s9tRPd9e3NedJjg0vjlKSWbNqe3142Vp1N6e10ioULX9bSKEIYtOWlGzCgAceSodGKBY67Ja7Ks4QCfD7O7RAy9OoC60xvM1wmkjMRHm7zChAKeT3kBeBb74D7Yi2hrBP1P98CXEHDJ0QvwtH+v+Txd16EMyoaxdpbX23hOMxwf7QZWpIJhK81eJzb0AvJsCfxewXwPi/Ej8Cz2wX1sFaShftR9pg6+A6oRf30ATR4nekJGOfeK9pGm9cW2GqRXOlUu6M7EKhqVIm5lCzK/9rVD8NBD6xGLKWmipCxrab+Phqbp5jF03nkHplfrZVQS3n+/YS5+220f4OyzDyj6dRApLrzwQvT19eG6665Dd3c3lixZMiJxx1u+Xyxx193djZqaGhx++OGUuCOI/ZDBQeMa13xoNQCjPZ6h6jrE5Dm6lLH0uq6n+WKORaWTVSwqZ3pdNCJDi2uQOAGRHWHYM9rrojtSSabYrih0VQcnZH8/8nk6ldNex/Ec2sNhzNCqEFzpR1AAmr4yBYKn/ImvKaHM2OfREo2jEVoXQN/ynjTvVbFKRMP5pU2b6+sz3v/6eheqqhzmvkUictr7TBCZjPn0OoIg9n/YhTauZs9qmYbVnsJvijNJtdelPJ0q3V6XWekE5K7QURQNvFOAd74HU78zHTWfr4P7YE/O9jog/7Q4RdFwcHU1OI5DvCMGXdfT2uuYEDBaaTjLLLLydgbHc3DNc0OskiC6BfgkCYolIAytCaJveQ+Cq3N7JLkP90Gqk1DnsY/4W7PPCalOgjzTeO9GBkyFBXiszdA73wN1SIEo8Dh/0Szki7GLbTWwVshZq54qTbmVTkx0mjPHGJv89a8vxjnnGKKPUemUek+L/S5YBS2WSWWwG4bMdVq/F0TpXHXVVdi9ezfi8Tg+/PBDHH300ebf3nrrLdx7773m77feequ5bHd3N1544QUsXbp0HPaaIIixxBSdDqjGlMta4KxNnW+Z/+KUy1pKEgqiUcUUWbxe25gaiTscYsnT60LrAtj5+52QexNAv4LO29uR2BiGFlWNa15YhdyXACzxgBbLvQ32+lyukdPrSmmv4znDRFyQeLSGQinhSgWCa4P5V1AgKaEsvdKplPa60LoAuu7pTBOcAEDxKyV7YrLjtK7Omea55fdXrtqL2D8h0YkgiLJhIkooo/KImWozn55SzC8Z6e11rNKp0qJTeqUTkLs8nGXwRImHe4EH9Wc0ovoztXBaxJ6vL5mPv5x9gvl7vmlxiqKhJxo129WU4fRKllSlU36PJLZfbPlMxJpUS1yTaIhHWkJDcJXRkx9aHYCWIzupKBp4l4Apx9TBPtMB+wwHPIf7YJ/pwLR51eBdAoaHYwBSAdNolVkj9994v6uCHHRVh2DjUO2045Cm2uyvp4RWA6vQ5PfH0dFR2hS80bAG9KV4OrGA/StfOQgvvngxfvCDY8xjPxZT0gL6ckSnTIGSHXeZxz5lMQmCIMYGdjNfW+uEZ7EP834+3/RnbPxWC2ZdO6/ksfQsaSdJRtv7WBiJs2uQ4elUfEsYE0giw8a10i4Y1yFR5SD3y/BvDUINGTGa4BHAO5OxUJ44kL0+a0zHRJxiK53icRVistJJkHi0BoNpfluRrSGo4fKr7zOrswoZxpINXdPRt3xkZbiVUjwxmYk4a62rrjaqnVjsR6Sj6zr+8peVeOSRDeO9K+MOiU4EQZQNE1GCidSN9XeOWoQvHTQbQKrCpxTzS4a1vY7dFFfa04kFTdb+/1zl4SwAsN6wO+e44LZMnLMJPOpdqd8VLfe0OHaDzyXPyn1PdKPZ4TBP0plG4rlFp+yVTgxd083S/ANcXui6bgpOjOj27B5J7DW7RBGiW4R7oQf1ZzZCdIuoFW2QeN4MnFOiU3Gl4WwbjjgHDhzsUxzgABzYUJ11+VJaDaytbvG4gnPPfQQff7w3zzNKI73SqXjRKfVZ8mhsNNoxmalqLKakHf+VrXTKXkno8aRPZiQIgiAqQ+bNvCgJEJ0CeJcAcbqjZGsCIN3PieNSE0orW+mUzdOpsOu+VSBJKMn1JKvG2TCRvncHoISNv/FOAbwjKR7lqXTKrBoCKtNeJ4g8goqCd7VBNH6lGbZmO6Aa/k7lkulDVaqnU7Q1klbh9Mi6nfjJKx8hKqceK8UTc2jIEJdqagyxibXY+f0kOmVj06Y+3HXXJ7j55vc/9b5XJDoRBFE2zEw8lBSdple58fl5LWawkE9sKZRU0GQ3b7wr3V7HbuJdrpSvUa5KJxYAWG/YOZ5Dy9lN5u+iwEPgU9PtZDX3tDhF0SDwvFmFBACfdTTg+wsX4ovTppnbYQFTrgBktEonXdHNdcxzezH05gDCG0PGcxqMQDTelT14YNt0cklTc5cAsVqEUCVC4nkcVFVlBiQjPZ0Ku9iaYl4yLvIeXgXRIaDe7UxbrrxWA+M49YoiDq2pwXyvF3ff/UnR6xmNSrXXWQVEduxrmp4W5BX7XbAe10KGH0aq0klLO86o0okgCGJssFY6MXIlAIrFOrkOAKZO9QIA1q7NXwlTDCx+Sp9eV9h+WwUSZtPApvjZkhVPsYCMWFIgEVwC+KT9QH7RKd0fCSjOZ9KKdXqdkIyvBuQExCoJ3sOMOCS8JQwtUbrht7HPmZVOpYlOmZ0Fj21oxfYBP/7V1pV3udHIPE6rqozEKrXXZWfr1gHz51I8zvYnSHQiCKJs2Mj7YDx5sbQlMzQ8E530kipSrLCgyTq9rpLtdbquW8rDxVGNMFOCQPpptP6wGghVIsDDNP6UeA4QONR+ObdxoyxrEDgu7T3iOQ4ix+EAnw/cduOCPlpp+KiVTophjC4ny8IjSVNO33HVZuCkDGcPQswqJD5ZdeUUjKzpIg84jsNhdXVmtpYFTCk/guIqnSTZeB8c0x0QJB7VVXa4mu2Q6iS0fG9GWa0G0agCDsCXZs7E56dMwTnTp2MG5xz1ecWg6zqCgVQQ9tJLO4qe/ma2cFqETSY6AenHQLGm+lZBK9M43jotyFoyb902QRAEUTkyK0gAlNSmlg2riTgAnHLKLPA8h02b+io27p5dg+x2EfZeFedNnw4oBXo5WoSPWI5Kp4SqQUm23vFOvuRKp9EsCnJhVjoJHARbuu+hbardqORXdSS6yhNfMlsCS522Z+0skC3PjWQIgcV2IDDRqaYmU3SqfKVTPK7g3Xfb0dkZwC23vI/du4cruv733mvHn/+8suhjoRj27El9vyrdnTHZINGJIIiK4Fnsg3i8FxA4eKyik8DBfoCrZIGAYTUSt5nTTCp3AreKS4Vk6tjjVkEgtC6Ant/vhupXAA1QdB28k4ej3g77VDts83NXepmiEwd4D/fBc5jPbLUDAGVbBGpIKaC9brRKJw08z+H5zk4MxI0xt76jq+A5yAux2vjcFL+Stc/fFJ2SO8Y8FVwL3IAA1Nps4MPGMpmVToV7OmngAIjJwiCpwYY4jHU2eJ3gXQLss51lCZixmIIDq6pQb0+1Ps5UHWWNEbaiqzr6n+7B3B08zp42DQDw/vt7cMMN/0JPT6jg9WSrphNF3gyarRSbQcsmaDGsRuIswDSeU9nKQoIgCMJgYGBkpZM1AVAO1vY6wBAMjjnGuDa98sqOstbNYElApyjAvi2BuV4vZoqFVbdbhY9Isv3LJRmPpUQnFUgKMEalE/N0KrXSqVhPJ9Zex0NMXiPZa+Y4DvZphlgY6yhcfFHDKsKbQ9CT4pyu6zmNxIsVHlkHAgAMxVJCWMIy8KeUDgQmjqYqnVh7XeUrnW65ZQV++MOXcc45j+DhhzfgO995oWLr1nUdP/jBy7j77k+wYsWeiq03k9bWIfNnEp0IgiAqhFwrwD7VjpYT69H89aloOqcJ9ql2oKr0qXUMVunk89nHxEjcejEortLJeG3MBJMLppZXNR1aVAPnV6FFVciyBi2mYvD1fnTd34n43lja+kSOA89x4EQOnkO92CVE8dCuXeiIRMDpQHBNYNSAKVtLFkPXdEAFeB7ojERwz86d8H6pwRQEBY9gBHWqDjWYfcIeADiQaq8DAN7GIyAZn8Usp+E9lGkkXmjApCgaPJJkXJwEQHALCOrGvtQmRSKrJ1MpRCMyjqmvBwB82N+PmKpCjAOx9ugozyyMRF8Ccr8MTdGxwOdDsyOVuS4m6MgmOgHZK45Kr3QaGQZYb3RY5Rr7vRR0XYf/w2H0v9iL4CeBT72vAfHpQlE03H77R2PiG0fsHyQSqimQsAoSABZvpMq01zHRCQCOProFALBr13BZ62aY03+HYdoEeLjCYj+rQBJJpItOEvOFtHGpmCPN0ymfkbgh4FiNxIsdbgIY17BYTIHA8xB4DqJ9ZOLT3mJc5+OdhYlOalRF//O98L87BP+HwwCM2IZdH0dWixd33WQdCAAwEEkJQkPR1M+ldCBktteNpZH48uWb037v7Q1XbN1796b8t0rx3CyU7dsHzZ9JdCIIgqgQrBqpbpYH3sOq4J1lZFDKDZh0XU/L1LGb7kpWOrF18TwHUeRHHflrrSiymmBaW5VYUCPyPOQhBfGYguDqAGKtUehxDeHNIcv6VIg8bwQAPAde5LFTiGJvNIr3envBcxyiOyIQMtadCRMGsokJLJvGgYMK42fZIgBwPGcGfpkjdq3vhS05r5h3pgLKgNP421yv4RWRKg0vrpRdUTRUS4anluARwfEcgjD2pd4UncoLEMSwjjq7HYqu46P+fmwNBKAoGoZ2FV6FlI9Ej3GssvdrYVWV+bdiAsdc1UjZRKdSPZ2yVzqlRCdrpVOpIm90RwThdUEkOuMIrvKj97FuhNZXZrw0QUx0li/fjHvuWYN///fnx3tXiAkKE/dFkU8Thqz+euVg9cRksJ8rZSbOYijngG5WadeJ9jzPSGEVSMKs0snGKp2SU+wOdJqtdPvSSFzXdPg3B6GEFHCq4YkpWqqBGfYpdoAHVL9iTtnLR+DDYbOtMLIphL1374G/NWTuI7ORKLXSCTA6EKZc1oJhLhUz9UdiJXtiappuHqspI/Gxa68bS6x+ZpW8l7DS3x9JE8pIdCIIC2+8sQuPPkpjHYnSYBcdVm6balErL2CKRhUzQEhvr6tcpZPVzwlIbzHKhrUKJXNKiLmMnlyGN6qHgrvCkIdSF/94Z9xs6WKVThzHgUtm4piAtScSgeAVocs6RL+xzlz9/fnEBCY6gYNphJn52YjVSdFpeKSww9Zt143nCq7UNsJuY91TnE7YeX7EuN9ijMSrbTZwPCB6k5lPzthuk9PIrJVb6VQXNY6f7YEA4pqG3phx3A5WSHSSe4wgvlcxAv0DLaJTMcFNcZVOpU2vy3acWG90WCk9UFqlk65apiOKyWMhoCDwwTCULNV0BLG/0dY2PN67QExwrNUj1sRV5drr0n2CrD9XSnSKxRTYeB5iVDdfQ61oK7htnQkkMSE5JTdZ6eT0SpDqJXB1ErSo8T4ILh68o3AjcZdrpOhUiEdSaF0AbTfswK7b2yAPyODCGmI7I1D7jPVar7u8nYdUY2wn0Zv/PdVVHbHdxmfOu5PJOxWIfBQAYHw27D0s1dOJ4VnsA/+FakiNNkh1EqItQsmemMFg3IzFWYXTWLbXjSXr1qVEp0BgbPb9kUfS76dJdCKIJLKs4sc/fhU33fR+WtkhQRQKO3GzzEelTTAFgYfdLliMxCtZ6cREJ2PdxXg65Zr+MafGuKgzT4K4X4YaTq1Pj2tmcKIoGniOA8/BIjql1uWcmRyj3M9Ep/yeTixYtaIn/8aJXM7XZ/o6ZTETVxQNEsdByFLpxDsFDCeM19LsdJqZxWInxZiiE8eZPg+DgiGAzXC74RSEsi/ctbKxbxuHhwHAFJ2ifeUHHrquI9FrrGdNZBiypsEtimaVVjHiUMoUfnTRqdhqwnyeTtYbnYGB1DjlUm585CEZakgFZ+fR/PWpqP1CfWp9ZRquEsRkgNpJidHo6zPOs9bWOqBy7XUshvJ4bFCCCobfHYRPE9L+Vi6RiIxmhwOCYLTByZoGAdmrpnPhWeyDdLQXUqMNU09pQMv3ZmDql6aAdwqIxxSokSyVTjk8nXRdN1+b1dOp0PY6Zpmg+BUkkubmAs8Dio7whwFoUXVEDCo1Gdd5FgPkIt4Vh57QwbsENH65GTWfrQNgJPsO8PnSRLJS2+us9PWHwdt58C4B/eF4yZ6YTBz1+exmDOnz7bvpdXwZXp6ZjLXoFInIeOyxjWmPjYXopIYVDLzSV5SX2HhBohNhYjU7G6tSQ2L/JRZTsG2b0btc6UondqJ2OETDsDFZjZRIqBUL6FPjftMrnXLtu/WmPXP6xx/POg4/PvFQLG6uNZZJTvFTJR1aJCkk1BtBUCLp6yTLyUonfmSlEwA4ZhnBqNCnQOK4nAFTPq8ePRm0GKJT9kouMflaspWHK4ohoDDfKU5Kz8j2JMUbQ3RKb68rptKp3m43Jvclq64SkiEMcQAW+HxltdepIQWSxkEHcO6/HYz//d/PYvFxUwAAXFyHGi0vuFeDKrSoBgjAbn8InVEjSJvuNryuihFu9kWlUzbvr1SlU/ntdUyQlapF8CIPx0wnPEuMFkyrpxlBTGZ0XUd7uz/reXmia06JhApN06HrOn72s9dw7bVvkFC2j9mypR8AMHduTdrjlWqvY9dMt1tCaF0Qkc1heNcnMN/rrYjopGk6AoE4ml0uSJIAoUFCTywGTUu1mxdKOCyDt/NoOKQarnluOJzJmCSuAck4QijA0ykeV83vo7XCqxAjcatlApCa+GYTeHAcB69NgjykYHg4lnaNtDUl47qe/O8pq3JyzHCAl3g457rgWeKFoho+kOkiWe7krabp+PWv3xkhbmRibfEKBuOIREqLoVjlM6tysv5c6fY6VqVmxfo5loOu69izJ2D+zioBK8nu3cOIRGTU1jqxaFEDgLERnfwf+BFvj2Hwpb6Kr7vSkOhEmLCLHlB+KS/x6eP//u9DdHYGUFvrxJFHTgVQuSyd2daVrEJi/wPApZc+XXYlFWBtr0uvdMq1bqu4YzXBBIAWnxvHTG80f2dT/IRaCbpsBDr2FiM7pIaM7cqyCoE3Aho2ocWa1bFNsUOoEsGpOg6qrs5ZOZTydMpS6aSkRKdcwazgSb7u4MjPjJl8czzAu4QRbQBdSYGl2eEYMe63GE+neocDHA9ItUa2z24XscVvtGjN83rLaq97+C9r4ffH0BeLYfa8GixbNg+SU8RQIgFV1REq0+ha7jeCF6nWhkAogY6wEexNdxn+ZqW012V+lo5kW4FbFHHe9Ok4obERcpHvSS5BS4trsCVjx0RCRVdXquWwlOuCkhSdrMKsfWrScLUrTje3xKQnFlPwk5+8hvPPfxT33bdmxN+tx7iu63j//T3YtWtoxHLjQTQq4+yzH8Z3vvM82tqG8eqrrXjppR1j1m5CZGfTJuOGkd2cMlLJr/JiKCYyOJ0SEl3GCV4UeJzR0gI+Vv45mLVdTXE6IYo8bI027A6HDQPuPcWJEdaqLCCVCEQiWaltM5Je5vS6HO11TLTgOC4tUWP6TCoa4ntjKdsBC1bLhL5wFN9/4X1jX0Tj2uu0iZjl80CLa2kDAmzJSid5IJF1vYxEt/H9sk9PiTf2aQ6oqoYZbneaB1U+T6dVq/Zi+fLN+N3v3su5LWCkAXdfX2mG3Jl+TkDl2zQZrPrPitMpZVmyeMJhOS15+fLLO/Cb37xb0XvfoaEYBI7D2TOm4QivkYAeC9GJxZwA0uw7JiIkOhEmVtGpkl45xKeDDz7oAAD89KcnWCqd8lcLFQo7HplQYgYhADZv7kNHRyDr84rbRvZKp0I8nawmmNmQBB5SjQgtGdxxdh5CUqRSI0x0YtPrgGwDXziOg3uRBxzH4aSmJsxxuLNuqxBPJ07kc3pFCJ7kfoWVEYKAomioTba+WUU2wPhsupno5HSOMBIv2I9A1VGVNBIXk/4IksRjT8QIQBodjrIqnXavMc5zeyMRzJ9vlLQ7HCL2RiLQNB3hjSGEN5bu7WSKTvUSQqGEud9jUel0UmMj5nq9OKa+HlXtxX3HslXExXZH0fNYF/j3QlhcXY1EQk1rtS6lApZVzAne1PEiNdoAHtBCKrRI+YIxQYwXQ0NRXHHFc3jjjV0A0uMohvU0un59L77//Zfw5S8/vq92MS9btvSjvz+Cjz/uwurVXebjlZwSReRH13Vs3GiITgcdlCk6VcbTiSVqXJIAZShZfVojQeJ5HOKuKmqSWzbY5LJpXhd4joO9wY62kHEdjXXGCvZ1ArKJTsmAKGGsg3k5sf91WYeWGHkdYSbiLpeUlsBjP/vaNAy80IfeJ7shZ3hYWi0TNvUOmz/Lljjm4KYaQNWxcmVKdBI8AngnD6i5BQAtrkFJ/o2JVABga7RD0TQ4BQHNnlSbZb4JwMwgHsjfxpsp4JT6/WbvqdWQnrUCllo9lY3orgiCLw/gpMZG2PlUjFKJBDMw8vUHAnE88cQmPPXU5hzPKJ7h4RiOb2jAfJcXB0oeHOjzVVx0UqNq2qTp2K6RQt1EgkQnwmTLlgHz50+72RlRHLquo7vbCDAWLKgzHx/NF6lQWMDFhBJR5M1xrUBl+rFHejrlzzBmVqEwE8xMMUasFlF9kBe8U4AaTt6Au3hz9C/zeDKNxNPa69K36TrADa5ahI3n8ZmaxqxeBtapeplYK51yBbOCWzCuDCpGCAKKoqEuo/WNwdrrNF2HV5Lg6DfWW0gpu5UqPukF5eQhOFLqW3+ydc8tiogHSwtuojsjWOg0fLYu+Y/D0NhoCEF2u4A3urvRbzPWG1oTyJulzIc8YKxDrJUQDifQHY1C0XU4BQFNDkdRgn4+0alaknBQdbX5mDOAovY5U5xUwyqG3hyAHtPA8Rw+O2UK5trcOEBzwy2m2lmLhQXvokV04iXeFDeVgAw1pCDRX/nydoIYa/7xj/XYvLnPrPrMlp233tBbqyImAtbz8vPPbzd/JtFp39HdHcLQUBSCwOOAA+rT/la59jrjPOyVkzFUjYjqI6sBAHV2e9mCgd8fBw+gxmGIEfY6G7qjUcRUFVpMhdxX+Pk9V6UTl7y+8XYeiYSKhK5C8CbjmO6RMWDKzym9OobnOcx0u+EcNN5T2S9jyxPt+OijTvOam2mZwBAt4tUhjbWAwGHVqtR3muM4iMkKbXkw+2uW+xOADgheAYLFF5MTOIRsxvanOVzm4/kSd1adKV8FOGsfY3Fzqf5LLOHndKbeHyY6KYpWkUqh+N4Yht4cgDKQwFH19Th/xgwIyfNruZOLGT092ROLAwPRrI+XQqgvhqPq6412U4HD56ZMQazMITiZJPbGAcsxEJ/gPpkkOhEAjKBo27aU6ETtdUQxBAJx85hhN/JA5YzEMyfLAcDtt59h/lyJst5UpVOmkXjhU+I8i32Ydd08tHxvBpq/PhUt35uBWdfOQ+1sj7ENv3HBFFwCBHdmpZMKgePAWYzEM00TeYmHcJIX/fE4eN0QUTJh73V2I/Fs7XXp33WO51KCWIavk6JoqLXbwXGAWJUeyNlshnHoh/1Gpl9fH4UaUS0mmIUdA1WCsV6hOrV+TdMh6zr8SaNyzV/8+SnRG8fQWwPQNR1DiQTcc1JBncMhIq5p2GqPgPcI0KIaeh7ZmzNozIWu66Z4IruSYpuuozVoVAsd4PMVVS2US0B0OETM9Rq+SO3hMEKKAl3VEc8SeOcis9IpsHIYuqxDarBBarJB5Dh8rrEZh9fW4kszZkDiuNLa65JtmtZKJyDlHZboSaD38W70P9ND0+yIScfOnYaP4ZlnzgeQXayxfm8qWQ1QCawJm/XrUx42JDrtO1jsPXduzYjrdsXb6+LGdcnWbIejzg6e51Bjs5UdQw0Px+CTJNgkARA42LwidAB7o1FoOiAPFn7cZ4pO5nuSrHTSBODssx/GpZc+DbE5OaAji4kye82ZPkCiwOGzzc3QdcAx04nOvUFsfLsLv/mvt3D//WsBIM0yQdZSscuihpTn1vxZNeDtPDo60lvymS2AkqPSiXlc2RrtI/42wBnPmc27zOqwfO111nNLrs9Q13Wz1XDqVCNuKNV/iQlb1nZFq6hX7vlNV3UMvzNkTPJTVMiahhaXC8c3pDyRKtGSz85vmf6YmQJlWfQY70XMqUMVAKcggB+q7L01i/mYl1i2AUATCRKdCADGBcN6M0RG4kQx9PQYJ/CaGmda0FQpI3F2PFpvvufPrzO9oypb6WRchOyjCGa5DLs5noNrnhvew6rgmucGx3NmKXIieVPNu0WjogiAHtOgJjRomg6B5w2hKYuROMPjsWP90BAUVUd4c8g0B2ekJp7l93TK1/rIBALmN2V9zXV2OzieM6fcMdjn/l5fH3piMYg8h+jOSJpwVkgJf7VoXDytlVQsG98XNz5nPce0wFxosoahNwcBDdgSCODenTvh8KT2n33m0biCqmOrjedENUR3Fpf1UkMq9JgG8EBAT+3j1oDR/rnA50OiQpVONclpeH1yHG2hEDRNzxp45yIlaAmQh2REdxgCZtXxNfB8pgZDiVQA2+JxYXFNTdHG/bqmm8Kl6Es/HlkmObjSbxyXGiCPMmaaIEplxYo9aG/3V3y97e3Gd/vww41hBP39kRHnOashLmtPASrXKlIOua6dJDrtO1hrWkODa8TfKtdeZxx39qToJNXZIHoFiAIPtygiWObkseHhGKpsNogSD8EjQEgabgcSCei6PiKWyIWm6eZ3hAkATBjgVGBoOIqd7UPo74+gtXUI720zqoyyDaVg3zurKTcATOecqLPboQpA9WdqsarXSJQdVltrCoBWy4REMmF27IwmzK+vMtcz84Kp5j5bPx+pxtgeq3rOhJmMS43p+9XaOoQ/P78OcVVFrd1mXpPzTa+zCk25RKdYTDHPSSnRqbTPm3XBWL2VBCFl1xCJyNA1HcE1AYS3FmdToPhl9D/XCzWggHcJWOHw48XOTgDA0tpaOATBSECWeT8BpM5vzGKBUYl1M+x+4z2P1/DwO4zjwzlcWQ9LVuHnOsBIbGsRNWur6USBRCcCwMhSw8nm6bRz5yBuvPGdks3xiPJgx09TU7rPUKWMxDNNvhlMzKmE6MSOnSk+F3qf6MLpXCM+19ycM9jLN3I+E6/XCC7Y5DrBJYCzcYBoBIDxQLIli+PAcan2ussvPwwejw2XXnqoua6qKjs2+f1IqCpifXH43x9KEwLY/mbbLy15k2OtdMr2+lJm4unijiZr8EmSUemUpb2O0a5FwYFDdHvY9CMARq920jQd1VLSx8kiarGbs75kix0fKuyiKg8mIA/KCHwwbAQybgEvtndA1fW0qjkW1MbjKpyzXHAfZFzA9SJvClkAINXZMBxITXlpDQah6jqqbTboBQbfuq7nMRIXUWszjilPkwO7QiHomo5YW6Rg7wyroBVcHQB0wDHbCVuDDQ6vhH/s2oWn2tvxbm8vXC4J05JG6MUEZWpYBTQAAgfelf4axCztC8VWlhFEIWzY0Iv/+I+XcP75j1Z0vZqmo7PTEJ2WLp0CjuOgKJopIjCsbS9WAapSrSLlQKLT+JNZ2WOlUr6YrAJFjBjXB6lWAu8QoCZPy5G+8iaPDQ/HUCVJkCQeos+YMixJPAKKgsHBKJ57bLNpQp2PaFQ24xn2frDpaMGBGNav78WzL6faQH9754fYuWsIypBiWhUwUp5OqWuNJmtYACNOHazToHA6Xt60BwAwx+PBcG+qepxZJig2Y39syTY3TuRQf14j6o+sHbEtAGZ7nTIoj0jSaLJmtkDZWxxpf3v22a0YCsbQ7VYwdaoPgY+GoUbzV4tbhaZs096s+8bzHGbXeXHu9OlobkNJ4gQ7Z1krhHRNx2GNdTipsRHht4fQ89BeBFf64X97aERSNB9Dbw2abZhVx1Rjb08I24NB8NUiJJ7HEXWGQFQJ+xd2fjtmZiNObW5GfTKJZ/XIKgdN1uCKJpPHTRKCHuN9cIdQlL9Z3m0kvcE0Xcc/17YjwRmfJzPAn4iQ6EQASFWqMCZbpdOVVz6PJ5/cjJ///K3x3pVPJewEbm2tA9Lb68opic00EmcwMacS7XVtbcPgABzjrIUypIDjOCyqroY8ipF4toqiTHw+44LGPJIEtzH5jbWxyUmPIoGJTskz89SpXrz++qX4/vePNtdlt4tQBeD5TsN/ILIljOG3U8JTQZ5OEp+3bD9V6ZR+HnCoyXVKXJoXQeb2hl0aICQzfeFUYDNapZOiaKhOiilSVXp7HQB0J0UnV5CDGk3tt+KXoVrGJqsxFf0v9qLvyR70PdmNyJYwwAGe46sR10a2H7IAigUzvDNlUFoMTHSyTbGbY5RbWnyQdd2c7CcGCwv02AhzYKSAqOtATfJ9qpnuwY5gEHFoUIMqYrsKq85in7tXEE3zSe9hht+VJPGIqSp2hkLoiETgdEmYWsL0PdPPySeMqNrL9D4DcmeGicmBqmp48MF12L59YPSF9yHWtrFK0t0dgqJosNkETJ3qNSc6ZSa/rDek1gqDcqZwVorMm6yDDzamrmbzpiLGBha/WM2ZGbna4ItB13VEowrsPA8+eU1jlcox3rgeRcsU/FmlkyQKZvwgijyCsoxt2wbQtSuAP/955ajrYe+FaBl2wqpzHILxe0xNvRdxTcOaHb2IJxQkeuNZ12WtdAqvD8LBCfDLMgbdGjZt6kNXKILeWAw8x8EbTL9OeRb74Du9HlKjDXVHVMN1oBvOBS64F3rB85xZ8WMVkMUaEeCMqXrx9nQxL94ZB1QdglcYkbhjYnXTsXWw19ugRTWEPgkUbCRuPc9YYWJUlceORREX5nm9cEaBeGfxQmNme52u6Rh6YwCfb2zGUfX1UDsT0KKWmK9AYUsZls1K57ozG+Cc6zJ9Ymd+rgnHHz8DR9XXwSdJFRHre3rCONDnw+FcFZbU1uLSOXMwxek0va/KRe6XocgqgrIMT5MDis+IqXglu/9YKSR6DT+nrXuG8KvfvYN/fWwMc1KGJ24cRaITAWBkVmuyVTqx/mSroR+x72CiZXOzJ+1xqyBTTitBNk8nICXmVKLSqa3NjzleL+oEGyBy4HkOdp4Hl2O6Vr4pcZmwYFJPGn/zDuM5vCs5IS+QEp143sikMZiJpJWqKgd2BoNILLQDPBDdFkas1RAb8olhhRiJA8ZUGyBVBs6o1ozHVffIfbJ+Nt5aO6S6ZHWXxctBDquI7owg3hXLKkImEgqqkpVO9pqU6MQyfK3BIHpjMXCKjuBKo1VGGZbR+2Q3+p/pha7qiLZF0P9UDxKd6ceEZ7EXqEvto7Vqjv3MBBVOMt7/Ys3EzQxmsx1DQ8Y5qb7eiUceuQBCQ/J1FXgvZ/2+ZB5jAz1heJPvk7fJAVXX0Ska2w5vKqykna1/juACdGNcs1RrG7G9rmgUTpcEjyTBJ0nFTd8LjJxcx7AatdqmJsdMT/Bxv0R+HnlkA2677QNcdNGT470raZQ7mSsXe/YY56Bp03zgeQ4NDUbSJTOesvqcMDEamBgDW6wi2EknzcSVVx4OYGQikhg72I1u9kqn8tvrZFmDqmpocDggCEb7G29Pxh5iMllV5o1qWqWTN+WLGZST085EEZ2dwXyrAJBe9cUSFQ6HiNpa5wjR6corD0dzswed0ShCoYTplcRgYgt7X9WIitC6IBx2AW/39GDP3oA5sTFUbTxnvuSBkvFeJ2QVvJ2Hb7bbSBiCMycMMxNtq+DDizycc40kzeDr/VD8qb/F243vv2Omc0QixnztXht8RxltfJGdEUhCee114bCMaknCedOnw4mU5QXzEy2GVHudcf0ObwwhtisKTuCwye9HaIaA6lNSFWDZht1kI7LdON/YZzhgn2qI90x0qj+4Cs4WB2yigOMaGipy3vT3RbFs6lTzdfAch880NSFUIdFJCciQZQ0DiQSqa5ywO0VsDwahqTqiBSYGR0PuN46rt9cZYtPWDsNfkCqdiAkP+3IzJlulE2OsgksiP6y9LlelE1BeeXjm9LrQ+iD6n+/FgTEXXIJQdkmsrutoaxtGvd0Op1OCc7YTASlpLJ4j9s7lt5MNVpEFmY385fHyyzvwt/s/QU9vGEpIBQdA4HlwSHk65cIU27w6vIdVQYeO1/5vI777recQiymotdnQnJAQ70rPZFlFp3xTcWxTjPUrg3JaYFLPJUWnmpGClvWzrq93wZb0K1CT1StVkoSh53ox9MYABp7vQ3BVYMQ65LAKKTke116VCsBZsKUDeLunB5qqmx4O4a1hQDWqagZf7cfQqwNQQ8ZUm4YvNcNzqBeuA93wHl6VEpU4Lu1zy6x0YqKTVmQrmepXAM4waWU3l7W1TsybV4vaeUa21hnN/9ma74WcW3TSk9VjUVU1K866dOP9kIdGlvTnW38LjACPtRQCxvvDjg9V1yHUiOA5oMXlKiohwUb5illEJ+tjnoON90YLGZOOiMnJ22/vHu9dyIo1Lii31dsK84iaNs2oEGxsNG40M6uErKJTf3/qb8Vm7JWQUpQhcyGwa+ePfnQcfv/7ZWbiiKwK9h2pSqexaa9jx1m93Q6B5yBaEzrJ4iqlSJ/ETFKeTumVTgEmOklSQbFSrlbDadN8I0SnadN8OPLIqeiMRBAMJkYkyTK9oQIr/dBlHWKDDVsDAezcOYgdO4wb9alH1yGqqvCJEvY+3Z1WLWKttNfZx5D0qmSiU+Z3ufqkWtia7YCaGvii6zpiyeoixwwnMrEeB/YWB3gnDz2moVZLTYfLxFqZk6u9LtIdw6Vz52K6yw1R4hHXNCiKNmI6cSFYPZ3UqIrgauMcuF4L4sXOTgzX6HDNc5tJJb0A0UlXdES2Gucb13zjHiISkc1kcnOzB74jqyAIPBZWVSE6nIAma4i2RtIq3othpuKAxPOwNdjw1+3boeo6prlccIYrcw+pBhQosobhRALV1Q44HCK2BwJQNQ2xtmhFzNC1qAoduinsDiZ9OK0i50SDRCcCjzyywZzYwJhslU5WfvnLf40Q0YixhWVFMz2drNU25QT7TCyw2QQoQQWBD4aR6IqjLi7i4jlzEA6Ul50YHIwiHE6g2maD0ylC8IoI25PeByEdt9zyPv75z51pz8nXxpYJE4l4y8jfu+76BH3hGLZu7Ufn1mFzch2Qml6Xi6oqY31+fwyexV5EBA3hoTga+nm07hjERbNnY9qwhIHn+0wzR03WzH55TuTMYClbdkxwCpDqjL8zcUfXdNRzyYqt2pGik7XSyRCdktUrPQl8pqkJ35w71/S0AoDQmsAI8085ebEMKQoEW+p9tQZbPbEYVM1oJdMSmmm2CQDxPcb6nPNcaPhSM6RaCb6jqlF9Yi04gUsLHq1ZRrbv7O98MjguptLJ9HOqlcDbeVN0qqkxgkvZnTRwlbmCgoJ8lU5fP+9giCKPeYfWm+KQPxl46HGtoEBPUTTU2GywczwgcCP8Jazth7YmY8rRVKezqO8x8wTLVunECRyqjquGZ4kP9hkOc/S1PMGnrxC5YdV9Ew2r6FTJ6XEdHYZwPn26ITqxSqdMwSa36FTYsa6rRgtL78Nd6Huye0RFRzmwGzt2jWKJo0AgXtFKLF3REW2NILYnanoLEgb5PJ0q0V7HjrNmt8vwWqq1DAFxGtcWLVxezM+m10kSD8FjnO8liUcoeV3iOQ4uYXQrglzvxdSpXlN0ilpEp4ULG9AZiSAUSkDuT6Rds61G4tHWCKLbjDZ7b7KKqLV12PwOz5xTjY2yUYkV6Yii79les10vNdlYBJIJMBajmRU/Ga1tnMDBdWBSQNkRMczU/Qq0kAoIgNQ08rNOq/LiOTiTE3Zb4jbwyC46jVbppIYUiGuisPE8opwK/RAnVvb3l1zpZPV0Cq0NQE/okOol9NiNx9m5jlXSabHRv+uRbWFoUQ2CR4BjlhEvsXs4r9cOt9sGqdGGIS0BgeOgvRtEz8NdGHp9AP73h4p+DWpCxQEOI9HlObwKQVnGJ4OG+DhfdVdEEJKHFciKhqF4HDU1hujUFgohoWnQImpFrAS0mIZoVEEk+X0YlI3PP9GbqMhrGAtIdMqgtzeMjz7qHO/d2GeEQgncfPP75u/19cX7dkw0nnlmK77//ZfGezc+VbAb7Lq69OkrPM+Z08sqUelktwum/wxgVAxVSRLsZWYn2tqGAQDTaj3gOQ6iV0QkKTqF2sJ4+OEN+H//7/W05xRX6ZQUnZLXeJnT0dERQEfYuDnZu27I9HMCjMkp+WCiUyAQBydwWM8ZwdLCqipM99uM0azJdfnfG0ZkRxh9y3uQSLZ/cQJnmnPmGp1rn2b8PbrdyCYNvNQHERziqgquevRKJzaZRR1ScGRdHSSeB18joelrU83Sc9aOxmCiU0BJvyCzceSAEXCyoDO0JgAtooKTODhmOgHO8FOoOqEGfBYxMJchfa5Kp2I8neIWPycAaZVOAGBzGUGHrukIbx69ioAdX9bvEGNajRvHHjsNhxwzxbwpiSZU8MmJiIVkrRXFGEXMcRxsDbYRQqdVdPLOcIHjueIrnQLJFtQspuEA4D7IC9+RVYa/GfMRC07ea8+nHavoVErV8VgFylbRJ5fvSSmkWmiN8xmbPmZtTbOOKwfS35dCK52G3xk0qyUAIFbElMrRYJUSrMrG7ZbM8+HAQGV8ndSoit7l3Rh6fQCDL/ej56EuRHZQJRWDVZuNVXsdO/5bPMbxyVrfAZhTdK0+PKUwPByDUxAgSTz4pJAlSQI0AGElWfFawKk9l+jU0pISneIW0WnRogYEZBmDgRh0TYdi8aFk33WPS4L/g2Hj50N9mH1YPQBgaCiKTZv6AAAzZlRh0KPikbY2hCUjcTP0+gC0hGaZbCyYJtDMd5NVUWX7LjtmOgGRg+pXjDa0ZFLM1mg3E1tWMtss3Qd5wEkcfIqAExobC6h0St8HXdcx+NoA9KiKwXgcH4p+eBd6EVYUKLIKLU+VkK4aInF4YzBNnGICppsXEN5kfIe9R1ab7wM715miU54EmBZTMfzuIPzvGcKR+2CvGfsy0WnKFKPykuM4bEqKglpYNRNrpYilga0hCByHoUQC1fM9+MUvTsZORJDQNHghmMnLcogOxKHrOoYSCVRVGaKTBqBHNtZdiW2oMRUBfxyR5PerPRiCCh1aSDX9NCcaJDplcPbZD+O7330BH3/86fAGyvTCmTHDyABMpkqnbBmg1tbi1W+idFhQwy48Vioxwc5aocL6oauOrwHXaGzPHR89g5aP3buNEuEp1UZQJngFxFw6ZE0DlwCaHIYAY70pKsZI3Ou1wc7zUJNZuA1b+yDLKvZEIlB0HXpURZPTaYgLHEY9M7OsNPPjeHf9XqxOZmoOcBsZnKGGZNCj6hh+czDtIsRJKdEpc9ISwznfDQhAvCOGngf3IrHXuIh+ODAAyTZSRLCKFPX1LmNsctIsujsWw/L2dthOqYLgFmBLZvlY5RVDSWZ/Qmr6BfO88xbiL385E//93ycCAAbixvNCa40gxLPYi9ov1KP5Gy1oOK85q+AEZGQsLTARyhSdRObpVHggzgQ9W3MO0ckmYPXgIFRNNzJ7oxhs5vMMU/wKOHAQfKK577KsmuJOMaITz3Hm55H5d0bdPMM0tcHhQCJSeDCTr9IpE5FEp0mNpulpAnahLc/r1/fgnXd24/rr38L55z9WkaEQmVjXWclKJ/Ya2fl45sxqAOnxhyxrOQW4Qiqd1IhqVnM6ZierJitY6cSuIew1cBxnJo8GBirjPRLZGjZaj0UOEIxqTHbuJoBQKNmClsVIvFLtdTyARqdxzZfqU3Ga6DbOu1yZY9bD/jh4joMkCqZnJdt31mKnhUffRqYIyqivd42odKqpcWD+/FpwHIfBcMz4rllECPa9b0zYoIWNpIz3MB+cTsk0J2e0tPjQ1ORGRySCbTVxCD4RakjF4Cv94OLG99duE41prIBpgcCMxLOJ2byNh3eJUQUZWDGMQFL4sk8d+Tlb95cdB2KVhOrPGK/viLo6SAkdakhBeFMI4c0hKMNy3kqn2O4o5L4EZE3DE+3tsLlFVFXZEVIUKKo+YtofQ9d1DL05kKwkGkbfUz3mZNlYTIHEcahr1QFVh22KHfYWu6XNMDmMJUN00nUdwdV+DL01gERfAoGVfvQ83IVIMgHnOsAN96JUi39Xl3F+sPrEDooK7m9tRaiZh3txsiW/yGEvABDYYghaW4MBOBwizjxzAW7542nYMDwMRdERayvvvKfrOmLJ9ysh6RBF3jxO9sSNdcezJA4eeGAt/u3fninYm1iLaojGFFN0UnQdSrKiPjOhO1Eg0SkDFmgzc7n9nVyiUzlZlX2N1QjTyt69FNTsK9iFhp1YrTBRphKVTl5RMiZccIBjltOsKqnWRr+pzYffHwMHwJecCCZ4RUh2wahM0XXM8xoXOGtWqdhKJ6cgGIbYArBytXFRqapxoCMSQSymYp7Xa7TXCdwIg8lMqqqM4DEQiMPvj+Hjj7vwXm+vmVGUNQ2xBh7Vn6k1J6RYR9brsj6q6CTVSKg6psb8nfcIeKq/Ex/192d9zZmiE8dxqD+zAQ3nNeGxjt1oDYXANDupISU6MSEvvDkEeZtxQe5T0r/TPM/hyCNbcPjhUwEA27uGobKMo8SZwQov8XlbE3NNQRxZ6ZQMmAoMaNSYCiVpgs2OSVYFwSZa2WwCWkMhBDUZelwb1fA73/GlJFvQxGrJ/H7F4ynRqZAsl5xQMcPlAscb7XOZWI91b4MDMWjgkBIGR0OztPmx1rl8MGFKCU6eaw+RorMzkCau5LouW9E0HZdd9gyuvvoVPP/8NuzZ4x+T2Mt6LFdSdGLxE7tJnDfPMNDduXPIfC9y+awAhRmJR3dGAB2wNdnMG9hEX+XaJzKFMwCoqzPELWsrYDmwc6N3qQ+NX55iPDYsFzVOfX8mX6VTJdrrIhEZ9Q4HbAIPzs6nDXGwe42YjUuUXmmoqhqUZKWU5BDMKh527WKik16Ah1BmuyfD57WZotN//uQ43HHHWeA4Dna7iOpqB4KKgpg/geCaACI7wkZFcTgBHkD9sLEfnkO9Znwwd24qtmlsdMPhEM3W0u6+EGpOrgUnckh0x7EwZoiwDkvcwCpy8lU6AYBniReeJV5wSREGPOCY5RqxnK7rWau8nLNdCDk18ByHxUNu9DzchYF/DeDNP27C8z/+GMdz1TilqQkH+nyIBVP7oGs6QquN1sFel4KALMPttsHnsyOsKIYw4s9hPL4hlJqCK3DQIioGXuxDoicOLq7j2IYGSDEdvEsw3ieOMycEmpVOjvT2usCHfgQ/DiC6PYL+p3sQWhOAruiQ6iTUndWA6pNq02I3VulkFZ2cThG9sRgG63U4kwK8XuR9hRpTkUjaOnToUTPW9npt2BEMQlE0RHdHzYq2UtAiGhTmTZms+mMx5u6IIbIleuNmcrC93Y+VKzvx0EMbsG5dD7797ecLKpzQYhri8VR7HQBEnMZ+J0h0mvhYA4BsN8/7I1bR6aijWkzRaSJMVSmUXDfNK1d+etokxxtrn3cmLGiqxPS6BsX4Xtqa7RBcAtzTjQtPDScVZfqcSSiUgEcUjSkhPCC4BEiSgB1BQ7ickxSdrJOHWBBYiKeT12uDQ0zeVAvAypWG6HTuuQdiVzAIXddxoM8HnuNG9XMCrJVOMVx77ZsIhxOIaxru3bkTD+3ahTt37ADn5MHbedSf04SGC5rRfPFU8/lSrWQRnXJfnNyLPGj4UhNqPl+PxvOb0RczvmvZhBBrxRer7hHcIqR6mzmBj02hk+psgGBcNJVhBbH2KAIfDEPXdaweHMS2aHbBePp0Hxob3RiIxhAIGPviPsQL3lFYpVuu9rpMT6dUpVNhgQe7wIs1EoTkvmS2nLJtblWNYCq0PohYe+6MWq5KOl3XTU8osUo0W3o6OgLmzUQhlU6eEIcqmw0anxLKMrfD4DgOQ7qxTbW/sEoUtg+8k8et//cBnnxyU9blnn12K/7855WmMDVRy8KJ/OzaNZz2e67rMmP16i688MK2EY9v2dJfyd0CkF4BkE8EKpbMqowZM6ogSQKiUdnM1OerZiqkvY611TnnuyHWSuAkDnpChzJU/vdE03TzNVhv8lm7YKXa69hUSqlGguARwDl4QEPFTdEnK/k8nSqRtItGFTQ5HOAFHlKdlJbUqp1ifNaJmAI9YZzzg8E4rrzyOTzyyIaC1h8IxOFMDgCxeVIxINt3f9LgWEyMfj1l1ZIsscb4zAmzUFfrxKxZ1fj8GfNwxBGpeKZKEDE8EEWoPYqh1wbQeXs72m7YgUBnBAdVV8OmcuBdAtwHpASMo4+eZv7MBgGw6qeOjgBsTXY0nNcECByqNAHTXC7YraJTAZVOgHHt9B1ZjSmXtqD561PRdPHUdE+tJLGYYsZHmcdBT72GoJwaEDKgJbCpZwixmIKpLhcOr6vDWdOmYUnAZVYXh9YGIQ/I4CQO7UIyVnIbSSo1uXk5rIwQV9SQguDHRuV/1fE1aL54KqR6CVpUQ/+zvTi/ugVH1deDFzhUHV9t+nexSicm6jORTUtoSPQnEF6fjOk4ACIHzs6j5rN1qD+vCfYp6Z81kIqRZ82qNh9j73U0KoOzsfUXOWG4PQZF1tAXi0FzpOJYr9eOjnAYMVWFElZGmNIXgzwkQ1U1+GUZzqQYZ7YsR+Kwt9gBDfB/MARd13H++Y/iO995Ic0L8IMPOvJuQ9d1aDEV8biCqJK6Fgzwxvsf2xObkKI+iU4WrGNuJ6oJV6VhF7tDD23Cn/98pvnFmEyeTrmC261bB/bxnnw60TTdvJlnpopWUuXh5RuJ1yaM9bMsh7fJiaiqQlP1ssath0IJY/KKaJhgcrwx3awjYgTd9XY7OKSLTsVUOgkCjxq3EdRHFcX0EfjiFxdgR8gQIVyisd1iRKd33mnH++/vgc0m4H//97OIqir2RqMIK4r5vvM2HlJyWk3T16ai5nN1sE93jFrpxJBqbXDOcoK382bgm+01s6ADSN20MJgnkWox4ZRqjItx3xPdGHylH7qiQ3PweLO7G0KO95TjOBx55FR0RaOmWOZZ7M26bDZSolP6cZpZ6cSbnk6FBfpma11SvFFVzQyeWaUT22ZrLAyxVoIe0zD4Sn/O4zbXe61FNMNrijO8kg44wPCn6O0NI8oZr2+0kbm6rqMplAyCvBp42+jHcC+M1yh0KwVdH9n0n95IDA8/vAE33vhu1v244YZ/4e67P8G6HcZ3wurJQUwe1q3rSfs933lFUTRceeVz+MUv/jXib5s39426rWLiM03WsDDmwrnTp+Nrs2eD21p5PyR2PhZFHrNnVwMwqp2A/CLXaFVXuqZDHkxAhw6+SQLHc6ZXXuYQhlIIhVIVU9bWrnyVTpqmF3Ut1zXdUpkpGh5yySEV8kDlWyknG7kqXBjsOl5O90E0KqPJ4YAgcJDq07cxc3Y14pphSMy8e55+egtWr+5K83vNh98fh0MQIIm8OU0VAKqrjWNqOCk6uSCMem+Rq9JJ1DkcfFAjZsyuNpNCABBaF4CjW0MwKkNWU9drxa9gcEsQx9bWQxB5eBZ705531lkLzJ+ZMDx7tlH91No6bGyzWoJrgQuapuOY+nrYrQmgAjydMuEdgpmUyoQdAzzPjYijdSeP+1pbsVuKofa0emypjeGx3bvx9+3b8WJnJ1YPDiIgyxAUoO+pHgy+2p8mHPmjKUN1AHAkq9tkWRvh5eX/YBi6rMPWbIdroRu8nUfd6Q1wzncBHKAl32OhwWbYNyRh8R8T36xG4sFVxr4457kw9fLphgB3ieHtma2qv7V1CBs29EIQeJx66hzzcRanRaNKWoxWzPUgtjsKRdWwIxhMO8bsdqNCb3sgAEXVEFozcrpyoduJd8agqjo6wmHz+EjtuwzfsTUAD8R3x9D59z24ZPZsSBnvw8aNvXm3oSd0QDMSpRFVNRO9//nL19HeE4Ae1ypyjag0JDpZsIpO1nLs8WJftLhlnuBZNn4ytdflCm5zGSQTlcVaFWcVHhgpT6fyKp2cggC3zCdb6wxRw+u1mxmg8GDpn3cwmIBPkiAKHASP8R2QJGPcr6LrEDgOVZKEoSFrpVPhnk4AUOsxxIfdXUYbyvTpVZg+vQr2agndUWO9HAdwBayOGYmzY3/Zsrk45ZTZaYbT2fZLcAtwzjEu9IWKTlbyCW02m4Dlyy/EU09dOKJ9TRCY6JQ6BhwzR2a3lHk26DnWzzjyyBZ0RCJ4ra8LDV/O7d+UDXas2jJEFhYQqKoxSpi110FFQdkiNrnOnhSdmBcKz3Nmxpa9J7G4ivozG8znqjlEllzvNatyEryiMSHHJZkVqtt7hgEYN3P5Kv8S3XE4ZR6KrmOoKv/3km2/V5ANj7OwZrS4jgJrqRlWLSX/GUGb9dhjopMWVidkho7IzyefpLfF5Tuv5PNt2rw5f6VT8JMAuu/rRLyzsPNWZFsYU3Q75nm9mOp0wtahlD0enpHZXgek2nbYKPZ8wtJonk5qUAFUYPPWfpx27kPo7g7BkRzwUAkjWtbWZbeLaefsfJ5Ov/jFWzjllPsKnhBsvAYdEFPDApjwUYkJTvuaWEwZYUtRDtGoYrZiZvoYAZVrr6u2GRXHrN2eMX16FSKKgoSsItBvHFPWmM6aaMvF8HAMTlGEKAmm2AAAX/rSIgCpyapVNtuo8UamxxiDtWlZEyS6pqNveQ9qHDYEEzKGY3EMRFLrX9hQDQ9ESF4RroXpk5U9Hhu+9rVDAAAXXXQwgNR3t6MjYIpjnkO8UDUdszweuKOpFjkmlrDqm1AogciOMIKr/fjklXasKrLTIm1yXYYAIQgcYqqKHXwEjulOdHUZ3z2/LGOT3483urvx0K5dGJaN1v1YWxTQAdciD5zzXClD9aSoWd/gQlhREAomENuT+nxj7VHEdhmizMrIYGoSnUNAzcl1mHLZNNy2dQsea2uD+6TqtP1k4krm9LpEd9w4V3GA9zCjoowTuLzDclgF7IknzjDFFCCV1I7FlFSMpgEo8KuhyRriHTEoiobtwWDa943jOHi9dqzo64Oi6Yh3xBBtM0R3xS9j4MVedN3Vge4HO/NWqAOG6KQoGnaFQiNEp1hMgVQjYXCKYWQfjylodjoxzW0cn15RxAyXC5s25b8OalEVOnQEozJUXcdBBxkxpQ7g6Q9bkZBVs0o21h6FGp4YyTwSnSz09KQuooWaYI4VN9zwLyxb9iA2bMivdpZLZtCU2WYyGWAXsTlzavDVrx6M7373SAAj/aqIsYFleDiOGyE2ANby8PKMxJuTRtuCTzQnrthsAqK6EYyEysiahkIJuEQRgshDcKXWrQMYihvHUZ3dXnKlEwDUeozv2NpNxnf6yCON8vCWFi92JqudeJ4DRplcB4wMyM4990DYbAKamlLl46O1/THRKRxOFPzZjPaaZ8wwhLRMWHud1fPFtTC1r0KViOZvtCBRm+4FkQ1WSfBhRx+k6uLaoEerdAKMqjprRnS0FjstrpltIsxEfNs2o8py1qxqUwi0Cvq8Q4AtaSaaa7pLqr0uQ3RiVQNVqX0+8ECj2ukH/+9VrNvZB6jZjSoZ4Y2GV9mm4eGU10QO2LEm2HhsCwSg6Tqiu0Zvu2EVXCGkgp1M4dk65evj9d3G+66TmfhkIx5XsHGjIRouXtwEIH/SxxpfCRyHOR4PDvD5YOd59PdH0toMrITWBRBc5Ycu64hszz39rLc3jGuueQUvv7QdkS1hKKoGJSl4qqqOyJbCBJN8JBKqeWPq9dqgyRrCW0JYMJv5Oo0uOo1mY6D4FSiqhi17hhCOyHjxxe2wJ1vK413xslrKgdQADeZlw2CVTpntdYFAHC+8sB2xmIKXXtqOXbtG9x2Rk22AUpVo3miy6WnWQRKapuPnP38T99+/tsRXs28499xH8NnP3lfQPcIzz2zBCSfcPaIK0Iq1wiWbPUFme93gYLRor61oVEGVzQZB4MyBDQyXS4JuMz6Xnt1GdYc16b7+oy7EumN5p5ClTa6ztCydcMIM4+/JSqcqScLwUP4bdha3s8Qag01aE5yp9UdbI1D8CqqddgTjCQzFEmgdCiKuqNB0HUdNbwQA2Kdnnxb3wx8eg0cfvQCnnTYPgGEL4PPZoeu6OdFYrJKwNWK0hrn3JNvvhXSxRYuq6HqpF523t6Pr/k5ceunTuOyc5Vj3Qnve12olc3KdFRYPvfvuHgwORk3B15pkDCkKnujdg7qzGuBe7IXv6CpUHWcIQ6zakgkgX/jCXARlGV3dIQy/M4jgmgAUv4yhfxnnrJe37sG1N72N3/9+Rdp+6BwQjStoj0Tg9KXvZ2Z7nVnpFDHEEWm6A2JVYfHanj3GcXjUUS1pj6e110nG0B0dOla8055WNJKL+J4YdEVHlNPQG4uNMO73em3wyzLizcZ3bvitQchDMvpf60e8Mw7ohnl3cJU/Z9WTGlWhDBjtdbvD4VR1mUV00jQd37zuJfzypY/hTx7vU5xOHODz4T8WL8RXZs2C2p/Iew+rxjQkEirCsgye58wWUQDYNDyMvXuDiO6IYOitAQy+2o/+5/ug5plWuK8g0cmCNQAe70qnZ5/dimAwjm9+8+kxmebCSE1LML4YZjZ+Eno6LV7chB/96DjTzLMQI9NiiO6MYPi9oQlZsjiesIuM0ylmLZWtxPSVREI1PAl4Y7x7GnZjm8G+0idOhEIJOAQBosibF0sW7A1YRCfrSPB8rWbZqHIa+z0QMPaTBTotLT4MJrfBFejpZPU7OOigRvNGb+pUq+iUv2TK47GZQUuh35VihTZGqtIpdaEWnAI8S3wYDsZx98otGAzEClo/u0Hq74+kVU4VQi5PJ0nizWM3HleNzyC5yGgtdtE2w+hXrBZNwZL50jAxyNhmeuvyaCOFc70XiV7js7KOvT7ggDrz59fX7wEAxNqzn6e0uIZY0ihz9eDgqOKktQp2VygETQMS3UVUOimpZTOvK9ZAcd26XiBZZVhOqyyx79mwoReKoqGhwW1mXPNVNLD4ysbzuHTOHJw/Ywa+OG0arpg/H7U224hqJ13XEfjYj8CHfvMxJccxomk6fvzjV/H227txx40fItobQ1xWcce2bXhmzx6oqobIzvK9iljsxHEcpAgw8Hwf/O8MYb5sVAn19UXSlsvGaC05il+B3x8zr0H9/RHjPOMVAFUv2yx27dpuAIa9gpVclU6rXtiNY+rrIXAcbr99JS658MlRjd/l5PlKtPjY2JqTolN/wjz/bdnSjxde2I4//3llWQmqQunqCuKccx7BP/6xruDnaJpuCj6sRT4fv/zl24jFFPzud+/lXMY6sSxf/JRIqFBVDV/72pM4++yHC9o+IxqRUSVJEHgu6yRRW/Kxvg5DzOjuDqFaknDe9Onoemgv3vntJvQ/25MzAZMSnYQ0f0We5/DiixfjR/9zPFxuCQLHwd+bOi9km+Caq72OtYFZB6Iw/79ahx2hROraklA1KJqx/KrOPnjrR1ZVs/2bO7fWjIM4jjOrnVh7LACs8g9C03WIbBMWsYfrlSH3ywgnP8fhWPL7rup47rb18H8ynHXbmeRrsWRJu2Awjuuue9OsdLrqqqPSltvVNoxrb30HvqOq4FnsM48nVunEBJAzzpiPj/1D2DMYRDCYQHClH72PdUOPaZAabLjr3c0AgGee2Zq2fuv5KrMFMGUkzqqjjH3WoeOTT7rx3397t+BCgGzDDYD09jqO48CJHPz+OH7+32/i+uvfgq7reVvgoq3Gd7dfZNMi099r9t4PNuiwTbVDl3Ws+b/teOuZndi4tQ/uzxjHhjwg56z2ju02zpkhQUNUVU2hj/2vKJrp97cjGMRHYUPoO7yuDme2tMDntsPpEDHN5crrb2j4ORmtdY2NbjQ0pBIHe6NRrOkdBHQguj0CaICt0ZZWhThejP8eTCCslU7jWSWTmRkbzVCsHDJP8OxLPRnb61jlBvu/kp+hrugYfnsQkU0hDLzQh8HX+6kFJAlrEciWpQNS4ke5RuJNyUonqS49WyIljQyDfaWLgabolJzuAqRu9geSWbpyK52m1BuCUFRVcfnlh+Gww4wpPlOnes1MIMchrcom57qmeOBwiOB5Djfe+DkzuGhpSWU7RhMTeL74FrtSRaeUp1P6MeA53IsbPvgET765HY89trGg9dfVuSAIPDRNL3qkd6q9Ll10MqbgpAvuXHIftDyVTrquI7w+6cl1QOqiv3XrSNGJbZNVkbIAQB+10il9X1krH7txA4yWQwYzv4+1R7Oeo+IdMUADQlDRH4/nfK+PP346AODSSw81978zGoWmaaO272myBjU5ha7H0u4QjcpYvbrLzPxbW3RkWcVAcmphooD2PWLisG5VNw6prsYXF8/EXN6FaknKK2SzG6zPT5mCOrsdiq4jpqpwSyLOnj4dW5Oik64apvmBD4bNSUyuA43vmTyUffrZu++2Y8OGXnAAPtfcjB07BrGmfxAxVUVbOAxV1aCFVGhxrWh/Iissvjh39nQMPtsLOWmwXxXiYOd5U1Bl59ZsSYDR2usUv4zh4ZhZbfvYYxvx05++BlSxSY/lJQfXrEmJTmpYNQUg5slnragJfDQMfWUIJzQ24sKZM3H5vHm46sAD8dLDW/JuI5ocP+6YnmqTEdwihCoR0FOjvVlliaJo5s+lous6tFHijfvuW4vOzgBuvfWDgr1arLG5Nsp0K6uXV74EUD6xwfpcRdHQ3R1Cf38EiYSKa655BZGIbCYxNm3qwzPPbMn6WuSQAp7jwAu8WSVuxV2bnLjaE0U8riDWE8c3583D3OQAlYGBCGIDCYTWjfS5AVLtdZIlacdobHTj9DMXQE2Gh4Hu5E35OqNNNnOd7LyRaSTOqjR4i2cUG5xR47QhGE+93wORGAYjcTy1qQ0r9vTCVpP9vc3GnDmGsLDlw24EV/sR2RHGcCSOzX4/+GScxRKDuqZD/sT4nscUY/96w6mY5JF1O3HOVx7DffeuwU9/+lrO+ypd09G/NQAtosKh8SPMva1a5AcfdJhixLHHTsPy5Rfi4Ye/ZP79jTd2ob3dn/Z8doyxaiSv146aA724e+dOdLmMYzqeUNA2FIT3lBqoyWMoM05i56tsXQ25Kp0ScRU7+wNYvbuvYIE3EBg53ADIMmXYxiMYTEDieXz0USdOO+0f+PnP38q6Ti2hIZZsSe7UY+b7YIWZlm/Y1Ieaz9WB9wjo6DCOz6c2tOGZD3bCucC4/gy9OWBaHVhhwlafkO6j5XbbTDGfmaQDwMrtRixk53nwHAebXYDHa0OT05lXWNaimmki3tTkxpe/vAgXXXQwfvrTEwAAr3buhWOWE7yTh3O+C9Wfqc3b0rivINHJgjXrOpbVRaOxd2/65Kbdu4fHbFtMUU6116XfGE0G9uwxTrDMsJedqCopOsX3xlJZHh6ItUYR2TF6OeenAXYByDXxsVJG4qzSKdMI054s2Y0Ol9de5xQECCJnqXRKik452uuKmV4HAKecMBMHH9yIf/+PI/Htbx9hPt7SkhKdeJ4zetRHweu145FHLsDLL19iTlxh62IU4jVVjOik67opGhUrOrF9ybzJ2rixDzuSo2FXrtxbkOjE81xqtHGBviKMXO111sfMgMY0qtSR6Eugb3k39t7Tgf4XepHoiRuC04YQlCGj1NtlmYyzZYvRXpde6ZTul8dbprtkgx1f1vdCDSuGmMMBtqZUwLRoUQPuuOMsADDM7x089JiWtcWOeTj0JI3Bcx0nv/vd5/HAA+fhi19cYL4/QVlGgjMMLK2tMZmwFkDeyaN7MHWe7O+P4Morn8O//dszkGV1REn87oDxeRbiGUVMDMIbg2jcqGLZ1Kk4yl2LaUEbzpo2bZRKpzh8koSFVUYr7qNtbbhn507YvBLq7Xaz/W3orQH0PtaN8Abjd9+x1ag6ocZIDKjZK+K2bze+e4un1qHB4UBHdxDv9hotzbKmIZasgIgPJfDlLz+OSy55ComEip/85FVceeVzePLJTbj55vfzigrt7X7cfPP7OKKuDgdVVwNInS9sNhEHV1ejtzdsVGgNxlAtSZhlaTuusdnQ7HAgOoqRuDKswD8cNxMfAPD667uwdZfxGnMJ1oUgyyo2bDBuag49sBG9T3Sh+4FODL7eD9+wsczgYNQQ5oZk9KwYQH9S5J/qcqHaZgMHYBac2TeA5BQnvwIIQEciitNOexC33GK8t/YW49rDxpdbhabt2wdLek2hdQF03deB7vs60X1Pp1l1kA2rAFCoyBUKJTDf68XJTU1AWzynN1hr6xD+/d+fN3/Pl3AbTXRiN/eJhIrOztS9QX9/BCeddA/OOuthvPZaKy699Cn88pdvZ/VE08PG9lU7st54VjUan+H2Df343Cn3YUHMCZHjsDcSwV07duD5jg60tQ2j6/2BrGIeq3QSpZGiE4MJRK89a0yVY1WLgQ/9CG8OIdGXgKZquSudIiPb65xzXBCrRNQ47QhbKp32BiPoj8SwpW8YVR47nHPSB5vkY4bdhfjeOFY8uQvdD+xF5+3t8G8N4cPOXjN5xvYl2hqBlPxqRmUFd328Ff/71pq09Q0EYvjDLR/gtddacf/9a/HPf+5MEwZD6wJou2EH2pfvhTwgQ98WQ9sNO9LEuEyxij1/yhQvZsyowvz5dfjRj44z/55ZqJDp6QQAzc1GvLIVYTR8qQkPrd+J/3z8PfziN2+by2R6tLLYyOEY2dWQMhJPxrLJ4yAckfFe8vz7+OObChpSxe5LM78TLF5lcThv4xCNyLAnJycODETw4ovbsXFjLx5/fCPefTfV3hhrjwKKDqFKRHdSGMw8xlg73wcfdEBwCOiZBbzR0YUn29vxUX8/Nm3qw257DLxXgBpUMfTWYNpnqUZVJPYa+96hRdPeFwCYM6caAPDRRym/r/Vtqe+rP5FA7zQdXo8djQ7HKKKTilhMQURV0dTkgdMp4T//8ziceKLR0rq3P4zqz9Wh+ZIW1JxcNyEEJ4BEJ5NEQk0rpxzPSqdM0ancrE8+Mkf+prLxlW2vS/TGjcxkhacC9vdHsGKFcYI99lgjM89OJMFgYtRsVKEw4zjXIg+8RxjBY2QTiU5AquQ22+Q6oDJG4pABnyQlK50ySmLrksaqgfKm19lztNf1x4yg2GivG1npVKiROJ8AamucmH1AbdrjU6d6EU/eCHEcZ06QGY1p03xpJotsXYxCxLBMQ/J8WFvjihWdZs40vjOtrekeINby7Y0bey1VAfnX39hoBJGF9PFbydVeB2SZYJesOFMDCgZf6TNMbxUdib1x9D/bi647OxD4YBiAYZDJjptAIG6WTy9YkGp7y2yvM0f+xgpvr2NtbVKdNGLi3GGHTQHPc9ABaFOMbUW2pb8/uqKb2b4uNT5i/VbsdhELFzaYwSW7NgRE4z3M1b4HpAQpqVZKq5awtrCHw7JZXcze+w2dxs1moj9BlaSTBN3OIxJMYDAeR9VsNyRJQLPTmTULzAgGEzjA54Mg8Djg2CbYGu0IKwqaTjJE2ka/iNCGIGKtqfNt1Uk18BzsNdrZ6pPTl/pHipMsM33WyXNx8MGNaAuHEVVT59Rg0ti+d1cAu3cPY+fOQdxxxyq8/vourF7dhRtvfBePPLJhhDG6lR/+8GVs+rgHJzQ2QhR5VB1fgynfnAbfcdWw2QSc0tyMM5umouv5HsxvE3H5/Pn47vwFuGT2bJwzfTq+NW8eLpkzB0vinhFVDeb7qumQBxKIRmUz8cEIJFt42Llj/foeXH31y2YCrhBaW4cQjyvw+eyoCwvGNCTdSKhhQxS1NhsURcPwcAzBj/3Y1TqMbX4/nh/ci9ZQSuyviQs5W4RZ3GSf6sCb77Shvz+Chx/egNtv/wj2pKcdq9xkca5XktC6pfjJw4m+BAIr/dATujHdE0BofTDn8uwcDaTfBOYjuHIY50yfjiPq6mDfKaP3ye6sx+Cf/vRRWmtMZ2f2CiHAeoOdP2lniE7GehodDhxWW4v5Xi/sUR2//J+38m6LS7amaY7sN54zFxoxSa0q4piaetTb7YiqKuqWNaBhlhdbAgFs3j2IDWt6zEoOK35/dk8nK0ecOgM2m4C5qhNr7tiBcMSYyggA/neH0P90D/pe7oOaTLZkCgJmpZOlvY7jOTSc34RqhzGA5NUdHfhoTy92DwcRiBvf88YDfAXfcIfWBTB7CweoOrb2++FPfs/icQVdHaER9y/hDUG4ROPatdsfwgtb2xFKZDnvJa9ld9yxCv/v/72O11/fZW6v655OKH4FkaRo5raJUPwKuu5JVYGdeeYCnHjijLR4wmYT0kSZr371YHz/+0cDGCk6MWGTtXgBKdGpuzsEqdaGp1a1QtZ1vPpqq7lMIBBPq07PF+tPmeIBx3Ho7Q2jry8M3mHYJ+yR4ub5IhCIm36X+cicCpq5zyyO4CQe4YgMG59+zF1zzT/x29++hx/+8GXzMXYtcc5xIZhD6D36aEN02ry5H35/DM+9vgMr+vrQqxvLv/ZaKy6/6nn8/v31gMRB7k0gsil1LoxsCwM6IDXaMBgduQ02HdH6+WgA3untRWsohAd37YJWLcLrtaHGZsO2PGbi8pCCwcEohhIJHHJIo/k4uyewTlCeSJDolOQPf/ggTewpVnTq6QnhP/7jRbzxxq6y94VdNFgfr9CpoO/pnlEd80th5PS6yhuJR3dG0P9ML/qe6MbAi31Qw5Vb9wsvbIOm6Vi8uMksi2WvRdf1ihjCa0pyGgQAxwwHXAvcgGAEvNkCjv2BaFTGdde9ibvv/qSAZce+0smWvI5zjpGZNF+jITqVelypqoZIRIaD59NEJ3aTPZxIQAcg8Txiw6mAothWMzalTPCmCx7WljiOS2XRSiG9va6ylU7WbG2xohOr+LEG4pGIjFde2fn/2bvv8Diq6+Hj39m+6r1a7r33XsHYppdQQocECAmEN5CEhBQgpJAEEuAXIEASQoAQCB2CKcZ0MBj33ot6l7b3nfeP0a52pZUs2bIlwfk8Dw+WtGV2Z3fmzLnnngtox51wWI2WHR/p8SMN02OnRIP2nX/ggc87/Nx2NL1O24b4hHtkdRT7ehthTxhDpoHsM/OwDI5J9CmQPC6F5Amtyb7IeSQ7Oyku4Gg3vc5ypEqn9o3EfZGpdfnmdrePnS7pydSCbO8hD66dMUHRfheqN4wuRU9dsGsJvohIddleh3Z+cm114DnkaReINzZ6ePEfW6mpdWLMN8dNgYz9nDmd/mjwuHDhIACeX7mLrbtqCflbm7OLvu2Qx8l/Dhzihbpyhl06EGOh9plPd3b8uXI4fIxOTycn28rIxYU8/fS5vPPO5Uw6vYQGvw8lqFL3oXasKFM93L1xK/681u9sZOAhmOAzEkk6FaRYycq0Empzob31QAMut5/G8taL50TNq202X4eDZKWlNmbl5GBQFGz6YHRlrOQxKSQPT8Jo0DEsNRXbbgcBv9bU2GLUM2NkASNSW48VGWEjrh2JqzX91T58riCuQJA6r5fZswdE/1Zv175HYW+YUCjM1Ve/yscfl/LII+u034dV/ve/Pdxxx/vRqb5tRY5Tgwam49kdn0jQKQqLhmkLXRz8pAbPQTfNdi+f1tVx/U9n81JpKffu2EGjz4fPE8LTQdV3JPlsLjJHV/MDeOut/dFV1AK2IP9+egvvvXeQTJOJbw8fzsBDOjzNfj788BBbt3bchDtW2eoaykrtGApMZK3Qzjf+qo6rkSJN1KFrSaeQO0Rwj3Ys2+9w4FFDEFS1JeZbPifBoHaht3t3/IW13e7rcPZE2+lkYW+I+tdqsK9tBlrP46WlNv7zn20MTk7m26NHcFJBAWeXlHDZ0KFcP3IkE1oq7hJNOVciK78lJY4JRi8qxK9TSTYYmJ6tJTZWVVVxxTWTueyyiQBsb27G7w9Rs6F98/jmZi+WaE+nxN/7nAnpDB+eRarRSOVhO298coAvkh2kTE1DabmP+5Cbhfn56PW6domNSE8nvTX+NaRMTGPMdUNAr7Cuop7VBypp8vhxG8IYc4zkDk2lKyIr4eUmWxmSmYqqqqyrqENVVfwtiRdHpQdjronU6ek4t9hp/rAJs6FlWn6b+Pb8cUO4aqpWJUybPp1r11ZEny/CHWhJOhlbX3fdyzWoYZW0NDP33beCe+9dFv1bpHdtrMgxYt26quiAezisRq/zIvEBxCZwnB3G5rE9zKDzVhqZmVbGj9eSHx9/rFUYpc1IZ01T/PEn9jjQ0XO27TUckZ+fHN1m0KpL3e4AJn38ZyJ2AQSPJ0CgKYC3PJJ0ssbM8Il//NzcZIYOzURVVVau3Msbb+wF4MYbZ8Td7r3PDrPOpr0O25pmPPvdqGEVd0uslTw6pV3zdmidutk2v/BFfT0vlZZqPaAyTaTlW1EUBb0j3OHqkc5KN3a7n1qPh5NOGhL9vdGojx5Lutt+4kSQpBNakPzCC1rjtMh8yO5Or/v73zewZk05t966ip07O2/wp4Y6b3YWCQbmzSvBrNMxJpyMv85H49v11L1S0+kIYne1VjrF93RKVOlUXe3knXf2U1np4NVXd3WpR48aVKMnTwB/pY/Gd+t7rOLpgw8OA3DGGSOjvzMYdNGSxp5oJu7a7iTsCaNP1WMusqC36jEXtpSGd5J0cjh8vPzyzn63ip6qqvzmNx+xcqXW1DN2RDCRI1U6tV19JVYwGObVV3cdsWLFHG6ZS5+gH0FmYUvptC/c4ahxZyKlx1a9Hr2+NekUmaoWBgJG7XEDjYFo4iJRUqAjaliNVjC17amQk5MUfY90x1gCG1vplKAnaTuROeZtkzeJ9HTSadWq/Xg8AQYOTGfFimEArF9f1aXHbw0+4j83+/c38dRTW3j44S8Tfu86m17Xrl9Ay3SZkK1lhapp6ZgLzGSenE3W8hxyv5FP4dUDSJ+bGVdqHgnSIn1RIiJJrVBIu1CM9nTqVqVTpJ9T+6QTxCQRwwFSp2kJSPuXtmiDzUj/qZRxKQS6mTSN7MOP9laRPE4LWJtW1VP193Kc2x3R13bNNa/hqvCwZ08jxtz4SqfYfzscvuj+W7x4cPT3mw7V09joJnAMq1GKE2fjpmpKXS4mTy5Ap1PImqBVNeaGTR32MPE1Bci3WNAbdVgGW7FajWRlWbEmGVmn2DngdOJw+NGn6vnZPz9lzdpynnqqtR9IZNXKQHOipJP2Wcw0ad+R6QsHxP29xulm/foqHNXtA3KrXk+h1YpZp+PWW1dx+unPtKs8jxjekjwqs/ij339Fp5C5OJvPA018VFvLMx/t5p8b9/DnnTtpnGxk4pWDMY9Lpnm4nlVVVdhsXva9WZmwqs9bqvXX2e9wkJ2TxB/+sJTLL9cSADWN2vco7A3x1lv7ovf5/JMyfvjDt/nr79aw858H2fZBJY8+uj7h9ke+e6NyMwi7Q+isOgq/NYCsZdr3fFp+NmcOGEBwnZNAIMyn1bU0+P1Mn14UfYxNTVq1lG2LPXEvoZb4yJhjirvYrKlxUuvUllEvP2zj0b98CcCSggIMikLAGeTfP/ycd/+0jedvX4fd3vmgSNgXZt1bpRw82MTK0gosJVYMhSYamzzYN7Wv/nK7A3Exx6FDR64Q85Z5tL5KHg8vl5WxNdUNBgV/lS86jfnuuz/m5JOfjJ5Pn3vufDIzraQbjVR2UO3Utiepa6cLf40f52YHti+aMQVbzy05dj3nDRxIUUEKrmCQep+PwUMyGDkim6umjaI4KandioMA+pZTYWSKW7u/G3XUpLfG/Fubm9ljt6MoCnPnlpCVZWVHczMAtgOudlPsmpt9WqVTgp5OEcZsI9nZVpJbYvPnDh/mlbf2kDYtncLLi8k8JZtgIMzUrCwGZqe0m74ViZ90Se0fP29WNtOXD8SYZ8KYbSQwyozplAx0Vn1coqUzkZXwAGYM0BZD+LS0hkC49bXqXGGSx6eQMik1mjBKMiZ+T/NStOSVtvHx3w29Xol7PgB7S0+qZFPr4wWbg3GVZUVFqaxadTk33TQreq0aa/hwrSm6xxOInmubm73R72Zsn6zWSidXdLW4RGJbGMROr0skMrXro48OR38X+d4PHJge93NHXC5/dHvb9lyKbLPd7sPtDuD2BwmFwtHpdW0NSEqi5otGmlbXQwjMJRYMmcYOK6mgNXH3pz+tIRAIMXlyAWeeOard7R5/fwfWkUmgQtN7DVQ9UUHIEUIx67AOS4peV8RPr8tMuJ1JSUZ++MM5LFkymFNOGUby4CSsVgNTs7ISrnwZDoSpO6RV3mUOTolbtRoS9+TrKyTpBKxcuZdQKMy4cXmceqq2olTscrhHUlZm4+WXW5sp/uMf7UfZ1aCKe5+L2herqXq8nIaVHSemIvO2Z84sZnJ2FmpY1YI3nTZy1PR+Y49NPWib8W07Gh/R0ODmqqte4Wc/W81ZZ/2HX//6o7hgpyPuvS5CzhC6FD255+aDQStJPNZVV0A7OG3frs0Vnju3JO5vkYPrsSZ81LCKa4u2P1KnpUcbCBoyW1YiaJkymOh5fv3rj/jtbz/mD3/45Ji24XgI+8LavkmwhOamTdXRChSA11/f0+ljHbmRuHaYiVxEBxoDNK6ux77exluv7ObXv/6I8857rtNEr0VtqfpLkHTKK9YOuH5/OG6qUjisYrN5CTmD0R48iURLj01GdIoSbSQ+aFAGzz9/AQ8+eBrLzhuJ2WwgXW+IngS6U+kUdoe07JUuvhEmaImmwsIUgqqacPWa7ogsdQ2JEyttRaa9xY76diR2NOxok0779zdFHyfyGTv77FGMG6eNkEWC9aOtdIr0cwESrvzRnel1cQ3d9WAeoB1TFJ2CZaAVY5Yp4UqDrUmn+KmPsfvD7w+16+kU8oTwx/RJavv5CvvC0RW7TIVHSDo1e0mZlAY6re9L2B0m2BDQ7m/Q+k+1Jk27Nj00sg8PH7ZhnJiMIaahv2e3dgH3zjv7MTSGyDSZUFWVxnAgbsW62CCoqsoZ3X8TJ+aTmam9X7VeL83NPm06I9q5sycHWkTPmj17ANdfPz068JMzSps2l2M2U1ma+GLG2qQdi73J7SsXRk/O5aXSUu5at5kfvfEFtoC27597bjtnnvkfHnjgcwKWlsa3WxviGjZ7vUHq6rTPYrKiPe6yc0dw882zowmbppb+SLYq7bNYWJDCuGE5FFqtfGv4cC4dMoQbRo1iRVERDXVu7rjj/bjtU1WVAouFZIOBQDhMfSj+3K/oFbwZCmvr63mzspJddu09SM2zkjoylXN/MoWZZwxmS1MTrmCQXVvrcCeoYveWevF5Q+xzOCgqSiU52cSsWdoFUXWD9r0JecP8+99bAZiZnc21g4YzqExP9p4wJcnJLC8qald1ExH57g1N0y6MzQMsKHoF8wALuhQ9WSkWRqWlUVntZJvDxmd1deTmJsWd57c2N+MPh3HVerUlxWOEvaHoYgLBZCV6YVvS0ttq/cYq/HqVw4eayWjpcTU0JQUVcPuDpAR0jMvIYGxqOnvXdz6Q6zmsVRo0+Hx8slGbuvLsl3vZtq2WPe9Wxa047D3soezf5czNzY3+rrq6/dSptnylXkJBNTpVqMHlJbmlws21zYnd7otOFzcoCsOyUhmQnMRlw4Zw7YgR1G1qTvi4kSkwGRkWVFXFvbv1nOba4kC3xkmq0UiWycTCvDx0ioKhxMLQbw+k6KIiZt4xlqEL8jCb9SzOz6ehvv1nyRLQzlPGzI5jgvNumsRbzdVUj1DYioPvfGdadLveeusyVpw3ClcwiMPuI1AXfzy2NXtJNhgwGvXRFVzbUhSFjIVZjJyUy45UD4FwmB076qLJP+vgJLzpCjpFYW5ebrv7R2K7tvFTxD/+cRb3PbgCXZIeWzAQXYq+q0mnUExF3KLB2iIvm6obqLC3nrNMej0hezAuYRSpdGorN9kSTToFmuOvJT2eYLTvYUS5XXsfClOT434falOpl5lp5YorJjF2bPv3SKdTorFRJFkUSWqmpZnj4qrYSqfYRFBqqpklSwZHk0SRlfLgyP1bIxXLa9dW8Je/fMEjj6zj4MFmAJYv1wYWY9vYJBJd2dSkb1eRnpxsijbmrqlx0mDTPuuR6XVmnY6TxgxgeVERlw0ZwjcHD8azzk6wKYjOoiNjgTZAGLlea5vUgtYpdhFXXTW53bWNoiiUl9upygmRPKEl4dNyTZ46NQ3FoLRbMRBgyJCMhK954sR8Lr54Avfcs0ybNjkhlYxMC8NSU1n7xqF2tw82BbDbvbiCQabPLW7390jsKUmnPkhVVV55RUsYnX32KJKSjNFqg8iHvzPvv3OA33x7FTnm1g9v26xxyBui9sVqmt9vjJaD+yt9HfZuiSSdBg5IY2FJAQD1RZB3YSGKWUegzp9wXnV3hcNhBuusTMjIiCadIhdjgUAoWp4ZCoW57bbV7T7AR1oqV1Vbyw1TxqdizDFpU9PofK59V23YoJWQlpSkk9oE1f+pxPZZE56DbtJ7qJl4oCFA2BtGMSlYh7VWLhhaTt7BpgD33fc5S5c+ydtvxyfhIlMtYxM4vS3kCtG4up6aZytp/qCRxrfbV51Fvg+RA+3rr+/pNCCLnIjaNh2MaK10ChG0BWhYWYv3gAfnBjvmLzxMyMjA6w3yf//3RYfPYWlZvz7Rcr/5hdqon98fwtekfWdDgTB//+GnvHrDWvY+doj612pxbU9czeNw+FCApJYRptiRuiFDMpk9ewBJeRYyMixkmc1s+qySpg8buaRwIDeMGoWy0d1hT4uIyNQ/fbI+YX+B4uJUXjh8mJBOJWNR+7LprlIUhfvuW85tt82PBg2dGTQwnbAvzL6Ndbj3uTqtFIskQXQ6pdsVWYWFKaSmmgkEQuzd24jPF4yunLR48eC4httw5KRTZKpXbEAE8YmmRNNKIgMJiabXtVZ5avtKidkGc5EFXRenoXVU6RT7nH5/KNqTKexT8RxwU/tsFfWv1OCr0ILEto3E/TU+UEGfbmh3oR4Rm3RS9Ar6lpUdg7YAnoORVaQs6My6bk8PzcqykpubjKqq7DvQROZJ2dHjYMAWRA2rfPLqAc4bqI12Nvn9fPx5WcL3BuCFF3YQDIYZMSKb/Pxkfve7k5gxo4gaj4fmZm+0SsK+zkbtSzW4d0sPvb5oxIhsrrlmarTE35BiINgSZ9fsbk54n1SXdvzwZbX/7E2bplXSHDrUHFc17vMFqapy8NRTWzjtgv/wxRcV7NvewH+e2hq9TaQ1QUaqGZ1fO5YZM41ceulE5s9v/VwC+Or8zM/L46ezJnL30hn86RtzsbZM09ApCuMzMpiRnc3GjdVxfXJsNl90Va9DTidlFe1jmdjlqyNiL34tFgMqsKclIVW1MX70P+QJ4ar1Ut/gptTlil4gFhZq/y+vcaKi0ljtZs+eBnLMZubnaYn7PEvr86QZjaS4SNjbI1LpVGhoaa0QSarrFdJnZZDaMjX4ncMV3Pn8F6hofQQBLrxwHFarEWuKkR02Gx5PEO/B+PjQXx/A6fLzwZelnHXec6iqSlaWlVNOGQrA+vWVHKyxEQqrDCvMYPnYgRQXp1Kt8/N2ZWXcY1VvaW63/XF/b5nytdduj8atT76xg63NzRw61Ixnn5vSUhvuQ24aV9XjrPIwNzeXm2eM56wBAyg2WjqdYh72hvBVeAmGwuxvWR301Vd389+1+wmFtQUbPn6rtRfOqcXFXDFiOA2v1zEgWfsslK9rSNhjNPK86elmvIe90USdMU97/5WgypnFxYxtmT530OkkfXEmS04eynnnjUGn05E2IwOjRavSUxrikxRqWCVZ1T7XlpzEgxUAw4Zl8cRr5/ODX87jtdcu5tprp0X/ptMpTJyUT6XbjcPhJ1DXGlerqkrArq2OZzDr0CUYGIxIHpXCqO8O5a6HTmHixHwAPvjgUHQ7a/0+CKkUGa1xsYgaVKNN8zs698UuMFJf7455X7uWdIqtAitMTWJSYTao8MbulmbUChh0Cvo0Q1wiKNNiwpqg2ik3yUKKyUim1QwhNS5GrNjZRN0r1a2vT1UpbdZimUEZ8VUrHVWndSRyjIgknSJ9SNsm3/LyklEUBb8/xM9+thqAs84axfvvX8k99yyL9gmKrXQ60qyGYcMyKSxMxe8P8a9/bebvf99AIBBi8OAMFizQElL79jV2ej3RUSP5iNheVPUtr82k1zMuI4PrR47k9KJiJmRkUGDVEi8uU5iUSanknpePPtkQVyTQdnodEF1VOqJtQQPAsmXaMex/b+wlfXYmmSdnY8gwkDI1LVoFHlnFL3Z6XWamlREjsts9XuS7EGHIMFIwVbsOGFhroOFA/Dkm0BDA6fBT5/VGB2xjRWYwJKp67G1f+6STw+HXyrqtRpYvH4aiKNE+HF1JWFSvqmNJQQFXDB3KXefMJM9iaTdVyLPXHT1IpU5LQzFpAVdH0wciI3X5XiMFGUnYAwHe2HgIQ6ohmvhomyXfsaOO6657vcsNEUOhMI/98FNOyitgeVERrHURDoTbjcYDPProejZsqCIpyciFF46L/v1IZZKB+oA2Wq1XcKar3HLL23xUqh1ofeXehFU23RHp/7Js8kBsnzYRdoZwbXfS9G4Di7K0L2LbYKu+zMl9332fX1z+Ji88u/2IzxG5ADQXWuKSBcaWSqdAU5BnntlKOKzy85+/x/PPb+f66/93XJu/HwvnZjveAx6taSha5Zxnf+uByen08+67WrLsgQdWYDLpqapytFuCNVZXG4mHPWEa3qwj7AmjGBQMWUZ8riDLi4pYmJfHhx8e7vBkFBm1NqUnnkte69NKiBv2OQgHwqz+/VbSGrQRkM2ba9iwsYr3/rqTw7vbj7LENhEH2jVoBjBkGMjIMDMpM5OCPSqePS5S9AbtIqU6QPWTFdS9WtNhH5qQM5J0SvweFRWlUu5283mKI5qYPVoLFgziG98Ye8TbObfY0b/UTKDWz8FtjZT+5VC7VVNidTdJEUtRFGbM0C4mr7vudU455Sn8/hC5uckMHJgeLQuPOFL1TaSfwd69jXGVNLFJp0SVTpGEUuLV61p6M0QeL6aaNGlE1/dJR0knnU6Jvnc+XyjaxyLsDWFb04waVKmpdfL3331BTY2z3fsdmVpn7mBqHbQGlpFpxYbI0uq2IN5D2nZFelJFKp26sz9Hj9YCpp076zBmGMn9RoE2DTGoUrqjEX+ZF0VRSEszs6qykuef35HwvYHWPipnnz2q5fNRzD33LKPe78PjCeCs9OCr8uLa5oCgis76tQ9X+o1AivZdth1qH/QGHUEsfq3hvVLQfqCibdCfiC8cxhnUvqf2itbniPRzGlWShYJWtZpoYYh6n4+gL8TsnBxSDAatN1uaiVKXi4d27+bNlqTH7NxcUg2G6LRf0BYviCSd9jmdTJ1a0G77EvWSjL3oy83Vjg27W5JOjpiE/3//u53nHt3M1q217CpvwhcOR6dNRy64mlxegkGVysPa/a9aMBqdotDo8/FJbS1vVlaysbERk0nPjJychM17q6udZJpMpKHtg8hqcgCWIVZyZmaytbmZdQ2t940knW69dR6rV1/BvHkl7LPb8XgCeEu9cefvQJ2fujo3e2tt0Ths+PCsaCXBhx8eZv1OrWr43AXD+cac4QwbmoW/QM8uu51Xy8qiCZ7IipuJ+Cq92Pe7UIHtNhuHDjVHL7T3ORzodAo7P6/mvPOeY90zB1BVlcpKByowPC+d8TmZnFJYSHWVgw8/PJQwdnNstKMGVJy6EDUtC4uEwyqPPrmBN9YcJBRWWfu2lmDPMZsZlZaGxaJ93nIHalPF/FU+XnpxZ7vHjhyrM9LNONZrcVbK5FRyz84n75uFmKwGSlJTmJ2jDcxsb26mKKZ3I7RUgJdo1y15nvjvVNAWRA2pBMJhkjpJOh3J+PF5VHg8OJ1+XBWt+6Ox0YMpqJ3jk3MsXa7WPvlkLUn93nsHoyu47Xy9nHBAJdWn4+Cv9kZjkei1gl6JXj8lEnuxHemF09VKp8hKeBFLh2mf0w8Oat99k16PMdOIdWhSXCLIZNBz74pZrBgxgMsnj+D0USUsGVpEYaq2Lfcsn8kNs8ZG44mgPUjZhkbCrtYkVKPHh8sfRFEUitNiBrczDN1aeQ+01gNhX5iDn9fi3ueisaWvT2R17+hjG3Tt4u3YPlGRY07s4gSJpozFUhSFhQsHtvv95ZdPZNiwTHQ6heZmb6e9hiLHzo6STpHWCjfd9BZrWxZ7OGPmEK6fPYZpkwsxpBtY39DAmro6XiwtZU+On7SZGdHY2+HwR2O8SJIyltVqjE6Du+yyidG4NFJBlplp5ayztOl2r7++B7vdh3VoEnkXFJI2LT36+W/t6RSf2Iok3WMl6s814rwBOK3a4g6f/Ce+oMFxwIXbE6Ta62XMmJx295XpdX1YWpqZxx47k9de+2b0w9G6+lnHSSeHw8f//r4NXa324Z0yuZAJOZlcPHgwI43JOJtb7xtpspg+N4PUqenREaVgguV+/f5QNNllrg2TX5DC53V1/G/lXh57bD20NMUMuVovtBobPfzwh++wYUMVDzzQcbVIrM/eKyWjQXssi8VAqMZP41v1mGIuQDZsqOKNN/bwYsuJ8uc/X8Ctt87j5ZcvArSkU2d9nSIjX8YSM7f+YjUffXSYu/70MbV+L4TBe7D1wPPZZ2VHrJxqa8+eBkampTHbkAEq6JL10QuqoaYkRqSmRt9Ld62XL+7dydb/20uhy8h4JRX3ygaad3deceWv9GJ3+NjbFJ90MbT0lPA7AnHzif/wh09Zt66S6657Pfo7k0nf46v2HQ01pOJuSTClzkiP9nxx72xNkm7aVI3PF6SkJJ2pUwuZNEnLwHeWzDxSI/HIST9lXwBvU4ADNTZed1bxSn0FKw9opfDTs7MJ2gPRUty2klqSTsbU9s+h0yl4W84dW96r4KWfr6Nxr4NAOMz/ysv5v5072Vtnw+3w8+GT7acKOp3+aBNxxagknDJlzDKSkaEFVG6nn30NNp47cIiXy8qi5d6BWj/1r9VEG4bHCkaaiKckTqZERjpKBqYl/HtPi6yakhEyYNLrCIbD1Lq8BG1BDjx2mAeueZ/77viEv/9tQzSJfixJJ4BzzhkNaEmdyCjQtGmFKIqCyaSPm+9+pOcoKUkjLy+ZQCDE5s1aIltV1bipJLsSrIDU2fS6yPSuyIUrOgiGwlRU2mm0BPnPf7by2GPr40b+Euko6QSt55a6OlfrksIOPwd2NnDgYBO7dzeg1gd54olN7XqGHamfE7RvDG/IMFDf4ObA+9XaQIVemxoIR7c/x4zRSvo3b9YuFrWVxLTz5qcrDzEkNZXMTAvesSZK3W4OH26Ou3+iYHPZsmHRf6ekmMgZlEogHMZp89HwvzpQwToyObrdou8zRFaXq2kfQ/nKvISCYSrcbpIy2n+Ws7KsDBqUAcBNN83igQdWRP9mMulZtepy7r77ZAqGa8fKUExflEjl4/A8rcrTkN66tPf48XmceeZIwsCzhw6xtbmZcrcb07hkCq8aQPG3Sig4u4C8Aalsb26mwu3GoCjMyMmJq5qsL3eSZ7FgMOpYevFIvvvd+CazADNmtJ/yEHvRl5ubzN/+diZ5o9PxhkJ47H4CdX78/hB//OOnfP72YTyeAFXulimALdULZrOBrCwrnpDW/sFl82HS6Ribk4nJpOetyko+r69ne3MzX9TXk5pmZkBSEqVb2h8La2tcnFZcjNmsxzzAEldBoigKuQtzGHh6AbGRS6TPYWRflJSkU+py4fAECLtD0cbhAL4yD35/kDKXi+RkEzNnFnPVVZOZMqWQoqJUnE4/B2rs6BSFQYYkCKoYc03kjdT2616HA8Zp33m9PdzhQiGOTXYcDh+bGhtp8vux233R6vJqj4dwWOXwtkYmZWZSuauZRpuXP2zcxtPlBxlyUj4Ws4FUo5H3X9nPD3/4Dhde+Hzc44d9YbavLOfQ4WYOmttXQx2st7NnTz2uag8Wi4FZLcmh8qCXwmsGMOGm4RQNSsWo03FwY/uBkEjSKc9lJNgYQDEppLQsTGFINZA6MoXp0wuZPXsAQ0Zm8o3vTWq36hZA8ljtM5KrGgk6Wr8TwaYAoWCYep+PlATTibqqqCiVcKqWqNi7to4DB7RB5/37m8gwmbBYDJgyEseAiSxZoiWd1n1Szu6/HiRoC/JFeS0Nbi/JRgMheyi6glvkc6VP0nWa1MrO1howh8NqNHnY1aRTZCW8iKmF2eh1CuGW2N2k05F7bj6KTsE6NAldcut5szA1ietmjOHcsYP59rTRfH/2uOh2ZiVZmFacQzio4qv0EbIFqXfHJ2gPt1Q5DUhLimuKnXN2freWundusWPc4CFQ6+cfj23k8Zs/Y8/fDhH2hKLxTazYavizzx4VTaZA60prsTF5Z7FNRGSKXezjnHrqCMxmA4MHZwBakURHIjOMEn3GoTXxrqoqFTXa9VuuycygQRkUTs3CeHI679fU8GldHfsb7JRvbIir4o/EbxkZlg5bUNx77zJuuWUON9zQemy///7lzJ49gEcfPYOZM4sZMSIbjyfASy+1TyRD4hUDAZYubU06LVkymFmziqNVuLEUvcLY07Tp1A077JSWNgParImmXVoPvVqDP5pojSVJpz5OVVWSAzrsX9qwfdFMVpp2kGpq6rjc9j//2kLd+w2oqsoXDfUMuqQYa5EFq8nAkoICal6uJuwL4y3zEKgPgA4sLVVKxiztyxTpWREr8iFJsRhR3GFSU00Ec7QvxmOPrWfDDi3Yj0zN06a+vRutjtq9u56VK/cmLOON9dlKrZpFTdWz8Kfj0Jn1+Kt9uNbZo6vm3XTTm/zqjg8YqFi4cOhgJjtTaHizjpSDIYrSk/H7Qxw82PH8XG+ZF58/yPqyuriDzGvrtOeOVNhUVzu56aY3ue661yktbaZpvwNvWftVkdqqqXExIzsbi9mAdXgS+RcVknVKDimT0zAY9MzPy8PW7CMcCrPq3m0c3NJATY2LRr8fWyCACR37XyzvsF+IGlLxVvnYtKmaXz7wcbR/FGjVMLoUPS6nn+yYqZXJBgNDU1JI8SpEThV+f6hLUzVB+yweTTPsIz5uSMX+RXN05aqUianRERR/Xevy5JHqkAkT8qLVB9BaVZZIJIHQUU+nKVMKmJCRQbguyJbtNfxq5Toe+9dGHvvbetbW11PucZOdaWVhfj7r1rV/nmAwRJqhZTQ2M3FQM2aeNjruOOgiWO0nEA7jGGuEIhO+cDg6Whs47MXpjL8Qcjj8WAwGDPqOm2AasozkLsjGnGHksMvFT15cwyGXi/0OB6ln5ZBzVh7GHBNqQMWxoX2lULTSqYOk02mnjeClly7iyisnJ/x7T4pdNUWnKBSltZT/t/QU+N/uUv7++lYef2QDD9z+CZed9wIbN1Ydc9Jp9uwB7RoezpnT2uQ3dordkZ5DURRmzmz9bNrtPh55ZF1cX7DSUlu7atXOptdFKiwin/XUqWlsrKjnjlXrOfvsZ/nTn9bw2GPr+d3vPu502yKJlUSB2ahRWqXQ7t0NKAYFVYEdO+soLbXxyW4t6Z5jNvPBqoPRCkKDQYcaVKOLFpjyEwdj0D7pVOv0sGNHHds/r6au3oUjU2XvwUZ2766Pnmu6unodEG0ivG5dZfT4bMwxoqoqlj1+skwmCgpSGDA5voQ8Emy2Lfc2mw3tRmCLB6RS6fFERyMN2UbSZ2d0eRtF70sZpH32DXaVsDc+WRBpyHzA6Uw4vQHg3ntP4be/PYnLL58YN70hNdVMZqaVU04ZRuEI7YLJGJPHjMRBw5NakjQx1Ts6ncIddyzmttvm4w2FeLuykmcPHSJ/fk60f9sVV0zi/vuXA7Cmrg6jUc/EzEwO7Gqt6na1DKaFU3Vc/u3JCUfkv/GNMdx++6K4c2Lb8+OUKYWcdNIQDrtcuFwBfBXe6AVRYcvUkOqWqprY6XoFBSlapZfLj9sTZFRaGmlJJsZMziN9cEr0OLbk1KEEW1b8C+6Jj2XDYZUkt/Y8lhQj6QsSN7j9znem89hjZ0Z/jl2oArSL1jBw0Kld/Ln3aO9/yBPCX6sl0fY7HNx661wefvh0Zs4sRqdTOPNMrf+Xze8nLz8Zo0GHMdtI1vIcRsQsC7/8nJFUuN14vUHqNza32z41pOKv0RJNGxtb99Gzz24D0HoQtfQEO6WwEJ2i8PaecryhEKecNYK8RTk0Jmmfz4Of1kbfm9j4uWaXjdLDNrbuq+OdDaXttqHe56Ouzk2O2cz3rprKgmHa+z/u7BIURUFRFJIGat8HtaZ9rNnc7CXPYiG1Qju/pk1PR2dpPT8lj0/BbDJgMuuZdOVQzj1/TLvHAMgZlEqpy0UgEMYds5qgr85HKKxqSacOLuS7ati0XALhMOX7m/nFDe/i94c4cKCJdKORpCQjhm5MBSsqSmXUyGx8jQHWlNfS7PWxubqRSrubrKTW723tS9XY1mjXGbEtLhLR63XRSpjIdymyhHxXpExMo/DqYgzpBqxGA+PyWr4XeoW0wUmkTNQSoopOIe/89hWOHcnItGjJ8ZY42xcM4QoE2VhZz6/e38DGKi0+LUlvM7Wug3gxkchAYpZO28eeQJBH1+5kw4FaAvUBkn3tk1c//OEcTj11OCtXXsovf7ko7vMRGQQ8eLB1dcauJJ2mTSvi5JOHcP75Y/nii2t47rnzo/FWZMpeZytSHqnSKXYb/SHtuxupvEqZlMqMmcXcdNEURispBGr9lH5cR8VDpdEq/kgvu7axaKyBA9O55JIJcRX3I0Zk8+CDpzF0qNYXKtIj8Nlnt7VbMCMYDEd/17bSaeDAdL7//Zlcf/107rlnGQ89dHrCeBRg9umDSEk3k6TX88Wb2rHHvdeF0+Gn0uOhaGRGwvtF9s+RFmjqDV/7pFPYG6LuxWrqX63FucmOa4uDs/OKMel0nU4psm20Y9XrafD5aMpWSSq0knVqLjtDTgLhMN56H9VPVtD4lnYRnzQqGX3LicTY0oA10VScyJd6VH4miqqNdPzirkXRv+8+rJ1Ywy2jPv/5zzbWr9emvk2erB0E77z9ff5072cdbntzs5eq3dprm7l0IFlDU8lcrJX3ubY7mZCdiQ4YlJzMVcOGsbyoiMlF2YQaA/jKvXh2u/jO2JEMSk5m587Ey/GGnEFq99v54osKfvPoGgAuvXQCAJ/srSIUVrVkR1iNVtFY9HqevfkLPvj9dureqKXhjTrCCVY8Ay0501jrosBqxWQ2kDq9tcl3ysRU9Cadlgyq8vPxX3biqfYSCId5Yv9+Ht+3D93iNEpdLmoqndjWNCd8jqAtgL3Jiz8cptHv57XXdsf93ZRtwun0MyglhcULBnFKYSHfHTmS8wYO5MLBg7lo8OBoj4iKDlYuiXs+Z5DaZ6uo+kc5lX8vo+bZSuzrbD3SNN7+ZXO0p1HKuBQUnYI+3aBN8Qmp0ameu3bVY9XrWZCVS+PqBmZlZ1NktbJhXWWHy6q2NhdsKV/dYKPmuSrq/1dL3Ss1TB6Wy9iMDDyeAG/tKydggosuipmmafCQnqk1LS1b234ExOcMYmypJrNkJg6aTj53eHSVEYNBR8biLK798UzuumsJN900i8deOQ+j1UCyTs8nrx+Mu6/T6ddWrjMoHSadFEUhZWIaKWfm8PzhwwRiEqImix5Tvpn0eRmAFngH21Q7RaqfOppepygKAwemH/PqdV3RdtWUSDn34WbtwmFTtRYATS3KIddqoWqvjW9f9go33vgmcPRJJ51O4Z57TuGWW+bw5JPnctNNs1ixYnj0791JOgHR6XpPPLGJpUufjC7g8N3vTmfQoAxUVWXjxvjqyc6m10Ueb+fOOpxOP6EkHb9+cz213vgLtjVryjtd0TFyDE80AhW7ip+iKNiavHg8Qa3x8rQMikdlYDTqKcTM2g+0KkCjUY+/zgchbcnrzno8pKdrgVok6fTe2taLpK076rjuD6u49NKXuPTSl6JTXrraSBy0ahGz2UBjo4cDB7QLAXOhheoaF35/CJNRT8HYdKbPLmZkzMVjJEHYtjI2Jyep3ch1cXEa/ysvZ5/OjXVkMtmn5nb4vRR9U+GIdOq8XtyuAO6YXj9rPimlbqeNYEjloMPR4UXwkCGZLF8+PHrRHhGbpEoq0S4mc0LG6EVRXZ2bVIOBPEW7XdKI9t/BSBUVaAmctknPyJSLQy4XxmwjBkVBXxNsXYK8WjtXetM6Plbr9TrOOmtU3HMlqtAYPjyLw04nLpcfb7k3WmUZ6UdS5dGqZ8aNa20aPGyYdjF4uFIb7V4ysBCTUU/h5EyeeupcHn74dH7/+6Xceus8LC3VL6kuhWBMH5r6ejdDU1JRFIX00akYUjo+pkSWQYf2x7RIpcRn5VrCxrPXrfWj2uoAFardHhzBYLseVxddNJ6TThrCsm+OZNT4XEzFZrJPz0Nv1ccdNyZOzKfcoF2E1q1vv4BOoDGAzxWg3uahKRCIrjwVeR8tFgPVntas5NamJp7bsA+z2cAVV0wCIJirHf/GZmREL4hik+PlW7WYu8ztjluoIqKu5fwwOCWFRZl5jBqVw/RTBzL9pNZkafY4LVmR7zcSaolpQ6Ewa9aUUVXlYGRaGkajDvMgC0lj4y+GjVkmslbkkHNGHpaSjhMomZkWdtq1z0TzDu38pIZVHC0JqFqPp13VRXfNmjMg2hh/mDGJPXsaOHCgiUyTieRkY7f7Dy2eUgIhlf9uPcC7+ytQVZWQqmKJac4dsoUI1GsrWaZOOXKfyshnALQERWSgp6tSJqYx+PbhFN8wkJMvGoExz4S5yExSTvxxInVyOhlLutZ/U5fgu9/o9vHrDzayuaoh2jeqbT+ntk3EOxI7kJibFL+da8u1mFq319du1cF58wby61+flHCaWSQedTh80YG0riSdDAYdf/jDKfz0p/O11aBjYtoJE7RKsmef3c6bb+5NeP/O+i0BnH76iGjy29cS81uTjJgKzBizTbi2OphTmcKiYu16+MODVWyvbSJoC1L1zwoOt1xjRJKTR+uUU4aSl5dMfb273aJakYF4SDwV8corJ3PNNVOP+Bw6gw5DiRbTWff5CXlDuHY4cTj9bG5qSthMHlqn6+3cWY/bHeD229/nww8PHbEY5UT42kdyOosedAoYFMzFZjAo5FmtTM7K6rAvTzgcJjugHVw/b6jn+u9pJXg6o47atCAvlJbiCbVeoFsGWUmfEzN1JKtl5bPmAGow/kMQ+VIPy9a+VMZcMyNHZvPb354EwI6WktaQS2v0/cILWs+MH/xgNrfePJfTBw3g5rFjydsaonlP4guj7dtryTWbSUoykj9COxlaBlpJmaw957emjOSnUyZw2chhZJnNeEIhPCUGspblkLEoC1ORmYw0M2cMGMC2ddUJnyMSQFV5PHhb3osrr5xMVpaVRq8PlzcAIZWgLciXX1aQYTRy6ZAhDExOxucL8vkXFWx+v4K61e0bXYNWkpxrMKMA1iwThpgG0zqzDtNw7eScXapSs7GZsKriGGqgcGQGP/vZAs79xhhW11Rjt/to2uNoNxoLWk+qZpsvetH59tv746ZcmgdZsDv8jE1P5/SsIi6eN5LUVDPFozIwWwyMzEnn/EGDMOp0HS67HBH2hWl6r4GQM0RYVdm1q559WxtwbrTTuCrxe9BVIVcIV8sUuvSFmSS3lG4rihKtmvDXtATShzxcNWwYA4JmvAfcZNTAVaOGc1ZOMR/HLIMaK1KRUeIwUfm3Mhzr7YTsQfxVPgJ1fgJfOhmdlwFojVPvumsJP/7xPJ544hzGjcvj4usnkdSyTXkN+naVXt567T13BYOYkxIHNbl5yVinpuJOg4U/HceZ14zHaNSmbF1xxSSS00yYWg7ejTviE4D19W4sej0moz66cl1HFi0aFLe8O7QmSEx5Zq35p6otFBChhtXo+2vMPragrye0DWQio3kfH6rBGwyyp15LSF8zbRQ/WzSZYdlpBJqCXV5ZrjNjx+ZyySUTGDs2lyuumBStqgTigsOuVN8sWDAoOooZOZlefPF4rr56SjSB1HZaaGT0KdHIUn5+ijZyH1Z5+OEvmT//8ejfJk7M5957lzF9ehGqqna4oqOqqp0GZqNGtSadAPbVNgNgLTLz7dtmMvm0geTnJbOsqIglShanFBZi0OvwVUam1pk6nV4QqXSqr3fjcvl57b19hFUVg0HHZ64GkrPM5OUlxyXdurM/TSY9U6ZowdyXX1aya1c91/3yLX67aj0bGhsxTUgma0kOOp3Cgw+exsyZxVx//fQOpzi0XeEPtCk8nlCItU0NZC7K6rBxrOi7Jk7MZ5/bqTX//kJrHFtV5eCh2z9j04Zq6l1e6ny+hKsHJXLNNVPR6RRuv711AC59mLbipymsRAdNGuvdnDFgACaTAVOhGUN6++PtiBFZWCwGLBYDf/zjKe2+T7HfjZRRKeh0CkMtyZSV2VCDKka7dqxR8o98LE9J6fw2I0dmU+7z4vUGObixntoDdnLMZqx6PUFVJaMkiddeuzgu2RO50Kiq147HxZnJWk+q0doFq8GgY+nSoVitRvKHp3HI6cTrDWq90dBaGWzaWMWwlBTMJj3WwZ1XgphMen75y4VccsmEaKVjREmJFj9urWyEVL3Wl+7pSpybtefaXKclptseC9PSzPzxj6dw5XVTKbisiJzT8qKJ5by8ZB5++HQef/xsTCY9SUOScAWDuBp8eA/FT8/1V/tobPJS6fEwYUIe5547Ovo3o1HPn/+8HH+WnoED06nQ+3izshIVrRItcu6wDrTiDgax6vXRXl2xC1Q4DmuxU5m7/VSVsWNzqfdpx+bkZBNKYwi9UWHg0vgqmAHTsnGHQ5gVHZVfaomr11/fw/e/rw3kDElJwWDQYx3SPgkPYCmxYsrv/Lui1+uo1/sJqyr2Cjefv3oA51YH/sYA3lCIg3533Pn2aMycWUyZqsXDo9LT2bSmgnffPUC6yaRVOiVY6KUzpw4upiA1iSaPj2c2a1Mii1Lbfx7VgErSqJT4FWU7EDtVaeHCQd0aVIlQdApJw5M5/dvjop/LRI3mc8/Kp+DK4g6bpxsyDGStyCHsDnPG6IGkW0ykW7SYu9rZ/vN0tE3EYwcSc5ITn2tTFQMH7+y4Z2dbJpM+2sMtMsDUlaRTZyJtJDyeAL/85ftsXlWGY4MtbvpbZFZIR+eGYcOyeO21i7XvtNuNLRAgaVgSmSdnxyXfMq2tSavffLCRYEuCav972t8j0/SOltGojw6et006RSruzWbDMcXLoLVCcQQCqI4Qex46wKbPKzlYaWOXzZawnxNoq+RFGrr/+c9rWLlyL7/85fudrhB+onTvCPEVlbk4G32yHp1Zh3uvi7oqJ9Oysvi8TT+KiKo9NpLQEwb+9up5WGJGD/LzU1jjLmdTtoepV2jzY3VmbR70m2/uZffuBhYuGEhRkp6wO4S/3h/XGDbypR7QsmymqWUFi8gI+dY9tahzVPyuED/8wduUl9tJSjKybMFgXO83c92K8axfX4XiDrD3pXKm/3h0ux41u3bVk2uxkJJiirsITp2WTrApyGC06RCKRcfrXxzguc0HeeL350ZHWaxDk0grtWMts8M+F2qCpd7rdtiw2XzR5WXPPHMkWVlWRo/O4bPPymgM+EjDRKDRz7Z1NVw8ZAjJBgOOQIDnDx/GotfzzcGDUd6tIHNaBqbc+Kx3TY2TkuRkTCY91gHtT1KTLxzMunfLyAoa8YRCVBeF+emv5vO9mO0cP6uA+nIf1dVOisq9JA2Pz3wH6v00N3uoaRkpczr9/OAHbzFhQj4FBSkMLEilrs5FpslEgdVCZn4Soy4fhLnYQqApQMP/aknZXEuNxxNdkTCRkCdE/as1hBwhFJPCnnQfv3p8IwOTk/ntwNlQ5iXsCqFPMbBxYxW1NU5OnjeYfbsa2VvexOlnj+q0Qsa1y0nAG+Rgs5MJOdkkx7wHpjwzvsNe/NU+6gJB5idpF/6phVZSRqUSbA6Qe1ibSvnpawc56eT2TfA8niD5FgtZdh207ApDphFjrgnPHhfBxgB5uclsaXLxjcvHR+d8jx+fx7/+dY723tp8rH/5EFb01G1tJm9Sa5LW29IXpNbn6zRoOv+WKR3+DSBjVCquPS6UuvikS22tiyS9HpPZgM7S+QnCaNRz773LcDr9nHHGM2RlWeMuUsyFZgK1fvzVvmhD8ECdH9UXRjHrMOYmHr05kdoGMvMHFfDPDXsoszm577NthMIquckW8lO0/gj3LJ/FewcqefTAXnRm3TGfRDsSSchA1xIhaWlm7r77ZL7//TcpKUnn8cfPipYyz5xZzAsv7Gg3LbS10qmDcubZAygttfHf/7YuMnDzzbO59FKtlNrl8rNuXSUffXSY666b1u7+Doc/WhGYKDCLHMf37m2ksdHDUxv2kmu08P2fzG+ppksl9TMrVNghDJPSMjA2mKIXjJZBnV8gDhmilX7v29fIokVPAPBxZgP33Xsq58dctLz00s7oNMHu7s8ZM4r4/PNyVq3az1NPbYkmI4fMyOW0myZEj0VZWVYefvh0AJ58cnPCx0r0HkVGMTs7Zoq+zWw2YBmeRLBBpfGAA9d2J7vrGxifqR3XtzVpFzEdjWa3dd1107j88olxUxWycpM47HQyLDWV5m0O8habyXDoKU5KwpSkJ31e4ilj6ekWnnnmGyQlGTu8ePrBD2azcWMVc84byvsbHRSFVdZ+UEbeAhN+jzZlq3DgkUfKzzlnNOvXV8VV78RKSzPz7Runsu/ZMnQHFcx+C2PTtWqOMpeLgaMz2k0PiqxWFIm5UlPNJI9LifZWi1VcnMrahgYGp6Tg2OlkvaORW3++mgKLhcuGDsVk1WMuOnLPm7PPHp3w95Hpjk1NHuwDdWTsVwl7w+iS9JjHJfPRo9qgZGcXqYl61kQqIwHGjMvli037GeRMw7XdETfFyl/jo67ORaXbzYIzh8QlHJKTjcycWczMmcWEfWFW/7ERtmoX01deOSl6uwElabzQvI9ZOTlMzcpir8NBdbWTiRPzCfvChFpWgyt3tZ+qMn/+QHbsqCOoqlrVng5yzynAmBWfbDSY9JTrfYxUk2he00ThuAzeeEMbuLDq9eRbLRgMSpf2RWdSsyzstNnQbVNgG5hGalPqPq2rw9ADyfukJCOPPHcWH/9xB00HnNSsamBBag55FgtJSUb0CRZ66YgaVvFtdvKdGaP51Xsbor+fU5Lf7raKUcE6tGvT5GI/O/PmtV95rDtip2B11OM3dXIaKRNTtcRPc4CQK4Q+2RBtAu7cpCV5vjV1FFdNGclDX+zg/QOVvLzjULvHGhiTdOpOE/HYgcS8DpJOaWYTYZfWJ6vwaqJTBTszdGgmpaU2Dh5sYubMYurqji3pNHhwBsnJJhz1HgJNQTb8dR9Jg7QErSHdQO55+dH3+Ujnhp//fAHXX/8GzZONZJ2sxVXufa5o8i3T2hrv+IIhap0eitKSqWvQVps+1kon0AY+//KXtWzZUkMwGI42Z3/66S1A+35OR2PEuBzuLv+IS4xDor00v2xoIKSq0R6bbSmKwoIFA/nvf7dHVyO/4IKxHU5ZPJG+9pVOoDUJjmSzrUOTsGaZSTYYSG1MfCFfvl4bqXCYQ3EJJ2gtza6pdaIz62h0eNmypYa//W0Dv/zl+zz99Bau/+4b1AW1rLm/TaPNSNIp36QdOCJJp5KSdJKSjDi9AWqbPGzdWsP2liqjFcuH411jJ2QLok8xEJhk1aaEVbrajQwB7N/VqC2lm2KK9pcC7eSfeUo2WctySF+QScHFRVxx7xyef/UiSkpay1oVg8KgUwvR6RQG6ZMo3dsc9/hqSKVqaxOqqpIyJIk33riEn/1sAdB60VXW0jhv7crDzEvOJs1kZM4pgzj59onYQkEqPR72OhzU1roo/bz9lKuaGhclydqIvbmw/RfJZDUQnpbEm5WVrPbXc9Od89olxs4+ezQHHA5qalxxUwAivLU+HHY/NV4vd999Mkajns2ba3j66S3ce+9n3PSjtylzuSgqTCVnRBq55+ZHe0gYM41kLs3GYjEwMTOT2n0djy64tjrwNPqxBfykL83m1ff34goG2Wmz4VC1A6izysNzz23jL7d+wuF/lbP6F1vY8tA+HC/V8ebvNnc4DRHAU+Zh65Zanli9g/vu+5zSUhtbttSwa1c9piLtvfMe8rDnRW31lUN4KL6omLTp6WQtzWHAbG2fhUt9CVd09HgCzMvLQ6/TVqTLPj2X3G/kk7koi/T5WuA/YEAqyy8ZzfXfnZ5wG1PSzZTptO9E9WcNcZVd3lotO98UOrYs/ZDpOYRVFb1XxdvY+ljV1U5yLBbMZn20QfyRpKSYeP31i3nmmW/EJfwiTZ59Va3vk7e8ZQXEYku3mkIeL9ahSXErgaWYjMwdqAV6X7aUYk8qyI77vswbmB/tRxA7CtyTkpKM0ekaXU2ETJtWxMqVl/Lvf58Xd0E6bZrWV+PAgaa4FSwjPZ06aiB5xhkj435++OHTueSSCdGfZ83SSvd3725I+F2I9JRJSzMnrKYqLk4lLc1MIBBi2bKnOGhz0pylMrqlekHRKxRMyuDlzQd5bcshwn6VzEYF1zYn4UD4iEFoUVEq3435jhkMOm64Yy6WNqPky5e3Nu/u6oV/RKTP2+bNNdTUOMnL05oi33vvsg6T3x2tbJkoeC1uWZmpstLRJxZgEEdn5oIBfFBdTUOjB/vaZuo3NDG4Zfn4bc3NpKWZu1zppNMp7XpjWCwGdnu0xKRjqx1fpZfCsHYby8SU6AqziQwcmN7phdNll03kT39ajjXTROpgbZstn3toXF2PyxVgv9PJ8ARLX7e1YsVwHnrotGjyNZELLxzHHp2bUFjFW+5lZksj6sMuV3SVu1iRqROVLZU3+cPTSJuRkfCx09LM1Kt+ar1evK4AW17XzvFTs7Vt96QrXaoe6Uyk2unDreXkXVhI1vIcduR7OeWa5wAtydPdY0ysMWNy2NLURG2di22fVOE+rL3uQFOAqk1NNDd7Kfd4WLZsGGazgQsu0FZuvfnm2dHH0Jl1LFo0GND6dsVWjs2aNQBXttYwuiQ5mVFpaVRWOnC7AzRvtuF2+an3+TBltH8NS5Zoj/l+dTWGQhN5Fxa2SzhFeAp0VLjdeBwBmj9tIj9PSzBMycoCVZtGp++gYqarhgzJ4O3KSra0JHXLyux4i/RsbGw85n5OEUlJJlLnZRBUVfItFsakp5OVZSVvRhbGbjQS9xxwE3aFmVSQHa3wKUlPievnBIAeLEOSElYtJt4+Iz/72QIuuGAsJycYJO2uyPm/sDC1w9tEKqPSpmeQuSibtOnpJA1P1tpYxAzy6RSFBS1Jlt318e1bzAY9ecmtibVI0/KuiH0Oi8HAXSdP466Tp3HG6NYkbKTCCqDu5Zou9Y6N9HX64osKwmE1Ou30aJNOOp3CbVfO1Poch1TqXK2xWWT6W+XOZqDjnk4R06YV8b//XczNN8+J/i42+TYgLZnpxa1JmUqHmzqXh601jRBSO+3p1FWDB2eQnm7B6w2ya1c9+/c38tFHh6ODlm2nFR+N3Nwk3MYwb1ZUUO/z8V51NesaGkhLM3faJD92RobZbIgOnPY2qXRqQ9Er5M3NQllTyZTkDBqrXGQVxn9wmg9qFxb6BA1dIyV727fX8dFHh/nJT95t1wsnHFZ58rXtfO+k8Vhq4i+k6+vdpBmNJBsNoANjtvYcOp3CyJHZbNpUzZr15WSZzWRazZx1yVjOnzQU/y4PilEh54w8pjUkcd9r+5ln0GPbZMMy1Bp3Adl00AlJFpJzze16ZSiKEjeabjEYEjaITh2URCBZQe9Q2L+6mkEjW0cV/TU+HI0+PKEQE+cXxX25I0mnDfvqmJCRSe22JgYkJVEyJIPiMwswZBi5//7luFwB1r56EGxQu6WZYWcUxb2G2ionBRYLJpMeU4KkE8C3rptKeraFZcuGtQtYQRsF+YfhSwKBEBUbG8lanI2uZVqPGlZpLnURVlXcRpWlS4dSVJTK6tUH2bWrPjpt5/2mWq65Yg4Zo1PbVZSZCy0kDUuCUhvmQ4GEFWFhf5jST+rYsaWWFw+Xsv/x+NH9GpeHJLOOv/z8I5ptXpYVahfTDY1uAuEwZr0exx4n6549wMzLh9OWGlQ5tKkBp8tPucvFtrea40pBFy4YxE/mTaRmn52yMjv7HA5mfXdEXCBaPDuHpDfKGK6msnFtJYuWDol7Dp8nyODkDHR6hcyTsuOC/eQx2r537XCSO7vz+e/hAUZC5Sqeai/+mtYKQFelljgNpRxbjrx4cDq1QR8FioXStfWMXKFNFaitdTHWnI3ZbOj0QqWtRBdMpnwzKNrJL+gMok/SRxvmWwYc2yhmT1F0ChmLsqL95gCunDKC/GQr/lAIk17PshED4u5jNuih5fN9PBMBo0fnUFpq61ZJfKITb3q6hZKSdMrKbOze3RAd/YxUOnXUuDG2XHnkyOy4UVPQgq2hQzM5cKCJdesqOemk+O9CpDqnbcPdCEVRuP766fzxj59Gf3fOOaOjxwXnFjv2F+sJBcPsqLeh1ylcOWUEalDFs9eNa5vjiCOUV101mfz8ZPbvb2LJksFxPVkikpNNPP742dTXu7sdfI0enYPVaoxOq/3xj+cyZUrny9x3tLJlouC1oEBbYtzrDdLU5O1WI1jRdyxYMIjf//5TBlXU43T4o6tA7bHbsQUCXHHxpGPuYWczh9lhszHZX0Dt67Vk602oQN6kjGN/AS3GXzSIsq2NuFx+Ghs9ePxBttua41bb7IiiKNFEdWe3GTergBffOMSC/HzyLdrxrNTlYkGCXismkx6TSc+HNTUYisxcdPGAhCuuRh67qCiVtbX1nOQdyCC/hSX5+YxOa2mIPPTYR76XLh0aHVgdMyaXhQsHcdcVH0X/nqhvW3eMHp2DOxRiY2MjOkXhwGuVjL58EM0fNFB62MZ+h4P5Zw6JJqtvvnkOZ545qt3Uk4ULB/Huu1dE+95FGAw6HvzHGbz71x3o9/s4KVjAvl0NXHDuc5yfU4JVr2dtfT0XXT6OBx9cC8Cddy4mO9vKiBHZ3HffcjZurGbuDaM7rcQeOTqbpz/axNjiLAZU+Mj26hmXkcHcXO3COGVix0mNrhoxIpu3397PO1VVfFRbS5Jej2OL1lQ9UQx8tEZPy+euOz9kSlYWF54/lrHLBiQc/O1MbILg54um8OzW/Zw+qv0qXqlT0sg6JfE0oo6cd17iZutH4wc/mE1xcWq7qaVdFVnpLuzSBoYn5GeSbjFh88Zf+5WkJ0d7P+mSdCSP7/rnwTo0CUO6IVrlMz5fi7UNOh3/26X1i0oxtV7HBZuDeA64283uaOvUU4fzz39u4qOPDvPqq7sIh7VrmOzsozsnq2GVUaVGvjFuCC9uP8jeBht7G2yMyNYGG52+AJ+sPoySb4z2f+pM29ilbYLvZ4smc88nW1hTWsN/tuyn3O4iEApjTDH1SKWTTqcweXI+H354mMceW89nn5VF/6YoSrQtzrFQFIVRo7L58stKdtpaE5VH6s80Y0YRv/rVYr74ooL58wf2mThKKp0SSJ+Qhl2nNS+u+DS+UbaqqgTrtWA7d0T74H/27AEkJ5vYs6eBW255m0AgRG5uMiUl6Vx77VQ++eRbjBiRze7aZnbtqsdX44u7iKuvd1NotWIy6TFmmeIu/i+5ZII2fcKqJy3NzK8un8Mlo4cS3qVdlKfPy8SQamDQoHQOKx78oTCNB534SluzyXa7D5NLe77sYUd/klMUBf0o7UMc2KeVK0Y497qw2b0ccDiY0eaibebMYnJykthV2cSWLTWEwyqmXBNTrh8erTKZM6eEpUuHUjIth6Cq4qr3RZcLj3BXeNApCopV1+E88qQkI5dfPqnDiyq9Xses5YNo8vupqXTi2dda7eSv8eO0+fGFQhQM0xpujhuXx003zYpWbQFMnFlI5ri0DoO+4adpybJcTJTvaL/SX82XjezeVke9x8t+R/vpJPvr7ezcVc8kSzqL8vPJy01GN9LCS84qNud7aWh5ew+srqF0T2O7+/trfTQ2uHEFgzQHWpvbFRWlYjDo+Ojjw/zu32vZ1dIQPm1eBqcsi09eGXOMmLKN6BWFw2vaV52lBQ3oFAWdVY8ho/2+SB6TQt43CtpNkWxr6JhsdthsOJ1+7J83E/KEtFW7WqqSzMc4NU1RFLyZ2n5q3mJDDauoqkpdrSta6dTRKGVX6cy6aO8F50Y73oMeQrYgikWHZUjfOOgDZJ2Sgy6p9fCfYTHzzYnDuGLKSL45cRhZ1jaBeYaBSdM7Tyz0hAsuGMukSfntkjlHY/RobTQ/0j8pGAxHV/NI1DgTtM/Iww+fzqRJ+fz610sS3iYSfH76afuVjCK92zpKOoH2Gq+7bholJenMnFnM6aePAOKbgc4coCWKNlU1sKa0ddXMroxQ6nQKp58+kptumtVp4DZx4tG9zzqdEjdqvmDBoE5urelOpZPJpI9WeFx44fOsWPE0K1Y8zdtv72t3W9F35eUlM3VqASsrKjjUMs3eHw7zXrVWoX3++WOP+Tmys62sqqzkgMsR/T5W+DykZPdcgj+zJJnqwjDbm5t5cPMu/rJrF5Z8S4eJ66Mxb14Jh1wu/n3gAJ/V1bG2vp5ar7fDkfI//WkZ808ezI2/nddh7BFRVJTKLrudHXXN+LxBpmVno1MUDjqdFIzKOOZtv/ji8dGL/Fdf3YWqqnHNczta1barkpNN3HzzbD6pq8MRCNBc6ab2+Wo81T5qm1y8V10dXaQGtOPH2LG5CRNdGRmWhL83mfScesN4MgYkk2wwkLU/zOmZRVj1emyBAHPOGxqtagLt2DlnjjZ1a8GCQdx006wj9ktatmwYtkCAd/dV4PMHGeVL4tQi7VyyuamJpBHHfhE8YkTrwJ43FKLR3zrd+0j9xbojK8vKDT+dzYyrhzPlymHdTjhBfIIgJ9nCjbPHMSSz/XkzbVZGr/b10+kULrpoPMOGda1peFuKTiFteutMEb1OxwXjh2Ix6rEY9dHPY2w/p7A7jOdA15e7V3QKuee1P9ePzElnSGYq6RYTxWnxn6+uNCkfMiQz+rn/7W+16fiZmZaj7g0W6T2V2zIF8POyWn7y9lp21zcD8MHBKvz+EEMK0qMr3XVHJPkWqyhViyUONjkIhMKg1xYMiiSpj1VktdDYhBPAbbfNj67ae6y+8Y2x5OUlU1ycFl3589Zb53V6H0XR4sC77lrCsmXDOr3tiSRJpwQURcHWUjnduMkW1+w75AjhcwYIqypDJrUvr87LS+ZXv1ocHamfOrWQV1/9Ji+/fBHf+c50LBYD99xzCs1qkPomD7Y6T1xSqKHBQ1Ek6ZQXf5F90klDeP75C7j4molMnlRAWkCP96CWcEoenxI9aSmKwsTphWxoaKC52Yvti+boa9i1q56ipCSsVgOpg47tJDdmYQH1Ph/OZj/2dVoGNuwPU7uxiVBIpSzsbTcamJJi4ve/X0qTGmBTUxN7dW6W3TkJc4ImidNnFbGjuRmbzYtjS3xCJlSnJVDCmcd2Mjrr7FFsamykqclL3Zetq6N4Sz04nX72O52MHBU/yjJgQBonnTQEk0nPt77VeR+hlHwrtpYleUvfqYlLMKohlf3vVhMIhqmwBPjHP7SeNMOGZfGb32gZ8nfWHMJu13oZzZxZzIwrhnHhL6bzwssX8uc/L+faX83Gn6JAWOXfd6+PTh+KcB5247D7KXO5uPZabbWECy8cx2uvXcztty9Cr9fxWVkN71VXsznFxfd+MKvda1AUhbSW1VdCpfHJv3BYJcmjnTRNReZjGtGcMCGPtfX11DS48dZ4qXuphvrXavB5griCQbKKjj0oSxmVgi8Uwl2vNSVtbvaShB6jTofZauj26iuJpM7QAgz3LhdN72lTcVPGp6Iz9Z3DraJTyL+o60mk3HPzufXWuYA2+nW8TJlSyD/+cXbcSnZHq23T7vJyO6FQGKvVmHDaSsTMmcX84x9ndxhkRsqWX3ttD+8/vzeuEWZklcri4k5K8RWF666bxssvX8TDD58eHYGObQa6eEjrvqmKaTgaGaHsbT/8oVbSfuONM7s0FbI7lU5AtFl5c7OX+no39fXuaJWa6D+WL9dWFf3v4cM8e+gQTx04wE23zuHPf17eaWK2qzIzLQRUlTte+5JXysr4qKaGL71Nx3QeSmTyshLerKxk/Z4aQqoad3HfE6ZNKyIry0oY2Oaz81GtlmhuW5UTMWdOCb/73ckJV8hsK3IsevCjrex3OKhwu/m0ro5Xy8oYNOjIq4EdiaIoXHih1lD3ww8PM3Pm3+OW6o40IT4Wl1wygbt+u4QXS0upbtQeu97v4+kDB8ksTu506lNXKQYF/UTt/SyyWskymcjJSeK0n0zkuzfMYODAdEaNyqGgIOWomhAXF6cxeXIBH9fUsNPnwOsLElZV1jU04BjUM0mVyNRLoF0VYU9WOgGceeaoY6ooSpQgaKs7fY36srZVS6eNLOHf5y/h6fOXcNpIrRJybG78tVJXV66LSJmYRuHVxeiSW8/HOkXh7lNm8OhZ87Ea49/rrsa6P/rR3Oj5GCDQSSuPI4m8pthphNC6wt4Hh7TVhs+YP/SojuGJkm9Faa2fn2HZafz6l4u4/fZFHQ48dtcppyRO6ERWk+8JS5cOZeXKS3n11W9y++2LWLXq8uMahx9PMr2uAzPOGMjuRw9hqnZh3+4gfZJ20V2/z47fH6LO52NEB0txLl48mDfeuISmJg9DhmS2O/gPGJDGyacMYeMXjZRUp5G90Y55oAVVhYoKO9Nyi7US6rzEJ4nUqemoARXvYQ/WYUlYRyRHVyGLbv+MIn7/1n5m1+UzyJaOfb2N9FkZ7NpZT5HVSkqyqd19umvsuDzuaf6YM8xmar9sjFYjNTd4afL7KZrQ/rWD9mX83xuXUFPjZOjQzA6z5qNG5bDL72BiMJOarc2kTUnDlGdGDatYm7XbWIqPbURzwIA0TEOteBxBqvbayVxnI3VqGt5DLUknh4P5o9s30fztb0/C7Q6Qnn7k5zeNTyH4uQvXYTfOzQ5SJ2ufJcdmOw0VTpzBIHMvHsKkSQWsXHkJFouB5mYviqJEl+PNzU0iZ1YWqZPis/Mmk4FTrhnNmof3kOc2surt/Zxx1qjo3ys2NGqrmZjD3HHdNM47b0z0Qu+000Ywc2YxjY0eDAYdQ4ZkdHigH7u0mENvVWP1KRzaUM/gqdoFfUWFnQKDGZ1OoWBcxpHf8E5MmlRAUq6FJ/bsY/j4HAbodITdIbzeIB/V1LC8+NhHxqfOKOK/b60jPdlM8ydN2HJhXm4uRqMOU5apR3oumQu0xq6u7drovjHPRPL4Y58/3tO0IAXqXqqJJjva0iXryb+wgJSJaYwBVq26vE80I+yKSOIqknSKrEY6eHDHn/OumDmzmNPnDuWlF3byf3d8yh+Xa4laQ7qBg/u1JOPRXFDHBpmZVjNpFhN2r5/hWWkd3q63LF06lHfeubzdcvMd6ajSqaOL5l//+iS+9a0phGKWSD/W1WbEibd8+TDefnsfRUWpbN5cw6SheT069SUyZUAF9iWoFO4p8+aVxE0pjb247wkWi4Fnnz2fujoXgwdnMG+etnJmbC/NoxVJyLhDIdxjTdgCYda8Vxf3t2M1bFgmeXnJ1Na62k2/jiSkjtWsWQNoDPh5eMsuBn+jmJVrqmjy+1k+e+SR79xFI+cW8Id7PmOINZlUg4Gplw2lZLIW5yuKwlNPnUswGD7qKrezzhrFpk3VPPLBdhrq3PgDIX586zxWrOiZC8jYC+lTTx3OSScN4Yc/fAegx3o69ZRIgqDqnxUd3qY7fY36MuvQJPRpekL21oETRVFQgEsmDmd6cS4T8+OPKUczAJoyMY2ksSkcvHMfYVdLKwFD+89qd5J5eXnJPPbYmcye/Q9CoXBcFWN3RV5Tbptm555AkFqXhwONdhRF4eSlR1/p3jaujVQ6oVc458pxnPPdnu1tlJeXzCWXTOCZZ7bG/b6nqpzaUhSFzMy+M2uiuyTp1IF58wfx8v9tYbbRyO7Xy5k+ahQ6i56qLdqojT+p49Fb0IKhzuZQnnPOaG5c+QbTa3IYWu3FuclBhdWP3qdSkpJEcpIx2pS4LX2Snswl2Ql7BEUsWjSYu+/+hBd2H2TSqFyUrQ6sg6007LRRqNNhTTN1uWlyR4xGPVmjUlm7r57imlRSWkZSmpo9fFJbyzcunNThfdPSzEe8eNXpFGYsLmHn5zbyqpLJfreBjAWZOMvdKO4wnlCIEQuOPO/3SE4/ZxRP/3EdaVYTheubcW1xEAqHaXZ4Oeh0Jqy6MBr1pKd3LfBYcsZQfvfqu5ykK6T+0wYCtX4MmUbKPqrF4w2y1tbI/50yH2gdjcrOTuLii8fzzDNb2dzUxKQVJaROTVwOWjApi+zCZPyHQ5R9Xg8tSadAUwB7uZuwqpIzLl2b5temXD8nJ6lLTQEz8qy4MiG1CXa/Xs6gKVqj6T2b6yiwWklONpI08NhGpHQ6hbPPHsXDD3/J47v28odrF+Cv8rHxi2a222x8q5Pqka6aMqWAHzU1MiglhQk2P4EqP6PT07V+Th0keY9G+txMbRXDxgDJE1LQHacV345VysQ0kse3rrwSdAa13gMKWIcnRZthRvSnk13ke1taamPv3oaYpNOxXcg5t9hZ4c3mpZDK/kYHTn+AFJORoC3IwbV1hA2hoyrdbhtkPnj6XNaU1bJwcEGnt+st3ekR0NG5sqNGmDqdctTTGUTfkZxs4tFHzwToNF45WomSJj2V5IhlNhs4++xRPPvsNtLTLSxadOQppd0VGzM+/fR5NDd7e6Qa7OSTh/DBB4c4+eQhXHTReFavPsB77x0E2lfDHK1Ir7q77vow+juDQcdddy2JW1HuWKSlmTn99BG8/voerv/ZW9Hfz517bCuUtX2OH/1uAf/v/73FwIHp/OKU+GpgnU45pmmVy5cP4/77P49OwwYtEXWsUxAjFEXhpJOG8N57B7n00olxiaaeeo6e1NHAlyHDQO65+V1aYa0/UHQKed8oSJhgsxoNTCqIL2A4lgovnUFH/oWJnyuiu8k8RVF4/vkL+P3vP4mbytpdkeq23GD8eb/c7uKLMq26c1xxJsVTj7xIQ2di49qkymyMmzajM+s485qePzeAVvEd6fF2//2fs3Tp0B47tn7V9L2jUB9hMOiYdf5Q6l+tRbe3idTnyhh6SkG0749SfGwXqBMn5pNfksqqikpG1WVjWK9je6iJiZmZZGRYsAywdNirKKKzAC4tzdxSkreXDbUNLEotomFlHcOazbgJYBmV1CMjCOefP5ZbbnmbHR/Z+OW0+YwekMnDT++i2uVp14T3aJxzzmi+/fKrFFiteLxBxjT6cLn8qKrKATwUlhz7Semkk4bw979v4O3SCoxWPVMnFFDb5OHFQ4fJKUhmwIBje45BgzIIDzLxYWk1JVVpmE0GOOyhptLJfoeDofPzEgYEN900C5fLj8ViYPTFAzvc34peIW1yGlWH7WTVQMAWwJhuxLnDQW2di0MuF/MWJ17yuDtGrCii8pkKXGUeGr5oImd2FvXbtGmVoXT9Ma+8AnDmmSN55JF1rNtURXMBDJqVz8r/0wLMngjArVYjY8fn8uLWUsbpijDoVcrdbpJzVU6deeyjyrEsg6xHXOK+L4isvPJVk5FhYcGCgXz8cSk//vEqhg3TytePZQQq0ncpJ9lCYWoSVQ43O2qbmDkgD1VVqXV5CITDFB5FVU7bZqApZiOnDI8/hvbX6QZtK52WLx9GRoalx0rcRd/X0wkn0OIPnU7B7w9xzjmjOXSouV0D6Z7ywx/O4dprp5Kaaj7uFxQ9Mb04Ij8/hcceOzP680knDeHnP1/AuHHd75nSmbPOGsXcuSWsWPE0oFUA9HQvkdtuW0BtrYsvvqhAp1O48spJzJnTeaP27po1awCvvvpNrFZjj39mzWYD55wzmief3AxoSdmeTgbdddcSbrllDgUFKXFVZ5GVVfua2ARByB5En6ad474KFU6xIgm2mueqCLs7n6J2rBVexyOZN3BgeqercHZFR9Vt22qa2NOymt/yC0f1yL6PxLVJw5P569/PQK/XdWk68tEwmfRceeVkoGeT4F9FknTqxDcvHs9vNr5PelWIXZ9UU7O9mdpaF7vtdqbMOraTqaJoVR0PPPAF7+0pZ4YjF4PNx6ycHDLSLSSNPvapBOefP5aVK/fy4HtbwR1m4oBsPC39cQaddOwVQqCtCHLppRP497+3ctv/fcTMmcVUuzwUFKR02tekq0aPzmHcpDye2XKQ+a483MEgRr2ODY2NZM458uoxXWEy6bnnnlO44opX2PT5ZharTewrb6bU7eZ7V83okQDzggvG8bOfrebgBxv5440LyUm38p8X97O5vpF//e7chPcxGHT88peLuvT4Y04r5tPn95ODmfd/sxWnMUyaR4ffH+JQyM2t8459tHHe0kHc9s8dTFcyWPv0fnj1EOaGAF7osQvh3Nxk5s0r4eOPS/nVrz5k8OCM6NL0PdX4b8mSwWzaVM3P/tm6gtgNp8+IrlwovjruvHMxl132MuXldsrLtX5Lx5J0iu27NCE/iyqHm99/tJnfnTKDwtQkvC1NWzO93U/AfpWnG+TlJaPTKdEVV37xi4WdVgoL0RVpaWauumpy9OfjmcRUFKVL0+n7OkVROPfcnpviGCu2atpm83Vyy6NjMul58MHTqK11aZX2x2lFpp5YTr0jy5cPi0k69fwx0GIxRKcixybNjuOis8fsqzrw1VYkwebe58L2aRPu3W7UmEWYerLCq68m8yIJsQv2DOOjXZXUOLW+xH5U5i4ZyMU/6LxP7tE40gqi4sQ5qqushx56iMGDB2OxWJg1axZr167t9PbPP/88o0ePxmKxMGHCBFauXHlUG3uiKYrCLXfOZ02giVqHm+pqJ/vtDjxDDJxxxrHPIz/99JEYjXpe2HWI9Qdqo/0CMielYxl87CfTiRPz+da3puALh/nTZ1u5c+U6VlZU8J6njuweWC4y4vvfn8XUqYW43QE++OAQoK3i1xOjRIqi8Ne/nsG9/7ecNY4G/rB+K79Zu5n3qquZ1YMjXEOGZHL77QsJqSqrPz/M4XIber2uR/YzwCmnDGXFiuHUeb3c9OiH3PC3D9hY38jwkdk9MqppsRo5mO2n2uOhscaNv9xLfYOb7c3NTFo2oEvNfo/EaNRzxS9m8Fl9HXa7D3uFG683SKPPx+C5PTcyGwmIt2yp4bXXdgNaEHgsc8ljffOb46MrTgCMH5/HpZf27Dxv0Tekp1v4wx+Wxk2JGDHi6Eu3Y/spTSlsfZw73lvPr97fAEBeihW99+gi/Egz0LYNVg0ZBgqvLu630w2sViN33aWtBpiaau6TUz2EED3nePVgUxSF/PyUPrMEeHeNHNl63ohtuH68/OY3JzF0aCY33DDjuD+XODJFp5A8MoWiq0sY9ruRFN8wkILLiyi+YSCDfzm8R8/xkWRe6tT0dq0SelPKxDR++fppvPb2JRizjRjzTJiLzDz877MwmyU2+CpT1LZd/47gueee44orruCRRx5h1qxZ3H///Tz//PPs3r2bvLz25bqfffYZCxcu5O677+aMM87gmWee4Q9/+AMbNmxg/PjxXXpOu91Oeno6NpuNtLQTH3Q3Nnp4c+Vewu4QyTkWTjttRI8FzRs2VLFpUzWoYApAyaB0Fp06tEceG7TVxd599wB//es6ysq08sXf/34pS5f23HMAuFx+3nhjL06nH7NZz2mnjejx/i/l5XZWrz5AKKSSnW3lzDNH9XiZ+9q1FWzbps0tHj8+r0emCEZ4PAGuuupV9u9vBECv1/HYY2cwaVLPrHJQWeng3VUHsDpUrD6FgAF8uXrOPndUj1YV7NxZx8YPKrD6FXxGlZwRqSztYAWHo6GqKm++uY/qamf0d3PnlvTolAO3O8Abb+whHFY57bQRpKb2j+bY4ujs2dPAJ5+UMmRIBkuWHH2TSvc+FxUPaUuzh1WV9w9U8vz2g9S2jNYB3DJvAhf9ceYxjdyqYbXPjVD2hC++KCcpyciECT1TadtTejvGOJ6+yq9N9D3bt9fywANf8NOfzm+3erHQXHDB8xw82ERmppVVqy7v7c0Rotf87ncf8+ab+3joodOYOLFvxQWia7oTY3Q76TRr1ixmzJjBgw8+CEA4HKakpITvf//7/PSnP213+4suugiXy8X//ve/6O9mz57N5MmTeeSRR7r0nBI0HTu73ce9937GhAl5XHDB8WmmJo6svNzOn/+8hqYmL5deOqHHk39CiONHDascumtfXJ8Eu9fP39fvpsrpZsmQIs6aOYTBvxz+lUgSfV18lWOMr/JrE6I/qqlx8qc/reGyyybKhbb4WlNVFZ8vJNXP/Vh3Yoxuzbnx+/2sX7+epUuXtj6ATsfSpUtZs2ZNwvusWbMm7vYAy5cv7/D2AD6fD7vdHvefODZpaWbuumuJJJx62YABafz5z8v55z/PloSTEP1MpO9SrDSLiVvmTeCe5bM4bWRJv+27JE6cr0uLAiFEe/n5Kfzxj6dIwkl87SmKIgmnr5FuJZ3q6+sJhULk58cfKPPz86murk54n+rq6m7dHuDuu+8mPT09+l9JiXSDF0II0fu+qn2XxInx3HPPccstt3DHHXewYcMGJk2axPLly6mtrU14+88++4yLL76Yb3/722zcuJFzzjmHc845h23btp3gLRdCCCGEODp9crmm2267DZvNFv2vrKystzdJCCGEALTE0+Dbhx/XJqDiq+nPf/4z1157LVdffTVjx47lkUceISkpiccffzzh7R944AFWrFjBj3/8Y8aMGcOvf/1rpk6dGm1xIIQQQgjR13Ur6ZSTk4Ner6empibu9zU1NRQUJG6GXFBQ0K3bA5jNZtLS0uL+E0IIIfqKvroyjOi7TlSLAiGEEEKIvqRbEylNJhPTpk1j9erVnHPOOYDWSHz16tXceOONCe8zZ84cVq9ezQ9+8IPo71atWsWcOXO6/LyRXufS20kIIYQQPSkSW3RzXZVu66xFwa5duxLep7stCnw+Hz6fL/qzzaatWivxkxBCCCF6Unfip25377rlllu48sormT59OjNnzuT+++/H5XJx9dVXA3DFFVdQXFzM3XffDcD/+3//j0WLFvGnP/2J008/nWeffZZ169bx2GOPdfk5HQ4HgPR2EkIIIcRx4XA4SE9P7+3NOCZ33303v/rVr9r9XuInIYQQQhwPXYmfup10uuiii6irq+P222+nurqayZMn89Zbb0VH4kpLS9HpWmftzZ07l2eeeYZf/OIX/OxnP2PEiBG88sorjB8/vsvPWVRURFlZGampqSjKiZnCYLfbKSkpoaysTKb39TLZF32H7Iuukfep75B90Xf01X2hqioOh4OioqLj+jwnokXBbbfdxi233BL9ORwO09jYSHZ29gmLn6Dv7uuvI9kXfYfsi66R96nvkH3RN/TV/dCd+ElRj3c9eT9lt9tJT0/HZrP1qZ37dST7ou+QfdE18j71HbIv+g7ZFzBr1ixmzpzJX/7yF0BLCg0cOJAbb7yRn/70p+1uf9FFF+F2u3n99dejv5s7dy4TJ07kkUceOWHb3V2yr/sO2Rd9h+yLrpH3qe+QfdE3fBX2Q7crnYQQQgghRPf1RosCIYQQQojeJEknIYQQQogToDdaFAghhBBC9CZJOnXAbDZzxx13YDabe3tTvvZkX/Qdsi+6Rt6nvkP2Rd8h+0Jz4403drji7wcffNDudxdccAEXXHDBcd6qniX7uu+QfdF3yL7oGnmf+g7ZF33DV2E/SE8nIYQQQgghhBBCCNHjdEe+iRBCCCGEEEIIIYQQ3SNJJyGEEEIIIYQQQgjR4yTpJIQQQgghhBBCCCF6XL9POq1du5Y5c+awcOFCLr74YgKBAM8//zxz587l5JNPpry8HIDvfOc7zJ07l9mzZ7Nq1SoAXC4X5513HvPnz+ePf/xjwsf/yU9+woIFC7j88ssJBAKAtqRxbm4uDz74YML7JHqujz/+mHHjxlFQUNDTb0Gf0V/2xRNPPMGIESNYvHgxl156aU+/DX1Cf9kX5eXlLF26lEWLFnHffff19NtwRCf6fXI4HJx00kksXLiQk046icOHD7e7z65du1i4cCFz585l9erVgBw/+tK+kONH39kXvX381UFu3AAAgEpJREFU6O/6y3lCjn99Z1/I8a/v7IvePv71l/OEHD/6zr6Q40ff2Re9cvxQ+7nKykrV7XarqqqqP/3pT9Xnn39enT17turz+dRPPvlEve6661RVVdX9+/erqqqqjY2N6owZM1RVVdX7779f/dvf/qaqqqouX75cLS8vj3vsTZs2qZdeeqmqqqr6m9/8Rn3mmWdUVVXViooK9Z///Kf6l7/8JeE2JXqu5uZm1eVyqdOmTeux197X9Jd90dntvyr6y7644YYb1HfffVdVVVU988wz1YqKip55A7roRL9PHo8n+hrfeust9YYbbmi3Teeee666Z88e1WazqXPnzlVVVY4ffWlfyPGj7+yL3j5+9Hf95Twhx7++sy/k+Nd39kVvH//6y3lCjh99Z1/I8aPv7IveOH70+0qnwsJCrFYrACaTid27dzNmzBhMJhPz5s1jy5YtAAwdOhTQlhxUFAWAzz77jGXLlgFwyimnsGbNmrjHjv37ihUr+PTTTwEoKirqdJsSPVd6ejpJSUnH/Hr7sv6yLwAefvhhFixYwLPPPntMr7mv6i/7Yv/+/UyePBmAiRMn8tlnnx3T6+6uE/0+WSyW6PtkMpnQ6dofgisrKxkxYgRpaWlkZWVRX18vx48+tC9Ajh99ZV/09vGjv+sv5wk5/vWdfQFy/Osr+6K3j3/95Twhx4++sy9Ajh99ZV/0xvGj3yedIg4fPsw777zD/PnzSUtLi/4+FArF3e62227j+9//PgBNTU3R26anp9PY2Bh32yP9/Uhin+vrpK/vi3POOYdt27axcuVK/vznP1NVVdW9F9iP9PV9MXbsWN577z2CwSAffPABTU1N3XuBPeREv09+v58777wz4fEhHA5H/300729/19f3hRw/+s6+6CvHj/6ur58nvk76+r6Q41/f2Rd95fjX188TXyd9fV/I8aPv7IveOH58JZJOdrudyy+/nCeeeILc3Fzsdnv0b3q9Pvrvxx9/nGAwyGWXXQZARkZG9LY2m42srCz+/Oc/s3jxYu65556Ef0+ksbGRxYsXs3jxYurq6hI+19dFf9gXGRkZ6HQ6UlNTWbx4MTt37uz5N6IP6A/74rbbbuO5557jtNNOo6SkpFfm3PfG+3Tdddfxve99jxEjRrR7n2JHKTp7f7+K+sO+kONH39kXfeH40d/1h/PE10V/2Bdy/Os7+6IvHP/6w3ni66I/7As5fvSdfdErx4/jPoHvOAsEAuqpp54anZfo9/ujcyc//fTT6NzJVatWqaeddpoaCASi973vvvvUf/zjH6qqquqKFSvUsrKyuMfeuHGjevnll6uqqqq//e1vo3OvVbXzeamJniviqzynuL/sC5vNpqqqqgaDQXXhwoXqwYMHj/GV9z39ZV9EBINB9bzzzlPtdvsxvOru64336c4771R/9atfdbhN55xzjrpv3z7VbrdH515HyPGj9/eFHD/6zr6I6K3jR3/X384Tcvzr/X0hx7++sy8iJH5qJfFT394XcvzoO/si4kQeP/p90unJJ59Us7Ky1EWLFqmLFi1Sn332WfXZZ59V58yZoy5ZskQtLS1VVVVVhw4dqk6dOlVdtGiRumLFClVVVdXhcKhnn322Om/ePPXuu+9O+Pg/+tGP1Pnz56uXXHKJ6vP5VFXVGoONHTtWHTVqlPqDH/yg3X0SPdeOHTvUk08+WU1NTVVPPvlkdcOGDcfj7ehV/WVf3HnnneqsWbPUmTNnqvfdd99xeCd6X3/ZF2+++aa6ePFidcmSJerKlSuPx1vRqRP9PpWWlqp6vT76fD/96U/b3Wf79u3q/Pnz1Tlz5qjvvPOOqqpy/OhL+0KOH31nX/T28aO/6y/nCTn+9Z19Ice/vrMvevv411/OE3L86Dv7Qo4ffWdf9MbxQ1FVVT3+9VRCCCGEEEIIIYQQ4uvkK9HTSQghhBBCCCGEEEL0LZJ0EkIIIYQQQgghhBA9TpJOQgghhBBCCCGEEKLHSdJJCCGEEEIIIYQQQvQ4SToJIYQQQgghhBBCiB4nSSchhBBCCCGEEEII0eMk6SSEEEIIIYQQQgghepwknYQQQgghhBBCCCFEj5OkkxBCCCGEEEIIIYTocZJ0EkIIIYQQQgghhBA9TpJOQgghhBBCCCGEEKLHSdJJCCGEEEIIIYQQQvQ4SToJIYQQQgghhBBCiB4nSSchhBBCCCGEEEII0eMk6SSEEEIIIYQQQgghepwknYQQQgghhBBCCCFEj5OkkxBCCCGEEEIIIYTocZJ0EqIPUxSF5ubmuN8NHjyYTZs2HfG+11xzDe+///7x2bBOnHbaaezevTvh384//3yeeOKJE7tBCVx11VXcf//9Cf/2yCOPcM899/To8x06dIjFixeTnp7O5MmTe+y2x+LDDz9kxowZjBs3jrFjx7JmzZrj9lxCCCHE8SYx0/HxdY+Znn32WSZPnsz48eMZP348f/rTn6J/C4fD/OhHP2L8+PGMHj2ab3/72/j9/uOyHUL0Z4be3gAhxPHx97//vVeed+XKlb3yvD3l+uuv7/HHTEtL4ze/+Q02m42f//znPXbbo1VZWcmVV17Jm2++yZgxY/D5fHg8nuPyXEIIIURfJzHT0fk6xEwlJSW89dZbFBQUYLPZmDZtGtOmTWPx4sX84x//YMOGDWzYsAGj0ch1113HAw88wI9//OPjsi1C9FdS6SREPzZ48GBuv/125syZw5AhQ/jNb34T/dvixYt55ZVXAKiqqmL58uWMHTuWpUuX8s1vfpM777wTgDvvvJMf/OAH0fs9+OCDXHXVVdGf7733XmbOnMnUqVNZsWIFhw8fPuI2RUYVd+3axdy5cxk3bhznnHMOdru9S6/rzjvv5MILL+TMM89k5MiRnHHGGWzbto3ly5czcuRILr74YsLhMADPPPMMs2bNYsqUKUyaNInXX389+jgVFRWcf/75TJgwgYkTJ/LLX/4y+redO3dy8sknM3LkSM4777zoyFTs+/HEE0+wdOlSLr74YiZMmMD06dM5cOBA9DGeeuopZs2axdSpU1m4cCGbN29O+HqysrKYP38+ycnJR3zt3bktwLp16xg9ejSqqkZ/N3fuXN58880O7/Pwww9zySWXMGbMGADMZjMZGRldej4hhBCiP5KYSWKmo4mZ5s2bR0FBAQDp6emMHj2aQ4cOAbB582aWLl2KyWRCURROPfVUnnrqqS5tixBfJ5J0EqKfa25uZs2aNXz55Zfcc889VFRUtLvNTTfdxMyZM9mxYwf/+te/WL16dZce+5lnnmH37t2sWbOGDRs2cOmll/K9732vy9t2+eWX8+1vf5vt27fz61//mg8//DD6t9dee41rrrmmw/uuW7eOJ598kt27d+NwOLjmmmt44YUX2LFjBzt37owGCMuXL+fzzz9n48aNvPrqq1x77bX4fD4ALrvsMqZNm8bWrVvZsmULN910U/TxN23axOuvv87OnTupqanhxRdfTLgdX375Jb/73e/YunUrS5cu5Q9/+AMAn376Kf/5z3/46KOP2LBhA7/97W+55JJLuvze9JTp06eTnZ3NqlWrANi4cSN1dXWsWLGiw/vs2LEDj8fD0qVLmTx5Mt///vdxuVwnapOFEEKIXiExk8RM3Y2ZYu3YsYM1a9awdOlSAKZNm8Zrr72G3W4nEAjw3//+N5qQEkK0kul1QvRDiqJE/x05aefk5DB06FAOHjxIcXFx3O1Xr17NvffeC0BxcTFnnXVWl57nlVde4csvv2TatGkAhEKhLm+j3W5n06ZN0RHACRMmMH/+/OjfzzrrrE63Y9myZWRmZgIwdepUzGYzqampAEyZMoW9e/cCcPDgQS699FLKy8sxGAw0NjZy8OBBBgwYwCeffMLbb78dfczc3Nzov88991ySkpIAmDlzJvv370+4HZER0ci///KXvwDw6quvsnnzZmbNmhW9bWNjIx6PB6vV2rU3qYf8v//3/3jwwQdZtmwZDz30EN/73vfiPiNtBYNBPvroI959911SUlK4+uqrueOOO6KfESGEEOKrQmImiZlidTdmiigvL+fss8/mkUceYcCAAYDW7+rw4cMsWrQIq9XK0qVLeeedd473SxCi35FKJyH6sNzcXBoaGuJ+V19fT15eXvRni8US/bderycYDB7xcWNPrgaDIS4w8nq90X+rqsptt93Gpk2b2LRpE1u3bmXr1q1H9VraPu+RtH1dHb3Ob37zm1xzzTVs27aNTZs2kZKSEvcauvr4Hb1vHd1OVVWuvPLK6HuzadMmqqqqsFqtnH/++UyePJnJkye3239tdee2HTnvvPPYsmULGzdu5LXXXuPqq6/u9PYDBw7k9NNPJzMzE6PRyMUXX8znn39+VM8thBBC9AUSM2kkZupcd2Mm0HphLl26lF/84hdccMEF0d8risKdd97Jxo0b+eyzzxg7dizjxo07qu0S4qtMkk5C9GHLly/n0Ucfjf785JNPMnToUAoLC7v1OEuXLuXxxx8HtF4Fr732WvRvw4cPZ926dYRCIdxud1zJ9DnnnMMjjzxCY2MjAIFAgI0bN3bpOdPS0pgyZQpPPvkkANu3b+eTTz7p1nZ3RVNTU3RU7emnn6apqQmAlJQUFi5cGLfKSF1dXY8971lnncXTTz9NaWkpoK1gsm7dOgBeeOGFaFCVnZ3d6eN057YdMRgMXH/99Zx11lmce+65R+zPdMkll/D+++9HS+rffPNNJk2adFTPLYQQQvQFEjMdmcRM3Y+ZqqqqOPnkk/nJT37ClVdeGfc3r9cbfQ/r6+v5/e9/z6233npU2yXEV5kknYTow+6//36qqqqYOHEikydP5plnnuH555/v9uM88MADfP7554wdO5YrrriCk046Kfq38847j6KiIsaMGcMZZ5zBlClTon+79NJLueqqq1iyZAmTJk1i8uTJvPfee11+3ieffJLHHnuM8ePH84tf/IKFCxdG/3ak/gTdeW3nn38+U6ZMYePGjQwcODD6t6eeeop169Yxbtw4Jk+ezIMPPnjMzxexYMEC/vjHP3LuuecyadIkxo0bx7PPPpvwtm63mwEDBnDBBRewY8cOBgwYwG233XbMt4317W9/m4qKCm688cYj3nbu3LmcddZZTJkyhQkTJlBfX89vf/vbI95PCCGE6KskZuraa5OYqXsx0+23305paSkPPPBAtMrqn//8JwA2my3a/H3BggVcf/31nHnmmUd8TCG+bhQ1tn2/EOJr4Uc/+hEpKSnR1VhE//fCCy/w17/+tcsNT4UQQghxZBIzffVIzCTEiSWNxIUQop9bsWIFe/bs4eWXX+7tTRFCCCGE6LMkZhLixJNKJyFEt91111289NJL7X7/4osvMmzYsF7Yoq++v//97wlL3f/yl7+wYMGCdr+PXQUn1pVXXsnNN998PDZRCCGEEG1IzHTiScwkRN8iSSchhBBCCCGEEEII0eOkkbgQQgghhBBCCCGE6HGSdBJCCCGEEEIIIYQQPa5fNBIPh8NUVlaSmpqKoii9vTlCCCGE+IpQVRWHw0FRURE63VdrLE7iJyGEEEIcD92Jn/pF0qmyspKSkpLe3gwhhBBCfEWVlZUxYMCA3t6MHiXxkxBCCCGOp67ET/0i6ZSamgpoLygtLa2Xt0YIIXqHGlbxHHQTcgTRpxqwDklC0Un1ghDHwm63U1JSEo01vkokfhJCfN1J7CTE8dGd+KnbSaePPvqIe+65h/Xr11NVVcXLL7/MOeec0+l9PvjgA2655Ra2b99OSUkJv/jFLxIuS9mRSEl4WlqaBE1CiK8l5xY7dS/VErQFo7/zpDvJPS+flIlyXBTiWB3v6WcSPwkhxIklsZMQx19X4qduNy9wuVxMmjSJhx56qEu3P3jwIKeffjpLlixh06ZN/OAHP+Caa67h7bff7u5TCyHE15Jzi52qf1bEBU0AQVuQqn9W4Nxi76UtE0J0lcRPQghx4kjsJETf0e1Kp1NPPZVTTz21y7d/5JFHGDJkCH/6058AGDNmDJ988gn33Xcfy5cv7+7TCyHE14oaVql7qSb6s9MXwGzQY9S3jhnUvVxD8vhUKRcXog+T+EkIIU6MtrFTWFWx+/xkWMzR30nsJMSJc9yXaVmzZg1Lly6N+93y5ctZs2ZNh/fx+XzY7fa4/4QQ4uvIc8AdHaVrcHu54sUP+Mk7a+NuE2wO4jng7o3NE0IcJxI/CSHE0YmNnQAe+mIH33rpIzZXN0R/J7GTECfOcU86VVdXk5+fH/e7/Px87HY7Ho8n4X3uvvtu0tPTo//JyitCiK+rkL01aPqivA6AQ02OTm8nhOj/JH4SQoij0zYmev9AJQDPbtnf6e2EEMfHcU86HY3bbrsNm80W/a+srKy3N0kIIXqFPq11FrTLH+jS7YQQX08SPwkhRMcxkTsQ6tLthBA967h/0woKCqipqYn7XU1NDWlpaVit1oT3MZvNmM3mhH8TQoivE+vQJAzpBoK2IC5/4hE5Q4YB69CkE7xlQojjSeInIYQ4OrGxUyx3oPVniZ2EOHGOe6XTnDlzWL16ddzvVq1axZw5c473UwshRL+n6BRyz9Om2Dg7qHTKPTdfGmEK8RUj8ZMQQhyd2NgpVmzSSWInIU6cbiednE4nmzZtYtOmTYC2pO+mTZsoLS0FtNLuK664Inr766+/ngMHDnDrrbeya9cuHn74Yf773/9y880398wrEEKIr7iUiWkUXl2MVxeO+70hw0Dh1cWkTEzrpS0TQnSVxE9CCHHiRGInQ3rrxB5PICixkxC9oNvT69atW8eSJUuiP99yyy0AXHnllTzxxBNUVVVFAyiAIUOG8MYbb3DzzTfzwAMPMGDAAP7+97/Lcr9CCNENKRPTUCYkYbSbIKRSfMNArEOTZJROiH5C4ichhDixUiamkTw+FeOLWuyEXmHwL4dL7CTECaaoqqr29kYcid1uJz09HZvNRlqaZKWFEF9Pl132Ert21QOwbt11vbw1Qnw1fJVjjK/yaxNCiK6aPv2x6L8lfhKiZ3QnxuiTq9cJIYRoz+HwR//dD8YLhBBCCCGEEF9zknQSQoh+QA2rNNe6CbtDhH1hQsHwke8khBBCCPE1l5Rk7O1NEOJrTZJOQgjRxzm32Dl01z4aDzoJNAQI1PrZf9denFvsvb1pQgghhBB9WkqKKfrvUEgG7YQ40STpJIQQfZhzi52qf1bgbfJDzIw6f3OAqn9WSOJJCCGEEKITyUlGwr4wYXeIms1NqGFpUSDEiSRJJyGE6KPUsErdSzUAOP2BuL+FWgKmupdrJHgSQgghhEjAucWOe6eLQK2fQEOAvQ8d5NBd+2TQTogTSJJOQgjRR3kOuAnaggDYffFJp0gf8WBzEM8B94neNCGEEEKIPi1SLR7yt06pcwWCBG1BqRYX4gSSpJMQQvRRIXsw+m+3Pxj3t6AaTng7IYQQQoivu9hq8XDMir/OmEE8qRYX4sSQpJMQQvRR+jRD9N+xARNAOCZIir2dEEIIIcTXXWy1eGwM5Qq0DtRJtbgQJ4YknYQQoo+yDk3CkK4llNolnVp+NGQYsA5NOtGbJoQQQgjRZ8VWgcdGUO5AsMPbCSGOD0k6CSFEH6XoFHLPywcg1CbpFPk599x8FJ1ywrdNCCGEEKKviq0CV2NiqDbhlFSLC3ECSNJJCCH6sJSJaRReXYySFH+4VlJ1FF5dTMrEtF7aMiGEEEKIvim2Wjx24C7231ItLsSJIUknIYTo41ImppF/VTHGPBPGbCPGPBNFNw6ShJMQQgghRAKx1eKx1U2xVU9SLS7EiSH1hEII0Q+EVdCZdTE/y2orQgghhBAd0arFgddbfxdWVQwZBnLPzZfBOyFOEEk6CSFEPxAKhdv8LEknIYQQQojOpExMwzzYirFGhZBKxtJsBt88XCqchDiBJOkkhBD9QNskU9sklBBCCCGEaC+2WtyQa5KEkxAnmPR0EkKIfiAcVjv9WQghhBBCtBcbM0n8JMSJJ0knIYToB4JBmV4nhBBCCNFdknQSondJ0kkIIfqBtkFS2ySUEEIIIYRoL3bFOkk6CXHiSdJJCCH6gbY9nCRoEkIIIYQ4stjqcImfhDjxJOkkhBD9gDQSF0IIIYToPql0EqJ3SdJJCCH6gbZBkvR0EkIIIYQ4Mql0EqJ3SdJJCCH6gbaVTVLpJIQQQghxZFLpJETvkqSTEEL0A+2n10nQJIQQQghxJLJ6nRC9S5JOQgjRD0gjcSGEEEKI7mkbL0n8JMSJJ0knIYToB9oGScGgTK8TQgghhOhM7NQ6kKSTEL1Bkk5CCNEPyOp1QgghhBDd034hFomfhDjRJOkkhBD9gEyvE0IIIYTonrbxkirhkxAnnCSdhBCiH5BG4kIIIYQQ3SOVTkL0Pkk6CSFEPyBBkxBCCCFE90ilkxC9T5JOQgjRD7RtHC6VTkIIIYQQnZNBOyF6nySdhBCiH5CgSQghhBCie9pWNklPTCFOPEk6CSFEP9A2ySSVTkIIIYQQnZOFWITofZJ0EkKIfqB9I3GpdBJCCCGE6IxUOgnR+yTpJIQQ/YCM1AkhhBBCdE/beEniJyFOPEk6CSFEP9C+p5METUIIIYQQnZGkkxC9T5JOQgjRD7RNMrVdzU4IIYQQQsSTQTshep8knYQQoh+Q6XVCCCGEEN3TNl5S2zZ5EkIcd5J0EkKIfqD9SJ1UOgkhhBBCdEYqnYTofZJ0EkKIfiASJBkMurifhRBCCCFEYlLpJETvk6STEEL0A5HKJpNJH/ezEEIIIYRITCqdhOh9knQSQoh+IBIktSadJGgSQgghhOiMrF4nRO+TpJMQQvQDkSDJaNTH/SyEEEIIIRJrO51O4ichTjxJOgkhRD8QDGrT6YxGXdzPQgghhBAisbaV4ZJ0EuLEk6STEEL0A5EgKTK9ToImIYQQQojOSaWTEL1Pkk5CCNEPSCNxIYQQQojukUonIXqfJJ2EEKIfkEbiQgghhBDdI5VOQvQ+SToJIUQ/IJVOQgghhBDdI6vXCdH7JOkkhBD9QLglxxRpJC6VTkIIIYQQnZOkkxC9T5JOQgjRD7StdJKgSQghhBCic5J0EqL3SdJJCCH6gUhlk9GoJZ2CQZleJ0R/9NBDDzF48GAsFguzZs1i7dq1Hd72iSeeQFGUuP8sFssJ3FohhOjfJOkkRO+TpJMQQvQDkSBJejoJ0X8999xz3HLLLdxxxx1s2LCBSZMmsXz5cmprazu8T1paGlVVVdH/Dh8+fAK3WAgh+re2SSZpTyDEiSdJJyGE6Adkep0Q/d+f//xnrr32Wq6++mrGjh3LI488QlJSEo8//niH91EUhYKCguh/+fn5J3CLhRCif2uzeF271eyEEMefJJ2EEKIfaJ1eJ43EheiP/H4/69evZ+nSpdHf6XQ6li5dypo1azq8n9PpZNCgQZSUlHD22Wezffv2Dm/r8/mw2+1x/wkhxNdZ28pwiZ+EOPGOKukk/QiEEOLEalvpJD2dhOhf6uvrCYVC7SqV8vPzqa6uTnifUaNG8fjjj/Pqq6/y9NNPEw6HmTt3LuXl5Qlvf/fdd5Oenh79r6SkpMdfhxBC9CdS6SRE7+t20kn6EQghxInXtqeTTK8T4qtvzpw5XHHFFUyePJlFixbx0ksvkZuby6OPPprw9rfddhs2my36X1lZ2QneYiGE6Fukp5MQva/bSSfpRyCEECdepLKptZG4BE1C9Cc5OTno9Xpqamrifl9TU0NBQUGXHsNoNDJlyhT27duX8O9ms5m0tLS4/4QQ4ussknRSFCXuZyHEidOtpNOJ6EcA0pNACCHaigRJRqOsXidEf2QymZg2bRqrV6+O/i4cDrN69WrmzJnTpccIhUJs3bqVwsLC47WZQgjxlRKJnwwGXdzPQogTp1tJpxPRjwCkJ4EQQrQljcSF6P9uueUW/va3v/Gvf/2LnTt38t3vfheXy8XVV18NwBVXXMFtt90Wvf1dd93FO++8w4EDB9iwYQOXXXYZhw8f5pprrumtlyCEEP2KJJ2E6H2G4/0Ec+bMiRvBmzt3LmPGjOHRRx/l17/+dcL73Hbbbdxyyy3Rn+12uySehBBfa20biUulkxD9z0UXXURdXR2333471dXVTJ48mbfeeis6mFdaWopO1zoe2NTUxLXXXkt1dTWZmZlMmzaNzz77jLFjx/bWSxBCiH5Fkk5C9L5uJZ1ORD8C0HoSmM3m7myaEEJ8pUUqm6SRuBD924033siNN96Y8G8ffPBB3M/33Xcf99133wnYKiGE+GqSpJMQva9b0+ukH4EQQvSOtqvXRRqLCyGEEEKIxNomnaRSXIgTr9vT62655RauvPJKpk+fzsyZM7n//vvb9SMoLi7m7rvvBrR+BLNnz2b48OE0Nzdzzz33SD8CIYTopkiQFGkkLiN1QgghhBCda5t0UiV8EuKE63bSSfoRCCHEidd2ep00EhdCCCGE6JyqSqWTEL3tqBqJSz8CIYQ4sdpOr6uqcrBjRx1jx+b25mYJIYQQQvRZkUE6qXQSovd0q6eTEEKIEy8cVqMjdUZj62H7mmte48CBpt7aLCGEEEKIPk0qnYTofZJ0EkKIPi62f1Ok0gnA7w9xxx0fdPlx1LCKe58LxwYb7n0uVOkLJYQQQoivsLaVTtITU4gT76im1wkhhDhxYkflSkrSKSpKxWIxcOBAEzt31lFX5yI3N7nTx3BusVP3Ug1BWzD6O0O6gdzz8kmZmHbctl0IIYQQore0rXSSpJMQJ55UOgkhRA/r6Yqi2KbhyclGXnnlmzz33PkMH54FwM6d9Z3e37nFTtU/K+ISTgBBW5Cqf1bg3GJv3faQirfMQzgg5edCCCGE6N9aV69T4n4WQpw4UukkhBA96HhUFMVWOul0CjqdFjiNHZvLvn2NbN9ey8KFgxLeVw2r1DxX1enj171cQ/L4VNSASuM79firfSSNTiZjQVaHj+k54CZkD6JL0aOGVbwHPABYhyeRNDwZpWUbO7q/GlDRmWXcQwghhBDHT2vSqTXmUFUVRek4ThFC9CxJOgkhRA+JVBS1FakoKryao0o8xY7K6fWtQdOYMTm89truTiudGlfVE3a3Jq3KbE7WVdRzxqiBGFseK9gcjCaR/NU+ANx7XKTNykBnignSwiqNq+pp/qgx7jFjNa1qQJekI/+iwoSv1VfppfmjRkLuENmn5WEuMHfxXRBCCCGE6J5IDBUbP4XDKnq9JJ2EOFEk6SSEED1ADavUvVTT+rOq4g+FMRtaG39HKoo6qwJKJHZ6nS7mvmPH5gKwfXsd4bCKTqe0q0Jq+rAxevtmr48739tAk8eH1ahnxYiS1uewB/HX+lufNAyeA26SR6cAWkKt5rmqDpNNscLuMFX/rKDgShV9ioGQPYg+zYBliJXmj5sIOUIAONbbMJ+e1633QgghhBCiq1paOsWt/hsKqej1HdxBCNHjJOkkhOhXYpMq+jQD1qFJ3U7iHA+eA+64KXV/+Xw7n5XV8sBpc8hPsQKtFUVJwztv+t1WZHqdrs3rHDEim5QUEzabl8cf38i0vGwyNvjb9W4CCKsqD6zZTpNHq2TaUNkQl3TSpxkI7HAScgcxZBgJNgewr7VhzDTiq/ZS/UTlEbcz0qxTURSavT5qH95PXrK19TlS9RgyjBhStVOPv9JHzX+rSB6TQvLYFBQZdRRCCCFED4rEUG2n1wkhThxJOgkh+o2+vAJbyB6f6PngoNZH6bVdh7l2+ugOb9elxw6170cAYDLp+cY3xvCvf23m4fu+INwY5A/LZpKXbCXFbIy77Ss7D7O5qgFFUVBVlW21jQTDYQw6HYpJwbnDgWOzA4Iq7oCT0mYnKVYj2fvtfLm9mjq7hzNHDcRk0BMIhXl2634GZ6Qyd2Aej63bRY3TQ7ndRbLRwPdnj+N3H27CEwzx0JnzyLJqU+hCjhAhRwjjlFSSRibj2uokZAti/7wZf42PzCXZkngSQgghRI+J5JdiY6jYCnIhxPEnSSchRL9wvPol9RR9WuvhNHYEzR0Idni7ror0I2hb6QRw0UXjefbZbdgrfRBW+dFbX2DU6xiQlozZoOfM0QPZVNXAqn3ae/edGaN5ecchapwe9tTbGJuXiepXsb3fFH3M/249wLv7KzhlWDGjmzKw6vSoqsqVL35AYVoyh5oc0dvubRwYfWyARnzc+vba6M+fHa5h2YhiTDF17O49LgouKyZ5XCq+Ug+2L5rxHvRQXVWJ3qrDOiwZY64Jz14XIUeQsD+MucRK6uQ0aT4uhBBCiC6TSichep8knYQQfV7bfkmHmhwEVZXhWa1JpqPtl9RTrEOTMKQbCNqCOHyB6O9d/piqrAxtOmB3BYNawBTbBDMiLy+ZR+9awZq/7Ob/Pt8GKgRCYQ62JIZ21TVHbzsmL4NThhUzLCuNd/aWs6ehmbF5mdG/q6pKud3Fa7sOA/DqrsN8WVHHJZOGMygzlVvmT+SLslpQVey+AO5AkB01TWRZzZgMepYNL+b9A5XUubwYdApOf5DX/3979x0fV3Xn//91y/TRzKg3S7JlueKOMdiAMb0mAVJYSEhCsoFs2GzyZfPblN1kCZtdkpCEbPpmQ8pmk6WGEjoxHUzA2Ma4W7ZlSVYv09st5/fHWCPJkmzZlm3ZnOfj4cdDHt25c+89ozv3vuecz9m2F4HgshlTcOwPnuyEnR9mqJ9WgFagE36pDzttY6ZtYmsjI49Bf4xUY5LgihCeaYd/DE9F0WiG73znVa68ciYrVtQc+gmSJEmS9B4zkC8NvYaSPZ0k6fiSoZMkSZPe0HpJpm1z21NvAPD7D63C58wNIzvSeklDHU29KEVVKL22nPbf7KNvf90kgM54Kv+zf3HgsEMxYQsSuxPYSQscNsIWI9ZRV+jHNa0St67RHInz/O42uoa8LoDPqfO3p89GURQCLgdLp5Tidw7/CGiPJbn7tXcBqAn6+NZFS3l6Zyv1hQUUeV3siyS4YmYNhm3j0jQi6SxZ20ZXFeaXF6GrKu+fXUc0nUUALze1U+H3oqoKfalsvrYVDB9m6K71UPaRSrIdGcyYSWpHAqPfwD3Vi6feAzbE1kUwwyb9f+kluyBL8MzQYR3HU9F///fbPPPMLp55Zhdr1958ojdHkiRJkiadgd7iQwuJD50VWJKkY0+GTpIkTXpDA4rokF5EvalMPnQ6cLnDNRH1ovwLAoTOT9H/h578Yx3xJLYQqIpC+IU+PFM9417fwDa1NYcxeg3MhELTHY0jtmlgyN5ZNWWcVVPG1XPqyJo2D27ew5bufr587kIKPS5UJRdWBV1OAMKpLC2ROEKArio8vLWJpnCcgNvJp06fRYHLyYfn1edfZ1rR8O22hSBlmLh1DU3NXcypikJofw2nRZXFdCXS7OqN8uKedj62sIHKAi9p06QrlaaAYH5dqkvFXZcLpfzzChBCoCiD4Zq7zkNsfZT4hiiJjTHcdR5cFa5xHceJJoQg1ZhEGAJ3nQfNd2KmwNm7d2SPMEmSJEmSBg0ETEN7OsnQSZKOLxk6SZI06Q2tgxRJZ/M/R9NZhuQWR1QvCY6+XtRAD6mBGd/6h2yjYdl0JVJU+HNDwjrvax/XMMCh22QN1HQaY5uGDu0DcGoaTk3jk0tmjrpup67xzM5WNrT3UuH3UOJ1051M0x5LMr04wHcvWTYs8BmLqijDQr8D1YUK0BSFO1/aAMCa5k7qQn46U2nEGp3f/OYDzJ9fPupzD3x9RVcInBHETlkktyeIrYvguqLskNt4LKT3pgi/2AdAak+SkitPzHYMPUTZrIXTKed/liRJkqShhtbFVFUF2xYydJKk40xWZJUkadIbCFVgeOjUnxr8+UjrJR1YL2o03Q93Isa4QIlvjNJ0RyP7ftpM5x/asRMW/UOG1wFs6Qrnf7aTNn3P9XAwB26TLUYWEu+8rz2/TQND+w7H8illCKCywMv04gBzSkMsm1LKrcvmjgh8VK9KaFXRYa1/QFXAR9DtzP9/bziO5c+tv6Uletjr887xA2D2H3mvtqNldA2+77KdGez9NbeOt1Rq8Bh0dMRPyDZIkiRJ0mR2YOg09DFJko4P2dNJmjSeemonmqZyySXTD+t5vb1J3n67nQsumDZiSnnp1DC0XlJ4SOgUTg+GO6XXlB9REfGh9aIMy+bP2/aytLqU2pA/v8xY9aLG6iF1YOh0/6bdnFtXgWN/1+7wy30UXVwy5vYO3aasafHLt7YBoA0JgwbCq+JLS4Fcr6fKmxgxRBAFGHptpQM2XNhQzYUN1WMfmCFCK4sovrQUd52Hrgc7sBPWqMupPg3vTC/x9YOz26mKwpfOWUBjb5Qzqkvomapw9zPvkE6bZLOjr+dgtIL9xciTFsIUKPrxLxxv9A0O8cTKhVBaQEekbfSQAzRI7UqiOgaHDB4LQ4Omffui1NYGD7L04Vu7to0//3k7//APZ1JcPP5AV5gCK2GiujU526AkSZJ0QsnQSZJOPBk6HWNCCJ57bjdTp4aYObP4RG/OMKmUgaapJ3RIRltbDK/XQUtLhK9//QUAvv3tV6mvL+QHP7iUV17ZS39/mhtumD+sl8eaNS089VQjixZV8KtfraOrK8ENN8znttuWn6hdkY6xgVAlfntL/rH+VAY9pFN6zfjrLh1oaB2ox7bt5Q/vNHL/5j3834fPH9bjJ7EpRqxA4HbrBINuhC3ovK89//tYJkvatHino48nd+S28WOLZvDE9ma64ineaOni3KkVQC4wOljR86Hb9OTOFnb25mr3pIzhIc2B4ZV/QQDfvIJhxdDdUz2km1JYURPVpxF+uQ8rapJpHR6MjUX1qhRdXAJAwaIA/gUF+aGEZtzETtiggKfBi7fBh6IqxBcNr491Wlkh86cVU/ahCgoWBVmb7Oe553aTyRx+byXVpaI4FIQhMGMmjsKRw/tSu5MIU+BpGH8h+MNh9OZCJ61Aw4pZ9D7RnQ/3VI+K5tXyyzirXLjrPPjm+FG08W2LsAX9L/WSeCeGs8pNyVWlaN7hH9e2LejsTOT/39YWO3A1R2zTpi5+//t3WL16D5Crg/HVr55Da2uUqVNDI3rCpZtTJLcnyPZksbM2zY1hAkEXwaCL3b1R3FO9LL6sJhfIkRsKaNsCp6pi9BoIMxfW6QXykkSSJEmaWAMBk6IgQydJOkHkFd4EaW2N8v3vv84118xhxYoaHnpoC0uWVNLdneRrX1uN06mxevXHCYfTeDwOQiH3Qdf36qvNrF/fzs03n87GjZ289NJe/u7vluLzOYcV2LVtMSyMOZBtCx56aAsLF1YwY0YRjz22nalTQ9TVhfjIRx7A73fym998IL++QOD4FeZtaYlw3XUP4vU6KCoa7A0QjWbYsKGDCy74Xf4xVVW44Yb5AMRiGf75n58nGs3w5JM788vce+8mrr12DlOnho7bPkjHl39BAPW8AI6dTrAE5jw3U7/eMO5g4cDi1DC8DtRLTbkQKWtabO0OM7esMP+7PS938Y/ff5LiYi/33/9hYi/0YSdthBAYts2Xn32Ljlhy2Lor/B7Om1bJI1uaWNvWnQ+d4OBFzwe2SQjBC7vb8o/Hs8aw5UYLrxRVGRFmDfzfSlkoKOgBB+5VXiIv9o+5DQPKr6scdnxHW/+BRgu/hs4EOBB0ZzKH39NJURS0Ah2zz8AaJXQywgb9q3uBXL2loktKRrT50cxSaKWtXC8rBHqhg0xrGsWhoHo1FFXBTtkYCYt33unAoavo2zQU4LQzK/DN9aO6VFSnihkx0EMO3LXDe0LFN0bpeqgDM2KiKArpvWni66P4P1DCi++2snJWFaEpPsLJDOeWlDLF66XM7ca7PsODjeuoOaOYMy+oy+2nEPzv/24kGHTz/vfPAnI9or73vdfp7U3xvvfN5IorZuDzDQ5/tCybO//1ZaJdKao8HmKmyZ8f285zz+0mlTL4p386m4985LTB7d0aI/pqOP//fW0xmvaGsYRg1oxi9jWGYUuYsojGQ2/uIuh0YKVsTNvmsrOm4nJo+7cV8Kp4y9z45vlxVrhQVCX399WdxVHqHFedMUmSJEkaamghcRk6SdKJIUOnIf7zP99g9eo9LFtWzZVXzuDdd7v40Ifm4vU6MAwLh2Nkj6Bs1mLLlm7++Z+fp7MzziuvNHPllTN44omdlJX58sMdslmLD15zH6Wmk9Kgh//vG+cQKHChejWc5YMX0489tp1Nm7r405+2AvDkEzuJ9qXJ2Lmb2+JiL3/49Tvc9Q/nEelL8/s/bWL+WRUkEgbt0SQf+vBc5s0spT+Wpm5mIY88so277nqdwkIPn/nMEr773dfw+Zxcc81s+vpS9PWluPDC/0FVFXRdZcmSSlIpg4byEJ+9egFKNjc9e7QnTVdzjLqZhWhOFTttowd1tAI9N8RFU1D0/f/2/5yJGagGKCoojtyNluJQUBwKO3b38ZPfvU02a5HNWoTD6YO2zQ9+sIZXX20mGs2wbdtgPRxVVbjqqpns2RPm3Xc7+djH/sTnP7+MK66YQUHBiZnZ6r3saG7mx6uvL5UfshOxzXGv/w9/2MhPfvIW//mfl7Fs2eCwMk+9F9Wn8srWdlojgz1HntrZMix0enlLG4lwllTK5H9+9w7+lxNEo1ke2dpEy5DnDTUl4CPkdvLIlibWt/WStSz6U1mShsn//O5N/q7iLKqqCoDhx071aygelW3NfcPWPacsNOI1DmfGPpHN1R5SHAplH6jAU+cdc7jc0fYgO1g45XLlPnoOZ3jd0ONjGzYCgRUbue/J7YPHK9OcxgwPD6biG6P87ltvsX53N7eeOReXphF1mMz7xDQ89V7Se1PYWQFC4JntY/3mThYvrkTTFNK7U/S/1EukM8nLa1vpjCZZOa2SgMuBN+jknu49nDm/ikK/ix9t2IKqKNT7/SwtLqZ8rx8rMnJ7Sz5QhrMsd676/V1raX6mg6XVpfSlMswoDhJ0O7HTNu/8YhfCzLBxk8HcuWU0NvaxtHiw92ykObffTVtTNNg+VIfKvpYIz/xmK2nLwtgQx5NV2LcnyhzbBbjofaiT+x7toazMR0yzyCZNytxu3uergGnQ0FBEV1eCSDRDzDDoTKXY8Ic9pN+JseL0KaQyJhuebGbGtCJmX1SFe4aXr3zur+xpi5CyLLw7NGYFg8wJBNi0sYsqwwkGgAZovPnGPlLCImmYFDldOHSVxYsqSO9NoTgVnKVOrKSF2W9SdHkp7ikH/7JGkiRJkg4kezpJ0on3ng+dhBCYYZPmbf1seaKVqZqb1le6+clLnaQtizXPN9Mwr5gHH9rKpz+9mE9/ejHptMmf/rSV55/fw86tvSSzgzcSKtD0WjdnlZTQncqwb3M/pxcVUeRyMdXvJ+jI3fy885vd1NUGEUBWE6R1gakJnnt0Cx5N48N1dXg0jUKnE0eZSsQwSLyZJKak+Ex9Azsez9WRuaSiEpoAnDTgpPN/2+gk1zNig6aQNiw+UV9P2rLYc18rH6qtRVUUxGsx/rahAZ+uoykKWdvGsG2MbhsbFyWGRusLXRQXeRFCsO7tdlIpg85tEYqLvRQXe/B6hvcwsIWgvz9FYaGHcDjN5s3dTKkuoLYuSGdngkDAhcfjYNeuPjo64izO+siGQiRME0+Bg898dDF1lQGErpDKGnT2Jpm9sJQf/vItXnipibffakNVFEpcuRu0f/3n85hXVwyGINyf5tc/exszY7H1j3uJvtjHtdefRnBx8KiHbAghEFYufDsWQ3VOFfGN0RH1hBSXQmhVEcWXlE7YsevvHwwoe3qSB1lyUHt7jLvvfgOAH/7wDb797YuoqPDz8st78Xh0Ht65g2dezQ0lCridxDMGmzr76Ygn8eo6j29v5sHNe3AU597zP/vRm8OKSR/oqtm1LKksoTbkx7Jt/E4H8azBPz3zJs3hOGgKrioXqz/UzM9/fiX1eOh5uItwd4qHtzSxpKqEZ/e0sr4l12Pn/Poqzp9WSbl/ZH2gw5mxz87uv/DaH9odOFzOSlhoPj1flP1Yvd9droGeTuMLzEZ9b+kKjkIHvtMK8o9FG+Mktg0vqJ1tS5NULdJpk8SWGKv/cyu/WLMZgLqQn6b+GJ2JFF8KG9TPK0b3Dx7Pvz65lx88vYGbLzqN5XOrsCImZsxk57ZedvdGeXJHCw9s3kOpz80VM2t5en0jq9fsRfUMfkHRk8mwNRLBX+LmnJIp+SF2IpMLANMtaZxlLlLJLO/+uYVFFcX07q8J9tDmPdy0ZCaWLehJ5t73O9rDdMZSZFImrckkexJxulJpan0+6gsKmOrz0fNumAK/i+4dYa6aMgUAozGFARRoOqFiN0VFHjo64iSTBvGeNArgAiKxVK7A/LQANTNDFBV76OxIoKqwZ084t1MtJjujHQghcCgqa7d3cueGd1E1lZaWSH7fk5bF+r4+NvT1sTASodzjIWoY9GYyKEA4m6Uzndsvt6ZR7nZjVOismFZOoitLaP/7FV3BihggQydJkiTpMAkhazpJ0ommiIG/xEksGo0SDAaJRCIEAkf2rftYbNvmpa9upLszMeYJKGGaudDHMJg2JYTPUInGMzi13LAJSwPLp1A3v5h3/9pOiTk8jCkt9aJpKvF4FluHDS29+HUdFSh2uXCooxdadbl0HLqKz+cgc0BvIEsItkQiBB0Ogk4nZaU+/JpOb28Sw7Zx6dohT6her4MF88tJJg2cLo2uzgSZrEV/f4ps1qIlmaR2YRGppMHa9e30Z7N4NQ2HppGxLE6rK2bhrFIsYN5ppby5Zh/bNncza0Yx/d0pusJJEqaJqig4VRWnpuFz6SgW+HUdh6pSWOhm7txSVEUZc+iEQBCPZ0kkDHRNxeXWUFUVn3f4ce7rT7F7dz/JZG4IUm1tkFnnVuQLLQtLkGlLIyywE7mbR7G/o4WikKvJooCdsjGjJmbUzBVgFgIxcPOjKWgeFdWjoTgVNLdG8NxCVMepUyw3Gs3gdutkMiYOh4bbfehQY6Cgdm8yze6+GEurDxjS5ICKG6ooWHT0hY4/+tE/sX17rrdbIODi+ec/Mez3P/jBGv7yl93853cu5Z0nmuneHiWWyNKTTKMrCrYQmPuHxJlCYNp2rsZMxOKCaZUsqS5lbzhGNGOgAE/taOHdzj6cmsYnl88iWOAiksjiMRQMW+DWNbKWRV8yg6pCazTJJxbNwOccfH/+5I3NPD9kmJyjxJEPJuyUBf0WNUEf7bEUKWNkEPMfF5/B7NLQiMf1kH5YwwszbWl6n+hGL9Qp+1DluJ5zLPz4x3/ld797Z1x12A4s1t6bTBPNZKkJ+EkYJhUfrKB4egF9m6P89ZE9OHSVhGLRToaPLJ6Oa6qHv/3Zarq6EsSakmDl/paLPC4uqK+iLuTHqWu4NI0FU4oInV2EVqjTsa6fjes78q+r6yregJO/bmpnbXM3+6IJrNE+PvcHiqMpL/dz221n0dmZILY1xhXV1dgCfLUemtZ0s2NHLwhY19ZDJJNl7b5uir1uFlUUs6svyt5wHEr0fE+/hoYibrnldPr70/z2txtoa4sx3e/nytoplNcFePndVuq9uYL4bWaainkhZswvYfnZNbkSVLagcXc/zz3RSLo3y6IlFezuidKZSvOP/98KAgEXwha5c2LE4Id3vEZ7cwynqubP7ZqisDkcpj+bC2G9Xgf/8i8r8fudPP10I1OnhrjnnvXDAsaCAhcPPPBhursTaJpKW1uM119vyffwVYAyt5tvfulc5p5WhrvWc0wLkh/La4wT7VTeN0mSpPH47ndf4/77N/PpTy/moYe2Eg6nuf/+D1NfX3joJ0uSNKbDucZ4z/d0UlWVbW39GBmLqGHwoY+eRk9nkpY9YWZPLWbrXzvw6TqlAQ/plIkdtclg43c7qasLUljowe3WUMjd9DUsn046bVJQ76N1ZxinolHREMBZ5sJR4sBV7aZiQzv//u+v0NeXojDgosbvoyrkIxM1KClwUzs1xN7+GJ+4+TR8xS40r0ayM8MrzzfRvyfOFK+X/359GyKg8s//fCahkJuKCj9Y0LQ3THmlH4em8sZLzezc1stZC6po3N6L26Vz+uJKnv3LLlRdZcXl0wmVe0DLFeWtNQXCsNm+oZt/v+tVdsVi0NSUP1YXXjiN0lIfzc0R3v7rPt7Z0M8fNzSOPKjNzQc95oWFHv7jX89nWsqFnbBRBNhZG82johXouaEzRi7oMeMmpG0K/C4K/LkbOcWloqiAluvpMHDzXusPMPWyCja808mj927B6dCo3ZsitiGK0ZMl055BpI9yanNLYMUtrPjgsCB3vQfP1PHP7DTZRCJpvvnNlzj//KksWFDOxz72MH6/k2TSoLq6gN/85gP80z89h8ul8+1vXzSihpiwBd1/6sQWgjteWEdLJMEnl8zk/bPrBhcyoON3baSb05S+v/yotre/P5X/ORrN8LWvrebf/u18NE0lGs3wyH1bOK+8nLfvys34VohOoVtnVmGAdNriwJzd6dRwuXRKcFDkzL3Hqgq8RDMRBHDZzBouqK8i6HFSUutnen0RVtIk3TQYApv7h786tNGL8n9kfj2xjEHKtnAFdFKqTdw0KaryseHVNrAEu/tGLwRdE/Qzq2T0sO5wZ+zL93RyntiQdGB43aF6Og28twasa+vh2y+/Q23Qx3ULcrNctv42Qf28Ytrb42SzFq+3d/FGTw8lLhfnVpaTbo0w0/QS0OFdkcTncuB1OvjwvGnDgsH17T08srWJFYXT2ROOsfetHq6srsapqrSnUmzo66OxN0q0PTViOwc4NZUFFcV45/n54MfnUVjoRtdVnnxyJ088sZPOzjhf/vJfAPDpOsGZNoqiULjdTV9PCtOyWdPSxe7+KOV+D6Yt6IyneKaxFUVRuLShmm2OJLOXlvHZzy5l+vSi/Gtfe+0cHntsO3fc8RI/3rINsSX3+OmnV/LTn1457BveoU6rqOS0FWMHkIqqoPk0NJ/G+/5hAT/5yZus39xNIpELmaZODXHeinqqqwuoqQmyZEllvkbfihU1AFx11Ux27uxl2rRCTNNG0xRKSryUlOTOmzNnFrNq1VS6uxO88kozAuhMp3nwjV18++ppY26bJEmSJB3KaD2dLOso7wckSTos7/nQCaD8mgp0XWXWrGJmzSoZ9rvwbI2Xn9jDZ26cS39HgldfbSbpElzzwZnUTAuh6ApmxMDoNTD6DMywQeEsH94GH2WMfnO9bFk1jz76N4csAj6Uv87L5TfNzf9/JfNGLqTDtOmDqf25l0zj3EtyF+xzV1XlH79+4ekHfa15FVNI/hyIgcOhUVMTYPnyKdx667J8AeBwOM2Pf/xXHn10+5jr+eQnFxEIuCgq8rBq1VT27g3T359mwYLycRcsF0LA/nxHmDZCgOY5+Gx7y0/z8x//9ybF/S7qOkOobw0eY3V/sKV5NLSAjuLY/zsbQIDI3ZDrQR09qO9/fP8QJltgGwI7ZWGnbPqezfW2sTMn9wfX7373Dmteaebll/dy3nl1pFIGqVSut9iOHb3cfPPjbN7cBcCLLzZxwQXDbwJTu5OYEZPnd7fl6w/9dt0O6kJ+FlYMn7Fxz5Pt/Pa1bXz8ttPp6Ijzla+s5tOfXsyHPpR7b2cyJr/73TssWVLJggXl3H33GmbMKOaii+r53OeeoL09TjQ6fNa1Z5/dxVVXzWRhWSGv/28jn505E3V/L6tOI0PDueXU1ASoLSlgZ1M/f3l2N8lYFiNjseC0Ms6/pCHfCy6+IRf8FLicvLynDZ/TycziAGfWlFE0vQC9QCdwVgitQKP9ntZ8+KiP0VsRAA2qagJ81D2L7nCSsjIfyaTBrJnFuBWVbd4a/m/jLta39xB0O7l4+hQ64knWtfXwodPqWVBZhObXh9VdOtJ6SwM1nU50z7yB4XWHquk08N4CSBkmP39zK6Zt0xSO81ZrN7UhP6VeN2vW7WN3Ms62aJR9ydyQy/ZUis07enCpKkuKiiBYyGUVVZR63ZT7PWQtm919UfaEYxS6XTy5owXDstn8v1FUb277frp9O1efP4NtHXFmnF/J0nQ1rnczBN1OGooCPLJtLwsrimgJJ+hLpTljShlzSkNU3FhFwZLBoHD+/HL+3/9bzre//SqPPZY7ZyZMk/ZUikqPh1f3dLBmXxfTVS+3njkXt65jC8HecJxoJsuUgA+/04FL16i+tXbMWlkXXjiNp57aiaoqlJX5mDWrhA9+cA66PjHtPXduKT/72ZVs2dLN7be/SGWln8997owRn5sHKivzUVZ28OLzAN/61gV84QtPs2FDrofZyy/v5b/+ay2KonDeeXWHfB1JkiRJOpBlDYZOmpb7PJz843wk6dTynh9eJ41u374oXV0JFi8++BAcIQSbNnXxm99soKGhiI985DRWr97NrFklLFxYfsJmG/r1r9fzp1+/y1U1UzhzVS0Ny8pwVblyMyBNVG2hF3pJNSYJnBXCP7/g0E+YhGxbcOO1D3J5QQVJ06QtmSRsGDTF47QmR9ZLKivzcdZZU6io8FNR4SeTMenbGqXzpR4e3rIX0x4ewE0vDvChudNYUFGEx6HzbGMrW3vCTGkI0ZNNs765h4hhsHhxBQ6Hxptv5oZReTwOzj23lmef3QVARYWfjo7BWj3BoJtf/vIqbr31SXp6kixaVMFFlMD+UMUqUOkstvjIzQuZMmXkOSObtVizpoXly2vyQSoMrx3UGU/xby+u44z6Mm770nJUr46rwoVnuje/7NBhXwfyLypAL3TkiucrCrYK0d40oUI3dtrGSlhkO9JkWjP5GfA64ylCbifdiTQlPjcBV25WsYKlgdzsaAq46jz4FxSgaocfJMQ3xYiuCeOu91B04Ym7gb/33k1873uvc8kl0/mP/7hwzOVi6yJ0/D43LPGet7fxxPYWyvweVk2r5P53d+eXcxQ7UL0aPp+TTMbENHPvgyKnkzq/nylFfuYVBLFjFnPLQjhH6ZGWNEz+2tLFo/F2OiNJrr9+HldfPZv6+sL8eSzZmGDfTw/ekxMYMxjKZi1uvvnPNDdHSKdNdAvOO6MWK6By3UdOI/BIbFjdqgMd7nDKk5EQgnTa5GMfe5i9e8P5x7/xjfPyM/BNtFP5GuNU3jdJkqTx+Pd/f5mHH97G3/3dUh56aCtdXQl+//trmDOn9ERvmiSd1OTwOumoVVcHqK4+9AWqoijMn1/OD35waf6x664bpRfWcXbjjQvYurWbX73QSNsMhTsWN0z4awwMUbKzJ1dPJ9sWPPNMI08+uZOOjgTumI0eUAg4HASCQUIhNw6Hhsuj0xFOsKG5h42JCF2JFF1diXxPjfz6Mna+qPZZNWV87sy5/OGdRp5t3Meu3ijfeeUdPjCnjvfNrqPQ42JFTTmqUJnq8rB0RiFx02Rfd5K2ZJIKt5vOdJpUysgHTgAdHXE0TeXb374Qp1Ojri7ElCkB7rzzQj7zmT+zZ3MvzMgNNXrB6OHb37qUwsKRRbcHOJ0a5503dcTj/gUBfPNyhbUroiYPf3nWmAW1/QsCVN7EiALXB+uFdODlTXxTlPZ79qEoCk5NoyaYq79T4HIOW87oyaJ5c6dro9sguS2Bp86Ds8qNI6SjBfVxBbzC2P9t3wnu6TQQ9B1qeN1AkfQ9/TGe2NECwGfPmMO88kI8uk5dyM+zja0suqaOGz63CKdTo7s7idOZq2mXTBpMnRpC0xSEYbPnW42QGP17Fq9D5+IltXz0H89lx85eFi6sGNET1VPvRQ/qhwyGPPWjD7d1OjXuuef92LYgEsnQ3Z0YdtEbV70HDTIPdzjlyUhRFDweB//2b+fz+OM78rUJp04NndgNkyRJkk5Kg7PXyZ5OknSiyNBJOiU5HBpnnjmFF15oyg8Vm2iqc/gsVCeDxsY+/uVfnqexsS//2JKiIurrC/F4dDL1TqYWFWC0pBGGoL4uxNK5FWiqguGAjnSKvlSG7miKrnCKsG2QzBq0vdnL+TVVXDi9ClVRuOWMOVw3v55HtuzlsW17mVZYwK6+KBs7ejEsgeJVqQp6WTarglTSZLanCIdDpbs7iaNAZ1NLH+2RBP4aL+19CbKa4Ka/W8LKlXXD9mfhwgqmTy/C0WNRVVVAw+ml/M2HzzmqY6SoypjDlw40NKSyoiZa4PBmffPNLThkiKF6VYLn5AI1oytXm8yOWyQ2x0lszvX+0kM6ngYfjhIHjhLnmENQBwJS5RgWZR6P8Q6vGwh5XlnfDiIXai6qzA3Z/MCc3Hth6Zxypn51sPePz+ccfWWaSuVHqg4Z6vj8zjF7eCqqQum15UcVDGmaiqYxrKbRgCMJMk9Vc+eWMneu/BZakiRJOjoDoZOmKQx8PydrOknS8SVDJ+mU5fHk3t6p1PimZT9cyv7eIrZxcnxdsmtXH5/5zJ+JxTL4/U4uv7wBVVW4sKaKipiOd46P0P5wQ1gCK2FhRk0SG6Nk2jNoNkx1+pjq9EEQqBlctznLINM6vNZSyO3ik0tmct38erZ1h0mZFk/taOXymVM4/5OzWXBBNeUlPozuLNnOLNnODLWdGURWMK+hBCHI12YCUPdp9D7VjepRUd25wsZ6QOe/fngF8U0x1KYs3srjP6X64YRUoz33UCFG+XWVw8IGYebqT6V25eodGX1ZzLBJbO3gVPWqV8NR6sBR7ETzajhKnThLnAhjoKbTie0tM1hIfGToJGwxLMQrubqc9f/3CgDLa0bWyTuc3j8TEeoc62DoaINMSZIkSZIGjdbT6VAzfEuSNLFk6CSdsjye3MxUx6yn0/7eIuIkGV73ox/9lVgsw/z55dx996WEQrmAJvxaP8ktcVTXYO8YRVPQAzp6QMc9xY2dtcl2ZDDDBlbcws7YmFETK2piGwI94MAqtjF7Rx5rj0NnStDH6l1trJxawcfPnc2c62flb6JdVW5cVbltEaYg3ZLCTtkYfbkwShi5+kd23CITH71nzEC/HUfpGL1cJrHDDTEUXcFd68Fdmxs+aGdtUruSZNoyGL3ZXJskLTJ7LTJ7B2fYc1W7sPfP3niiZ68bHF43vD2H1tQaEFYMWjJJFE1hQcXgbG1HGvJMRKhzrIOhowkyJUmSJEkaNDCUTtMGZ6+ToZMkHV8ydJJOWW73se3ppJ5ENZ22b+/htddaUFWFO+5YlQ+cYHB4oOoeO4hQnWou5KgdvU6SnbERhk1iZ4LOP7TlZxwcUOrzcN38ehRFofK66jFvzhVdwTNtZD0c27AxurO5wCttYaVsrLiJGTEx+wwQgAquivHNijjZHE2IoTpVfHP8+Obk6kHZho3ZZ5DtzGBGTKyERWZfmsy+wZ5oJ7qm08Df5tCaTmMVZl+3qxs7ZVNfFKCw2E1gaRDfvIKjCnkmItSRwZAkSZIkTX4DQ+kURYZOknSiyNBJOmUNDK9Lp4/R8LqToKZTX1+Ke+/dxP33bwbg4ovrqakJDlvGTucSooOFToeiulRwqQQWBylYGKD32W7CL/YPOzZ6SKfs2oojGn6kOtR8b6gDWWkLozuL6tbQg44j3ocTbaJCDNWh4ix34SwfDODMiEFyR4LUriR22sZZcWJ7hA30dBqo6SRsQfefOvO/F0LkC6O/0ZJ7fGl1CXbCJvxSvxxuJkmSJEnSuAz0dFJVGTpJ0okiQyfplDUwvO5YhU7HsqeTlbIw+w3MiImjyDEsQDiULVu6eeSRbdxyy+l85zuv8fzzewAoL/fzxS+eNWL5gSFX6gQVl1ZUhZLLyii+pPS41KXR3Bpazdgz1UmgBx0EzghRsDQXOI5nprtjaaCQ+MDfZmp3Mj+kbk1LJ//5+iZuWTaHZdWlbGjPFb1fUTtYz6n74U588wpk8CRJkiRJh+HAuonvhS9xBno6ydBJkk4cGTpJp6xjXkjceXSFxK20hZ3MDUvLFYQ2MPuyGH0GdmowyFIcChU3VqNoY18UtLREWL++g8svb+DLX/4L7e0x/vSnrfnfL1hQzte/vpLS0pE9aexxDK87EnL40eRzosOmAQOFxAd6OlnRwb/RX63dTtay+fGazcwuDWHaNtUBHzWBwfeSGTZJ7U7K95ckSZIkjdNodRP1oE7ptaf27Kij9XSyrMkdOr0Xw0Hp1CZDJ+mUNVjTaWIKiT/77C5aWiJ86lOLc+PCB4bXZe38cKB33ungf/93I2ecUU1ra5SPfnQ+5eX+/DqslEW2I0N6b4pUYzJXi2g0CmgFOlbURBgCO2ujebRRF7Vtwf/7f8/Q1BTmjjteGvH7FStq+NGPLh9zv/Kh0wT1dJKkQzlweJ0W0FnX1sMP12winhn8e93WHQbg6jl1IwKzoUGVJEmSJEljG6tuohkxaf/NPipv4pQNngZ6Namqgrb/C1whDj90Ol5B0Hs1HJRObTJ0kk5ZA8PrTNPGNG10/chClXvuWcejj26nrS0GwLnn1jFzZvHgDGB2btY1xaHw05++xbp17bz84l6meL1UCifvu2QmRm8WoyeL2T/8Rll1qygOBa1Ax1HoQC92IHwq//q9l6moLuBj5VMRGTtXG2mM0OmZZxppagoPe8zrdeBy6ZSWern11jPG3DdhCsT+nlqqe/T1S9JEO3B4nafey593t+QDp5DbyZzSEH6Xgwvqq5hVEhqxDi0gP74kSZIk6VCG1k00LJst3f3MKQnh1Aev+07lYetDQ6eBL7AOt6fT8QqC3svhoHRqk1ft0ilroKcT5Ho7FRQc/sxmPT1Jfv7ztcMe6+1NAsUougIqudApa9MXSeNoNvhEfT0BpxOXqlLRqRF9Izzs+XqRA2eFC+8ML86ywW2ybcEvfrGW3/3unfz48xtvm4bIjF03avv2Hr73vTUATJtWSDDoorq6gNtuW04wOHrh7aHsgSnr1cHC6JJ0rA0Mr7NtgWXZCAE7jXj+959dNodlU8rGfL4eyn3DKEmSJEnSwQ2tm/j7d3by+LZmLppezefOnJtf5lQetn60PZ2OVxB04KQqozmVw0Hp1CZDJ+mU5XCoqKqCbQvSafOIQqeXXmrK/+zxOEilDMLhNJCrj6M4VUTaJrU7ReOTrZxbVobf76S42MuWXT10WxkW1HtwFDpwlDhxljnH7FH04otN/PrX64c9ZioCFfK9kYb69a/X8/Ofr0UIwWmnlfFf/3XVsKBtPIYOrZss9X6kU99ATyeATMaisbEPS4fiqX7uuewc7Kh10OeXXlMuL7gkSZIkaRyGDkd/fFszAH/ZtW9Y6HTgcqcKYQuyfVnspIXRkck/Pt6eTgcGQW+1dlNe4KE2OFg6Y6KCoKHhYHM4zp0vb+C6+dNZNa0yv4wZNolvilEgeztJJxkZOkmnLEVR8HgcJBLZIy4m/sILTQD8wz+cybZtPTz77K586AS5GeystM3uJ9po2tZHzDBwzvSTnOLiF0/tYGmwig9feOa4XuuRR7aNeMzAxsVgODQgHs/yq1+tQwjBypV13H77qsMOnIw+g/7nczODyXpO0vHkcAwNnUzWrm0DYNl5NdT/6wxSu5MkNsWIro1iJwYDKD2kU3qNrGkgSZIkSeM13uHoRzNsfTIWvh4YEhfdGMPoNeh7sodUSww7bY179rqhQdCOngh3vrwBgD/dcHF+mYFeYiJjYyVt/IsLUI+gpMfQ0O93G3bQGU/xozWbOG9qxbAvhnse60JRFPzzCw77NSbCZGxrafKToZN0SvN4dBKJbL52zHhFIml6e1O8+WauO+2qVVPp6MgN/xkaOllJC4Fgz55+NveHCdcq3HnzOWzY0IEAIpHMaKsfoa0txpo1rQA8/PB13Hzz43R3J8hYNi7UEcPrXnqpiWzWYtq0Qr7//UsO2UtJmIL03hTZzgyqV8OKmiR3JmD/alWvrOckHT+qquBwaBiGRSpl8uc/7wDgrLOm5Gc99Db4KHl/ubywkSRJkqSj4Kn3ogf1YfWIDnQ0w9Ynut7RRIQaQ4fEDQylUwAMgdFjkGhMwEWHXs/QIGhHbyT/c9a0htXEMvsN4u/EQEC6JUXpB8oPOuv0aIaGfrEhk6rsDceZWjgYMJlhg9jbEXxz/eN6jYkMiWSRc+lIydBJOqUNFBM/nBnsenqSXH/9Q/T3pwBYurSK2togoVCuRtLQ0Mld7aZjYz87eiK80N/FM/d+DI/HQTCYG8oXjR46dHrzzX3cccdLCCFYvnwKNTVBgkHX/tDJAlTEkNApFsvwwANbALjkkvoxAyfbsBGGILkjQWJTDDs1si6Us9KFHtDxzDj1xvBLk5vLlQud3v/+/wMgGHRz2WUNw5YZCKAkSZIkSToyiqpQem35qHWJBhzpsPWJrnc0EaGGsAWd97Xn/2/vD500VUHdf83c/2of4mZxyH0eGgQljcFtao8nqQsN6WmkkJ+R2uw1yHZkcFUfurbqUJ56L6pPxYpbdMRS+cdfb+4cFjphgRkxyHZlcFUe/DUmMiSaqLYWtkBk7RM+gVF/f4r+/jT19YUndDveK2ToJJ3SPJ7cW3y04XXZrMUdd7zE3Lml3HDDfIQQbNrUxfe+tyYfOAF87GMLAEYNnew5bh54cA9P7N3L1dfOyYdcgcD4Qqe33trH5z73RP7/n/vcGcOen/uAc2Bncp9kQgj+/u+fYvPmLpxOjcsvn5F/rrAFmZY0qT1JjF4Ds2940Kb6Ndy1HkTWRtEUPA1eXFWH94EoSRPF6Rx+sXHDDfPweh0naGskSZIk6dTlXxCg/BMC7lPAGrymdBQ6jnjY+oH1joQQWEKgq4NDyw6n3tGhQo2KTwgKFgUPuZ6+53qwk4NftEb39xrShsxeZ8StcRVOH9pLrCOWzD/eGh0MnfSQjuYffkudbk2PK3Qa0QtpYQH/898biGcHr+G3dIdHPs8QZFoPHjodSUiUaUsTeT2Ms9xJYFkoX35jIouc9z3XQ2ZfmuCKQnyz/WMul06bvPDCHi64YFp+ApqJdMstj7N7dz/33/9hGTwdBzJ0kk5pA3WORuvp9NJLTTz9dCNPP93I6tW76epK0t4ey/9+3rwyZs0qZsWKGmBk6HTnna/w0ENb86/zN38zL//cgZnjkkkD07TRxxjb/eSTO/M/f/zjC5kzpxQ4IHTSB2evW7++g82bu1hQUsiXblqGr9Gge20nVsLCTln5b1mGcpQ58c3157rTHmZXX0k6VoaGTp/+9GI++clFJ25jJEmSJOkUZ0914apy5eqEWoLCT1VSMi90xEOthtY7AvjB6++ysaOP7156JuV+DzD+WfEODDW6EymCLuewIWwd/9MGKBQsGjsgE7Yg/FJf/v9t0QTN4TiKojC3tJC/7BoccjeewumKquBfEiD8Qh8d8cEvpNuiifzPzloXPU93Y/UbqF4N1aWSbk4RPDM0bLuSjQmSOxMYfQZCCMywidGaGTZZ0B+27uKhd3YfsFO57R06skFxKCQ2xxC2wD+vAM2nDQuwFK9K5/0dB9230UKi2NoIZr+B2W8gbCg8rwgY3tbxjMGv3t7GkqoSVk4dXuT8UG1tZ2wyzbn7qMgr/TiKHMNm8h7q+99/nYcf3sZbb7XxjW+cd9B9OZAZyd336cHRv8zs60uxe3c/kJvISYZOx54MnaRT2kDoNFpNpzfeaM3//M47uQ86r9fB8uVT+MAHZufDpgGDoVOGzs44Dz+cK/zt8zm5666Lh52w/H5n/udoNENRkWfE62ezVr5Q+S9/+T6WLBk8cQ+ETomMATr54XUPPbiFS6uquHj2FEJRlVQ0OWydikPBO9uHs9SFs9KFoimySLg0KfX1DV68feYzp6Np8n0qSZIkvXcNBBOpxty1nafBi7fBN2G1DHt6cusduC5MF6pHte6hoU3WsnijpQvLFjy9s4VPLJ6Z/11iU+yQodPQUKOxN8KXn32LFbVl/OPZCwYXEtDxu30o6tjDuFK7k8PKSby8Nxe8LKosIuh2ouYqO2ELMa7C6fGNUcIv5EKszqGh05BeT8mNgwGUtX/23UxLGleVi9DZRcQ3Rum8r31Y76vRGJbNc1sH700+MKcOTVGYVRLCsG2cWi6A04IarloPZo9BYmOMVGMS7wwPvU/2jFm3a3tPhKb+GBdNr0Lb3xPtwJDIjBhkO7P556R2JwmelevtZEVNuhMpfrhmE1u7wgC83NTBgooiQu7B0OhQQV6mffgIkNTu5Jih08B91mOPbT+s0MkIG7kA0xJ4ZvoIrSwcUYpk/frB4ZfRfUmynRkcJc4J/3LesmyeeWYXJSVeli2rntB1n2xk6CSd0oYOrzMMC01TUVUFIUS+cPeSJZXMm1fG3LmlnHtu7ZhdOIf2dHrwwS3YtmDJkkr+67+uGnEyU1WFggIXsVgmHzr19aXw+Rw4HBrr1rXz4INbiMezlJb6WLSoYtjzB0KnWNoAX66n047tPZjvJlhcWERVVQGeGV70oAO90IHm09C8Gqrn6C4gJOl4yWaHzEp3BLO8SJIkSdKpYrRgov+5XtCh8MJiii8pPerru97e4V9U9venqak59HC1sQwNbZr641j7Z4RbvbuN6xdMz4cksbejlLz/4DWjhoYVT+xoQQjBa3s7mVPawmlloWH1kw42jOvA0GNNcxcA59TlrrPz1+tOZdTC6UN7C6l+ja79va/Spkl/ajAwaQ7HR/Q+GsaG7gc7ib8bI7U9OfoyQ6QMkwc27SaazrJyWiWfWDSDoMvJ5u5+0qZFVzzFlGBuKFr0dBfFK0MEIoLIG2EyrWliayNjrrs/lSGWyaIAzza2snJqJT5nrgeQGTby+x1bFwXAVePGSlqYvQa9T3fjmuIm05ZmQ3svfYkMqgK1QT/n11cRTmeHhU7JxiSOUieuaveo7ZPZl+vlpPo07IRFuilF4MzQiONoGNaw/yeTxrhKMAghiL4VwYoZCEMQ3xBBdSoUnBHMzyjY0RHnpz99C7emcW1NDTM6nLkZAV0q/nl+vHP8aJ6jqzf15pv7+O0964g0p4jE0vQaWR557G8oLx97OOHhMnqyZNrSpPak0IM6/kUBHKHJW6ZChk7SKW2gxtLatW1873uvIwTccsvprFhRQ1dXAqdT48c/vnxcY4UHQqfe3mR+WN31188b8wMnEMiFTn19Kf74x3f505+2omkqLpdGMjk43O/zn1+GesCJOV8TKpmFYsjEDR78zmYWFxZRWuplylUVssCydEoY6I0oSZJ0skkmDZ5/fg8XXVQvz2XSEQmH03zt1meYF/VxccMoPSFM6H+ml/CLfVTcUHVUM4QN9HQaMLR+6ZEYKHxtJ2x2DpnZLZ4xeL25i1XTcj34rYPUTxro3RV+bXBIXHdisHbqr9Zuo7LAy0+uWpG/3j6wh87QoMiMDYZOvck0LZHc0LqlVSUADFxue+aM7EE2WtHtAW1DRxYosKc/xl2vbuSqWbU4NZXqgA+HqvJ0Ywv9qSyXNkyh0OOEcQROfakMO3siuHSND8yp45KGKRR6XKBBxrS4Z+02LptZw9S6EOtLk/zHN1+huNjLP/3TCtwhlYI1CTyMHpL0pdKsb+sl4HZS6M3dW+zoiRByO1FVlW33bKfp7gSzpxahZwS9fSm6OxQ++IHZ0GdgdGUxurJYtk2J382nls4CIOR2Ek5n6U2kqSrw4tQ0FF3BjBj0Pd2Do8xJyZVloAEWWAmTbGeW1K4kAoGr2kVsXRQraRJ9I4yj2IlnujdXTsSGHU29qEC5x0NnKsXKlb/h3/7t/GG1bA9kxky67msnuT2BMAeHLGZaO4mujRA4I0gGm9vvfJnilMZl9fUEHA5i8QymKtAzNrG3o8TWR3EUO3FWuvAvLEA7jILnwhJsfLaVl+/ZyjmeEGppIZRC2rJY8187uOT6WehBPTdk0hZofh294PA+O4QQRNeE6X6rn0g0g9er43LppJpSBJeHcNd6hoVmBw1HjyP5CSmd0gZ6Oj377K78Y7/85du8/PJegIP2bDrQwIx0kBsyV1lZwMqVdQddft8++NrXVuc/6C3LJpm08fudNDQUce21c7jiipEn0IKC3PC8SCqLQPDm8y3Umx4cusqcD9bIwEk6ZRzNt6ySJEkn0o9+9FcefHALa9e2cfvtq0705hyxDRs68HodzJxZfEzWb9uCF19sYsmSyvwXeFLOA/dv5pUXmnnFEuiawoyiICGPE79zeI8FkRFHNBscwMaNnfz61+vzPfwH9Penx3jG+CiqQmBpkPBL/WzrCQMQdDuJpLM8s7MlHzrB6MOuRuvdlbWsYQEWQHssSWs0QU1wsJfIwPpGDYr2zyS3vr0XgBnFAQpcuetqVVFABe/8IbPBMXbR7QGPb28G4Oy6cpZWlfDUzlZ6k2nue3c3502rpD+dZUd3mIe2NAGwsaOPhqIAuqYyozhAwOXErWu4dI2ht/+GZRPOZFHVXM2pyoCXYk/ufqP4ylL6XgvTv8ni/vZm/ry6I18upLc3yZe//BfsjI3WZ7G4qoQSr4ugy0lDce79sXZfN6/s7SSSzrKitoz3z55K0jAxbJuuRBoLgcvSKdWc9LbEMWybp9va2L4xygMv7OCi5XVU6G4Cls6+rhjRWJKZvgCLK3PniSd2NPPIlr1EM1n+6ZyFXPSxmThKXKR2JjC6svQ80YUwxbCJjcyYSbYzQ3LL4JDETGtnbjbt/eGLQLCvvZ+bGhoodDoJZ7N0p9N0PNhOrxLKzbo904fm10jvSpJqSiFMQXpPkvTeke9pYQrSu1MIQ7CrLcyqYCkEIRhw0dIb56HmZr63eQvvO30qKyrKcGcVXC066jsKxmqB4VXwehxEs1kMHQpLPbg8OsVlXopLvSiqghkxMbqzJPYmaX6znSleLyUlXqqmBkinTHZs7iG7K8X63+7K99hSFAXDsGnNJjFiJsUeFxlVENFNsoqN7tVZvrKW6qkBVLeKoikYEYNtz7Sxb10f8USW9lSKvYkENV4vU3w+vG/so6jIgzPgwB1yottgqjD/s9PHfG8fLzJ0kk5pAz2dhspmLTZu7ERVFW65Zem413VgOPXhD889aB2ageCopyeJoijcddfFzJlTQnd3kunTC0fdtgEDhcj7Y2m6u5NkYga6rjL/oilUrSgd9zZL0mR1882n89vfbuD22w+vOKQkSdJk8eCDWwB4/PEdfPKTi6irC06Kb5THY2DI//btvXzmM3/G49F59NG/IRRyT/g+PPzwVu6881WWLavmZz+7ckLXPRmFw2m6uxNUVwcOOiRICMFTD+/Izyb34zWbAXDpGlfOquF9s+oIup3DnnM4s8FBLvD77rdexRcWnF5YRNayCDgcNMZidHUlDr2CQ/Ce5udXP3ub1/Z2UlXg5eYz5rCtO0zQ7aQ5HKN2/7C4A+snjRXyvNLUgWHlQiiHpuZ/3tLVnw+dYpksyec7qdiVJPp6eORGiVyY83JTrm7PosrBMFVTFRxFDnbv7GPD6la6OuPYliD8bA+FqpOaoA+HNthLxBaCJ7Y382JTO+U+D7ecMQe/08HS6lLaY0ni2VwIlLUsnt/TzpSgj3llhWzvifBMYy7kc6gqQbeTq2bVUhnw0p/MsKGjl/ZYkrRhMacsRH1RAVfMrM2FYvu5azysumY6v3tsE7Yt8qMk5s8vp6LCx759MdLdGbZ3d7OmeeyZ5SoLvPzt0tmE3C5sIdjeE+at1m76axQScYMV86tIZE2ak0mWn1WP9WozjY19/OmZHcPWo6oKX/90LXqbjhW1qC8M0JfKgKbw/a1bOHP+fOrrC3FWu+h/rofEvhSWaeN261hCkM1YiJYM+yIJepJpFlQUoSgKwszNvm1Xu2gLJ2hri2GaNoVOJyXFXvSISsjpBAP6tkfxeZ3EN8dIJk0sy8bl0nA6NCJ7kyRTBg5Vwe9yjjgOPc1xXm1qx+dwcMX7ZlC9oIi7HlhL787csMk/v93En2miwOFgitfLuWVlBBwj/3776R98P2kq2pA6UJYliGaybE/H+Mp/LKKw2odtCV74ehftG/upTibx6Tq2yP3Nh5yD29kdzr2XFCAXO5q8uWUHDl1F1VScTo10ysAwbWwheL6rg0yZTltfjLf6e1kYLGReKEQiOXzyLN2tMU/Un/DPJkUIMcp8V5NLNBolGAwSiUQIBI68W6n03vOzn73Fr3+9HoBFiyq46aZFfOELT6MoCp/5zBJuvvn0w1rf1VffS2trlGDQzaOP/s2wguEH+vKXn2P16j0A/O3fLuGznx1/wLVmTQuf//xTLJpRxvuDlSSTBlOnhjj9izNxFI39mpJ0MjEMC4fj6MbNS9LROt7XGD/96U+566676OjoYOHChfz4xz9m2bJlYy7/wAMP8PWvf52mpiZmzJjBd77zHa644opxvdax3rdk0mDjxk6WLq06otpsb7zRSldXgksvnT4hU2LbtuDxx3fw0ENbOf30Sm655fRjMtW2bQs2beriU596dNjj118/j3/8xxUT+lpmzMSKWzhKHKiOkcdYCEFvb4riYs+4byp27OjlU596FKdTIx7PYtuDtwKzZpXws59dkf/ya0A6nauNWVAwetHf0USjaf7y2C4euGcjxS4XEcPgmz+6kGlziyf8BkgIgTDFqMfoeNm1q4/vf38Nb745GKZUVhZQXx9i+vQipk4NDRuG2d4e4z+/swarz+TihmqebdwHQuQnIlYUhRW1ZXx0QQPRjIFh2RR7XRSfW4Qj5KCjO0FHXwK9yMGic6upbQiN+DL0iUe3s/ePrRS5XJSWePH5nWQyFu3tMdpSKdQqBw3nlDPntDK6W+O4UUnFsphpG69Tp687icepU17uxx90UlDixhF0oHpUTNPm9796h7WPNDG/rJBphQXMKA7S1B+jN5XBrWkUe13sTSbwnhVk9qwS3LqGyNpEnunBh46+v6i1EIJ3O/t4vbmLtGkyuyTEBdOr2NYdoS2aoNTvwevQEAIShonqVtEMCDgdqIqCrqn4nTpBl5P+dIbHtjYTzWRx6xofnldPoceF4lLo81ps3NaNXx9yXrAHZ4nWFAWfQ8+XvUhkTbZ2h+lPZVhRWz4swBoqY5oYlsDvGgwpUoZJJJ0rzB03TPZF4ySzZj6oAnBqGouriqkNDq/1o/k1pn1zBoqqEI3m6sNCLviprPTn/36SjQl23L2LaMagL5WhORwnnh0MHUp9Hs6uLccx5H2h+TXKPlwxZo+5bNZizZoW9uwJY1k2pmnT35/m0kuns3hx5bDhjDu7Itzx89dp3RclEHDh9zvp6UkyuyDATF8BcdNkbbiPcDpDojVNyOEgvP+YnFlTxpSAL9/+fdksG8wIDlVlblGIC1dN5bKPzcHqzvKb327gtfX78GgaC6uKqXV6yWYtutJptkQiJA2TjuYYnfEkAoWGogA1QR8hjxNlf9+yLd39NJLkgkvr+d73Lsm/bjSaIZ02Wb16D7t29eX3QbcVymwnRtYiHElTGfLhQSMZyyJMQSphoIjceyZqGHSkUrQmkxDSuONbF7BgQXn+mAoheOGFJh5/fAfRaAZVVTBNm9mlQaq9PoqrffQYGdyGgiejoNnQ25GkszWOW9PwaBoOVSVmGOxLJ6k+u4SP3rI4X45FCEFnZ4INGzp4/NHteC2VnrYkliIonernOz+85JhM2HM41xgydJJOad/97mvcf3/um6Mf/ehyVqyoobGxj1DITUnJyAKCh/Lqq828804HN920+JAF7W688WG2bu0G4OWXbxpXAbwBmzd38YlPPIJH07h11iwcuso51zVQfmnZYW+zJEmSNLbjeY1x33338fGPf5xf/OIXnHnmmfzwhz/kgQceYPv27ZSVjTy/v/7666xcuZI777yTq666ij/+8Y985zvfYd26dcybN++Qr3es9+0vjzfy87v+isfnYOGSChwujRlzirng0nrcPseI3hi2bbPl7S7+8tAO2nZHiUezIARpy0L36pyxtIpzz8zNHBuJZNB1laJCD2bGJBbPEirz4ijQ0Lw6pVP86B4t/xrJpME3b3+Rda/uY4rXy1S/n6qgj4YpIXSXijvoJKsItKBOZUMAWwjWresgmzGpmxpE3X/z6w84mT6zGM2jojhVVIeam+1LgZYd/bz2RBM9WyIoCRsVsIGkaZLY/++Ka2cxZV4hW3f1Ul7iQ7MhkzLp607i9jiYUhegoNBFsNiDN+BE1RUUh5qfNSkVy/LWc810bYrgSyn40YhEMiSTBhkPFNR6UYIaCgpdbXH27YvS0RZnal2I0lIvqq6yrztG/Zxilp5djbfIRUmlD5dLRwhBOmHyL198jvDeBBUeD35dx61puLTcsJ+kaaIWaOhBB1nbpqEmRLQrxZ7dYRJZg5kziymv8KO6VUqq/FQ1BCivK0Dz6/l9iHWm2PLMPtrW9JJNDh9W5XRohCq89NlZkpaJx63T15/G49IpL/Vh2jbvbO2iN5ZmSn2QxWdVESzzUFsfIljoRlEARaGzNcb2N7vo3xtHjduUOF2oJnREknTHUtTUB/EXu9ndE0XTFLo7ElSU+gj63WAJ+iNp0pZFWa2fGYtK8Re7KSr34A24QM0Nydn2TjdvrN7LjvXdaEKh0OHEpaiEyjz09aeIpg3mLy7Hoah0tcfZuyuMBphCoDs14qksWdsmnM3Sm8mQsiwylkXGtrGEQAUqdTdXVVSzaloVpm2joBBOZ9jWHaYjniKZNakr9ONxDIYkqkOBUWbZMhFYTkgKC0MIBAJ/WsWn69RODTL7vCrslEV7W4ytr3cMCxvHy+HQcO4P9jJZC9O0wRZM8fgo8+V6ycUzWZ5u3Edd0A8KqE5lsJgS5EMehVzooirkesLs79VU4fdQHfChKgpZy2JLV5iMabGrL8qGjl5SXkF1oZ8Zii8X1oyRX2qKwqyGYooK3SgOBdWb+7vZ2xyhuTmCoQvcPgcia5PpzRJNZwmns6QME5/TQdDlJOhxoioKNUEfpd6J7wU4lopPVFOw6NDnbGELmu5oHHPWugOpPpVpt8/IF9WeCHv3hrn++oeGTRAzwOXSyWRM7IyN0ZUd5dnDlc8M8qV/PpsLLpiG0zn4peSbb+7jC194Ol9gPOhwoOgKroCT7u4EZtzE6jMJup3DCr4fyFHs4Lf3XjssEDpSpmnT1hYbtt+KArW1wQn7QjWZNOjoiJNMGvnek1OnhoYdmxNJhk6StN+TT+7kG994gYICF88///Hj2rXwsce2c8cdL/F3f7eUT396yWE9t6UlwjXX3IcKfG7WLGY1FHPGbbPQg5N3VgJJkqST0fG8xjjzzDM544wz+MlPfgLkQpiamho+//nP85WvfGXE8tdddx2JRILHH388/9hZZ53FokWL+MUvfnHI1zvW+/bcPVuJvR4me8BMQ4qi5Hp0aGAgMISNioKSFdjGwacNHy9VVfB4HFhKrmdIOm1iZi1cmkZhkYd4PEsmM74bsRHrVhR0XcV1QHHwRCI74ka9oaEIt0unozM+olDzobhdOo79Nw82AlPYGElrxGskTBOffuQ9tmxyx0tTQNi5IUOKolBTE0BTFUpKfXR1JUgksvT2pjjcWwNVVRh6eWXb5NdhC0FPJkPWCS5LoVh3DhtCdKSvY1kTf/uiKAr7s0eE4IhCmUDAxezZJbhdOoZpkUwYJJIGyaRBKmXmj4sg1wbFhR6CcRVl5P06iaxBcyROPGuiKgq2LehPZ+h1mBiaIOB3Mr06hIhYWDFzzO0NVXhYedtcvBWe/GPpSJZ9a3vZ8XIHos8kGslg6ZAWNjgUVIdCfyyNw6OTzBgkkyZm2sKn6xQ6nbhUNTc0SoN5Z1dSPyVI9M0IVjS3I2+39fDYzr1U1QQ447QKlLSgvStO1rZJJQzC3SnC6Sxp0yJrWTg1Db9T54L6ak6vLhm2/aZl0xZL0BxJoM72cPanZlLcp/Dc9zexuz9Gwsj1Aqvwewm4nEQyWZyayulVJdRfUoF3ph/FqeQDZMWponhVHL7c31SyMcG+nzZjC8Huvigt0QTm/veX36kzt6xwxDDH8QqdX0T4hb5DL3jAc0rfP/5Q5FD1qIaqvKn6qIrRj6WrK0FnZxzITbwkBHi9DoqKPLS3x0htjhN5uJv2eJKQ20VvMs0brV0MnGocqkJtqIBrvrKQkrNG702WTBq5sNCwUFWF+vpcqZJs1mLnqx1kH+rF73TQEUuyqy9KSyRBwhj+GXD6R6fx4VsWTvj+v1cdzjWGrOkkndIuvrgeXVdZvnzKcR/L+r73zeSss6ZQVnb4Rb9LS30UFORmv3sm2sm1N58hAydJkqSTWDab5e233+arX/1q/jFVVbnoootYs2bNqM9Zs2YNt91227DHLr30Uh555JFRl89kMmQyg9/yRqPRo9/wgzhnVR3RYIjujgTdnQlsU9DfncLMWqRSg0M89tf1zQ0bUhU8JU4cIQduv4NFCytIRrL0dSbYsqWHpvYImqYSKHBimDaRWAYU8HqdiLSFT9NxqxouWyWRyA57jQKvk1lzSiidXoBW7uTtXV3sbOknEcvS0hgm4HQSQkdkcnc6wf3DQVL7i/MiBLFIFsUSud4/aRXXkPouphA4gjrFcwOcdk4VybRBVUUBImMzJWbw4jN72P1uL2UOF36fk0TaQGi5G3iHW8M0bJLRLFigCbDSAm2UYMx0gHeKm1RAoVdkmTarlFm1RTSt66F/VwwtA8mMSVGJB1Qor/DT1h7H4VDJpk08mk64I4mZsHCggC3AFgzkGqpTZeYZZdQvKUEPOFBcKlOcCijQ0xpnw2ttqCmBrij0xNM4/Tpz55ehWrB9ew+xSBY7Y5Hsz2InLAp0B/oB11gR3cSY4uCSG2bT1BzhjDOqsG3BKy/upWtnhBLdjdelE4mk8focZLIWsXgWFYWqEh8VxT4at/SSCmdRsgIrY6NYAlXJDZYxhUAUqLhKnSghnX2xBJZDoaEyhJWy2LaxCw8aNYV+kimDQJEbw7LJmBZCgcKgG10odDfHMaMmDqGgC7CGhD9CBV+Jm4qGAIpTxdQEikelvyeF1+PASJi07omQNi2Ky72gKSy7aBpup44wBcIShLI2ZtjAjJrYWYHIDA9dFZeK6lCIvjlyynuf08Gc0kIMy0JVFDRVRQ/pTP16w4hehFbWpnVnmN7mOMr+GcAUG7yFLqafU4Z2QM8Id9DJ9AsrmX5hJbZhY9o2Dqd20GvlTMakqSmcH+pVUODK1fDZv+7iy8vyw67eH6jluvpzRq09lWxM0PqTvfSns7THkli2QFMV6gsLhvXoGqBrKnUVQZZ9YRYFi4L5dSyuKmFx1WBAZdo28ayBW9dw7w9p/QsDh5x8x1PvRQ/qmBGThuIgDcWHnuBE9ebSyaFF0If93qdR/pHcEDbPVM+IgumjUdwq5ddV5PdxvPwLAlTexJgz7wHoIZ3Sa8qPSeAEUFbmG/N+p7o6QDKlIdwRAvvDu3K/h7llhSOW9ZaMPdGA1+tg9uySEY87nRpzV1XR9HISM2JSUeClomDkaBY9pDP1Mw3j3SVpgsnQSTqlORwal1xyYir2K4pyRIET5KaR/7//+yBtbTFmziw+aO0oSZIkafLr6enBsizKy4d/g11eXs62bdtGfU5HR8eoy3d0dIy6/J133sk3v/nNidngcfBM9+KZ7mXoFgoh6O1OsmdnP5m4gWKR68WhQEGpm4Z5JXh8w79EKQKmAAsY3w2BbQtaWyLsa4pipS0QoOsqp80rw1/qzg/zuujMQi46zH0yDIvu7iSxWIbOzkSuy4sFioCCIhcLF1WMemPuBa5esnjcrxOJpNm9u59YJINik3sNW1Bc5mX2orJRX2PmwsOfSMQ2bXraEhhZC1QFRYPyKQVj1veornRTfcbIG7sBs5gy7P+madPVFUcYIp8s6h6NsnJffh9mDrlRvPqDc8a97fOZlv85lTKGzbbm8zlG1J06Wv39KZKR/UGmolBc7sHtntgv/IQtEIbIDS9TyQ35UhR8p/np+EMbIjuyt9LQwtal15SPGuRoTpW604qoO63osLdJdag4OfRwK5dLZ9assd8biqqMa3blgZCnSFEo8hy8RpjqVQmtLKLo4pJh+z00KBqgqyoh9+D69JCOp/7QpTQUVaH02vJx9xYCKL+uEt+8ApKNCZI7Exj7Z2hzFDnwzvDhbfDlt9e/IDBi2YEeb4qijPqcwzXwGgOhn+rf34MybqEFcsfhSNc9EUZrrwONt71GM542HOtvRzo+ZOgkSZNURYWfigr/oReUJEmSJOCrX/3qsJ5R0WiUmpqa47oNiqJQUuaj5Ai/dBkPVVWorQtRWxea8HU7HBpVVQVAwUFvsI9WMOhm8eLKQy94lFRdpay24NALHiFdV6mqOvalLzwex0Fn/Z0IhYUeCgs9h17wKCiqguJScnXChvAvCDB9XgG9z3bTv7oPzOHh09CeMyc7RVUo+2DFIUOeostKRoRNQ9cxkSHDmL2FBrpp7ndgjyHfTD++mYe+VldUZdzLHqnxhn4nwvEIhcZqw2Pdy0saHxk6SZIkSZIkHWMlJSVomkZn5/CprTs7O6moqBj1ORUVFYe1vMvlwuUa/+xikiRNHoqqUHJZGcWXlJJsTJBqzNUI8zR4j6oXzGQ0EBCMNuxsvAHbRIcMB/YW0gI67qke0k2p/P9PdI+hk9nxCIVGa0PZZpODDJ0kSZIkSZKOMafTyemnn87q1au5+uqrgVwh8dWrV/P3f//3oz5n+fLlrF69mi9+8Yv5x5577jmWL19+HLZYkqQT4Xj0ipkMhg47O9KAbaJDhtF6C03W3kMno+MRCk3mHl/vZSdF6DQw7vVYF8SUJEmSJOm9ZeDa4nhM5nvbbbfxiU98gqVLl7Js2TJ++MMfkkgkuOmmmwD4+Mc/TnV1NXfeeScAX/jCFzjvvPP4/ve/z5VXXsm9997L2rVr+eUvfzmu15PXT5IkTXoV4KzI1eeysInFY4e/jjKgTMHEOrLnS8eXbK9TwuFcP50UoVMslnszHu+6BJIkSZIkvTfEYjGCwcObNehwXXfddXR3d/ONb3yDjo4OFi1axNNPP50vFt7c3IyqDtZ6WbFiBX/84x/5l3/5F772ta8xY8YMHnnkEebNmzeu15PXT5IkSZIkHUvjuX5SxPH4au8o2bZNW1sbBQUFx23a+4Himy0tLQQCsvDYiSTbYvKQbTE+8jhNHrItJo/J2hZCCGKxGFVVVcMCn1PBibh+gsnb1u9Fsi0mD9kW4yOP0+Qh22JymKztcDjXTydFTydVVZkyZcqhFzwGAoHApGrc9zLZFpOHbIvxkcdp8pBtMXlMxrY41j2cTpQTef0Ek7Ot36tkW0wesi3GRx6nyUO2xeQwGdthvNdPp9ZXepIkSZIkSZIkSZIkSdKkIEMnSZIkSZIkSZIkSZIkacLJ0GkMLpeLf/3Xf8Xlcp3oTXnPk20xeci2GB95nCYP2RaTh2yL9w7Z1pOHbIvJQ7bF+MjjNHnItpgcToV2OCkKiUuSJEmSJEmSJEmSJEknF9nTSZIkSZIkSZIkSZIkSZpwMnSSJEmSJEmSJEmSJEmSJpwMnSRJkiRJkiRJkiRJkqQJd9KHTm+++SbLly9n5cqVXH/99RiGwQMPPMCKFSu48MILaW1tBeCWW25hxYoVnHXWWTz33HMAJBIJrr32Ws455xy++93vjrr+L3/5y5x77rnceOONGIYBwMc//nFKS0v5yU9+MupzRnutV155hdNOO42KioqJPgSTxsnSFr/97W+ZMWMGq1at4qMf/ehEH4ZJ4WRpi9bWVi666CLOO+887r777ok+DId0vI9TLBbjggsuYOXKlVxwwQXs3bt3xHO2bdvGypUrWbFiBatXrwbk+WMytYU8f0yetjjR54+T3cnyOSHPf5OnLeT5b/K0xYk+/50snxPy/DF52kKePyZPW5yQ84c4ybW1tYlkMimEEOIrX/mKeOCBB8RZZ50lMpmMePXVV8XNN98shBBi165dQggh+vr6xBlnnCGEEOKHP/yh+O///m8hhBCXXnqpaG1tHbbuDRs2iI9+9KNCCCG+9a1viT/+8Y9CCCH27dsnfvOb34gf//jHo27TaK8VDodFIpEQp59++oTt+2RzsrTFwZY/VZwsbXHrrbeKv/zlL0IIId73vveJffv2TcwBGKfjfZxSqVR+H59++mlx6623jtima665RuzYsUNEIhGxYsUKIYQ8f0ymtpDnj8nTFif6/HGyO1k+J+T5b/K0hTz/TZ62ONHnv5Plc0KePyZPW8jzx+RpixNx/jjpezpVVlbi8XgAcDqdbN++nTlz5uB0Ojn77LPZuHEjAPX19UBuykFFUQB4/fXXueSSSwC4+OKLWbNmzbB1D/39ZZddxmuvvQZAVVXVQbdptNcKBoN4vd6j3t/J7GRpC4Cf/exnnHvuudx7771Htc+T1cnSFrt27WLRokUALFiwgNdff/2o9vtwHe/j5Ha788fJ6XSiqiNPwW1tbcyYMYNAIEBRURE9PT3y/DGJ2gLk+WOytMWJPn+c7E6Wzwl5/ps8bQHy/DdZ2uJEn/9Ols8Jef6YPG0B8vwxWdriRJw/TvrQacDevXt59tlnOeeccwgEAvnHLcsattxXv/pVPv/5zwPQ39+fXzYYDNLX1zds2UP9/lCGvtZ7yWRvi6uvvppNmzbx5JNP8oMf/ID29vbD28GTyGRvi7lz5/L8889jmiYvvvgi/f39h7eDE+R4H6dsNsvtt98+6vnBtu38z0dyfE92k70t5Plj8rTFZDl/nOwm++fEe8lkbwt5/ps8bTFZzn+T/XPivWSyt4U8f0yetjgR549TInSKRqPceOON/Pa3v6W0tJRoNJr/naZp+Z9//etfY5omH/vYxwAIhUL5ZSORCEVFRfzgBz9g1apV3HXXXaP+fjR9fX2sWrWKVatW0d3dPeprvVecDG0RCoVQVZWCggJWrVrF1q1bJ/5ATAInQ1t89atf5b777uOKK66gpqbmhIy5PxHH6eabb+Zzn/scM2bMGHGchn5LcbDjeyo6GdpCnj8mT1tMhvPHye5k+Jx4rzgZ2kKe/yZPW0yG89/J8DnxXnEytIU8f0yetjgh549jPoDvGDMMQ1x++eX5cYnZbDY/dvK1117Lj5187rnnxBVXXCEMw8g/9+677xb33HOPEEKIyy67TLS0tAxb9/r168WNN94ohBDi3//93/Njr4U4+LjU0V5rwKk8pvhkaYtIJCKEEMI0TbFy5UqxZ8+eo9zzyedkaYsBpmmKa6+9VkSj0aPY68N3Io7T7bffLr75zW+OuU1XX321aGxsFNFoND/2eoA8f5z4tpDnj8nTFgNO1PnjZHeyfU7I89+Jbwt5/ps8bTFAXj8NktdPk7st5Plj8rTFgON5/jjpQ6f/+Z//EUVFReK8884T5513nrj33nvFvffeK5YvXy7OP/980dzcLIQQor6+XixZskScd9554rLLLhNCCBGLxcQHPvABcfbZZ4s777xz1PV/6UtfEuecc4644YYbRCaTEULkCoPNnTtXzJo1S3zxi18c8ZzRXmvLli3iwgsvFAUFBeLCCy8U69atOxaH44Q6Wdri9ttvF2eeeaZYtmyZuPvuu4/BkTjxTpa2eOqpp8SqVavE+eefL5588sljcSgO6ngfp+bmZqFpWv71vvKVr4x4zubNm8U555wjli9fLp599lkhhDx/TKa2kOePydMWJ/r8cbI7WT4n5Plv8rSFPP9NnrY40ee/k+VzQp4/Jk9byPPH5GmLE3H+UIQQ4tj3p5IkSZIkSZIkSZIkSZLeS06Jmk6SJEmSJEmSJEmSJEnS5CJDJ0mSJEmSJEmSJEmSJGnCydBJkiRJkiRJkiRJkiRJmnAydJIkSZIkSZIkSZIkSZImnAydJEmSJEmSJEmSJEmSpAknQydJkiRJkiRJkiRJkiRpwsnQSZIkSZIkSZIkSZIkSZpwMnSSJEmSJEmSJEmSJEmSJpwMnSRJkiRJkiRJkiRJkqQJJ0MnSZIkSZIkSZIkSZIkacLJ0EmSJEmSJEmSJEmSJEmacP8/AEqR8aWTRFQAAAAASUVORK5CYII=", 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", 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", 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", "text/plain": [ "
" ] @@ -340,7 +331,7 @@ "threshold = np.percentile(filtered_df['accumulated_anomaly_score'], 95)\n", "plt.figure(figsize=(12, 3))\n", "plt.plot(filtered_df['ts'], filtered_df['accumulated_anomaly_score'], label='Score', color='navy', alpha=0.8)\n", - "plt.axhline(y=threshold, color='red', linestyle='--', label=f'95% Threshold')\n", + "plt.axhline(y=threshold, color='red', linestyle='--', label='95% Threshold')\n", "plt.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", " filtered_df.loc[filtered_df['anomaly'] == 1, 'accumulated_anomaly_score'], \n", " color='orchid', label='Anomaly Detected', alpha=0.8)\n", @@ -350,6 +341,18 @@ "plt.legend(labels=['Score', '95% Threshold', 'Anomaly Detected'])\n", "plt.show()\n" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the figure above, we can see that even though some points fall below the 95% confidence interval, they are still flagged as anomalies because, in other series, a value at the same time step exceeded the threshold." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] } ], "metadata": { diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index b2f4b304..d1241b1f 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -1654,7 +1654,6 @@ " date_features_to_one_hot: Union[bool, list[str]],\n", " model: _Model,\n", " refit: bool,\n", - " validate_api_key: bool,\n", " num_partitions: Optional[int],\n", " ) -> DistributedDFType:\n", " import fugue.api as fa\n", @@ -1693,7 +1692,6 @@ " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", " refit=refit,\n", - " validate_api_key=validate_api_key,\n", " num_partitions=None, \n", " ),\n", " partition=partition_config,\n", @@ -1722,7 +1720,6 @@ " date_features_to_one_hot: Union[bool, list[str]] = False,\n", " model: _Model = 'timegpt-1',\n", " refit: bool = False,\n", - " validate_api_key: bool = False,\n", " num_partitions: Optional[_PositiveInt] = None,\n", " ) -> AnyDFType:\n", " \"\"\"\n", @@ -1819,7 +1816,6 @@ " date_features_to_one_hot=date_features_to_one_hot,\n", " model=model,\n", " refit=refit,\n", - " validate_api_key=validate_api_key,\n", " num_partitions=num_partitions,\n", " )\n", " if threshold_method == \"multivariate\" and num_partitions is not None and num_partitions > 1:\n", @@ -1837,7 +1833,7 @@ " id_col=id_col,\n", " time_col=time_col,\n", " target_col=target_col,\n", - " validate_api_key=validate_api_key,\n", + " validate_api_key=False,\n", " model=model,\n", " freq=freq,\n", " )\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index c5aeb526..96a270be 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -1593,7 +1593,6 @@ def _distributed_detect_anomalies_online( date_features_to_one_hot: Union[bool, list[str]], model: _Model, refit: bool, - validate_api_key: bool, num_partitions: Optional[int], ) -> DistributedDFType: import fugue.api as fa @@ -1632,7 +1631,6 @@ def _distributed_detect_anomalies_online( date_features_to_one_hot=date_features_to_one_hot, model=model, refit=refit, - validate_api_key=validate_api_key, num_partitions=None, ), partition=partition_config, @@ -1661,7 +1659,6 @@ def detect_anomalies_online( date_features_to_one_hot: Union[bool, list[str]] = False, model: _Model = "timegpt-1", refit: bool = False, - validate_api_key: bool = False, num_partitions: Optional[_PositiveInt] = None, ) -> AnyDFType: """ @@ -1758,7 +1755,6 @@ def detect_anomalies_online( date_features_to_one_hot=date_features_to_one_hot, model=model, refit=refit, - validate_api_key=validate_api_key, num_partitions=num_partitions, ) if ( @@ -1780,7 +1776,7 @@ def detect_anomalies_online( id_col=id_col, time_col=time_col, target_col=target_col, - validate_api_key=validate_api_key, + validate_api_key=False, model=model, freq=freq, ) From f681749c500e1bfb8edde8a0d7ac773d68c85bdb Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 16 Dec 2024 14:25:04 -0500 Subject: [PATCH 31/38] remove unnecessary import in SDk reference --- nbs/docs/reference/01_nixtla_client.ipynb | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/nbs/docs/reference/01_nixtla_client.ipynb b/nbs/docs/reference/01_nixtla_client.ipynb index a504279b..b7f9135a 100644 --- a/nbs/docs/reference/01_nixtla_client.ipynb +++ b/nbs/docs/reference/01_nixtla_client.ipynb @@ -592,7 +592,6 @@ ], "source": [ "#| echo: false\n", - "from nbdev.showdoc import show_doc\n", "show_doc(NixtlaClient.detect_anomalies, title_level=2)" ] }, @@ -735,7 +734,7 @@ ], "source": [ "#| echo: false\n", - "show_doc(NixtlaClient.detect_anomalies_realtime, title_level=2)" + "show_doc(NixtlaClient.detect_anomalies_online, title_level=2)" ] } ], From 7e40d4d650dced3218307ec850d3f0294b75ede6 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 16 Dec 2024 14:38:02 -0500 Subject: [PATCH 32/38] Add weights_x back to historical anomaly detection capabilities --- .../02_anomaly_exogenous.ipynb | 36 +++++++++++++++++-- .../03_anomaly_detection_date_features.ipynb | 34 +++++++++++++++++- 2 files changed, 67 insertions(+), 3 deletions(-) diff --git a/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb index 347c0a28..0c01bb9d 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb @@ -143,15 +143,16 @@ "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Inferred freq: H\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Querying model metadata...\n", "INFO:nixtla.nixtla_client:Using the following exogenous features: ['Exogenous1', 'Exogenous2', 'day_0', 'day_1', 'day_2', 'day_3', 'day_4', 'day_5', 'day_6']\n", "INFO:nixtla.nixtla_client:Calling Anomaly Detector Endpoint...\n" ] }, { "data": { - 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", "text/plain": [ - "
" + "
" ] }, "execution_count": null, @@ -175,6 +176,37 @@ "nixtla_client.plot(df, anomalies_df)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot weights of date features\n", + "nixtla_client.weights_x.plot.barh(x='features', y='weights')" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb index b1c3b496..36688a6f 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb @@ -131,13 +131,14 @@ "text": [ "INFO:nixtla.nixtla_client:Validating inputs...\n", "INFO:nixtla.nixtla_client:Preprocessing dataframes...\n", + "INFO:nixtla.nixtla_client:Querying model metadata...\n", "INFO:nixtla.nixtla_client:Using the following exogenous features: ['month_1.0', 'month_2.0', 'month_3.0', 'month_4.0', 'month_5.0', 'month_6.0', 'month_7.0', 'month_8.0', 'month_9.0', 'month_10.0', 'month_11.0', 'month_12.0', 'year_2007.0', 'year_2008.0', 'year_2009.0', 'year_2010.0', 'year_2011.0', 'year_2012.0', 'year_2013.0', 'year_2014.0', 'year_2015.0', 'year_2016.0']\n", "INFO:nixtla.nixtla_client:Calling Anomaly Detector Endpoint...\n" ] }, { "data": { - "image/png": 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" ] @@ -165,6 +166,37 @@ "nixtla_client.plot(df, anomalies_df_x)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": null, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot weights of date features\n", + "nixtla_client.weights_x.plot.barh(x='features', y='weights')" + ] + }, { "cell_type": "markdown", "metadata": {}, From 1619447e22cffef2fad536c88b3a11d222fbdb8b Mon Sep 17 00:00:00 2001 From: marcopeix Date: Mon, 16 Dec 2024 14:51:09 -0500 Subject: [PATCH 33/38] Enforce hierchicalforecast<1.0.0 --- settings.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/settings.ini b/settings.ini index ef45b380..b21531c9 100644 --- a/settings.ini +++ b/settings.ini @@ -16,7 +16,7 @@ custom_sidebar = True license = apache2 status = 4 requirements = annotated-types httpx[zstd] orjson pandas tenacity tqdm utilsforecast>=0.2.8 -dev_requirements = black datasetsforecast fire hierarchicalforecast jupyterlab nbdev neuralforecast numpy<2 plotly polars pre-commit pyreadr python-dotenv pyyaml setuptools<70 statsforecast tabulate +dev_requirements = black datasetsforecast fire hierarchicalforecast<1.0.0 jupyterlab nbdev neuralforecast numpy<2 plotly polars pre-commit pyreadr python-dotenv pyyaml setuptools<70 statsforecast tabulate distributed_requirements = fugue[dask,ray,spark]>=0.8.7 pandas<2.2 ray<2.6.3 plotting_requirements = utilsforecast[plotting] date_extra_requirements = holidays From cb74940c993085cbf32261394acb99b59f788221 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 17 Dec 2024 11:23:04 -0500 Subject: [PATCH 34/38] remove version condition on hierarchicalforecast --- settings.ini | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/settings.ini b/settings.ini index b21531c9..ef45b380 100644 --- a/settings.ini +++ b/settings.ini @@ -16,7 +16,7 @@ custom_sidebar = True license = apache2 status = 4 requirements = annotated-types httpx[zstd] orjson pandas tenacity tqdm utilsforecast>=0.2.8 -dev_requirements = black datasetsforecast fire hierarchicalforecast<1.0.0 jupyterlab nbdev neuralforecast numpy<2 plotly polars pre-commit pyreadr python-dotenv pyyaml setuptools<70 statsforecast tabulate +dev_requirements = black datasetsforecast fire hierarchicalforecast jupyterlab nbdev neuralforecast numpy<2 plotly polars pre-commit pyreadr python-dotenv pyyaml setuptools<70 statsforecast tabulate distributed_requirements = fugue[dask,ray,spark]>=0.8.7 pandas<2.2 ray<2.6.3 plotting_requirements = utilsforecast[plotting] date_extra_requirements = holidays From b4b768c9b2021d9317521c3b03242f4baa6b7459 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Tue, 17 Dec 2024 11:55:03 -0500 Subject: [PATCH 35/38] remove datasets from assets --- nbs/assets/SMD_test.csv | 36101 ----------------------------------- nbs/assets/machine-1-1.csv | 2777 --- 2 files changed, 38878 deletions(-) delete mode 100644 nbs/assets/SMD_test.csv delete mode 100644 nbs/assets/machine-1-1.csv diff --git a/nbs/assets/SMD_test.csv b/nbs/assets/SMD_test.csv deleted file mode 100644 index f235fe0a..00000000 --- a/nbs/assets/SMD_test.csv 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15:00:00,machine-1-1_y_0,0.086022,0.0,train -2020-01-20 16:00:00,machine-1-1_y_0,0.096774,0.0,train -2020-01-20 17:00:00,machine-1-1_y_0,0.086022,0.0,train -2020-01-20 18:00:00,machine-1-1_y_0,0.096774,0.0,train -2020-01-20 19:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-20 20:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-20 21:00:00,machine-1-1_y_0,0.182796,0.0,test -2020-01-20 22:00:00,machine-1-1_y_0,0.258065,0.0,test -2020-01-20 23:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-21 00:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-21 01:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-21 02:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-21 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-21 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-21 05:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-21 06:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-21 07:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 08:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-21 09:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-21 10:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-21 11:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-21 12:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-21 13:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-01-21 14:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 15:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-21 16:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-21 17:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 18:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 19:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 20:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-21 21:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-21 22:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-21 23:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-22 00:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-22 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-22 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-22 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-22 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-22 05:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-22 06:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-22 07:00:00,machine-1-1_y_0,0.215054,0.0,test -2020-01-22 08:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-01-22 09:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-22 10:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-22 11:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-22 12:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-22 13:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-22 14:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-22 15:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-22 16:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-22 17:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-22 18:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-22 19:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-22 20:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-22 21:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-22 22:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-22 23:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-23 00:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-23 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-23 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-23 03:00:00,machine-1-1_y_0,0.021505,0.0,test -2020-01-23 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-23 05:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-23 06:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-23 07:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-23 08:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-23 09:00:00,machine-1-1_y_0,0.268817,0.0,test -2020-01-23 10:00:00,machine-1-1_y_0,0.247312,0.0,test -2020-01-23 11:00:00,machine-1-1_y_0,0.322581,0.0,test -2020-01-23 12:00:00,machine-1-1_y_0,0.365591,0.0,test -2020-01-23 13:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-23 14:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-23 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21:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-25 22:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-25 23:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-26 00:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-26 01:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-26 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-26 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-26 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-26 05:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-26 06:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 07:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-26 08:00:00,machine-1-1_y_0,0.107527,0.0,test -2020-01-26 09:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 10:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 11:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 12:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-26 13:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 14:00:00,machine-1-1_y_0,0.107527,0.0,test -2020-01-26 15:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-26 16:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-26 17:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-26 18:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-26 19:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-26 20:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-26 21:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-01-26 22:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-26 23:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-27 00:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-27 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-27 02:00:00,machine-1-1_y_0,0.021505,0.0,test -2020-01-27 03:00:00,machine-1-1_y_0,0.021505,0.0,test -2020-01-27 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-27 05:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-27 06:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-27 07:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 08:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 09:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-27 10:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 11:00:00,machine-1-1_y_0,0.107527,0.0,test -2020-01-27 12:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-27 13:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-27 14:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-27 15:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 16:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 17:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-27 18:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 19:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 20:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-27 21:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-27 22:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-27 23:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-28 00:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-28 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-28 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-28 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-28 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-28 05:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-28 06:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-28 07:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-28 08:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-28 09:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-28 10:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-28 11:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-28 12:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-28 13:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-28 14:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-28 15:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-01-28 16:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-28 17:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-28 18:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-01-28 19:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-28 20:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-28 21:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-28 22:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-28 23:00:00,machine-1-1_y_0,0.064516,0.0,test -2020-01-29 00:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-29 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-29 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-29 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-29 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-29 05:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-29 06:00:00,machine-1-1_y_0,0.268817,0.0,test -2020-01-29 07:00:00,machine-1-1_y_0,0.344086,0.0,test -2020-01-29 08:00:00,machine-1-1_y_0,0.354839,0.0,test -2020-01-29 09:00:00,machine-1-1_y_0,0.473118,0.0,test -2020-01-29 10:00:00,machine-1-1_y_0,0.430108,0.0,test -2020-01-29 11:00:00,machine-1-1_y_0,0.473118,0.0,test -2020-01-29 12:00:00,machine-1-1_y_0,0.494624,0.0,test -2020-01-29 13:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-29 14:00:00,machine-1-1_y_0,0.107527,0.0,test -2020-01-29 15:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-29 16:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-29 17:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-29 18:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-29 19:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-29 20:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-01-29 21:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-29 22:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-29 23:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-30 00:00:00,machine-1-1_y_0,0.053763,0.0,test -2020-01-30 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-30 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-30 03:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-30 04:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-30 05:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-01-30 06:00:00,machine-1-1_y_0,0.365591,0.0,test -2020-01-30 07:00:00,machine-1-1_y_0,0.494624,0.0,test -2020-01-30 08:00:00,machine-1-1_y_0,0.505376,0.0,test -2020-01-30 09:00:00,machine-1-1_y_0,0.580645,0.0,test -2020-01-30 10:00:00,machine-1-1_y_0,0.333333,0.0,test -2020-01-30 11:00:00,machine-1-1_y_0,0.344086,0.0,test -2020-01-30 12:00:00,machine-1-1_y_0,0.215054,0.0,test -2020-01-30 13:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-30 14:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-30 15:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-30 16:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-30 17:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-30 18:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-01-30 19:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-30 20:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-30 21:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-30 22:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-30 23:00:00,machine-1-1_y_0,0.075269,0.0,test -2020-01-31 00:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-31 01:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-31 02:00:00,machine-1-1_y_0,0.032258,0.0,test -2020-01-31 03:00:00,machine-1-1_y_0,0.043011,0.0,test -2020-01-31 04:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-31 05:00:00,machine-1-1_y_0,0.258065,0.0,test -2020-01-31 06:00:00,machine-1-1_y_0,0.311828,0.0,test -2020-01-31 07:00:00,machine-1-1_y_0,0.55914,0.0,test -2020-01-31 08:00:00,machine-1-1_y_0,0.591398,0.0,test -2020-01-31 09:00:00,machine-1-1_y_0,0.516129,0.0,test -2020-01-31 10:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-31 11:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-31 12:00:00,machine-1-1_y_0,0.268817,0.0,test -2020-01-31 13:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-01-31 14:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-01-31 15:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-01-31 16:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-01-31 17:00:00,machine-1-1_y_0,0.107527,0.0,test -2020-01-31 18:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-01-31 19:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-01-31 20:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-01-31 21:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-01-31 22:00:00,machine-1-1_y_0,0.516129,1.0,test -2020-01-31 23:00:00,machine-1-1_y_0,0.548387,1.0,test -2020-02-01 00:00:00,machine-1-1_y_0,0.365591,1.0,test -2020-02-01 01:00:00,machine-1-1_y_0,0.677419,1.0,test -2020-02-01 02:00:00,machine-1-1_y_0,0.44086,1.0,test -2020-02-01 03:00:00,machine-1-1_y_0,0.655914,1.0,test -2020-02-01 04:00:00,machine-1-1_y_0,0.333333,0.0,test -2020-02-01 05:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-02-01 06:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-02-01 07:00:00,machine-1-1_y_0,0.215054,0.0,test -2020-02-01 08:00:00,machine-1-1_y_0,0.247312,0.0,test -2020-02-01 09:00:00,machine-1-1_y_0,0.27957,0.0,test -2020-02-01 10:00:00,machine-1-1_y_0,0.268817,0.0,test -2020-02-01 11:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-02-01 12:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-02-01 13:00:00,machine-1-1_y_0,0.516129,1.0,test -2020-02-01 14:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-02-01 15:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-02-01 16:00:00,machine-1-1_y_0,0.505376,1.0,test -2020-02-01 17:00:00,machine-1-1_y_0,0.569892,1.0,test -2020-02-01 18:00:00,machine-1-1_y_0,0.311828,1.0,test -2020-02-01 19:00:00,machine-1-1_y_0,0.612903,1.0,test -2020-02-01 20:00:00,machine-1-1_y_0,0.860215,1.0,test -2020-02-01 21:00:00,machine-1-1_y_0,0.989247,1.0,test -2020-02-01 22:00:00,machine-1-1_y_0,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_0,0.322581,0.0,test -2020-02-02 00:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-02-02 01:00:00,machine-1-1_y_0,0.215054,0.0,test -2020-02-02 02:00:00,machine-1-1_y_0,0.236559,0.0,test -2020-02-02 03:00:00,machine-1-1_y_0,0.247312,0.0,test -2020-02-02 04:00:00,machine-1-1_y_0,0.27957,0.0,test -2020-02-02 05:00:00,machine-1-1_y_0,0.225806,0.0,test -2020-02-02 06:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-02-02 07:00:00,machine-1-1_y_0,0.505376,1.0,test -2020-02-02 08:00:00,machine-1-1_y_0,0.505376,1.0,test -2020-02-02 09:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-02-02 10:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-02-02 11:00:00,machine-1-1_y_0,0.55914,1.0,test -2020-02-02 12:00:00,machine-1-1_y_0,0.569892,1.0,test -2020-02-02 13:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-02-02 14:00:00,machine-1-1_y_0,0.83871,1.0,test -2020-02-02 15:00:00,machine-1-1_y_0,0.591398,1.0,test -2020-02-02 16:00:00,machine-1-1_y_0,0.27957,0.0,test -2020-02-02 17:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-02-02 18:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-02-02 19:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-02-02 20:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-02-02 21:00:00,machine-1-1_y_0,0.096774,0.0,test -2020-02-02 22:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-02-02 23:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-02-03 00:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-02-03 01:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-02-03 02:00:00,machine-1-1_y_0,0.11828,0.0,test -2020-02-03 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21:00:00,machine-1-1_y_0,0.139785,0.0,test -2020-02-03 22:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-02-03 23:00:00,machine-1-1_y_0,0.16129,0.0,test -2020-02-04 00:00:00,machine-1-1_y_0,0.182796,0.0,test -2020-02-04 01:00:00,machine-1-1_y_0,0.204301,0.0,test -2020-02-04 02:00:00,machine-1-1_y_0,0.172043,0.0,test -2020-02-04 03:00:00,machine-1-1_y_0,0.129032,0.0,test -2020-02-04 04:00:00,machine-1-1_y_0,0.086022,0.0,test -2020-02-04 05:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-02-04 06:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-02-04 07:00:00,machine-1-1_y_0,0.483871,1.0,test -2020-02-04 08:00:00,machine-1-1_y_0,0.494624,1.0,test -2020-02-04 09:00:00,machine-1-1_y_0,0.537634,1.0,test -2020-02-04 10:00:00,machine-1-1_y_0,0.268817,1.0,test -2020-02-04 11:00:00,machine-1-1_y_0,0.451613,1.0,test -2020-02-04 12:00:00,machine-1-1_y_0,0.258065,0.0,test -2020-02-04 13:00:00,machine-1-1_y_0,0.225806,0.0,test -2020-02-04 14:00:00,machine-1-1_y_0,0.150538,0.0,test -2020-02-04 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-2020-01-22 13:00:00,machine-1-1_y_1,0.189619,0.0,test -2020-01-22 14:00:00,machine-1-1_y_1,0.136653,0.0,test -2020-01-22 15:00:00,machine-1-1_y_1,0.145127,0.0,test -2020-01-22 16:00:00,machine-1-1_y_1,0.210805,0.0,test -2020-01-22 17:00:00,machine-1-1_y_1,0.190678,0.0,test -2020-01-22 18:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-01-22 19:00:00,machine-1-1_y_1,0.209746,0.0,test -2020-01-22 20:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-22 21:00:00,machine-1-1_y_1,0.207627,0.0,test -2020-01-22 22:00:00,machine-1-1_y_1,0.132415,0.0,test -2020-01-22 23:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-01-23 00:00:00,machine-1-1_y_1,0.170551,0.0,test -2020-01-23 01:00:00,machine-1-1_y_1,0.128178,0.0,test -2020-01-23 02:00:00,machine-1-1_y_1,0.106992,0.0,test -2020-01-23 03:00:00,machine-1-1_y_1,0.082627,0.0,test -2020-01-23 04:00:00,machine-1-1_y_1,0.083686,0.0,test -2020-01-23 05:00:00,machine-1-1_y_1,0.129237,0.0,test -2020-01-23 06:00:00,machine-1-1_y_1,0.206568,0.0,test -2020-01-23 07:00:00,machine-1-1_y_1,0.166314,0.0,test -2020-01-23 08:00:00,machine-1-1_y_1,0.291314,0.0,test -2020-01-23 09:00:00,machine-1-1_y_1,0.348517,0.0,test -2020-01-23 10:00:00,machine-1-1_y_1,0.355932,0.0,test -2020-01-23 11:00:00,machine-1-1_y_1,0.362288,0.0,test -2020-01-23 12:00:00,machine-1-1_y_1,0.283898,0.0,test -2020-01-23 13:00:00,machine-1-1_y_1,0.237288,0.0,test -2020-01-23 14:00:00,machine-1-1_y_1,0.158898,0.0,test -2020-01-23 15:00:00,machine-1-1_y_1,0.1875,0.0,test -2020-01-23 16:00:00,machine-1-1_y_1,0.128178,0.0,test -2020-01-23 17:00:00,machine-1-1_y_1,0.231992,0.0,test -2020-01-23 18:00:00,machine-1-1_y_1,0.397246,0.0,test -2020-01-23 19:00:00,machine-1-1_y_1,0.213983,0.0,test -2020-01-23 20:00:00,machine-1-1_y_1,0.197034,0.0,test -2020-01-23 21:00:00,machine-1-1_y_1,0.355932,0.0,test -2020-01-23 22:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-01-23 23:00:00,machine-1-1_y_1,0.183263,0.0,test -2020-01-24 00:00:00,machine-1-1_y_1,0.136653,0.0,test -2020-01-24 01:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-01-24 02:00:00,machine-1-1_y_1,0.097458,0.0,test -2020-01-24 03:00:00,machine-1-1_y_1,0.098517,0.0,test -2020-01-24 04:00:00,machine-1-1_y_1,0.159958,0.0,test -2020-01-24 05:00:00,machine-1-1_y_1,0.087924,0.0,test -2020-01-24 06:00:00,machine-1-1_y_1,0.165254,0.0,test -2020-01-24 07:00:00,machine-1-1_y_1,0.145127,0.0,test -2020-01-24 08:00:00,machine-1-1_y_1,0.211864,0.0,test -2020-01-24 09:00:00,machine-1-1_y_1,0.242585,0.0,test -2020-01-24 10:00:00,machine-1-1_y_1,0.200212,0.0,test -2020-01-24 11:00:00,machine-1-1_y_1,0.216102,0.0,test -2020-01-24 12:00:00,machine-1-1_y_1,0.148305,0.0,test -2020-01-24 13:00:00,machine-1-1_y_1,0.10911,0.0,test -2020-01-24 14:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-01-24 15:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-24 16:00:00,machine-1-1_y_1,0.184322,0.0,test -2020-01-24 17:00:00,machine-1-1_y_1,0.200212,0.0,test -2020-01-24 18:00:00,machine-1-1_y_1,0.15572,0.0,test -2020-01-24 19:00:00,machine-1-1_y_1,0.184322,0.0,test -2020-01-24 20:00:00,machine-1-1_y_1,0.151483,0.0,test -2020-01-24 21:00:00,machine-1-1_y_1,0.188559,0.0,test -2020-01-24 22:00:00,machine-1-1_y_1,0.191737,0.0,test -2020-01-24 23:00:00,machine-1-1_y_1,0.148305,0.0,test -2020-01-25 00:00:00,machine-1-1_y_1,0.084746,0.0,test -2020-01-25 01:00:00,machine-1-1_y_1,0.092161,0.0,test -2020-01-25 02:00:00,machine-1-1_y_1,0.096398,0.0,test -2020-01-25 03:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-01-25 04:00:00,machine-1-1_y_1,0.079449,0.0,test -2020-01-25 05:00:00,machine-1-1_y_1,0.133475,0.0,test -2020-01-25 06:00:00,machine-1-1_y_1,0.205508,0.0,test -2020-01-25 07:00:00,machine-1-1_y_1,0.240466,0.0,test -2020-01-25 08:00:00,machine-1-1_y_1,0.361229,0.0,test -2020-01-25 09:00:00,machine-1-1_y_1,0.313559,0.0,test -2020-01-25 10:00:00,machine-1-1_y_1,0.327331,0.0,test -2020-01-25 11:00:00,machine-1-1_y_1,0.367585,0.0,test -2020-01-25 12:00:00,machine-1-1_y_1,0.291314,0.0,test -2020-01-25 13:00:00,machine-1-1_y_1,0.204449,0.0,test -2020-01-25 14:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-25 15:00:00,machine-1-1_y_1,0.173729,0.0,test -2020-01-25 16:00:00,machine-1-1_y_1,0.14089,0.0,test -2020-01-25 17:00:00,machine-1-1_y_1,0.202331,0.0,test -2020-01-25 18:00:00,machine-1-1_y_1,0.216102,0.0,test -2020-01-25 19:00:00,machine-1-1_y_1,0.242585,0.0,test -2020-01-25 20:00:00,machine-1-1_y_1,0.177966,0.0,test -2020-01-25 21:00:00,machine-1-1_y_1,0.227754,0.0,test -2020-01-25 22:00:00,machine-1-1_y_1,0.170551,0.0,test -2020-01-25 23:00:00,machine-1-1_y_1,0.115466,0.0,test -2020-01-26 00:00:00,machine-1-1_y_1,0.108051,0.0,test -2020-01-26 01:00:00,machine-1-1_y_1,0.083686,0.0,test -2020-01-26 02:00:00,machine-1-1_y_1,0.091102,0.0,test -2020-01-26 03:00:00,machine-1-1_y_1,0.052966,0.0,test -2020-01-26 04:00:00,machine-1-1_y_1,0.115466,0.0,test -2020-01-26 05:00:00,machine-1-1_y_1,0.087924,0.0,test -2020-01-26 06:00:00,machine-1-1_y_1,0.169492,0.0,test -2020-01-26 07:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-01-26 08:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-26 09:00:00,machine-1-1_y_1,0.209746,0.0,test -2020-01-26 10:00:00,machine-1-1_y_1,0.202331,0.0,test -2020-01-26 11:00:00,machine-1-1_y_1,0.169492,0.0,test -2020-01-26 12:00:00,machine-1-1_y_1,0.148305,0.0,test -2020-01-26 13:00:00,machine-1-1_y_1,0.154661,0.0,test -2020-01-26 14:00:00,machine-1-1_y_1,0.177966,0.0,test -2020-01-26 15:00:00,machine-1-1_y_1,0.190678,0.0,test -2020-01-26 16:00:00,machine-1-1_y_1,0.179025,0.0,test -2020-01-26 17:00:00,machine-1-1_y_1,0.231992,0.0,test -2020-01-26 18:00:00,machine-1-1_y_1,0.189619,0.0,test -2020-01-26 19:00:00,machine-1-1_y_1,0.143008,0.0,test -2020-01-26 20:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-01-26 21:00:00,machine-1-1_y_1,0.189619,0.0,test -2020-01-26 22:00:00,machine-1-1_y_1,0.150424,0.0,test -2020-01-26 23:00:00,machine-1-1_y_1,0.10911,0.0,test -2020-01-27 00:00:00,machine-1-1_y_1,0.113347,0.0,test -2020-01-27 01:00:00,machine-1-1_y_1,0.084746,0.0,test -2020-01-27 02:00:00,machine-1-1_y_1,0.075212,0.0,test -2020-01-27 03:00:00,machine-1-1_y_1,0.074153,0.0,test -2020-01-27 04:00:00,machine-1-1_y_1,0.079449,0.0,test -2020-01-27 05:00:00,machine-1-1_y_1,0.10911,0.0,test -2020-01-27 06:00:00,machine-1-1_y_1,0.123941,0.0,test -2020-01-27 07:00:00,machine-1-1_y_1,0.151483,0.0,test -2020-01-27 08:00:00,machine-1-1_y_1,0.190678,0.0,test -2020-01-27 09:00:00,machine-1-1_y_1,0.144068,0.0,test -2020-01-27 10:00:00,machine-1-1_y_1,0.120763,0.0,test -2020-01-27 11:00:00,machine-1-1_y_1,0.148305,0.0,test -2020-01-27 12:00:00,machine-1-1_y_1,0.181144,0.0,test -2020-01-27 13:00:00,machine-1-1_y_1,0.139831,0.0,test -2020-01-27 14:00:00,machine-1-1_y_1,0.144068,0.0,test -2020-01-27 15:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-27 16:00:00,machine-1-1_y_1,0.121822,0.0,test -2020-01-27 17:00:00,machine-1-1_y_1,0.137712,0.0,test -2020-01-27 18:00:00,machine-1-1_y_1,0.154661,0.0,test -2020-01-27 19:00:00,machine-1-1_y_1,0.172669,0.0,test -2020-01-27 20:00:00,machine-1-1_y_1,0.225636,0.0,test -2020-01-27 21:00:00,machine-1-1_y_1,0.194915,0.0,test -2020-01-27 22:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-01-27 23:00:00,machine-1-1_y_1,0.118644,0.0,test -2020-01-28 00:00:00,machine-1-1_y_1,0.157839,0.0,test -2020-01-28 01:00:00,machine-1-1_y_1,0.091102,0.0,test -2020-01-28 02:00:00,machine-1-1_y_1,0.081568,0.0,test -2020-01-28 03:00:00,machine-1-1_y_1,0.108051,0.0,test -2020-01-28 04:00:00,machine-1-1_y_1,0.104873,0.0,test -2020-01-28 05:00:00,machine-1-1_y_1,0.10911,0.0,test -2020-01-28 06:00:00,machine-1-1_y_1,0.152542,0.0,test -2020-01-28 07:00:00,machine-1-1_y_1,0.132415,0.0,test -2020-01-28 08:00:00,machine-1-1_y_1,0.098517,0.0,test -2020-01-28 09:00:00,machine-1-1_y_1,0.235169,0.0,test -2020-01-28 10:00:00,machine-1-1_y_1,0.119703,0.0,test -2020-01-28 11:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-01-28 12:00:00,machine-1-1_y_1,0.161017,0.0,test -2020-01-28 13:00:00,machine-1-1_y_1,0.117585,0.0,test -2020-01-28 14:00:00,machine-1-1_y_1,0.150424,0.0,test -2020-01-28 15:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-28 16:00:00,machine-1-1_y_1,0.1875,0.0,test -2020-01-28 17:00:00,machine-1-1_y_1,0.152542,0.0,test -2020-01-28 18:00:00,machine-1-1_y_1,0.206568,0.0,test -2020-01-28 19:00:00,machine-1-1_y_1,0.201271,0.0,test -2020-01-28 20:00:00,machine-1-1_y_1,0.23411,0.0,test -2020-01-28 21:00:00,machine-1-1_y_1,0.17161,0.0,test -2020-01-28 22:00:00,machine-1-1_y_1,0.164195,0.0,test -2020-01-28 23:00:00,machine-1-1_y_1,0.113347,0.0,test -2020-01-29 00:00:00,machine-1-1_y_1,0.091102,0.0,test -2020-01-29 01:00:00,machine-1-1_y_1,0.072034,0.0,test -2020-01-29 02:00:00,machine-1-1_y_1,0.045551,0.0,test -2020-01-29 03:00:00,machine-1-1_y_1,0.133475,0.0,test -2020-01-29 04:00:00,machine-1-1_y_1,0.096398,0.0,test -2020-01-29 05:00:00,machine-1-1_y_1,0.204449,0.0,test -2020-01-29 06:00:00,machine-1-1_y_1,0.340042,0.0,test -2020-01-29 07:00:00,machine-1-1_y_1,0.379237,0.0,test -2020-01-29 08:00:00,machine-1-1_y_1,0.473517,0.0,test -2020-01-29 09:00:00,machine-1-1_y_1,0.679025,0.0,test -2020-01-29 10:00:00,machine-1-1_y_1,0.54661,0.0,test -2020-01-29 11:00:00,machine-1-1_y_1,0.615466,0.0,test -2020-01-29 12:00:00,machine-1-1_y_1,0.485169,0.0,test -2020-01-29 13:00:00,machine-1-1_y_1,0.168432,0.0,test -2020-01-29 14:00:00,machine-1-1_y_1,0.190678,0.0,test -2020-01-29 15:00:00,machine-1-1_y_1,0.165254,0.0,test -2020-01-29 16:00:00,machine-1-1_y_1,0.227754,0.0,test -2020-01-29 17:00:00,machine-1-1_y_1,0.21822,0.0,test -2020-01-29 18:00:00,machine-1-1_y_1,0.189619,0.0,test -2020-01-29 19:00:00,machine-1-1_y_1,0.210805,0.0,test -2020-01-29 20:00:00,machine-1-1_y_1,0.198093,0.0,test -2020-01-29 21:00:00,machine-1-1_y_1,0.204449,0.0,test -2020-01-29 22:00:00,machine-1-1_y_1,0.213983,0.0,test -2020-01-29 23:00:00,machine-1-1_y_1,0.127119,0.0,test -2020-01-30 00:00:00,machine-1-1_y_1,0.081568,0.0,test -2020-01-30 01:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-01-30 02:00:00,machine-1-1_y_1,0.100636,0.0,test -2020-01-30 03:00:00,machine-1-1_y_1,0.104873,0.0,test -2020-01-30 04:00:00,machine-1-1_y_1,0.060381,0.0,test -2020-01-30 05:00:00,machine-1-1_y_1,0.20339,0.0,test -2020-01-30 06:00:00,machine-1-1_y_1,0.381356,0.0,test -2020-01-30 07:00:00,machine-1-1_y_1,0.511653,0.0,test -2020-01-30 08:00:00,machine-1-1_y_1,0.570975,0.0,test -2020-01-30 09:00:00,machine-1-1_y_1,0.574153,0.0,test -2020-01-30 10:00:00,machine-1-1_y_1,0.431144,0.0,test -2020-01-30 11:00:00,machine-1-1_y_1,0.407839,0.0,test -2020-01-30 12:00:00,machine-1-1_y_1,0.266949,0.0,test -2020-01-30 13:00:00,machine-1-1_y_1,0.211864,0.0,test -2020-01-30 14:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-01-30 15:00:00,machine-1-1_y_1,0.210805,0.0,test -2020-01-30 16:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-01-30 17:00:00,machine-1-1_y_1,0.256356,0.0,test -2020-01-30 18:00:00,machine-1-1_y_1,0.213983,0.0,test -2020-01-30 19:00:00,machine-1-1_y_1,0.226695,0.0,test -2020-01-30 20:00:00,machine-1-1_y_1,0.193856,0.0,test -2020-01-30 21:00:00,machine-1-1_y_1,0.205508,0.0,test -2020-01-30 22:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-01-30 23:00:00,machine-1-1_y_1,0.137712,0.0,test -2020-01-31 00:00:00,machine-1-1_y_1,0.149364,0.0,test -2020-01-31 01:00:00,machine-1-1_y_1,0.110169,0.0,test -2020-01-31 02:00:00,machine-1-1_y_1,0.123941,0.0,test -2020-01-31 03:00:00,machine-1-1_y_1,0.123941,0.0,test -2020-01-31 04:00:00,machine-1-1_y_1,0.172669,0.0,test -2020-01-31 05:00:00,machine-1-1_y_1,0.276483,0.0,test -2020-01-31 06:00:00,machine-1-1_y_1,0.383475,0.0,test -2020-01-31 07:00:00,machine-1-1_y_1,0.617585,0.0,test -2020-01-31 08:00:00,machine-1-1_y_1,0.599576,0.0,test -2020-01-31 09:00:00,machine-1-1_y_1,0.614407,0.0,test -2020-01-31 10:00:00,machine-1-1_y_1,0.255297,0.0,test -2020-01-31 11:00:00,machine-1-1_y_1,0.238347,0.0,test -2020-01-31 12:00:00,machine-1-1_y_1,0.318856,0.0,test -2020-01-31 13:00:00,machine-1-1_y_1,0.216102,0.0,test -2020-01-31 14:00:00,machine-1-1_y_1,0.205508,0.0,test -2020-01-31 15:00:00,machine-1-1_y_1,0.188559,0.0,test -2020-01-31 16:00:00,machine-1-1_y_1,0.195975,0.0,test -2020-01-31 17:00:00,machine-1-1_y_1,0.169492,0.0,test -2020-01-31 18:00:00,machine-1-1_y_1,0.145127,1.0,test -2020-01-31 19:00:00,machine-1-1_y_1,0.132415,1.0,test -2020-01-31 20:00:00,machine-1-1_y_1,0.117585,1.0,test -2020-01-31 21:00:00,machine-1-1_y_1,0.141949,1.0,test -2020-01-31 22:00:00,machine-1-1_y_1,0.164195,1.0,test -2020-01-31 23:00:00,machine-1-1_y_1,0.28072,1.0,test -2020-02-01 00:00:00,machine-1-1_y_1,0.420551,1.0,test -2020-02-01 01:00:00,machine-1-1_y_1,0.629237,1.0,test -2020-02-01 02:00:00,machine-1-1_y_1,0.539195,1.0,test -2020-02-01 03:00:00,machine-1-1_y_1,0.572034,1.0,test -2020-02-01 04:00:00,machine-1-1_y_1,0.329449,0.0,test -2020-02-01 05:00:00,machine-1-1_y_1,0.266949,0.0,test -2020-02-01 06:00:00,machine-1-1_y_1,0.324153,0.0,test -2020-02-01 07:00:00,machine-1-1_y_1,0.277542,0.0,test -2020-02-01 08:00:00,machine-1-1_y_1,0.337924,0.0,test -2020-02-01 09:00:00,machine-1-1_y_1,0.322034,0.0,test -2020-02-01 10:00:00,machine-1-1_y_1,0.318856,0.0,test -2020-02-01 11:00:00,machine-1-1_y_1,0.278602,0.0,test -2020-02-01 12:00:00,machine-1-1_y_1,0.193856,0.0,test -2020-02-01 13:00:00,machine-1-1_y_1,0.237288,1.0,test -2020-02-01 14:00:00,machine-1-1_y_1,0.152542,1.0,test -2020-02-01 15:00:00,machine-1-1_y_1,0.125,1.0,test -2020-02-01 16:00:00,machine-1-1_y_1,0.150424,1.0,test -2020-02-01 17:00:00,machine-1-1_y_1,0.255297,1.0,test -2020-02-01 18:00:00,machine-1-1_y_1,0.403602,1.0,test -2020-02-01 19:00:00,machine-1-1_y_1,0.556144,1.0,test -2020-02-01 20:00:00,machine-1-1_y_1,0.902542,1.0,test -2020-02-01 21:00:00,machine-1-1_y_1,0.985169,1.0,test -2020-02-01 22:00:00,machine-1-1_y_1,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_1,0.315678,0.0,test -2020-02-02 00:00:00,machine-1-1_y_1,0.266949,0.0,test -2020-02-02 01:00:00,machine-1-1_y_1,0.247881,0.0,test -2020-02-02 02:00:00,machine-1-1_y_1,0.305085,0.0,test -2020-02-02 03:00:00,machine-1-1_y_1,0.338983,0.0,test -2020-02-02 04:00:00,machine-1-1_y_1,0.338983,0.0,test -2020-02-02 05:00:00,machine-1-1_y_1,0.264831,0.0,test -2020-02-02 06:00:00,machine-1-1_y_1,0.216102,0.0,test -2020-02-02 07:00:00,machine-1-1_y_1,0.189619,1.0,test -2020-02-02 08:00:00,machine-1-1_y_1,0.169492,1.0,test -2020-02-02 09:00:00,machine-1-1_y_1,0.141949,1.0,test -2020-02-02 10:00:00,machine-1-1_y_1,0.118644,1.0,test -2020-02-02 11:00:00,machine-1-1_y_1,0.361229,1.0,test -2020-02-02 12:00:00,machine-1-1_y_1,0.345339,1.0,test -2020-02-02 13:00:00,machine-1-1_y_1,0.560381,1.0,test -2020-02-02 14:00:00,machine-1-1_y_1,0.807203,1.0,test -2020-02-02 15:00:00,machine-1-1_y_1,0.630297,1.0,test -2020-02-02 16:00:00,machine-1-1_y_1,0.376059,0.0,test -2020-02-02 17:00:00,machine-1-1_y_1,0.34428,0.0,test -2020-02-02 18:00:00,machine-1-1_y_1,0.176907,0.0,test -2020-02-02 19:00:00,machine-1-1_y_1,0.172669,0.0,test -2020-02-02 20:00:00,machine-1-1_y_1,0.208686,0.0,test -2020-02-02 21:00:00,machine-1-1_y_1,0.17161,0.0,test -2020-02-02 22:00:00,machine-1-1_y_1,0.237288,0.0,test -2020-02-02 23:00:00,machine-1-1_y_1,0.211864,0.0,test -2020-02-03 00:00:00,machine-1-1_y_1,0.21822,0.0,test -2020-02-03 01:00:00,machine-1-1_y_1,0.175847,0.0,test -2020-02-03 02:00:00,machine-1-1_y_1,0.216102,0.0,test -2020-02-03 03:00:00,machine-1-1_y_1,0.138771,0.0,test -2020-02-03 04:00:00,machine-1-1_y_1,0.205508,0.0,test -2020-02-03 05:00:00,machine-1-1_y_1,0.131356,1.0,test -2020-02-03 06:00:00,machine-1-1_y_1,0.108051,1.0,test -2020-02-03 07:00:00,machine-1-1_y_1,0.106992,1.0,test -2020-02-03 08:00:00,machine-1-1_y_1,0.145127,1.0,test -2020-02-03 09:00:00,machine-1-1_y_1,0.096398,1.0,test -2020-02-03 10:00:00,machine-1-1_y_1,0.145127,1.0,test -2020-02-03 11:00:00,machine-1-1_y_1,0.189619,1.0,test -2020-02-03 12:00:00,machine-1-1_y_1,0.326271,1.0,test -2020-02-03 13:00:00,machine-1-1_y_1,0.334746,1.0,test -2020-02-03 14:00:00,machine-1-1_y_1,0.485169,1.0,test -2020-02-03 15:00:00,machine-1-1_y_1,0.539195,1.0,test -2020-02-03 16:00:00,machine-1-1_y_1,0.76589,1.0,test -2020-02-03 17:00:00,machine-1-1_y_1,0.683263,1.0,test -2020-02-03 18:00:00,machine-1-1_y_1,0.211864,0.0,test -2020-02-03 19:00:00,machine-1-1_y_1,0.228814,0.0,test -2020-02-03 20:00:00,machine-1-1_y_1,0.202331,0.0,test -2020-02-03 21:00:00,machine-1-1_y_1,0.198093,0.0,test -2020-02-03 22:00:00,machine-1-1_y_1,0.264831,0.0,test -2020-02-03 23:00:00,machine-1-1_y_1,0.263771,0.0,test -2020-02-04 00:00:00,machine-1-1_y_1,0.231992,0.0,test -2020-02-04 01:00:00,machine-1-1_y_1,0.366525,0.0,test -2020-02-04 02:00:00,machine-1-1_y_1,0.221398,0.0,test -2020-02-04 03:00:00,machine-1-1_y_1,0.225636,0.0,test -2020-02-04 04:00:00,machine-1-1_y_1,0.195975,0.0,test -2020-02-04 05:00:00,machine-1-1_y_1,0.127119,1.0,test -2020-02-04 06:00:00,machine-1-1_y_1,0.151483,1.0,test -2020-02-04 07:00:00,machine-1-1_y_1,0.130297,1.0,test -2020-02-04 08:00:00,machine-1-1_y_1,0.105932,1.0,test -2020-02-04 09:00:00,machine-1-1_y_1,0.205508,1.0,test -2020-02-04 10:00:00,machine-1-1_y_1,0.354873,1.0,test -2020-02-04 11:00:00,machine-1-1_y_1,0.431144,1.0,test -2020-02-04 12:00:00,machine-1-1_y_1,0.356992,0.0,test -2020-02-04 13:00:00,machine-1-1_y_1,0.246822,0.0,test -2020-02-04 14:00:00,machine-1-1_y_1,0.226695,0.0,test -2020-02-04 15:00:00,machine-1-1_y_1,0.15678,0.0,test -2020-02-04 16:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-02-04 17:00:00,machine-1-1_y_1,0.165254,0.0,test -2020-02-04 18:00:00,machine-1-1_y_1,0.213983,0.0,test -2020-02-04 19:00:00,machine-1-1_y_1,0.186441,0.0,test -2020-02-04 20:00:00,machine-1-1_y_1,0.189619,0.0,test -2020-02-04 21:00:00,machine-1-1_y_1,0.237288,0.0,test -2020-02-04 22:00:00,machine-1-1_y_1,0.168432,0.0,test -2020-02-04 23:00:00,machine-1-1_y_1,0.118644,0.0,test -2020-02-05 00:00:00,machine-1-1_y_1,0.101695,0.0,test -2020-02-05 01:00:00,machine-1-1_y_1,0.099576,0.0,test -2020-02-05 02:00:00,machine-1-1_y_1,0.084746,0.0,test -2020-02-05 03:00:00,machine-1-1_y_1,0.167373,0.0,test -2020-02-05 04:00:00,machine-1-1_y_1,0.362288,0.0,test -2020-02-05 05:00:00,machine-1-1_y_1,0.457627,0.0,test -2020-02-05 06:00:00,machine-1-1_y_1,0.539195,0.0,test -2020-02-05 07:00:00,machine-1-1_y_1,0.497881,0.0,test -2020-02-05 08:00:00,machine-1-1_y_1,0.480932,0.0,test -2020-02-05 09:00:00,machine-1-1_y_1,0.370763,0.0,test -2020-02-05 10:00:00,machine-1-1_y_1,0.209746,0.0,test -2020-02-05 11:00:00,machine-1-1_y_1,0.181144,0.0,test -2020-02-05 12:00:00,machine-1-1_y_1,0.15572,0.0,test -2020-02-05 13:00:00,machine-1-1_y_1,0.175847,0.0,test -2020-02-05 14:00:00,machine-1-1_y_1,0.162076,0.0,test -2020-02-05 15:00:00,machine-1-1_y_1,0.180085,0.0,test -2020-02-05 16:00:00,machine-1-1_y_1,0.226695,0.0,test -2020-02-05 17:00:00,machine-1-1_y_1,0.209746,0.0,test -2020-02-05 18:00:00,machine-1-1_y_1,0.163136,0.0,test -2020-02-05 19:00:00,machine-1-1_y_1,0.126059,0.0,test -2020-02-05 20:00:00,machine-1-1_y_1,0.134534,0.0,test -2020-02-05 21:00:00,machine-1-1_y_1,0.067797,0.0,test -2020-02-05 22:00:00,machine-1-1_y_1,0.101695,0.0,test -2020-02-05 23:00:00,machine-1-1_y_1,0.050847,0.0,test -2020-02-06 00:00:00,machine-1-1_y_1,0.064619,0.0,test -2020-02-06 01:00:00,machine-1-1_y_1,0.070975,0.0,test -2020-02-06 02:00:00,machine-1-1_y_1,0.096398,0.0,test -2020-02-06 03:00:00,machine-1-1_y_1,0.116525,0.0,test -2020-02-06 04:00:00,machine-1-1_y_1,0.242585,0.0,test -2020-02-06 05:00:00,machine-1-1_y_1,0.263771,0.0,test -2020-02-06 06:00:00,machine-1-1_y_1,0.332627,0.0,test -2020-02-06 07:00:00,machine-1-1_y_1,0.411017,0.0,test -2020-02-06 08:00:00,machine-1-1_y_1,0.32839,0.0,test -2020-02-06 09:00:00,machine-1-1_y_1,0.413136,0.0,test -2020-02-06 10:00:00,machine-1-1_y_1,0.21822,0.0,test -2020-02-06 11:00:00,machine-1-1_y_1,0.147246,0.0,test -2020-02-06 12:00:00,machine-1-1_y_1,0.159958,0.0,test -2020-02-06 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13:00:00,machine-1-1_y_10,0.272888,0.0,train -2020-01-16 14:00:00,machine-1-1_y_10,0.321401,0.0,train -2020-01-16 15:00:00,machine-1-1_y_10,0.27231,0.0,train -2020-01-16 16:00:00,machine-1-1_y_10,0.304716,0.0,train -2020-01-16 17:00:00,machine-1-1_y_10,0.289881,0.0,train -2020-01-16 18:00:00,machine-1-1_y_10,0.304177,0.0,train -2020-01-16 19:00:00,machine-1-1_y_10,0.328029,0.0,train -2020-01-16 20:00:00,machine-1-1_y_10,0.327605,0.0,train -2020-01-16 21:00:00,machine-1-1_y_10,0.293503,0.0,train -2020-01-16 22:00:00,machine-1-1_y_10,0.329108,0.0,train -2020-01-16 23:00:00,machine-1-1_y_10,0.313733,0.0,train -2020-01-17 00:00:00,machine-1-1_y_10,0.419197,0.0,train -2020-01-17 01:00:00,machine-1-1_y_10,0.318357,0.0,train -2020-01-17 02:00:00,machine-1-1_y_10,0.286067,0.0,train -2020-01-17 03:00:00,machine-1-1_y_10,0.28414,0.0,train -2020-01-17 04:00:00,machine-1-1_y_10,0.317933,0.0,train -2020-01-17 05:00:00,machine-1-1_y_10,0.547472,0.0,train -2020-01-17 06:00:00,machine-1-1_y_10,0.320746,0.0,train -2020-01-17 07:00:00,machine-1-1_y_10,0.307645,0.0,train -2020-01-17 08:00:00,machine-1-1_y_10,0.3167,0.0,train -2020-01-17 09:00:00,machine-1-1_y_10,0.311344,0.0,train -2020-01-17 10:00:00,machine-1-1_y_10,0.325678,0.0,train -2020-01-17 11:00:00,machine-1-1_y_10,0.33693,0.0,train -2020-01-17 12:00:00,machine-1-1_y_10,0.355849,0.0,train -2020-01-17 13:00:00,machine-1-1_y_10,0.321131,0.0,train -2020-01-17 14:00:00,machine-1-1_y_10,0.342594,0.0,train -2020-01-17 15:00:00,machine-1-1_y_10,0.323636,0.0,train -2020-01-17 16:00:00,machine-1-1_y_10,0.288841,0.0,train -2020-01-17 17:00:00,machine-1-1_y_10,0.31092,0.0,train -2020-01-17 18:00:00,machine-1-1_y_10,0.296239,0.0,train -2020-01-17 19:00:00,machine-1-1_y_10,0.311151,0.0,train -2020-01-17 20:00:00,machine-1-1_y_10,0.39496,0.0,train -2020-01-17 21:00:00,machine-1-1_y_10,0.320476,0.0,train -2020-01-17 22:00:00,machine-1-1_y_10,0.32483,0.0,train -2020-01-17 23:00:00,machine-1-1_y_10,0.352266,0.0,train -2020-01-18 00:00:00,machine-1-1_y_10,0.458847,0.0,train -2020-01-18 01:00:00,machine-1-1_y_10,0.324869,0.0,train -2020-01-18 02:00:00,machine-1-1_y_10,0.286182,0.0,train -2020-01-18 03:00:00,machine-1-1_y_10,0.32221,0.0,train -2020-01-18 04:00:00,machine-1-1_y_10,0.284718,0.0,train -2020-01-18 05:00:00,machine-1-1_y_10,0.468365,0.0,train -2020-01-18 06:00:00,machine-1-1_y_10,0.335003,0.0,train -2020-01-18 07:00:00,machine-1-1_y_10,0.305872,0.0,train -2020-01-18 08:00:00,machine-1-1_y_10,0.309032,0.0,train -2020-01-18 09:00:00,machine-1-1_y_10,0.332267,0.0,train -2020-01-18 10:00:00,machine-1-1_y_10,0.310805,0.0,train -2020-01-18 11:00:00,machine-1-1_y_10,0.346563,0.0,train -2020-01-18 12:00:00,machine-1-1_y_10,0.317586,0.0,train -2020-01-18 13:00:00,machine-1-1_y_10,0.321016,0.0,train -2020-01-18 14:00:00,machine-1-1_y_10,0.382745,0.0,train -2020-01-18 15:00:00,machine-1-1_y_10,0.292155,0.0,train -2020-01-18 16:00:00,machine-1-1_y_10,0.341053,0.0,train -2020-01-18 17:00:00,machine-1-1_y_10,0.28965,0.0,train -2020-01-18 18:00:00,machine-1-1_y_10,0.381859,0.0,train -2020-01-18 19:00:00,machine-1-1_y_10,0.332421,0.0,train -2020-01-18 20:00:00,machine-1-1_y_10,0.313039,0.0,train -2020-01-18 21:00:00,machine-1-1_y_10,0.31092,0.0,train -2020-01-18 22:00:00,machine-1-1_y_10,0.345291,0.0,train -2020-01-18 23:00:00,machine-1-1_y_10,0.309995,0.0,train -2020-01-19 00:00:00,machine-1-1_y_10,0.369182,0.0,train -2020-01-19 01:00:00,machine-1-1_y_10,0.291191,0.0,train -2020-01-19 02:00:00,machine-1-1_y_10,0.306373,0.0,train -2020-01-19 03:00:00,machine-1-1_y_10,0.286683,0.0,train -2020-01-19 04:00:00,machine-1-1_y_10,0.302559,0.0,train -2020-01-19 05:00:00,machine-1-1_y_10,0.813425,0.0,train -2020-01-19 06:00:00,machine-1-1_y_10,0.301326,0.0,train -2020-01-19 07:00:00,machine-1-1_y_10,0.380163,0.0,train -2020-01-19 08:00:00,machine-1-1_y_10,0.312885,0.0,train -2020-01-19 09:00:00,machine-1-1_y_10,0.317008,0.0,train -2020-01-19 10:00:00,machine-1-1_y_10,0.332152,0.0,train -2020-01-19 11:00:00,machine-1-1_y_10,0.330957,0.0,train -2020-01-19 12:00:00,machine-1-1_y_10,0.343442,0.0,train -2020-01-19 13:00:00,machine-1-1_y_10,0.400355,0.0,train -2020-01-19 14:00:00,machine-1-1_y_10,0.313155,0.0,train -2020-01-19 15:00:00,machine-1-1_y_10,0.309032,0.0,train -2020-01-19 16:00:00,machine-1-1_y_10,0.307414,0.0,train -2020-01-19 17:00:00,machine-1-1_y_10,0.307992,0.0,train -2020-01-19 18:00:00,machine-1-1_y_10,0.313039,0.0,train -2020-01-19 19:00:00,machine-1-1_y_10,0.359047,0.0,train -2020-01-19 20:00:00,machine-1-1_y_10,0.370838,0.0,train -2020-01-19 21:00:00,machine-1-1_y_10,0.331843,0.0,train -2020-01-19 22:00:00,machine-1-1_y_10,0.331073,0.0,train -2020-01-19 23:00:00,machine-1-1_y_10,0.344174,0.0,train -2020-01-20 00:00:00,machine-1-1_y_10,0.343711,0.0,train -2020-01-20 01:00:00,machine-1-1_y_10,0.335427,0.0,train -2020-01-20 02:00:00,machine-1-1_y_10,0.29308,0.0,train -2020-01-20 03:00:00,machine-1-1_y_10,0.29254,0.0,train -2020-01-20 04:00:00,machine-1-1_y_10,0.329069,0.0,train -2020-01-20 05:00:00,machine-1-1_y_10,0.72557,0.0,train -2020-01-20 06:00:00,machine-1-1_y_10,0.32537,0.0,train -2020-01-20 07:00:00,machine-1-1_y_10,0.370916,0.0,train -2020-01-20 08:00:00,machine-1-1_y_10,0.310766,0.0,train -2020-01-20 09:00:00,machine-1-1_y_10,0.337238,0.0,train -2020-01-20 10:00:00,machine-1-1_y_10,0.339088,0.0,train -2020-01-20 11:00:00,machine-1-1_y_10,0.294698,0.0,train -2020-01-20 12:00:00,machine-1-1_y_10,0.345368,0.0,train -2020-01-20 13:00:00,machine-1-1_y_10,0.356389,0.0,train -2020-01-20 14:00:00,machine-1-1_y_10,0.295353,0.0,train -2020-01-20 15:00:00,machine-1-1_y_10,0.292039,0.0,train -2020-01-20 16:00:00,machine-1-1_y_10,0.337893,0.0,train -2020-01-20 17:00:00,machine-1-1_y_10,0.328453,0.0,train -2020-01-20 18:00:00,machine-1-1_y_10,0.340321,0.0,train -2020-01-20 19:00:00,machine-1-1_y_10,0.32853,0.0,test -2020-01-20 20:00:00,machine-1-1_y_10,0.325254,0.0,test -2020-01-20 21:00:00,machine-1-1_y_10,0.341091,0.0,test -2020-01-20 22:00:00,machine-1-1_y_10,0.314619,0.0,test -2020-01-20 23:00:00,machine-1-1_y_10,0.355965,0.0,test -2020-01-21 00:00:00,machine-1-1_y_10,0.359163,0.0,test -2020-01-21 01:00:00,machine-1-1_y_10,0.309032,0.0,test -2020-01-21 02:00:00,machine-1-1_y_10,0.354308,0.0,test -2020-01-21 03:00:00,machine-1-1_y_10,0.324021,0.0,test -2020-01-21 04:00:00,machine-1-1_y_10,0.308454,0.0,test -2020-01-21 05:00:00,machine-1-1_y_10,0.624306,0.0,test -2020-01-21 06:00:00,machine-1-1_y_10,0.352921,0.0,test -2020-01-21 07:00:00,machine-1-1_y_10,0.312731,0.0,test -2020-01-21 08:00:00,machine-1-1_y_10,0.370299,0.0,test -2020-01-21 09:00:00,machine-1-1_y_10,0.311498,0.0,test -2020-01-21 10:00:00,machine-1-1_y_10,0.312153,0.0,test -2020-01-21 11:00:00,machine-1-1_y_10,0.376503,0.0,test -2020-01-21 12:00:00,machine-1-1_y_10,0.338047,0.0,test -2020-01-21 13:00:00,machine-1-1_y_10,0.334348,0.0,test -2020-01-21 14:00:00,machine-1-1_y_10,0.296162,0.0,test -2020-01-21 15:00:00,machine-1-1_y_10,0.366137,0.0,test -2020-01-21 16:00:00,machine-1-1_y_10,0.310111,0.0,test -2020-01-21 17:00:00,machine-1-1_y_10,0.321208,0.0,test -2020-01-21 18:00:00,machine-1-1_y_10,0.308531,0.0,test -2020-01-21 19:00:00,machine-1-1_y_10,0.325948,0.0,test -2020-01-21 20:00:00,machine-1-1_y_10,0.322827,0.0,test -2020-01-21 21:00:00,machine-1-1_y_10,0.293503,0.0,test -2020-01-21 22:00:00,machine-1-1_y_10,0.296432,0.0,test -2020-01-21 23:00:00,machine-1-1_y_10,0.293388,0.0,test -2020-01-22 00:00:00,machine-1-1_y_10,0.447287,0.0,test -2020-01-22 01:00:00,machine-1-1_y_10,0.3209,0.0,test -2020-01-22 02:00:00,machine-1-1_y_10,0.308685,0.0,test -2020-01-22 03:00:00,machine-1-1_y_10,0.300748,0.0,test -2020-01-22 04:00:00,machine-1-1_y_10,0.823983,0.0,test -2020-01-22 05:00:00,machine-1-1_y_10,0.308454,0.0,test -2020-01-22 06:00:00,machine-1-1_y_10,0.32483,0.0,test -2020-01-22 07:00:00,machine-1-1_y_10,0.309148,0.0,test -2020-01-22 08:00:00,machine-1-1_y_10,0.353576,0.0,test -2020-01-22 09:00:00,machine-1-1_y_10,0.348644,0.0,test -2020-01-22 10:00:00,machine-1-1_y_10,0.528591,0.0,test -2020-01-22 11:00:00,machine-1-1_y_10,0.298359,0.0,test -2020-01-22 12:00:00,machine-1-1_y_10,0.310227,0.0,test -2020-01-22 13:00:00,machine-1-1_y_10,0.328491,0.0,test -2020-01-22 14:00:00,machine-1-1_y_10,0.325909,0.0,test -2020-01-22 15:00:00,machine-1-1_y_10,0.330842,0.0,test -2020-01-22 16:00:00,machine-1-1_y_10,0.281134,0.0,test -2020-01-22 17:00:00,machine-1-1_y_10,0.328876,0.0,test -2020-01-22 18:00:00,machine-1-1_y_10,0.320823,0.0,test -2020-01-22 19:00:00,machine-1-1_y_10,0.316546,0.0,test -2020-01-22 20:00:00,machine-1-1_y_10,0.314504,0.0,test -2020-01-22 21:00:00,machine-1-1_y_10,0.331959,0.0,test -2020-01-22 22:00:00,machine-1-1_y_10,0.297626,0.0,test -2020-01-22 23:00:00,machine-1-1_y_10,0.313964,0.0,test 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17:00:00,machine-1-1_y_10,0.333385,0.0,test -2020-01-23 18:00:00,machine-1-1_y_10,0.336544,0.0,test -2020-01-23 19:00:00,machine-1-1_y_10,0.323366,0.0,test -2020-01-23 20:00:00,machine-1-1_y_10,0.30645,0.0,test -2020-01-23 21:00:00,machine-1-1_y_10,0.317663,0.0,test -2020-01-23 22:00:00,machine-1-1_y_10,0.298628,0.0,test -2020-01-23 23:00:00,machine-1-1_y_10,0.296201,0.0,test -2020-01-24 00:00:00,machine-1-1_y_10,0.34271,0.0,test -2020-01-24 01:00:00,machine-1-1_y_10,0.294582,0.0,test -2020-01-24 02:00:00,machine-1-1_y_10,0.294544,0.0,test -2020-01-24 03:00:00,machine-1-1_y_10,0.358624,0.0,test -2020-01-24 04:00:00,machine-1-1_y_10,0.32641,0.0,test -2020-01-24 05:00:00,machine-1-1_y_10,0.306874,0.0,test -2020-01-24 06:00:00,machine-1-1_y_10,0.323328,0.0,test -2020-01-24 07:00:00,machine-1-1_y_10,0.312847,0.0,test -2020-01-24 08:00:00,machine-1-1_y_10,0.314118,0.0,test -2020-01-24 09:00:00,machine-1-1_y_10,0.313463,0.0,test -2020-01-24 10:00:00,machine-1-1_y_10,0.312847,0.0,test 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04:00:00,machine-1-1_y_10,0.310227,0.0,test -2020-01-25 05:00:00,machine-1-1_y_10,0.326603,0.0,test -2020-01-25 06:00:00,machine-1-1_y_10,0.310689,0.0,test -2020-01-25 07:00:00,machine-1-1_y_10,0.34059,0.0,test -2020-01-25 08:00:00,machine-1-1_y_10,0.34244,0.0,test -2020-01-25 09:00:00,machine-1-1_y_10,0.329223,0.0,test -2020-01-25 10:00:00,machine-1-1_y_10,0.328953,0.0,test -2020-01-25 11:00:00,machine-1-1_y_10,0.345253,0.0,test -2020-01-25 12:00:00,machine-1-1_y_10,0.307799,0.0,test -2020-01-25 13:00:00,machine-1-1_y_10,0.320707,0.0,test -2020-01-25 14:00:00,machine-1-1_y_10,0.287261,0.0,test -2020-01-25 15:00:00,machine-1-1_y_10,0.346756,0.0,test -2020-01-25 16:00:00,machine-1-1_y_10,0.302443,0.0,test -2020-01-25 17:00:00,machine-1-1_y_10,0.331959,0.0,test -2020-01-25 18:00:00,machine-1-1_y_10,0.303368,0.0,test -2020-01-25 19:00:00,machine-1-1_y_10,0.352112,0.0,test -2020-01-25 20:00:00,machine-1-1_y_10,0.320707,0.0,test -2020-01-25 21:00:00,machine-1-1_y_10,0.322287,0.0,test 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15:00:00,machine-1-1_y_10,0.318973,0.0,test -2020-01-26 16:00:00,machine-1-1_y_10,0.320515,0.0,test -2020-01-26 17:00:00,machine-1-1_y_10,0.3167,0.0,test -2020-01-26 18:00:00,machine-1-1_y_10,0.334541,0.0,test -2020-01-26 19:00:00,machine-1-1_y_10,0.336352,0.0,test -2020-01-26 20:00:00,machine-1-1_y_10,0.336082,0.0,test -2020-01-26 21:00:00,machine-1-1_y_10,0.32144,0.0,test -2020-01-26 22:00:00,machine-1-1_y_10,0.336737,0.0,test -2020-01-26 23:00:00,machine-1-1_y_10,0.314273,0.0,test -2020-01-27 00:00:00,machine-1-1_y_10,0.310535,0.0,test -2020-01-27 01:00:00,machine-1-1_y_10,0.309649,0.0,test -2020-01-27 02:00:00,machine-1-1_y_10,0.35111,0.0,test -2020-01-27 03:00:00,machine-1-1_y_10,0.312192,0.0,test -2020-01-27 04:00:00,machine-1-1_y_10,0.290691,0.0,test -2020-01-27 05:00:00,machine-1-1_y_10,0.313772,0.0,test -2020-01-27 06:00:00,machine-1-1_y_10,0.310458,0.0,test -2020-01-27 07:00:00,machine-1-1_y_10,0.362284,0.0,test -2020-01-27 08:00:00,machine-1-1_y_10,0.332807,0.0,test -2020-01-27 09:00:00,machine-1-1_y_10,0.35477,0.0,test -2020-01-27 10:00:00,machine-1-1_y_10,0.296432,0.0,test -2020-01-27 11:00:00,machine-1-1_y_10,0.331651,0.0,test -2020-01-27 12:00:00,machine-1-1_y_10,0.311999,0.0,test -2020-01-27 13:00:00,machine-1-1_y_10,0.283485,0.0,test -2020-01-27 14:00:00,machine-1-1_y_10,0.314812,0.0,test -2020-01-27 15:00:00,machine-1-1_y_10,0.322942,0.0,test -2020-01-27 16:00:00,machine-1-1_y_10,0.301248,0.0,test -2020-01-27 17:00:00,machine-1-1_y_10,0.37315,0.0,test -2020-01-27 18:00:00,machine-1-1_y_10,0.409988,0.0,test -2020-01-27 19:00:00,machine-1-1_y_10,0.333577,0.0,test -2020-01-27 20:00:00,machine-1-1_y_10,0.346062,0.0,test -2020-01-27 21:00:00,machine-1-1_y_10,0.302636,0.0,test -2020-01-27 22:00:00,machine-1-1_y_10,0.373266,0.0,test -2020-01-27 23:00:00,machine-1-1_y_10,0.328067,0.0,test -2020-01-28 00:00:00,machine-1-1_y_10,0.30988,0.0,test -2020-01-28 01:00:00,machine-1-1_y_10,0.329069,0.0,test -2020-01-28 02:00:00,machine-1-1_y_10,0.297125,0.0,test -2020-01-28 03:00:00,machine-1-1_y_10,0.325062,0.0,test -2020-01-28 04:00:00,machine-1-1_y_10,0.340667,0.0,test -2020-01-28 05:00:00,machine-1-1_y_10,0.324638,0.0,test -2020-01-28 06:00:00,machine-1-1_y_10,0.311961,0.0,test -2020-01-28 07:00:00,machine-1-1_y_10,0.317047,0.0,test -2020-01-28 08:00:00,machine-1-1_y_10,0.349183,0.0,test -2020-01-28 09:00:00,machine-1-1_y_10,0.317317,0.0,test -2020-01-28 10:00:00,machine-1-1_y_10,0.345368,0.0,test -2020-01-28 11:00:00,machine-1-1_y_10,0.31959,0.0,test -2020-01-28 12:00:00,machine-1-1_y_10,0.314118,0.0,test -2020-01-28 13:00:00,machine-1-1_y_10,0.313386,0.0,test -2020-01-28 14:00:00,machine-1-1_y_10,0.296355,0.0,test -2020-01-28 15:00:00,machine-1-1_y_10,0.402127,0.0,test -2020-01-28 16:00:00,machine-1-1_y_10,0.33115,0.0,test -2020-01-28 17:00:00,machine-1-1_y_10,0.318896,0.0,test -2020-01-28 18:00:00,machine-1-1_y_10,0.309918,0.0,test -2020-01-28 19:00:00,machine-1-1_y_10,0.412338,0.0,test -2020-01-28 20:00:00,machine-1-1_y_10,0.293157,0.0,test -2020-01-28 21:00:00,machine-1-1_y_10,0.318742,0.0,test -2020-01-28 22:00:00,machine-1-1_y_10,0.300786,0.0,test -2020-01-28 23:00:00,machine-1-1_y_10,0.401241,0.0,test -2020-01-29 00:00:00,machine-1-1_y_10,0.311845,0.0,test -2020-01-29 01:00:00,machine-1-1_y_10,0.278822,0.0,test -2020-01-29 02:00:00,machine-1-1_y_10,0.313733,0.0,test -2020-01-29 03:00:00,machine-1-1_y_10,0.372264,0.0,test -2020-01-29 04:00:00,machine-1-1_y_10,0.308184,0.0,test -2020-01-29 05:00:00,machine-1-1_y_10,0.372765,0.0,test -2020-01-29 06:00:00,machine-1-1_y_10,0.234279,0.0,test -2020-01-29 07:00:00,machine-1-1_y_10,0.29412,0.0,test -2020-01-29 08:00:00,machine-1-1_y_10,0.355772,0.0,test -2020-01-29 09:00:00,machine-1-1_y_10,0.353229,0.0,test -2020-01-29 10:00:00,machine-1-1_y_10,0.364827,0.0,test -2020-01-29 11:00:00,machine-1-1_y_10,0.305102,0.0,test -2020-01-29 12:00:00,machine-1-1_y_10,0.330148,0.0,test -2020-01-29 13:00:00,machine-1-1_y_10,0.340744,0.0,test -2020-01-29 14:00:00,machine-1-1_y_10,0.357352,0.0,test -2020-01-29 15:00:00,machine-1-1_y_10,0.316854,0.0,test -2020-01-29 16:00:00,machine-1-1_y_10,0.321786,0.0,test -2020-01-29 17:00:00,machine-1-1_y_10,0.304293,0.0,test -2020-01-29 18:00:00,machine-1-1_y_10,0.290035,0.0,test -2020-01-29 19:00:00,machine-1-1_y_10,0.348066,0.0,test -2020-01-29 20:00:00,machine-1-1_y_10,0.304678,0.0,test -2020-01-29 21:00:00,machine-1-1_y_10,0.357429,0.0,test -2020-01-29 22:00:00,machine-1-1_y_10,0.321324,0.0,test -2020-01-29 23:00:00,machine-1-1_y_10,0.362939,0.0,test -2020-01-30 00:00:00,machine-1-1_y_10,0.313348,0.0,test -2020-01-30 01:00:00,machine-1-1_y_10,0.312847,0.0,test -2020-01-30 02:00:00,machine-1-1_y_10,0.340629,0.0,test -2020-01-30 03:00:00,machine-1-1_y_10,0.31065,0.0,test -2020-01-30 04:00:00,machine-1-1_y_10,0.331497,0.0,test -2020-01-30 05:00:00,machine-1-1_y_10,0.299746,0.0,test -2020-01-30 06:00:00,machine-1-1_y_10,0.356312,0.0,test 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00:00:00,machine-1-1_y_10,0.335774,0.0,test -2020-01-31 01:00:00,machine-1-1_y_10,0.193164,0.0,test -2020-01-31 02:00:00,machine-1-1_y_10,0.350339,0.0,test -2020-01-31 03:00:00,machine-1-1_y_10,0.333654,0.0,test -2020-01-31 04:00:00,machine-1-1_y_10,0.214396,0.0,test -2020-01-31 05:00:00,machine-1-1_y_10,0.32799,0.0,test -2020-01-31 06:00:00,machine-1-1_y_10,0.364365,0.0,test -2020-01-31 07:00:00,machine-1-1_y_10,0.382283,0.0,test -2020-01-31 08:00:00,machine-1-1_y_10,0.261406,0.0,test -2020-01-31 09:00:00,machine-1-1_y_10,0.352189,0.0,test -2020-01-31 10:00:00,machine-1-1_y_10,0.358585,0.0,test -2020-01-31 11:00:00,machine-1-1_y_10,0.350223,0.0,test -2020-01-31 12:00:00,machine-1-1_y_10,0.337469,0.0,test -2020-01-31 13:00:00,machine-1-1_y_10,0.325177,0.0,test -2020-01-31 14:00:00,machine-1-1_y_10,0.38656,0.0,test -2020-01-31 15:00:00,machine-1-1_y_10,0.321979,0.0,test -2020-01-31 16:00:00,machine-1-1_y_10,0.290074,0.0,test -2020-01-31 17:00:00,machine-1-1_y_10,0.232699,0.0,test 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01:00:00,machine-1-1_y_11,0.067568,0.0,train -2020-01-20 02:00:00,machine-1-1_y_11,0.040541,0.0,train -2020-01-20 03:00:00,machine-1-1_y_11,0.067568,0.0,train -2020-01-20 04:00:00,machine-1-1_y_11,0.067568,0.0,train -2020-01-20 05:00:00,machine-1-1_y_11,0.189189,0.0,train -2020-01-20 06:00:00,machine-1-1_y_11,0.108108,0.0,train -2020-01-20 07:00:00,machine-1-1_y_11,0.121622,0.0,train -2020-01-20 08:00:00,machine-1-1_y_11,0.202703,0.0,train -2020-01-20 09:00:00,machine-1-1_y_11,0.135135,0.0,train -2020-01-20 10:00:00,machine-1-1_y_11,0.175676,0.0,train -2020-01-20 11:00:00,machine-1-1_y_11,0.135135,0.0,train -2020-01-20 12:00:00,machine-1-1_y_11,0.148649,0.0,train -2020-01-20 13:00:00,machine-1-1_y_11,0.148649,0.0,train -2020-01-20 14:00:00,machine-1-1_y_11,0.121622,0.0,train -2020-01-20 15:00:00,machine-1-1_y_11,0.108108,0.0,train -2020-01-20 16:00:00,machine-1-1_y_11,0.162162,0.0,train -2020-01-20 17:00:00,machine-1-1_y_11,0.189189,0.0,train -2020-01-20 18:00:00,machine-1-1_y_11,0.162162,0.0,train -2020-01-20 19:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-20 20:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-20 21:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-20 22:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-20 23:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-21 00:00:00,machine-1-1_y_11,0.094595,0.0,test -2020-01-21 01:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-21 02:00:00,machine-1-1_y_11,0.054054,0.0,test -2020-01-21 03:00:00,machine-1-1_y_11,0.027027,0.0,test -2020-01-21 04:00:00,machine-1-1_y_11,0.027027,0.0,test -2020-01-21 05:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-21 06:00:00,machine-1-1_y_11,0.094595,0.0,test -2020-01-21 07:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-21 08:00:00,machine-1-1_y_11,0.418919,0.0,test -2020-01-21 09:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-21 10:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-01-21 11:00:00,machine-1-1_y_11,0.162162,0.0,test 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05:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-01-22 06:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-22 07:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-22 08:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 09:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-22 10:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 11:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 12:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 13:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 14:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 15:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-22 16:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-22 17:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 18:00:00,machine-1-1_y_11,0.283784,0.0,test -2020-01-22 19:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-22 20:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-22 21:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-22 22:00:00,machine-1-1_y_11,0.135135,0.0,test 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16:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-23 17:00:00,machine-1-1_y_11,0.216216,0.0,test -2020-01-23 18:00:00,machine-1-1_y_11,0.337838,0.0,test -2020-01-23 19:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-23 20:00:00,machine-1-1_y_11,0.216216,0.0,test -2020-01-23 21:00:00,machine-1-1_y_11,0.216216,0.0,test -2020-01-23 22:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-23 23:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-24 00:00:00,machine-1-1_y_11,0.054054,0.0,test -2020-01-24 01:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-24 02:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-24 03:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-24 04:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-24 05:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-24 06:00:00,machine-1-1_y_11,0.27027,0.0,test -2020-01-24 07:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-24 08:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-24 09:00:00,machine-1-1_y_11,0.27027,0.0,test 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03:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-25 04:00:00,machine-1-1_y_11,0.054054,0.0,test -2020-01-25 05:00:00,machine-1-1_y_11,0.108108,0.0,test -2020-01-25 06:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-25 07:00:00,machine-1-1_y_11,0.243243,0.0,test -2020-01-25 08:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 09:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-01-25 10:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 11:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-25 12:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-25 13:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-25 14:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 15:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 16:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 17:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-25 18:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-25 19:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-25 20:00:00,machine-1-1_y_11,0.162162,0.0,test 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14:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-26 15:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-26 16:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-26 17:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-26 18:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-26 19:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-26 20:00:00,machine-1-1_y_11,0.216216,0.0,test -2020-01-26 21:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-26 22:00:00,machine-1-1_y_11,0.310811,0.0,test -2020-01-26 23:00:00,machine-1-1_y_11,0.094595,0.0,test -2020-01-27 00:00:00,machine-1-1_y_11,0.108108,0.0,test -2020-01-27 01:00:00,machine-1-1_y_11,0.054054,0.0,test -2020-01-27 02:00:00,machine-1-1_y_11,0.054054,0.0,test -2020-01-27 03:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-27 04:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-27 05:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-27 06:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-27 07:00:00,machine-1-1_y_11,0.202703,0.0,test 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01:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-28 02:00:00,machine-1-1_y_11,0.040541,0.0,test -2020-01-28 03:00:00,machine-1-1_y_11,0.040541,0.0,test -2020-01-28 04:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-28 05:00:00,machine-1-1_y_11,0.108108,0.0,test -2020-01-28 06:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-28 07:00:00,machine-1-1_y_11,0.22973,0.0,test -2020-01-28 08:00:00,machine-1-1_y_11,0.418919,0.0,test -2020-01-28 09:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-28 10:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-28 11:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-28 12:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-28 13:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-28 14:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-28 15:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-28 16:00:00,machine-1-1_y_11,0.135135,0.0,test -2020-01-28 17:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-28 18:00:00,machine-1-1_y_11,0.162162,0.0,test 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12:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-29 13:00:00,machine-1-1_y_11,0.22973,0.0,test -2020-01-29 14:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-29 15:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-29 16:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-29 17:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-29 18:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-29 19:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-29 20:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-29 21:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-29 22:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-29 23:00:00,machine-1-1_y_11,0.094595,0.0,test -2020-01-30 00:00:00,machine-1-1_y_11,0.108108,0.0,test -2020-01-30 01:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-30 02:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-30 03:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-30 04:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-30 05:00:00,machine-1-1_y_11,0.094595,0.0,test 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23:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-31 00:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-31 01:00:00,machine-1-1_y_11,0.108108,0.0,test -2020-01-31 02:00:00,machine-1-1_y_11,0.067568,0.0,test -2020-01-31 03:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-01-31 04:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-01-31 05:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-31 06:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-01-31 07:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-31 08:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-31 09:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-01-31 10:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-01-31 11:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-31 12:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-01-31 13:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-31 14:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-01-31 15:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-01-31 16:00:00,machine-1-1_y_11,0.148649,0.0,test 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10:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-02-01 11:00:00,machine-1-1_y_11,0.297297,0.0,test -2020-02-01 12:00:00,machine-1-1_y_11,0.121622,0.0,test -2020-02-01 13:00:00,machine-1-1_y_11,0.945946,1.0,test -2020-02-01 14:00:00,machine-1-1_y_11,1.0,1.0,test -2020-02-01 15:00:00,machine-1-1_y_11,0.445946,1.0,test -2020-02-01 16:00:00,machine-1-1_y_11,0.594595,1.0,test -2020-02-01 17:00:00,machine-1-1_y_11,0.810811,1.0,test -2020-02-01 18:00:00,machine-1-1_y_11,0.189189,1.0,test -2020-02-01 19:00:00,machine-1-1_y_11,0.202703,1.0,test -2020-02-01 20:00:00,machine-1-1_y_11,0.243243,1.0,test -2020-02-01 21:00:00,machine-1-1_y_11,0.256757,1.0,test -2020-02-01 22:00:00,machine-1-1_y_11,0.405405,1.0,test -2020-02-01 23:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-02-02 00:00:00,machine-1-1_y_11,0.202703,0.0,test -2020-02-02 01:00:00,machine-1-1_y_11,0.22973,0.0,test -2020-02-02 02:00:00,machine-1-1_y_11,0.216216,0.0,test -2020-02-02 03:00:00,machine-1-1_y_11,0.202703,0.0,test 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21:00:00,machine-1-1_y_11,0.162162,0.0,test -2020-02-02 22:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-02-02 23:00:00,machine-1-1_y_11,0.175676,0.0,test -2020-02-03 00:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-02-03 01:00:00,machine-1-1_y_11,0.189189,0.0,test -2020-02-03 02:00:00,machine-1-1_y_11,0.310811,0.0,test -2020-02-03 03:00:00,machine-1-1_y_11,0.148649,0.0,test -2020-02-03 04:00:00,machine-1-1_y_11,0.081081,0.0,test -2020-02-03 05:00:00,machine-1-1_y_11,0.324324,1.0,test -2020-02-03 06:00:00,machine-1-1_y_11,0.662162,1.0,test -2020-02-03 07:00:00,machine-1-1_y_11,0.513514,1.0,test -2020-02-03 08:00:00,machine-1-1_y_11,0.5,1.0,test -2020-02-03 09:00:00,machine-1-1_y_11,0.716216,1.0,test -2020-02-03 10:00:00,machine-1-1_y_11,0.77027,1.0,test -2020-02-03 11:00:00,machine-1-1_y_11,0.418919,1.0,test -2020-02-03 12:00:00,machine-1-1_y_11,0.148649,1.0,test -2020-02-03 13:00:00,machine-1-1_y_11,0.175676,1.0,test -2020-02-03 14:00:00,machine-1-1_y_11,0.189189,1.0,test 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01:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-15 02:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-15 03:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-15 04:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-15 05:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-15 06:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-15 07:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-15 09:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 10:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 11:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 12:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 13:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 14:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 15:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-15 16:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-15 17:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 18:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 19:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 20:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 21:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-15 22:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-15 23:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 00:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 01:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 02:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-16 03:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-16 04:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-16 05:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 06:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-16 07:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-16 09:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 10:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 11:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 12:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 13:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 14:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 15:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-16 16:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-16 17:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-16 18:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 19:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 20:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-16 21:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-16 22:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-16 23:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-17 00:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-17 01:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-17 02:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-17 03:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-17 04:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-17 05:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-17 06:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-17 07:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 09:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 10:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-17 11:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-17 12:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-17 13:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 14:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-17 15:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-17 16:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 17:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 18:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 19:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-17 20:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-17 21:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-17 22:00:00,machine-1-1_y_12,0.150685,0.0,train -2020-01-17 23:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 00:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-18 01:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-18 02:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-18 03:00:00,machine-1-1_y_12,0.123288,0.0,train -2020-01-18 04:00:00,machine-1-1_y_12,0.109589,0.0,train -2020-01-18 05:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 06:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-18 07:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 09:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 10:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 11:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 12:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 13:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 14:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 15:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 16:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 17:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 18:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 19:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-18 20:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 21:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-18 22:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-18 23:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 00:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-19 01:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-19 02:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-19 03:00:00,machine-1-1_y_12,0.164384,0.0,train -2020-01-19 04:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-19 05:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-19 06:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-19 07:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 09:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 10:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 11:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 12:00:00,machine-1-1_y_12,0.123288,0.0,train -2020-01-19 13:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 14:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 15:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-19 16:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 17:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-19 18:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-19 19:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 20:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-19 21:00:00,machine-1-1_y_12,0.082192,0.0,train -2020-01-19 22:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-19 23:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 00:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-20 01:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-20 02:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-20 03:00:00,machine-1-1_y_12,0.013699,0.0,train -2020-01-20 04:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-20 05:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 06:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-20 07:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-20 08:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-20 09:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 10:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 11:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-20 12:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 13:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 14:00:00,machine-1-1_y_12,0.041096,0.0,train -2020-01-20 15:00:00,machine-1-1_y_12,0.027397,0.0,train -2020-01-20 16:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 17:00:00,machine-1-1_y_12,0.068493,0.0,train -2020-01-20 18:00:00,machine-1-1_y_12,0.054795,0.0,train -2020-01-20 19:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-20 20:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-20 21:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-20 22:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-20 23:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-21 00:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-21 01:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-21 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-21 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-21 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-21 05:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-21 06:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-21 07:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-21 08:00:00,machine-1-1_y_12,0.136986,0.0,test -2020-01-21 09:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-21 10:00:00,machine-1-1_y_12,0.041096,0.0,test 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04:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 05:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 07:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-22 08:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 09:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 10:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 11:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 12:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 13:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 15:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-22 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 17:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-22 18:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-22 19:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-22 20:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-22 21:00:00,machine-1-1_y_12,0.041096,0.0,test 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15:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-23 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-23 17:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-23 18:00:00,machine-1-1_y_12,0.109589,0.0,test -2020-01-23 19:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-23 20:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-23 21:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-23 22:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-23 23:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 00:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 01:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-24 05:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-24 06:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-24 07:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-24 08:00:00,machine-1-1_y_12,0.041096,0.0,test 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02:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-25 03:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-25 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-25 05:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 07:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-25 08:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 09:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 10:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 11:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 12:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 13:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 15:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 17:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-25 18:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-25 19:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 20:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-25 21:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 22:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-25 23:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-26 00:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-26 01:00:00,machine-1-1_y_12,0.150685,0.0,test -2020-01-26 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-26 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-26 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-26 05:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-26 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 07:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 08:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 09:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 10:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-26 11:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 12:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 13:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 14:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 15:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-26 16:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-26 17:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 18:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 19:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-26 20:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 21:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 22:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-26 23:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-27 00:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-27 01:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-27 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-27 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-27 04:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-27 05:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 06:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-27 07:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-27 08:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 09:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 10:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 11:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-27 12:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 13:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 15:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-27 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-27 17:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 18:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-27 19:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-27 20:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-27 21:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-27 22:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-27 23:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-28 00:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-28 01:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-28 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-28 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-28 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-28 05:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-28 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 07:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-28 08:00:00,machine-1-1_y_12,0.123288,0.0,test -2020-01-28 09:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 10:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 11:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-28 12:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 13:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-28 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-28 15:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 17:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 18:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 19:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 20:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 21:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-28 22:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-28 23:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-29 00:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-29 01:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-29 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-29 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-29 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-29 05:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-29 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 07:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-29 08:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 09:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-29 10:00:00,machine-1-1_y_12,0.109589,0.0,test -2020-01-29 11:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-29 12:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-29 13:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-29 15:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-29 16:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-29 17:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 18:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 19:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 20:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 21:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 22:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-29 23:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-30 00:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-30 01:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-30 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-30 03:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-30 04:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-30 05:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-30 06:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-30 07:00:00,machine-1-1_y_12,0.136986,0.0,test -2020-01-30 08:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-30 09:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 10:00:00,machine-1-1_y_12,0.09589,0.0,test -2020-01-30 11:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 12:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 13:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 14:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-30 15:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 16:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-30 17:00:00,machine-1-1_y_12,0.082192,0.0,test -2020-01-30 18:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 19:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 20:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-30 21:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-30 22:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-30 23:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-31 00:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-31 01:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-31 02:00:00,machine-1-1_y_12,0.013699,0.0,test -2020-01-31 03:00:00,machine-1-1_y_12,0.027397,0.0,test -2020-01-31 04:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-31 05:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-31 06:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-31 07:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-31 08:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-31 09:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-31 10:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-31 11:00:00,machine-1-1_y_12,0.068493,0.0,test -2020-01-31 12:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-31 13:00:00,machine-1-1_y_12,0.041096,0.0,test -2020-01-31 14:00:00,machine-1-1_y_12,0.054795,0.0,test -2020-01-31 15:00:00,machine-1-1_y_12,0.054795,0.0,test 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06:00:00,machine-1-1_y_13,0.077178,0.0,train -2020-01-19 07:00:00,machine-1-1_y_13,0.078123,0.0,train -2020-01-19 08:00:00,machine-1-1_y_13,0.079689,0.0,train -2020-01-19 09:00:00,machine-1-1_y_13,0.07269,0.0,train -2020-01-19 10:00:00,machine-1-1_y_13,0.062726,0.0,train -2020-01-19 11:00:00,machine-1-1_y_13,0.059008,0.0,train -2020-01-19 12:00:00,machine-1-1_y_13,0.071193,0.0,train -2020-01-19 13:00:00,machine-1-1_y_13,0.064544,0.0,train -2020-01-19 14:00:00,machine-1-1_y_13,0.057026,0.0,train -2020-01-19 15:00:00,machine-1-1_y_13,0.058863,0.0,train -2020-01-19 16:00:00,machine-1-1_y_13,0.066681,0.0,train -2020-01-19 17:00:00,machine-1-1_y_13,0.067986,0.0,train -2020-01-19 18:00:00,machine-1-1_y_13,0.082551,0.0,train -2020-01-19 19:00:00,machine-1-1_y_13,0.079783,0.0,train -2020-01-19 20:00:00,machine-1-1_y_13,0.078282,0.0,train -2020-01-19 21:00:00,machine-1-1_y_13,0.089649,0.0,train -2020-01-19 22:00:00,machine-1-1_y_13,0.067925,0.0,train -2020-01-19 23:00:00,machine-1-1_y_13,0.054393,0.0,train -2020-01-20 00:00:00,machine-1-1_y_13,0.089074,0.0,train -2020-01-20 01:00:00,machine-1-1_y_13,0.060799,0.0,train -2020-01-20 02:00:00,machine-1-1_y_13,0.046842,0.0,train -2020-01-20 03:00:00,machine-1-1_y_13,0.069463,0.0,train -2020-01-20 04:00:00,machine-1-1_y_13,0.0605,0.0,train -2020-01-20 05:00:00,machine-1-1_y_13,0.05791,0.0,train -2020-01-20 06:00:00,machine-1-1_y_13,0.065391,0.0,train -2020-01-20 07:00:00,machine-1-1_y_13,0.087919,0.0,train -2020-01-20 08:00:00,machine-1-1_y_13,0.10931,0.0,train -2020-01-20 09:00:00,machine-1-1_y_13,0.083519,0.0,train -2020-01-20 10:00:00,machine-1-1_y_13,0.090439,0.0,train -2020-01-20 11:00:00,machine-1-1_y_13,0.084052,0.0,train -2020-01-20 12:00:00,machine-1-1_y_13,0.088938,0.0,train -2020-01-20 13:00:00,machine-1-1_y_13,0.080835,0.0,train -2020-01-20 14:00:00,machine-1-1_y_13,0.075233,0.0,train -2020-01-20 15:00:00,machine-1-1_y_13,0.071165,0.0,train -2020-01-20 16:00:00,machine-1-1_y_13,0.087746,0.0,train -2020-01-20 17:00:00,machine-1-1_y_13,0.094703,0.0,train -2020-01-20 18:00:00,machine-1-1_y_13,0.086927,0.0,train -2020-01-20 19:00:00,machine-1-1_y_13,0.100511,0.0,test -2020-01-20 20:00:00,machine-1-1_y_13,0.09749,0.0,test -2020-01-20 21:00:00,machine-1-1_y_13,0.10095,0.0,test -2020-01-20 22:00:00,machine-1-1_y_13,0.091898,0.0,test -2020-01-20 23:00:00,machine-1-1_y_13,0.088667,0.0,test -2020-01-21 00:00:00,machine-1-1_y_13,0.061145,0.0,test -2020-01-21 01:00:00,machine-1-1_y_13,0.048151,0.0,test -2020-01-21 02:00:00,machine-1-1_y_13,0.047408,0.0,test -2020-01-21 03:00:00,machine-1-1_y_13,0.078432,0.0,test -2020-01-21 04:00:00,machine-1-1_y_13,0.076524,0.0,test -2020-01-21 05:00:00,machine-1-1_y_13,0.060467,0.0,test -2020-01-21 06:00:00,machine-1-1_y_13,0.052219,0.0,test -2020-01-21 07:00:00,machine-1-1_y_13,0.092665,0.0,test -2020-01-21 08:00:00,machine-1-1_y_13,0.095489,0.0,test -2020-01-21 09:00:00,machine-1-1_y_13,0.079451,0.0,test 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03:00:00,machine-1-1_y_13,0.060925,0.0,test -2020-01-22 04:00:00,machine-1-1_y_13,0.052593,0.0,test -2020-01-22 05:00:00,machine-1-1_y_13,0.059032,0.0,test -2020-01-22 06:00:00,machine-1-1_y_13,0.109105,0.0,test -2020-01-22 07:00:00,machine-1-1_y_13,0.100239,0.0,test -2020-01-22 08:00:00,machine-1-1_y_13,0.09057,0.0,test -2020-01-22 09:00:00,machine-1-1_y_13,0.074378,0.0,test -2020-01-22 10:00:00,machine-1-1_y_13,0.077758,0.0,test -2020-01-22 11:00:00,machine-1-1_y_13,0.085193,0.0,test -2020-01-22 12:00:00,machine-1-1_y_13,0.081686,0.0,test -2020-01-22 13:00:00,machine-1-1_y_13,0.070039,0.0,test -2020-01-22 14:00:00,machine-1-1_y_13,0.065419,0.0,test -2020-01-22 15:00:00,machine-1-1_y_13,0.093469,0.0,test -2020-01-22 16:00:00,machine-1-1_y_13,0.086572,0.0,test -2020-01-22 17:00:00,machine-1-1_y_13,0.086221,0.0,test -2020-01-22 18:00:00,machine-1-1_y_13,0.077861,0.0,test -2020-01-22 19:00:00,machine-1-1_y_13,0.092333,0.0,test -2020-01-22 20:00:00,machine-1-1_y_13,0.093979,0.0,test 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12:00:00,machine-1-1_y_13,0.063951,0.0,test -2020-01-26 13:00:00,machine-1-1_y_13,0.067205,0.0,test -2020-01-26 14:00:00,machine-1-1_y_13,0.074485,0.0,test -2020-01-26 15:00:00,machine-1-1_y_13,0.127897,0.0,test -2020-01-26 16:00:00,machine-1-1_y_13,0.115576,0.0,test -2020-01-26 17:00:00,machine-1-1_y_13,0.105804,0.0,test -2020-01-26 18:00:00,machine-1-1_y_13,0.102456,0.0,test -2020-01-26 19:00:00,machine-1-1_y_13,0.099641,0.0,test -2020-01-26 20:00:00,machine-1-1_y_13,0.099412,0.0,test -2020-01-26 21:00:00,machine-1-1_y_13,0.064367,0.0,test -2020-01-26 22:00:00,machine-1-1_y_13,0.056544,0.0,test -2020-01-26 23:00:00,machine-1-1_y_13,0.055352,0.0,test -2020-01-27 00:00:00,machine-1-1_y_13,0.050728,0.0,test -2020-01-27 01:00:00,machine-1-1_y_13,0.05351,0.0,test -2020-01-27 02:00:00,machine-1-1_y_13,0.078544,0.0,test -2020-01-27 03:00:00,machine-1-1_y_13,0.054828,0.0,test -2020-01-27 04:00:00,machine-1-1_y_13,0.04708,0.0,test -2020-01-27 05:00:00,machine-1-1_y_13,0.075757,0.0,test 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23:00:00,machine-1-1_y_13,0.048221,0.0,test -2020-01-28 00:00:00,machine-1-1_y_13,0.053393,0.0,test -2020-01-28 01:00:00,machine-1-1_y_13,0.088279,0.0,test -2020-01-28 02:00:00,machine-1-1_y_13,0.058765,0.0,test -2020-01-28 03:00:00,machine-1-1_y_13,0.066695,0.0,test -2020-01-28 04:00:00,machine-1-1_y_13,0.053033,0.0,test -2020-01-28 05:00:00,machine-1-1_y_13,0.068972,0.0,test -2020-01-28 06:00:00,machine-1-1_y_13,0.087919,0.0,test -2020-01-28 07:00:00,machine-1-1_y_13,0.097537,0.0,test -2020-01-28 08:00:00,machine-1-1_y_13,0.055604,0.0,test -2020-01-28 09:00:00,machine-1-1_y_13,0.084431,0.0,test -2020-01-28 10:00:00,machine-1-1_y_13,0.090766,0.0,test -2020-01-28 11:00:00,machine-1-1_y_13,0.073209,0.0,test -2020-01-28 12:00:00,machine-1-1_y_13,0.055343,0.0,test -2020-01-28 13:00:00,machine-1-1_y_13,0.05358,0.0,test -2020-01-28 14:00:00,machine-1-1_y_13,0.07161,0.0,test -2020-01-28 15:00:00,machine-1-1_y_13,0.097027,0.0,test -2020-01-28 16:00:00,machine-1-1_y_13,0.092291,0.0,test 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10:00:00,machine-1-1_y_13,0.094105,0.0,test -2020-01-29 11:00:00,machine-1-1_y_13,0.080325,0.0,test -2020-01-29 12:00:00,machine-1-1_y_13,0.067902,0.0,test -2020-01-29 13:00:00,machine-1-1_y_13,0.04904,0.0,test -2020-01-29 14:00:00,machine-1-1_y_13,0.070048,0.0,test -2020-01-29 15:00:00,machine-1-1_y_13,0.118321,0.0,test -2020-01-29 16:00:00,machine-1-1_y_13,0.11789,0.0,test -2020-01-29 17:00:00,machine-1-1_y_13,0.099856,0.0,test -2020-01-29 18:00:00,machine-1-1_y_13,0.088382,0.0,test -2020-01-29 19:00:00,machine-1-1_y_13,0.092295,0.0,test -2020-01-29 20:00:00,machine-1-1_y_13,0.105677,0.0,test -2020-01-29 21:00:00,machine-1-1_y_13,0.085885,0.0,test -2020-01-29 22:00:00,machine-1-1_y_13,0.068112,0.0,test -2020-01-29 23:00:00,machine-1-1_y_13,0.059953,0.0,test -2020-01-30 00:00:00,machine-1-1_y_13,0.051457,0.0,test -2020-01-30 01:00:00,machine-1-1_y_13,0.053468,0.0,test -2020-01-30 02:00:00,machine-1-1_y_13,0.058288,0.0,test -2020-01-30 03:00:00,machine-1-1_y_13,0.061566,0.0,test 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21:00:00,machine-1-1_y_13,0.055506,0.0,test -2020-01-30 22:00:00,machine-1-1_y_13,0.064011,0.0,test -2020-01-30 23:00:00,machine-1-1_y_13,0.062445,0.0,test -2020-01-31 00:00:00,machine-1-1_y_13,0.05574,0.0,test -2020-01-31 01:00:00,machine-1-1_y_13,0.07023,0.0,test -2020-01-31 02:00:00,machine-1-1_y_13,0.064717,0.0,test -2020-01-31 03:00:00,machine-1-1_y_13,0.05155,0.0,test -2020-01-31 04:00:00,machine-1-1_y_13,0.083846,0.0,test -2020-01-31 05:00:00,machine-1-1_y_13,0.08631,0.0,test -2020-01-31 06:00:00,machine-1-1_y_13,0.090112,0.0,test -2020-01-31 07:00:00,machine-1-1_y_13,0.089003,0.0,test -2020-01-31 08:00:00,machine-1-1_y_13,0.10427,0.0,test -2020-01-31 09:00:00,machine-1-1_y_13,0.086352,0.0,test -2020-01-31 10:00:00,machine-1-1_y_13,0.073817,0.0,test -2020-01-31 11:00:00,machine-1-1_y_13,0.116764,0.0,test -2020-01-31 12:00:00,machine-1-1_y_13,0.098313,0.0,test -2020-01-31 13:00:00,machine-1-1_y_13,0.084351,0.0,test -2020-01-31 14:00:00,machine-1-1_y_13,0.086394,0.0,test 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08:00:00,machine-1-1_y_13,0.085604,0.0,test -2020-02-01 09:00:00,machine-1-1_y_13,0.102535,0.0,test -2020-02-01 10:00:00,machine-1-1_y_13,0.099884,0.0,test -2020-02-01 11:00:00,machine-1-1_y_13,0.07975,0.0,test -2020-02-01 12:00:00,machine-1-1_y_13,0.058204,0.0,test -2020-02-01 13:00:00,machine-1-1_y_13,0.92082,1.0,test -2020-02-01 14:00:00,machine-1-1_y_13,0.127789,1.0,test -2020-02-01 15:00:00,machine-1-1_y_13,0.108043,1.0,test -2020-02-01 16:00:00,machine-1-1_y_13,0.085941,1.0,test -2020-02-01 17:00:00,machine-1-1_y_13,0.157831,1.0,test -2020-02-01 18:00:00,machine-1-1_y_13,0.10852,1.0,test -2020-02-01 19:00:00,machine-1-1_y_13,0.100024,1.0,test -2020-02-01 20:00:00,machine-1-1_y_13,0.122973,1.0,test -2020-02-01 21:00:00,machine-1-1_y_13,0.139011,1.0,test -2020-02-01 22:00:00,machine-1-1_y_13,0.143953,1.0,test -2020-02-01 23:00:00,machine-1-1_y_13,0.059429,0.0,test -2020-02-02 00:00:00,machine-1-1_y_13,0.05826,0.0,test -2020-02-02 01:00:00,machine-1-1_y_13,0.071605,0.0,test 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02:00:00,machine-1-1_y_14,0.043203,0.0,test -2020-01-22 03:00:00,machine-1-1_y_14,0.031114,0.0,test -2020-01-22 04:00:00,machine-1-1_y_14,0.068371,0.0,test -2020-01-22 05:00:00,machine-1-1_y_14,0.114943,0.0,test -2020-01-22 06:00:00,machine-1-1_y_14,0.15973,0.0,test -2020-01-22 07:00:00,machine-1-1_y_14,0.186484,0.0,test -2020-01-22 08:00:00,machine-1-1_y_14,0.169639,0.0,test -2020-01-22 09:00:00,machine-1-1_y_14,0.136346,0.0,test -2020-01-22 10:00:00,machine-1-1_y_14,0.139913,0.0,test -2020-01-22 11:00:00,machine-1-1_y_14,0.160523,0.0,test -2020-01-22 12:00:00,machine-1-1_y_14,0.146849,0.0,test -2020-01-22 13:00:00,machine-1-1_y_14,0.128815,0.0,test -2020-01-22 14:00:00,machine-1-1_y_14,0.127428,0.0,test -2020-01-22 15:00:00,machine-1-1_y_14,0.156956,0.0,test -2020-01-22 16:00:00,machine-1-1_y_14,0.167063,0.0,test -2020-01-22 17:00:00,machine-1-1_y_14,0.147642,0.0,test -2020-01-22 18:00:00,machine-1-1_y_14,0.229885,0.0,test -2020-01-22 19:00:00,machine-1-1_y_14,0.171423,0.0,test 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13:00:00,machine-1-1_y_14,0.141696,0.0,test -2020-01-23 14:00:00,machine-1-1_y_14,0.1413,0.0,test -2020-01-23 15:00:00,machine-1-1_y_14,0.231867,0.0,test -2020-01-23 16:00:00,machine-1-1_y_14,0.169441,0.0,test -2020-01-23 17:00:00,machine-1-1_y_14,0.142885,0.0,test -2020-01-23 18:00:00,machine-1-1_y_14,0.169045,0.0,test -2020-01-23 19:00:00,machine-1-1_y_14,0.144669,0.0,test -2020-01-23 20:00:00,machine-1-1_y_14,0.144471,0.0,test -2020-01-23 21:00:00,machine-1-1_y_14,0.184701,0.0,test -2020-01-23 22:00:00,machine-1-1_y_14,0.185692,0.0,test -2020-01-23 23:00:00,machine-1-1_y_14,0.092152,0.0,test -2020-01-24 00:00:00,machine-1-1_y_14,0.062822,0.0,test -2020-01-24 01:00:00,machine-1-1_y_14,0.052319,0.0,test -2020-01-24 02:00:00,machine-1-1_y_14,0.035672,0.0,test -2020-01-24 03:00:00,machine-1-1_y_14,0.04459,0.0,test -2020-01-24 04:00:00,machine-1-1_y_14,0.071145,0.0,test -2020-01-24 05:00:00,machine-1-1_y_14,0.191241,0.0,test -2020-01-24 06:00:00,machine-1-1_y_14,0.20868,0.0,test 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00:00:00,machine-1-1_y_14,0.07174,0.0,test -2020-01-25 01:00:00,machine-1-1_y_14,0.081054,0.0,test -2020-01-25 02:00:00,machine-1-1_y_14,1.0,0.0,test -2020-01-25 03:00:00,machine-1-1_y_14,0.042013,0.0,test -2020-01-25 04:00:00,machine-1-1_y_14,0.067578,0.0,test -2020-01-25 05:00:00,machine-1-1_y_14,0.12822,0.0,test -2020-01-25 06:00:00,machine-1-1_y_14,0.161118,0.0,test -2020-01-25 07:00:00,machine-1-1_y_14,0.170828,0.0,test -2020-01-25 08:00:00,machine-1-1_y_14,0.192628,0.0,test -2020-01-25 09:00:00,machine-1-1_y_14,0.147047,0.0,test -2020-01-25 10:00:00,machine-1-1_y_14,0.144669,0.0,test -2020-01-25 11:00:00,machine-1-1_y_14,0.157352,0.0,test -2020-01-25 12:00:00,machine-1-1_y_14,0.144075,0.0,test -2020-01-25 13:00:00,machine-1-1_y_14,0.132382,0.0,test -2020-01-25 14:00:00,machine-1-1_y_14,0.131589,0.0,test -2020-01-25 15:00:00,machine-1-1_y_14,0.168054,0.0,test -2020-01-25 16:00:00,machine-1-1_y_14,0.153983,0.0,test -2020-01-25 17:00:00,machine-1-1_y_14,0.161712,0.0,test -2020-01-25 18:00:00,machine-1-1_y_14,0.189853,0.0,test -2020-01-25 19:00:00,machine-1-1_y_14,0.163496,0.0,test -2020-01-25 20:00:00,machine-1-1_y_14,0.172414,0.0,test -2020-01-25 21:00:00,machine-1-1_y_14,0.161316,0.0,test -2020-01-25 22:00:00,machine-1-1_y_14,0.13476,0.0,test -2020-01-25 23:00:00,machine-1-1_y_14,0.101665,0.0,test -2020-01-26 00:00:00,machine-1-1_y_14,0.074713,0.0,test -2020-01-26 01:00:00,machine-1-1_y_14,0.25109,0.0,test -2020-01-26 02:00:00,machine-1-1_y_14,0.04241,0.0,test -2020-01-26 03:00:00,machine-1-1_y_14,0.039834,0.0,test -2020-01-26 04:00:00,machine-1-1_y_14,0.064407,0.0,test -2020-01-26 05:00:00,machine-1-1_y_14,0.11633,0.0,test -2020-01-26 06:00:00,machine-1-1_y_14,0.181926,0.0,test -2020-01-26 07:00:00,machine-1-1_y_14,0.25981,0.0,test -2020-01-26 08:00:00,machine-1-1_y_14,0.140111,0.0,test -2020-01-26 09:00:00,machine-1-1_y_14,0.135157,0.0,test -2020-01-26 10:00:00,machine-1-1_y_14,0.148831,0.0,test -2020-01-26 11:00:00,machine-1-1_y_14,0.130995,0.0,test 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05:00:00,machine-1-1_y_14,0.117519,0.0,test -2020-01-27 06:00:00,machine-1-1_y_14,0.157154,0.0,test -2020-01-27 07:00:00,machine-1-1_y_14,0.238407,0.0,test -2020-01-27 08:00:00,machine-1-1_y_14,0.171027,0.0,test -2020-01-27 09:00:00,machine-1-1_y_14,0.127229,0.0,test -2020-01-27 10:00:00,machine-1-1_y_14,0.140111,0.0,test -2020-01-27 11:00:00,machine-1-1_y_14,0.23583,0.0,test -2020-01-27 12:00:00,machine-1-1_y_14,0.149227,0.0,test -2020-01-27 13:00:00,machine-1-1_y_14,0.137931,0.0,test -2020-01-27 14:00:00,machine-1-1_y_14,0.135949,0.0,test -2020-01-27 15:00:00,machine-1-1_y_14,0.180143,0.0,test -2020-01-27 16:00:00,machine-1-1_y_14,0.155569,0.0,test -2020-01-27 17:00:00,machine-1-1_y_14,0.170036,0.0,test -2020-01-27 18:00:00,machine-1-1_y_14,0.150416,0.0,test -2020-01-27 19:00:00,machine-1-1_y_14,0.178161,0.0,test -2020-01-27 20:00:00,machine-1-1_y_14,0.166667,0.0,test -2020-01-27 21:00:00,machine-1-1_y_14,0.140309,0.0,test -2020-01-27 22:00:00,machine-1-1_y_14,0.095918,0.0,test 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16:00:00,machine-1-1_y_14,0.151803,0.0,test -2020-01-28 17:00:00,machine-1-1_y_14,0.157947,0.0,test -2020-01-28 18:00:00,machine-1-1_y_14,0.185493,0.0,test -2020-01-28 19:00:00,machine-1-1_y_14,0.214625,0.0,test -2020-01-28 20:00:00,machine-1-1_y_14,0.175585,0.0,test -2020-01-28 21:00:00,machine-1-1_y_14,0.167856,0.0,test -2020-01-28 22:00:00,machine-1-1_y_14,0.139913,0.0,test -2020-01-28 23:00:00,machine-1-1_y_14,0.099881,0.0,test -2020-01-29 00:00:00,machine-1-1_y_14,0.065795,0.0,test -2020-01-29 01:00:00,machine-1-1_y_14,0.040824,0.0,test -2020-01-29 02:00:00,machine-1-1_y_14,0.035275,0.0,test -2020-01-29 03:00:00,machine-1-1_y_14,0.041419,0.0,test -2020-01-29 04:00:00,machine-1-1_y_14,0.070353,0.0,test -2020-01-29 05:00:00,machine-1-1_y_14,0.112961,0.0,test -2020-01-29 06:00:00,machine-1-1_y_14,0.189457,0.0,test -2020-01-29 07:00:00,machine-1-1_y_14,0.300832,0.0,test -2020-01-29 08:00:00,machine-1-1_y_14,0.163694,0.0,test -2020-01-29 09:00:00,machine-1-1_y_14,0.197186,0.0,test 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14:00:00,machine-1-1_y_15,0.308997,0.0,train -2020-01-20 15:00:00,machine-1-1_y_15,0.305817,0.0,train -2020-01-20 16:00:00,machine-1-1_y_15,0.352144,0.0,train -2020-01-20 17:00:00,machine-1-1_y_15,0.340222,0.0,train -2020-01-20 18:00:00,machine-1-1_y_15,0.351841,0.0,train -2020-01-20 19:00:00,machine-1-1_y_15,0.341925,0.0,test -2020-01-20 20:00:00,machine-1-1_y_15,0.33867,0.0,test -2020-01-20 21:00:00,machine-1-1_y_15,0.35328,0.0,test -2020-01-20 22:00:00,machine-1-1_y_15,0.32671,0.0,test -2020-01-20 23:00:00,machine-1-1_y_15,0.370766,0.0,test -2020-01-21 00:00:00,machine-1-1_y_15,0.366489,0.0,test -2020-01-21 01:00:00,machine-1-1_y_15,0.320048,0.0,test -2020-01-21 02:00:00,machine-1-1_y_15,0.365808,0.0,test -2020-01-21 03:00:00,machine-1-1_y_15,0.33356,0.0,test -2020-01-21 04:00:00,machine-1-1_y_15,0.323001,0.0,test -2020-01-21 05:00:00,machine-1-1_y_15,0.633208,0.0,test -2020-01-21 06:00:00,machine-1-1_y_15,0.361644,0.0,test -2020-01-21 07:00:00,machine-1-1_y_15,0.32372,0.0,test 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10:00:00,machine-1-1_y_15,0.312554,0.0,test -2020-01-26 11:00:00,machine-1-1_y_15,0.330873,0.0,test -2020-01-26 12:00:00,machine-1-1_y_15,0.308164,0.0,test -2020-01-26 13:00:00,machine-1-1_y_15,0.339465,0.0,test -2020-01-26 14:00:00,machine-1-1_y_15,0.312554,0.0,test -2020-01-26 15:00:00,machine-1-1_y_15,0.332046,0.0,test -2020-01-26 16:00:00,machine-1-1_y_15,0.333295,0.0,test -2020-01-26 17:00:00,machine-1-1_y_15,0.329208,0.0,test -2020-01-26 18:00:00,machine-1-1_y_15,0.349646,0.0,test -2020-01-26 19:00:00,machine-1-1_y_15,0.347299,0.0,test -2020-01-26 20:00:00,machine-1-1_y_15,0.413308,0.0,test -2020-01-26 21:00:00,machine-1-1_y_15,0.33409,0.0,test -2020-01-26 22:00:00,machine-1-1_y_15,0.346429,0.0,test -2020-01-26 23:00:00,machine-1-1_y_15,0.326558,0.0,test -2020-01-27 00:00:00,machine-1-1_y_15,0.324174,0.0,test -2020-01-27 01:00:00,machine-1-1_y_15,0.323266,0.0,test -2020-01-27 02:00:00,machine-1-1_y_15,0.361833,0.0,test -2020-01-27 03:00:00,machine-1-1_y_15,0.325915,0.0,test 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21:00:00,machine-1-1_y_15,0.31509,0.0,test -2020-01-27 22:00:00,machine-1-1_y_15,0.385451,0.0,test -2020-01-27 23:00:00,machine-1-1_y_15,0.340827,0.0,test -2020-01-28 00:00:00,machine-1-1_y_15,0.323531,0.0,test -2020-01-28 01:00:00,machine-1-1_y_15,0.341546,0.0,test -2020-01-28 02:00:00,machine-1-1_y_15,0.310094,0.0,test -2020-01-28 03:00:00,machine-1-1_y_15,0.337307,0.0,test -2020-01-28 04:00:00,machine-1-1_y_15,0.350441,0.0,test -2020-01-28 05:00:00,machine-1-1_y_15,0.336853,0.0,test -2020-01-28 06:00:00,machine-1-1_y_15,0.324515,0.0,test -2020-01-28 07:00:00,machine-1-1_y_15,0.330154,0.0,test -2020-01-28 08:00:00,machine-1-1_y_15,0.361114,0.0,test -2020-01-28 09:00:00,machine-1-1_y_15,0.336929,0.0,test -2020-01-28 10:00:00,machine-1-1_y_15,0.357216,0.0,test -2020-01-28 11:00:00,machine-1-1_y_15,0.332046,0.0,test -2020-01-28 12:00:00,machine-1-1_y_15,0.325044,0.0,test -2020-01-28 13:00:00,machine-1-1_y_15,0.326937,0.0,test -2020-01-28 14:00:00,machine-1-1_y_15,0.308694,0.0,test 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08:00:00,machine-1-1_y_15,0.368911,0.0,test -2020-01-29 09:00:00,machine-1-1_y_15,0.364407,0.0,test -2020-01-29 10:00:00,machine-1-1_y_15,0.373756,0.0,test -2020-01-29 11:00:00,machine-1-1_y_15,0.318307,0.0,test -2020-01-29 12:00:00,machine-1-1_y_15,0.340487,0.0,test -2020-01-29 13:00:00,machine-1-1_y_15,0.351122,0.0,test -2020-01-29 14:00:00,machine-1-1_y_15,0.368419,0.0,test -2020-01-29 15:00:00,machine-1-1_y_15,0.327732,0.0,test -2020-01-29 16:00:00,machine-1-1_y_15,0.332841,0.0,test -2020-01-29 17:00:00,machine-1-1_y_15,0.317361,0.0,test -2020-01-29 18:00:00,machine-1-1_y_15,0.301995,0.0,test -2020-01-29 19:00:00,machine-1-1_y_15,0.360319,0.0,test -2020-01-29 20:00:00,machine-1-1_y_15,0.316453,0.0,test -2020-01-29 21:00:00,machine-1-1_y_15,0.369479,0.0,test -2020-01-29 22:00:00,machine-1-1_y_15,0.332917,0.0,test -2020-01-29 23:00:00,machine-1-1_y_15,0.374967,0.0,test -2020-01-30 00:00:00,machine-1-1_y_15,0.325007,0.0,test -2020-01-30 01:00:00,machine-1-1_y_15,0.325423,0.0,test 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19:00:00,machine-1-1_y_15,0.334242,0.0,test -2020-01-30 20:00:00,machine-1-1_y_15,0.337913,0.0,test -2020-01-30 21:00:00,machine-1-1_y_15,0.355702,0.0,test -2020-01-30 22:00:00,machine-1-1_y_15,0.39567,0.0,test -2020-01-30 23:00:00,machine-1-1_y_15,0.347867,0.0,test -2020-01-31 00:00:00,machine-1-1_y_15,0.349646,0.0,test -2020-01-31 01:00:00,machine-1-1_y_15,0.202869,0.0,test -2020-01-31 02:00:00,machine-1-1_y_15,0.361493,0.0,test -2020-01-31 03:00:00,machine-1-1_y_15,0.345483,0.0,test -2020-01-31 04:00:00,machine-1-1_y_15,0.22872,0.0,test -2020-01-31 05:00:00,machine-1-1_y_15,0.340449,0.0,test -2020-01-31 06:00:00,machine-1-1_y_15,0.376897,0.0,test -2020-01-31 07:00:00,machine-1-1_y_15,0.393626,0.0,test -2020-01-31 08:00:00,machine-1-1_y_15,0.275349,0.0,test -2020-01-31 09:00:00,machine-1-1_y_15,0.365088,0.0,test -2020-01-31 10:00:00,machine-1-1_y_15,0.369441,0.0,test -2020-01-31 11:00:00,machine-1-1_y_15,0.363196,0.0,test -2020-01-31 12:00:00,machine-1-1_y_15,0.350554,0.0,test 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06:00:00,machine-1-1_y_15,0.345937,0.0,test -2020-02-01 07:00:00,machine-1-1_y_15,0.374853,0.0,test -2020-02-01 08:00:00,machine-1-1_y_15,0.337535,0.0,test -2020-02-01 09:00:00,machine-1-1_y_15,0.347678,0.0,test -2020-02-01 10:00:00,machine-1-1_y_15,0.365013,0.0,test -2020-02-01 11:00:00,machine-1-1_y_15,0.380076,0.0,test -2020-02-01 12:00:00,machine-1-1_y_15,0.337951,0.0,test -2020-02-01 13:00:00,machine-1-1_y_15,0.349798,1.0,test -2020-02-01 14:00:00,machine-1-1_y_15,0.350403,1.0,test -2020-02-01 15:00:00,machine-1-1_y_15,0.360887,1.0,test -2020-02-01 16:00:00,machine-1-1_y_15,0.482116,1.0,test -2020-02-01 17:00:00,machine-1-1_y_15,0.368343,1.0,test -2020-02-01 18:00:00,machine-1-1_y_15,0.270542,1.0,test -2020-02-01 19:00:00,machine-1-1_y_15,0.280005,1.0,test -2020-02-01 20:00:00,machine-1-1_y_15,0.46728,1.0,test -2020-02-01 21:00:00,machine-1-1_y_15,0.644639,1.0,test -2020-02-01 22:00:00,machine-1-1_y_15,0.515272,1.0,test -2020-02-01 23:00:00,machine-1-1_y_15,0.383331,0.0,test 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00:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 01:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 02:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 03:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 04:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 05:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 06:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 07:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 08:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 09:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 10:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 11:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 12:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 13:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 14:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 15:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 16:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 17:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 18:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 19:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 20:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 21:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 22:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-26 23:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 00:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 01:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 02:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 03:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 04:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 05:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 06:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 07:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 08:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 09:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 10:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 11:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 12:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 13:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 14:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 15:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 16:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 17:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 18:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 19:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 20:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 21:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 22:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-27 23:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 00:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 01:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 02:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 03:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 04:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 05:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 06:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 07:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 08:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-28 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04:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 05:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 06:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 07:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 08:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 09:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 10:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 11:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 12:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 13:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 14:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 15:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 16:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 17:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 18:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 19:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 20:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 21:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 22:00:00,machine-1-1_y_17,0.0,0.0,test -2020-01-29 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00:00:00,machine-1-1_y_18,0.092233,0.0,test -2020-01-22 01:00:00,machine-1-1_y_18,0.062084,0.0,test -2020-01-22 02:00:00,machine-1-1_y_18,0.048186,0.0,test -2020-01-22 03:00:00,machine-1-1_y_18,0.040584,0.0,test -2020-01-22 04:00:00,machine-1-1_y_18,0.049061,0.0,test -2020-01-22 05:00:00,machine-1-1_y_18,0.092578,0.0,test -2020-01-22 06:00:00,machine-1-1_y_18,0.146629,0.0,test -2020-01-22 07:00:00,machine-1-1_y_18,0.190318,0.0,test -2020-01-22 08:00:00,machine-1-1_y_18,0.189345,0.0,test -2020-01-22 09:00:00,machine-1-1_y_18,0.164679,0.0,test -2020-01-22 10:00:00,machine-1-1_y_18,0.151668,0.0,test -2020-01-22 11:00:00,machine-1-1_y_18,0.163102,0.0,test -2020-01-22 12:00:00,machine-1-1_y_18,0.115236,0.0,test -2020-01-22 13:00:00,machine-1-1_y_18,0.109655,0.0,test -2020-01-22 14:00:00,machine-1-1_y_18,0.107708,0.0,test -2020-01-22 15:00:00,machine-1-1_y_18,0.104098,0.0,test -2020-01-22 16:00:00,machine-1-1_y_18,0.116862,0.0,test -2020-01-22 17:00:00,machine-1-1_y_18,0.130575,0.0,test 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16:00:00,machine-1-1_y_19,0.092723,0.0,test -2020-01-22 17:00:00,machine-1-1_y_19,0.115312,0.0,test -2020-01-22 18:00:00,machine-1-1_y_19,0.128137,0.0,test -2020-01-22 19:00:00,machine-1-1_y_19,0.175973,0.0,test -2020-01-22 20:00:00,machine-1-1_y_19,0.124409,0.0,test -2020-01-22 21:00:00,machine-1-1_y_19,0.111715,0.0,test -2020-01-22 22:00:00,machine-1-1_y_19,0.096767,0.0,test -2020-01-22 23:00:00,machine-1-1_y_19,0.072144,0.0,test -2020-01-23 00:00:00,machine-1-1_y_19,0.048371,0.0,test -2020-01-23 01:00:00,machine-1-1_y_19,0.037081,0.0,test -2020-01-23 02:00:00,machine-1-1_y_19,0.029089,0.0,test -2020-01-23 03:00:00,machine-1-1_y_19,0.026922,0.0,test -2020-01-23 04:00:00,machine-1-1_y_19,0.033045,0.0,test -2020-01-23 05:00:00,machine-1-1_y_19,0.069678,0.0,test -2020-01-23 06:00:00,machine-1-1_y_19,0.111373,0.0,test -2020-01-23 07:00:00,machine-1-1_y_19,0.133988,0.0,test -2020-01-23 08:00:00,machine-1-1_y_19,0.144638,0.0,test -2020-01-23 09:00:00,machine-1-1_y_19,0.249607,0.0,test 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03:00:00,machine-1-1_y_19,0.031949,0.0,test -2020-01-24 04:00:00,machine-1-1_y_19,0.034747,0.0,test -2020-01-24 05:00:00,machine-1-1_y_19,0.067073,0.0,test -2020-01-24 06:00:00,machine-1-1_y_19,0.09153,0.0,test -2020-01-24 07:00:00,machine-1-1_y_19,0.107794,0.0,test -2020-01-24 08:00:00,machine-1-1_y_19,0.104943,0.0,test -2020-01-24 09:00:00,machine-1-1_y_19,0.124848,0.0,test -2020-01-24 10:00:00,machine-1-1_y_19,0.13126,0.0,test -2020-01-24 11:00:00,machine-1-1_y_19,0.137664,0.0,test -2020-01-24 12:00:00,machine-1-1_y_19,0.092022,0.0,test -2020-01-24 13:00:00,machine-1-1_y_19,0.073731,0.0,test -2020-01-24 14:00:00,machine-1-1_y_19,0.071135,0.0,test -2020-01-24 15:00:00,machine-1-1_y_19,0.080828,0.0,test -2020-01-24 16:00:00,machine-1-1_y_19,0.095083,0.0,test -2020-01-24 17:00:00,machine-1-1_y_19,0.115926,0.0,test -2020-01-24 18:00:00,machine-1-1_y_19,0.100811,0.0,test -2020-01-24 19:00:00,machine-1-1_y_19,0.109707,0.0,test -2020-01-24 20:00:00,machine-1-1_y_19,0.09496,0.0,test 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14:00:00,machine-1-1_y_19,0.102785,0.0,test -2020-01-25 15:00:00,machine-1-1_y_19,0.108321,0.0,test -2020-01-25 16:00:00,machine-1-1_y_19,0.119391,0.0,test -2020-01-25 17:00:00,machine-1-1_y_19,0.132585,0.0,test -2020-01-25 18:00:00,machine-1-1_y_19,0.1204,0.0,test -2020-01-25 19:00:00,machine-1-1_y_19,0.139173,0.0,test -2020-01-25 20:00:00,machine-1-1_y_19,0.13898,0.0,test -2020-01-25 21:00:00,machine-1-1_y_19,0.127269,0.0,test -2020-01-25 22:00:00,machine-1-1_y_19,0.111312,0.0,test -2020-01-25 23:00:00,machine-1-1_y_19,0.086565,0.0,test -2020-01-26 00:00:00,machine-1-1_y_19,0.063161,0.0,test -2020-01-26 01:00:00,machine-1-1_y_19,0.045449,0.0,test -2020-01-26 02:00:00,machine-1-1_y_19,0.04137,0.0,test -2020-01-26 03:00:00,machine-1-1_y_19,0.035309,0.0,test -2020-01-26 04:00:00,machine-1-1_y_19,0.032194,0.0,test -2020-01-26 05:00:00,machine-1-1_y_19,0.059143,0.0,test -2020-01-26 06:00:00,machine-1-1_y_19,0.090925,0.0,test -2020-01-26 07:00:00,machine-1-1_y_19,0.1279,0.0,test 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01:00:00,machine-1-1_y_19,0.041291,0.0,test -2020-01-27 02:00:00,machine-1-1_y_19,0.033966,0.0,test -2020-01-27 03:00:00,machine-1-1_y_19,0.031835,0.0,test -2020-01-27 04:00:00,machine-1-1_y_19,0.033273,0.0,test -2020-01-27 05:00:00,machine-1-1_y_19,0.06231,0.0,test -2020-01-27 06:00:00,machine-1-1_y_19,0.070986,0.0,test -2020-01-27 07:00:00,machine-1-1_y_19,0.093688,0.0,test -2020-01-27 08:00:00,machine-1-1_y_19,0.08667,0.0,test -2020-01-27 09:00:00,machine-1-1_y_19,0.082626,0.0,test -2020-01-27 10:00:00,machine-1-1_y_19,0.081907,0.0,test -2020-01-27 11:00:00,machine-1-1_y_19,0.098408,0.0,test -2020-01-27 12:00:00,machine-1-1_y_19,0.071705,0.0,test -2020-01-27 13:00:00,machine-1-1_y_19,0.05995,0.0,test -2020-01-27 14:00:00,machine-1-1_y_19,0.079688,0.0,test -2020-01-27 15:00:00,machine-1-1_y_19,0.078635,0.0,test -2020-01-27 16:00:00,machine-1-1_y_19,0.083512,0.0,test -2020-01-27 17:00:00,machine-1-1_y_19,0.093697,0.0,test -2020-01-27 18:00:00,machine-1-1_y_19,0.092951,0.0,test 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12:00:00,machine-1-1_y_19,0.074951,0.0,test -2020-01-28 13:00:00,machine-1-1_y_19,0.065371,0.0,test -2020-01-28 14:00:00,machine-1-1_y_19,0.073661,0.0,test -2020-01-28 15:00:00,machine-1-1_y_19,0.090618,0.0,test -2020-01-28 16:00:00,machine-1-1_y_19,0.093285,0.0,test -2020-01-28 17:00:00,machine-1-1_y_19,0.127392,0.0,test -2020-01-28 18:00:00,machine-1-1_y_19,0.154849,0.0,test -2020-01-28 19:00:00,machine-1-1_y_19,0.170622,0.0,test -2020-01-28 20:00:00,machine-1-1_y_19,0.145778,0.0,test -2020-01-28 21:00:00,machine-1-1_y_19,0.12419,0.0,test -2020-01-28 22:00:00,machine-1-1_y_19,0.10425,0.0,test -2020-01-28 23:00:00,machine-1-1_y_19,0.08053,0.0,test -2020-01-29 00:00:00,machine-1-1_y_19,0.054739,0.0,test -2020-01-29 01:00:00,machine-1-1_y_19,0.040414,0.0,test -2020-01-29 02:00:00,machine-1-1_y_19,0.037124,0.0,test -2020-01-29 03:00:00,machine-1-1_y_19,0.034414,0.0,test -2020-01-29 04:00:00,machine-1-1_y_19,0.035861,0.0,test -2020-01-29 05:00:00,machine-1-1_y_19,0.079644,0.0,test 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23:00:00,machine-1-1_y_19,0.086083,0.0,test -2020-01-30 00:00:00,machine-1-1_y_19,0.054353,0.0,test -2020-01-30 01:00:00,machine-1-1_y_19,0.039563,0.0,test -2020-01-30 02:00:00,machine-1-1_y_19,0.032835,0.0,test -2020-01-30 03:00:00,machine-1-1_y_19,0.029633,0.0,test -2020-01-30 04:00:00,machine-1-1_y_19,0.034809,0.0,test -2020-01-30 05:00:00,machine-1-1_y_19,0.09661,0.0,test -2020-01-30 06:00:00,machine-1-1_y_19,0.349419,0.0,test -2020-01-30 07:00:00,machine-1-1_y_19,0.458696,0.0,test -2020-01-30 08:00:00,machine-1-1_y_19,0.496864,0.0,test -2020-01-30 09:00:00,machine-1-1_y_19,0.544261,0.0,test -2020-01-30 10:00:00,machine-1-1_y_19,0.349814,0.0,test -2020-01-30 11:00:00,machine-1-1_y_19,0.356174,0.0,test -2020-01-30 12:00:00,machine-1-1_y_19,0.227475,0.0,test -2020-01-30 13:00:00,machine-1-1_y_19,0.152059,0.0,test -2020-01-30 14:00:00,machine-1-1_y_19,0.125584,0.0,test -2020-01-30 15:00:00,machine-1-1_y_19,0.132997,0.0,test -2020-01-30 16:00:00,machine-1-1_y_19,0.134787,0.0,test 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20:00:00,machine-1-1_y_2,0.128205,0.0,test -2020-01-21 21:00:00,machine-1-1_y_2,0.100334,0.0,test -2020-01-21 22:00:00,machine-1-1_y_2,0.133779,0.0,test -2020-01-21 23:00:00,machine-1-1_y_2,0.117057,0.0,test -2020-01-22 00:00:00,machine-1-1_y_2,0.09922,0.0,test -2020-01-22 01:00:00,machine-1-1_y_2,0.052397,0.0,test -2020-01-22 02:00:00,machine-1-1_y_2,0.047938,0.0,test -2020-01-22 03:00:00,machine-1-1_y_2,0.060201,0.0,test -2020-01-22 04:00:00,machine-1-1_y_2,0.045708,0.0,test -2020-01-22 05:00:00,machine-1-1_y_2,0.091416,0.0,test -2020-01-22 06:00:00,machine-1-1_y_2,0.144928,0.0,test -2020-01-22 07:00:00,machine-1-1_y_2,0.202899,0.0,test -2020-01-22 08:00:00,machine-1-1_y_2,0.160535,0.0,test -2020-01-22 09:00:00,machine-1-1_y_2,0.156076,0.0,test -2020-01-22 10:00:00,machine-1-1_y_2,0.136009,0.0,test -2020-01-22 11:00:00,machine-1-1_y_2,0.216276,0.0,test -2020-01-22 12:00:00,machine-1-1_y_2,0.103679,0.0,test -2020-01-22 13:00:00,machine-1-1_y_2,0.112598,0.0,test -2020-01-22 14:00:00,machine-1-1_y_2,0.085842,0.0,test -2020-01-22 15:00:00,machine-1-1_y_2,0.095875,0.0,test -2020-01-22 16:00:00,machine-1-1_y_2,0.117057,0.0,test -2020-01-22 17:00:00,machine-1-1_y_2,0.118172,0.0,test -2020-01-22 18:00:00,machine-1-1_y_2,0.12709,0.0,test -2020-01-22 19:00:00,machine-1-1_y_2,0.137124,0.0,test -2020-01-22 20:00:00,machine-1-1_y_2,0.132664,0.0,test -2020-01-22 21:00:00,machine-1-1_y_2,0.123746,0.0,test -2020-01-22 22:00:00,machine-1-1_y_2,0.098105,0.0,test -2020-01-22 23:00:00,machine-1-1_y_2,0.09476,0.0,test -2020-01-23 00:00:00,machine-1-1_y_2,0.091416,0.0,test -2020-01-23 01:00:00,machine-1-1_y_2,0.055741,0.0,test -2020-01-23 02:00:00,machine-1-1_y_2,0.053512,0.0,test -2020-01-23 03:00:00,machine-1-1_y_2,0.039019,0.0,test -2020-01-23 04:00:00,machine-1-1_y_2,0.044593,0.0,test -2020-01-23 05:00:00,machine-1-1_y_2,0.073579,0.0,test -2020-01-23 06:00:00,machine-1-1_y_2,0.128205,0.0,test -2020-01-23 07:00:00,machine-1-1_y_2,0.134894,0.0,test -2020-01-23 08:00:00,machine-1-1_y_2,0.157191,0.0,test -2020-01-23 09:00:00,machine-1-1_y_2,0.272018,0.0,test -2020-01-23 10:00:00,machine-1-1_y_2,0.26087,0.0,test -2020-01-23 11:00:00,machine-1-1_y_2,0.285396,0.0,test -2020-01-23 12:00:00,machine-1-1_y_2,0.250836,0.0,test -2020-01-23 13:00:00,machine-1-1_y_2,0.148272,0.0,test -2020-01-23 14:00:00,machine-1-1_y_2,0.112598,0.0,test -2020-01-23 15:00:00,machine-1-1_y_2,0.146042,0.0,test -2020-01-23 16:00:00,machine-1-1_y_2,0.093645,0.0,test -2020-01-23 17:00:00,machine-1-1_y_2,0.164994,0.0,test -2020-01-23 18:00:00,machine-1-1_y_2,0.190635,0.0,test -2020-01-23 19:00:00,machine-1-1_y_2,0.153846,0.0,test -2020-01-23 20:00:00,machine-1-1_y_2,0.138239,0.0,test -2020-01-23 21:00:00,machine-1-1_y_2,0.261984,0.0,test -2020-01-23 22:00:00,machine-1-1_y_2,0.130435,0.0,test -2020-01-23 23:00:00,machine-1-1_y_2,0.119287,0.0,test -2020-01-24 00:00:00,machine-1-1_y_2,0.081382,0.0,test -2020-01-24 01:00:00,machine-1-1_y_2,0.06243,0.0,test -2020-01-24 02:00:00,machine-1-1_y_2,0.051282,0.0,test -2020-01-24 03:00:00,machine-1-1_y_2,0.054627,0.0,test -2020-01-24 04:00:00,machine-1-1_y_2,0.071349,0.0,test -2020-01-24 05:00:00,machine-1-1_y_2,0.056856,0.0,test -2020-01-24 06:00:00,machine-1-1_y_2,0.105909,0.0,test -2020-01-24 07:00:00,machine-1-1_y_2,0.108138,0.0,test -2020-01-24 08:00:00,machine-1-1_y_2,0.12932,0.0,test -2020-01-24 09:00:00,machine-1-1_y_2,0.12709,0.0,test -2020-01-24 10:00:00,machine-1-1_y_2,0.128205,0.0,test -2020-01-24 11:00:00,machine-1-1_y_2,0.144928,0.0,test -2020-01-24 12:00:00,machine-1-1_y_2,0.107023,0.0,test -2020-01-24 13:00:00,machine-1-1_y_2,0.083612,0.0,test -2020-01-24 14:00:00,machine-1-1_y_2,0.085842,0.0,test -2020-01-24 15:00:00,machine-1-1_y_2,0.083612,0.0,test -2020-01-24 16:00:00,machine-1-1_y_2,0.130435,0.0,test -2020-01-24 17:00:00,machine-1-1_y_2,0.138239,0.0,test -2020-01-24 18:00:00,machine-1-1_y_2,0.123746,0.0,test -2020-01-24 19:00:00,machine-1-1_y_2,0.103679,0.0,test -2020-01-24 20:00:00,machine-1-1_y_2,0.102564,0.0,test -2020-01-24 21:00:00,machine-1-1_y_2,0.128205,0.0,test -2020-01-24 22:00:00,machine-1-1_y_2,0.118172,0.0,test -2020-01-24 23:00:00,machine-1-1_y_2,0.078038,0.0,test -2020-01-25 00:00:00,machine-1-1_y_2,0.068004,0.0,test -2020-01-25 01:00:00,machine-1-1_y_2,0.06243,0.0,test -2020-01-25 02:00:00,machine-1-1_y_2,0.043478,0.0,test -2020-01-25 03:00:00,machine-1-1_y_2,0.055741,0.0,test -2020-01-25 04:00:00,machine-1-1_y_2,0.054627,0.0,test -2020-01-25 05:00:00,machine-1-1_y_2,0.076923,0.0,test -2020-01-25 06:00:00,machine-1-1_y_2,0.146042,0.0,test -2020-01-25 07:00:00,machine-1-1_y_2,0.180602,0.0,test -2020-01-25 08:00:00,machine-1-1_y_2,0.255295,0.0,test -2020-01-25 09:00:00,machine-1-1_y_2,0.246377,0.0,test -2020-01-25 10:00:00,machine-1-1_y_2,0.212932,0.0,test -2020-01-25 11:00:00,machine-1-1_y_2,0.278707,0.0,test -2020-01-25 12:00:00,machine-1-1_y_2,0.212932,0.0,test -2020-01-25 13:00:00,machine-1-1_y_2,0.136009,0.0,test -2020-01-25 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02:00:00,machine-1-1_y_2,0.035674,0.0,test -2020-01-27 03:00:00,machine-1-1_y_2,0.037904,0.0,test -2020-01-27 04:00:00,machine-1-1_y_2,0.037904,0.0,test -2020-01-27 05:00:00,machine-1-1_y_2,0.051282,0.0,test -2020-01-27 06:00:00,machine-1-1_y_2,0.075808,0.0,test -2020-01-27 07:00:00,machine-1-1_y_2,0.093645,0.0,test -2020-01-27 08:00:00,machine-1-1_y_2,0.109253,0.0,test -2020-01-27 09:00:00,machine-1-1_y_2,0.098105,0.0,test -2020-01-27 10:00:00,machine-1-1_y_2,0.071349,0.0,test -2020-01-27 11:00:00,machine-1-1_y_2,0.092531,0.0,test -2020-01-27 12:00:00,machine-1-1_y_2,0.086957,0.0,test -2020-01-27 13:00:00,machine-1-1_y_2,0.056856,0.0,test -2020-01-27 14:00:00,machine-1-1_y_2,0.069119,0.0,test -2020-01-27 15:00:00,machine-1-1_y_2,0.092531,0.0,test -2020-01-27 16:00:00,machine-1-1_y_2,0.080268,0.0,test -2020-01-27 17:00:00,machine-1-1_y_2,0.09922,0.0,test -2020-01-27 18:00:00,machine-1-1_y_2,0.09922,0.0,test -2020-01-27 19:00:00,machine-1-1_y_2,0.103679,0.0,test -2020-01-27 20:00:00,machine-1-1_y_2,0.125975,0.0,test -2020-01-27 21:00:00,machine-1-1_y_2,0.134894,0.0,test -2020-01-27 22:00:00,machine-1-1_y_2,0.080268,0.0,test -2020-01-27 23:00:00,machine-1-1_y_2,0.06243,0.0,test -2020-01-28 00:00:00,machine-1-1_y_2,0.076923,0.0,test -2020-01-28 01:00:00,machine-1-1_y_2,0.047938,0.0,test -2020-01-28 02:00:00,machine-1-1_y_2,0.039019,0.0,test -2020-01-28 03:00:00,machine-1-1_y_2,0.054627,0.0,test -2020-01-28 04:00:00,machine-1-1_y_2,0.046823,0.0,test -2020-01-28 05:00:00,machine-1-1_y_2,0.074693,0.0,test -2020-01-28 06:00:00,machine-1-1_y_2,0.081382,0.0,test -2020-01-28 07:00:00,machine-1-1_y_2,0.072464,0.0,test -2020-01-28 08:00:00,machine-1-1_y_2,0.069119,0.0,test -2020-01-28 09:00:00,machine-1-1_y_2,0.125975,0.0,test -2020-01-28 10:00:00,machine-1-1_y_2,0.088071,0.0,test -2020-01-28 11:00:00,machine-1-1_y_2,0.093645,0.0,test -2020-01-28 12:00:00,machine-1-1_y_2,0.091416,0.0,test -2020-01-28 13:00:00,machine-1-1_y_2,0.070234,0.0,test -2020-01-28 14:00:00,machine-1-1_y_2,0.093645,0.0,test -2020-01-28 15:00:00,machine-1-1_y_2,0.119287,0.0,test -2020-01-28 16:00:00,machine-1-1_y_2,0.100334,0.0,test -2020-01-28 17:00:00,machine-1-1_y_2,0.115942,0.0,test -2020-01-28 18:00:00,machine-1-1_y_2,0.137124,0.0,test -2020-01-28 19:00:00,machine-1-1_y_2,0.151616,0.0,test -2020-01-28 20:00:00,machine-1-1_y_2,0.138239,0.0,test -2020-01-28 21:00:00,machine-1-1_y_2,0.154961,0.0,test -2020-01-28 22:00:00,machine-1-1_y_2,0.117057,0.0,test -2020-01-28 23:00:00,machine-1-1_y_2,0.076923,0.0,test -2020-01-29 00:00:00,machine-1-1_y_2,0.056856,0.0,test -2020-01-29 01:00:00,machine-1-1_y_2,0.037904,0.0,test -2020-01-29 02:00:00,machine-1-1_y_2,0.027871,0.0,test -2020-01-29 03:00:00,machine-1-1_y_2,0.045708,0.0,test -2020-01-29 04:00:00,machine-1-1_y_2,0.037904,0.0,test -2020-01-29 05:00:00,machine-1-1_y_2,0.09922,0.0,test -2020-01-29 06:00:00,machine-1-1_y_2,0.229654,0.0,test -2020-01-29 07:00:00,machine-1-1_y_2,0.316611,0.0,test -2020-01-29 08:00:00,machine-1-1_y_2,0.340022,0.0,test -2020-01-29 09:00:00,machine-1-1_y_2,0.521739,0.0,test -2020-01-29 10:00:00,machine-1-1_y_2,0.429208,0.0,test -2020-01-29 11:00:00,machine-1-1_y_2,0.442586,0.0,test -2020-01-29 12:00:00,machine-1-1_y_2,0.438127,0.0,test -2020-01-29 13:00:00,machine-1-1_y_2,0.123746,0.0,test -2020-01-29 14:00:00,machine-1-1_y_2,0.113712,0.0,test -2020-01-29 15:00:00,machine-1-1_y_2,0.115942,0.0,test -2020-01-29 16:00:00,machine-1-1_y_2,0.150502,0.0,test -2020-01-29 17:00:00,machine-1-1_y_2,0.141583,0.0,test -2020-01-29 18:00:00,machine-1-1_y_2,0.147157,0.0,test -2020-01-29 19:00:00,machine-1-1_y_2,0.114827,0.0,test -2020-01-29 20:00:00,machine-1-1_y_2,0.136009,0.0,test -2020-01-29 21:00:00,machine-1-1_y_2,0.16165,0.0,test -2020-01-29 22:00:00,machine-1-1_y_2,0.136009,0.0,test -2020-01-29 23:00:00,machine-1-1_y_2,0.082497,0.0,test -2020-01-30 00:00:00,machine-1-1_y_2,0.045708,0.0,test -2020-01-30 01:00:00,machine-1-1_y_2,0.069119,0.0,test -2020-01-30 02:00:00,machine-1-1_y_2,0.050167,0.0,test -2020-01-30 03:00:00,machine-1-1_y_2,0.039019,0.0,test -2020-01-30 04:00:00,machine-1-1_y_2,0.031215,0.0,test -2020-01-30 05:00:00,machine-1-1_y_2,0.149387,0.0,test -2020-01-30 06:00:00,machine-1-1_y_2,0.346711,0.0,test -2020-01-30 07:00:00,machine-1-1_y_2,0.442586,0.0,test -2020-01-30 08:00:00,machine-1-1_y_2,0.509476,0.0,test -2020-01-30 09:00:00,machine-1-1_y_2,0.500557,0.0,test -2020-01-30 10:00:00,machine-1-1_y_2,0.329989,0.0,test -2020-01-30 11:00:00,machine-1-1_y_2,0.341137,0.0,test -2020-01-30 12:00:00,machine-1-1_y_2,0.22631,0.0,test -2020-01-30 13:00:00,machine-1-1_y_2,0.162765,0.0,test -2020-01-30 14:00:00,machine-1-1_y_2,0.115942,0.0,test -2020-01-30 15:00:00,machine-1-1_y_2,0.12709,0.0,test -2020-01-30 16:00:00,machine-1-1_y_2,0.128205,0.0,test -2020-01-30 17:00:00,machine-1-1_y_2,0.166109,0.0,test -2020-01-30 18:00:00,machine-1-1_y_2,0.147157,0.0,test -2020-01-30 19:00:00,machine-1-1_y_2,0.150502,0.0,test -2020-01-30 20:00:00,machine-1-1_y_2,0.132664,0.0,test -2020-01-30 21:00:00,machine-1-1_y_2,0.16388,0.0,test -2020-01-30 22:00:00,machine-1-1_y_2,0.123746,0.0,test -2020-01-30 23:00:00,machine-1-1_y_2,0.100334,0.0,test -2020-01-31 00:00:00,machine-1-1_y_2,0.061315,0.0,test -2020-01-31 01:00:00,machine-1-1_y_2,0.059086,0.0,test -2020-01-31 02:00:00,machine-1-1_y_2,0.056856,0.0,test -2020-01-31 03:00:00,machine-1-1_y_2,0.059086,0.0,test -2020-01-31 04:00:00,machine-1-1_y_2,0.12709,0.0,test -2020-01-31 05:00:00,machine-1-1_y_2,0.225195,0.0,test -2020-01-31 06:00:00,machine-1-1_y_2,0.263099,0.0,test -2020-01-31 07:00:00,machine-1-1_y_2,0.496098,0.0,test -2020-01-31 08:00:00,machine-1-1_y_2,0.523969,0.0,test -2020-01-31 09:00:00,machine-1-1_y_2,0.521739,0.0,test -2020-01-31 10:00:00,machine-1-1_y_2,0.164994,0.0,test -2020-01-31 11:00:00,machine-1-1_y_2,0.16388,0.0,test -2020-01-31 12:00:00,machine-1-1_y_2,0.216276,0.0,test -2020-01-31 13:00:00,machine-1-1_y_2,0.147157,0.0,test -2020-01-31 14:00:00,machine-1-1_y_2,0.12709,0.0,test -2020-01-31 15:00:00,machine-1-1_y_2,0.136009,0.0,test -2020-01-31 16:00:00,machine-1-1_y_2,0.170569,0.0,test -2020-01-31 17:00:00,machine-1-1_y_2,0.107023,0.0,test -2020-01-31 18:00:00,machine-1-1_y_2,0.09476,1.0,test -2020-01-31 19:00:00,machine-1-1_y_2,0.083612,1.0,test -2020-01-31 20:00:00,machine-1-1_y_2,0.086957,1.0,test -2020-01-31 21:00:00,machine-1-1_y_2,0.075808,1.0,test -2020-01-31 22:00:00,machine-1-1_y_2,0.114827,1.0,test -2020-01-31 23:00:00,machine-1-1_y_2,0.180602,1.0,test -2020-02-01 00:00:00,machine-1-1_y_2,0.350056,1.0,test -2020-02-01 01:00:00,machine-1-1_y_2,0.57748,1.0,test -2020-02-01 02:00:00,machine-1-1_y_2,0.435897,1.0,test -2020-02-01 03:00:00,machine-1-1_y_2,0.493868,1.0,test -2020-02-01 04:00:00,machine-1-1_y_2,0.331104,0.0,test -2020-02-01 05:00:00,machine-1-1_y_2,0.189521,0.0,test -2020-02-01 06:00:00,machine-1-1_y_2,0.250836,0.0,test -2020-02-01 07:00:00,machine-1-1_y_2,0.211817,0.0,test -2020-02-01 08:00:00,machine-1-1_y_2,0.272018,0.0,test -2020-02-01 09:00:00,machine-1-1_y_2,0.257525,0.0,test -2020-02-01 10:00:00,machine-1-1_y_2,0.246377,0.0,test -2020-02-01 11:00:00,machine-1-1_y_2,0.246377,0.0,test -2020-02-01 12:00:00,machine-1-1_y_2,0.154961,0.0,test -2020-02-01 13:00:00,machine-1-1_y_2,0.146042,1.0,test -2020-02-01 14:00:00,machine-1-1_y_2,0.102564,1.0,test -2020-02-01 15:00:00,machine-1-1_y_2,0.070234,1.0,test -2020-02-01 16:00:00,machine-1-1_y_2,0.09922,1.0,test -2020-02-01 17:00:00,machine-1-1_y_2,0.235229,1.0,test -2020-02-01 18:00:00,machine-1-1_y_2,0.285396,1.0,test -2020-02-01 19:00:00,machine-1-1_y_2,0.491639,1.0,test -2020-02-01 20:00:00,machine-1-1_y_2,0.852843,1.0,test -2020-02-01 21:00:00,machine-1-1_y_2,0.994426,1.0,test -2020-02-01 22:00:00,machine-1-1_y_2,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_2,0.272018,0.0,test -2020-02-02 00:00:00,machine-1-1_y_2,0.19175,0.0,test -2020-02-02 01:00:00,machine-1-1_y_2,0.222965,0.0,test -2020-02-02 02:00:00,machine-1-1_y_2,0.229654,0.0,test -2020-02-02 03:00:00,machine-1-1_y_2,0.238573,0.0,test -2020-02-02 04:00:00,machine-1-1_y_2,0.248606,0.0,test -2020-02-02 05:00:00,machine-1-1_y_2,0.232999,0.0,test -2020-02-02 06:00:00,machine-1-1_y_2,0.162765,0.0,test -2020-02-02 07:00:00,machine-1-1_y_2,0.108138,1.0,test -2020-02-02 08:00:00,machine-1-1_y_2,0.124861,1.0,test -2020-02-02 09:00:00,machine-1-1_y_2,0.091416,1.0,test -2020-02-02 10:00:00,machine-1-1_y_2,0.076923,1.0,test -2020-02-02 11:00:00,machine-1-1_y_2,0.26087,1.0,test -2020-02-02 12:00:00,machine-1-1_y_2,0.298774,1.0,test -2020-02-02 13:00:00,machine-1-1_y_2,0.462653,1.0,test -2020-02-02 14:00:00,machine-1-1_y_2,0.726867,1.0,test -2020-02-02 15:00:00,machine-1-1_y_2,0.51728,1.0,test -2020-02-02 16:00:00,machine-1-1_y_2,0.28874,0.0,test -2020-02-02 17:00:00,machine-1-1_y_2,0.243032,0.0,test -2020-02-02 18:00:00,machine-1-1_y_2,0.117057,0.0,test -2020-02-02 19:00:00,machine-1-1_y_2,0.140468,0.0,test -2020-02-02 20:00:00,machine-1-1_y_2,0.118172,0.0,test -2020-02-02 21:00:00,machine-1-1_y_2,0.09922,0.0,test -2020-02-02 22:00:00,machine-1-1_y_2,0.142698,0.0,test -2020-02-02 23:00:00,machine-1-1_y_2,0.141583,0.0,test -2020-02-03 00:00:00,machine-1-1_y_2,0.125975,0.0,test -2020-02-03 01:00:00,machine-1-1_y_2,0.13155,0.0,test -2020-02-03 02:00:00,machine-1-1_y_2,0.125975,0.0,test -2020-02-03 03:00:00,machine-1-1_y_2,0.110368,0.0,test -2020-02-03 04:00:00,machine-1-1_y_2,0.114827,0.0,test -2020-02-03 05:00:00,machine-1-1_y_2,0.084727,1.0,test -2020-02-03 06:00:00,machine-1-1_y_2,0.061315,1.0,test -2020-02-03 07:00:00,machine-1-1_y_2,0.06243,1.0,test -2020-02-03 08:00:00,machine-1-1_y_2,0.089186,1.0,test -2020-02-03 09:00:00,machine-1-1_y_2,0.047938,1.0,test -2020-02-03 10:00:00,machine-1-1_y_2,0.080268,1.0,test -2020-02-03 11:00:00,machine-1-1_y_2,0.12932,1.0,test -2020-02-03 12:00:00,machine-1-1_y_2,0.238573,1.0,test -2020-02-03 13:00:00,machine-1-1_y_2,0.285396,1.0,test -2020-02-03 14:00:00,machine-1-1_y_2,0.426979,1.0,test -2020-02-03 15:00:00,machine-1-1_y_2,0.487179,1.0,test -2020-02-03 16:00:00,machine-1-1_y_2,0.680045,1.0,test -2020-02-03 17:00:00,machine-1-1_y_2,0.641026,1.0,test -2020-02-03 18:00:00,machine-1-1_y_2,0.162765,0.0,test -2020-02-03 19:00:00,machine-1-1_y_2,0.156076,0.0,test -2020-02-03 20:00:00,machine-1-1_y_2,0.164994,0.0,test -2020-02-03 21:00:00,machine-1-1_y_2,0.137124,0.0,test -2020-02-03 22:00:00,machine-1-1_y_2,0.134894,0.0,test -2020-02-03 23:00:00,machine-1-1_y_2,0.170569,0.0,test -2020-02-04 00:00:00,machine-1-1_y_2,0.177258,0.0,test -2020-02-04 01:00:00,machine-1-1_y_2,0.218506,0.0,test -2020-02-04 02:00:00,machine-1-1_y_2,0.179487,0.0,test -2020-02-04 03:00:00,machine-1-1_y_2,0.152731,0.0,test -2020-02-04 04:00:00,machine-1-1_y_2,0.098105,0.0,test -2020-02-04 05:00:00,machine-1-1_y_2,0.074693,1.0,test -2020-02-04 06:00:00,machine-1-1_y_2,0.083612,1.0,test -2020-02-04 07:00:00,machine-1-1_y_2,0.093645,1.0,test -2020-02-04 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07:00:00,machine-1-1_y_20,0.246447,0.0,test -2020-01-22 08:00:00,machine-1-1_y_20,0.227479,0.0,test -2020-01-22 09:00:00,machine-1-1_y_20,0.173874,0.0,test -2020-01-22 10:00:00,machine-1-1_y_20,0.142535,0.0,test -2020-01-22 11:00:00,machine-1-1_y_20,0.146109,0.0,test -2020-01-22 12:00:00,machine-1-1_y_20,0.098084,0.0,test -2020-01-22 13:00:00,machine-1-1_y_20,0.113368,0.0,test -2020-01-22 14:00:00,machine-1-1_y_20,0.10229,0.0,test -2020-01-22 15:00:00,machine-1-1_y_20,0.102482,0.0,test -2020-01-22 16:00:00,machine-1-1_y_20,0.108887,0.0,test -2020-01-22 17:00:00,machine-1-1_y_20,0.136048,0.0,test -2020-01-22 18:00:00,machine-1-1_y_20,0.145751,0.0,test -2020-01-22 19:00:00,machine-1-1_y_20,0.148198,0.0,test -2020-01-22 20:00:00,machine-1-1_y_20,0.139896,0.0,test -2020-01-22 21:00:00,machine-1-1_y_20,0.126618,0.0,test -2020-01-22 22:00:00,machine-1-1_y_20,0.099074,0.0,test -2020-01-22 23:00:00,machine-1-1_y_20,0.072903,0.0,test -2020-01-23 00:00:00,machine-1-1_y_20,0.051873,0.0,test -2020-01-23 01:00:00,machine-1-1_y_20,0.04063,0.0,test -2020-01-23 02:00:00,machine-1-1_y_20,0.032053,0.0,test -2020-01-23 03:00:00,machine-1-1_y_20,0.030871,0.0,test -2020-01-23 04:00:00,machine-1-1_y_20,0.038211,0.0,test -2020-01-23 05:00:00,machine-1-1_y_20,0.092613,0.0,test -2020-01-23 06:00:00,machine-1-1_y_20,0.139676,0.0,test -2020-01-23 07:00:00,machine-1-1_y_20,0.167139,0.0,test -2020-01-23 08:00:00,machine-1-1_y_20,0.165929,0.0,test -2020-01-23 09:00:00,machine-1-1_y_20,0.35506,0.0,test -2020-01-23 10:00:00,machine-1-1_y_20,0.278858,0.0,test -2020-01-23 11:00:00,machine-1-1_y_20,0.393793,0.0,test -2020-01-23 12:00:00,machine-1-1_y_20,0.327927,0.0,test -2020-01-23 13:00:00,machine-1-1_y_20,0.142755,0.0,test -2020-01-23 14:00:00,machine-1-1_y_20,0.118207,0.0,test -2020-01-23 15:00:00,machine-1-1_y_20,0.145532,0.0,test -2020-01-23 16:00:00,machine-1-1_y_20,0.126426,0.0,test -2020-01-23 17:00:00,machine-1-1_y_20,0.156967,0.0,test -2020-01-23 18:00:00,machine-1-1_y_20,0.146136,0.0,test -2020-01-23 19:00:00,machine-1-1_y_20,0.173434,0.0,test -2020-01-23 20:00:00,machine-1-1_y_20,0.163125,0.0,test -2020-01-23 21:00:00,machine-1-1_y_20,0.159606,0.0,test -2020-01-23 22:00:00,machine-1-1_y_20,0.123347,0.0,test -2020-01-23 23:00:00,machine-1-1_y_20,0.088655,0.0,test -2020-01-24 00:00:00,machine-1-1_y_20,0.06034,0.0,test -2020-01-24 01:00:00,machine-1-1_y_20,0.046513,0.0,test -2020-01-24 02:00:00,machine-1-1_y_20,0.037771,0.0,test -2020-01-24 03:00:00,machine-1-1_y_20,0.035544,0.0,test -2020-01-24 04:00:00,machine-1-1_y_20,0.04074,0.0,test -2020-01-24 05:00:00,machine-1-1_y_20,0.08948,0.0,test -2020-01-24 06:00:00,machine-1-1_y_20,0.118811,0.0,test -2020-01-24 07:00:00,machine-1-1_y_20,0.139896,0.0,test -2020-01-24 08:00:00,machine-1-1_y_20,0.124364,0.0,test -2020-01-24 09:00:00,machine-1-1_y_20,0.1507,0.0,test -2020-01-24 10:00:00,machine-1-1_y_20,0.156335,0.0,test -2020-01-24 11:00:00,machine-1-1_y_20,0.145092,0.0,test -2020-01-24 12:00:00,machine-1-1_y_20,0.097534,0.0,test -2020-01-24 13:00:00,machine-1-1_y_20,0.093878,0.0,test -2020-01-24 14:00:00,machine-1-1_y_20,0.079336,0.0,test -2020-01-24 15:00:00,machine-1-1_y_20,0.105781,0.0,test -2020-01-24 16:00:00,machine-1-1_y_20,0.113176,0.0,test -2020-01-24 17:00:00,machine-1-1_y_20,0.144954,0.0,test -2020-01-24 18:00:00,machine-1-1_y_20,0.115458,0.0,test -2020-01-24 19:00:00,machine-1-1_y_20,0.13734,0.0,test -2020-01-24 20:00:00,machine-1-1_y_20,0.106496,0.0,test -2020-01-24 21:00:00,machine-1-1_y_20,0.128158,0.0,test -2020-01-24 22:00:00,machine-1-1_y_20,0.102097,0.0,test -2020-01-24 23:00:00,machine-1-1_y_20,0.078126,0.0,test -2020-01-25 00:00:00,machine-1-1_y_20,0.057454,0.0,test -2020-01-25 01:00:00,machine-1-1_y_20,0.043159,0.0,test -2020-01-25 02:00:00,machine-1-1_y_20,0.039778,0.0,test -2020-01-25 03:00:00,machine-1-1_y_20,0.03351,0.0,test -2020-01-25 04:00:00,machine-1-1_y_20,0.038293,0.0,test -2020-01-25 05:00:00,machine-1-1_y_20,0.08959,0.0,test -2020-01-25 06:00:00,machine-1-1_y_20,0.185804,0.0,test -2020-01-25 07:00:00,machine-1-1_y_20,0.198422,0.0,test -2020-01-25 08:00:00,machine-1-1_y_20,0.230008,0.0,test -2020-01-25 09:00:00,machine-1-1_y_20,0.353603,0.0,test -2020-01-25 10:00:00,machine-1-1_y_20,0.249993,0.0,test -2020-01-25 11:00:00,machine-1-1_y_20,0.30709,0.0,test -2020-01-25 12:00:00,machine-1-1_y_20,0.24565,0.0,test -2020-01-25 13:00:00,machine-1-1_y_20,0.146026,0.0,test -2020-01-25 14:00:00,machine-1-1_y_20,0.112874,0.0,test -2020-01-25 15:00:00,machine-1-1_y_20,0.131484,0.0,test -2020-01-25 16:00:00,machine-1-1_y_20,0.145944,0.0,test -2020-01-25 17:00:00,machine-1-1_y_20,0.165847,0.0,test -2020-01-25 18:00:00,machine-1-1_y_20,0.135415,0.0,test -2020-01-25 19:00:00,machine-1-1_y_20,0.158452,0.0,test -2020-01-25 20:00:00,machine-1-1_y_20,0.159331,0.0,test -2020-01-25 21:00:00,machine-1-1_y_20,0.139704,0.0,test -2020-01-25 22:00:00,machine-1-1_y_20,0.113038,0.0,test -2020-01-25 23:00:00,machine-1-1_y_20,0.092916,0.0,test -2020-01-26 00:00:00,machine-1-1_y_20,0.064931,0.0,test -2020-01-26 01:00:00,machine-1-1_y_20,0.048382,0.0,test -2020-01-26 02:00:00,machine-1-1_y_20,0.043956,0.0,test -2020-01-26 03:00:00,machine-1-1_y_20,0.038183,0.0,test -2020-01-26 04:00:00,machine-1-1_y_20,0.038211,0.0,test -2020-01-26 05:00:00,machine-1-1_y_20,0.07579,0.0,test -2020-01-26 06:00:00,machine-1-1_y_20,0.112516,0.0,test -2020-01-26 07:00:00,machine-1-1_y_20,0.168788,0.0,test -2020-01-26 08:00:00,machine-1-1_y_20,0.124804,0.0,test -2020-01-26 09:00:00,machine-1-1_y_20,0.132859,0.0,test -2020-01-26 10:00:00,machine-1-1_y_20,0.134838,0.0,test -2020-01-26 11:00:00,machine-1-1_y_20,0.118811,0.0,test -2020-01-26 12:00:00,machine-1-1_y_20,0.09649,0.0,test -2020-01-26 13:00:00,machine-1-1_y_20,0.112626,0.0,test -2020-01-26 14:00:00,machine-1-1_y_20,0.123622,0.0,test -2020-01-26 15:00:00,machine-1-1_y_20,0.151799,0.0,test -2020-01-26 16:00:00,machine-1-1_y_20,0.146109,0.0,test -2020-01-26 17:00:00,machine-1-1_y_20,0.127443,0.0,test -2020-01-26 18:00:00,machine-1-1_y_20,0.139264,0.0,test -2020-01-26 19:00:00,machine-1-1_y_20,0.134398,0.0,test -2020-01-26 20:00:00,machine-1-1_y_20,0.135773,0.0,test -2020-01-26 21:00:00,machine-1-1_y_20,0.161256,0.0,test -2020-01-26 22:00:00,machine-1-1_y_20,0.110427,0.0,test -2020-01-26 23:00:00,machine-1-1_y_20,0.083267,0.0,test -2020-01-27 00:00:00,machine-1-1_y_20,0.062347,0.0,test -2020-01-27 01:00:00,machine-1-1_y_20,0.044616,0.0,test -2020-01-27 02:00:00,machine-1-1_y_20,0.036424,0.0,test -2020-01-27 03:00:00,machine-1-1_y_20,0.03516,0.0,test -2020-01-27 04:00:00,machine-1-1_y_20,0.039091,0.0,test -2020-01-27 05:00:00,machine-1-1_y_20,0.076367,0.0,test -2020-01-27 06:00:00,machine-1-1_y_20,0.085219,0.0,test -2020-01-27 07:00:00,machine-1-1_y_20,0.111307,0.0,test -2020-01-27 08:00:00,machine-1-1_y_20,0.098331,0.0,test -2020-01-27 09:00:00,machine-1-1_y_20,0.093521,0.0,test -2020-01-27 10:00:00,machine-1-1_y_20,0.098386,0.0,test -2020-01-27 11:00:00,machine-1-1_y_20,0.126563,0.0,test -2020-01-27 12:00:00,machine-1-1_y_20,0.081233,0.0,test -2020-01-27 13:00:00,machine-1-1_y_20,0.069439,0.0,test -2020-01-27 14:00:00,machine-1-1_y_20,0.09506,0.0,test -2020-01-27 15:00:00,machine-1-1_y_20,0.087418,0.0,test -2020-01-27 16:00:00,machine-1-1_y_20,0.103994,0.0,test -2020-01-27 17:00:00,machine-1-1_y_20,0.105094,0.0,test -2020-01-27 18:00:00,machine-1-1_y_20,0.101795,0.0,test -2020-01-27 19:00:00,machine-1-1_y_20,0.101603,0.0,test -2020-01-27 20:00:00,machine-1-1_y_20,0.114056,0.0,test -2020-01-27 21:00:00,machine-1-1_y_20,0.104791,0.0,test -2020-01-27 22:00:00,machine-1-1_y_20,0.093851,0.0,test -2020-01-27 23:00:00,machine-1-1_y_20,0.069302,0.0,test -2020-01-28 00:00:00,machine-1-1_y_20,0.048795,0.0,test -2020-01-28 01:00:00,machine-1-1_y_20,0.039146,0.0,test -2020-01-28 02:00:00,machine-1-1_y_20,0.039008,0.0,test -2020-01-28 03:00:00,machine-1-1_y_20,0.036232,0.0,test -2020-01-28 04:00:00,machine-1-1_y_20,0.036946,0.0,test -2020-01-28 05:00:00,machine-1-1_y_20,0.062402,0.0,test -2020-01-28 06:00:00,machine-1-1_y_20,0.106798,0.0,test -2020-01-28 07:00:00,machine-1-1_y_20,0.110784,0.0,test -2020-01-28 08:00:00,machine-1-1_y_20,0.093438,0.0,test -2020-01-28 09:00:00,machine-1-1_y_20,0.112709,0.0,test -2020-01-28 10:00:00,machine-1-1_y_20,0.0955,0.0,test -2020-01-28 11:00:00,machine-1-1_y_20,0.099156,0.0,test -2020-01-28 12:00:00,machine-1-1_y_20,0.101795,0.0,test -2020-01-28 13:00:00,machine-1-1_y_20,0.081453,0.0,test -2020-01-28 14:00:00,machine-1-1_y_20,0.08192,0.0,test -2020-01-28 15:00:00,machine-1-1_y_20,0.103912,0.0,test -2020-01-28 16:00:00,machine-1-1_y_20,0.106633,0.0,test -2020-01-28 17:00:00,machine-1-1_y_20,0.134426,0.0,test -2020-01-28 18:00:00,machine-1-1_y_20,0.162273,0.0,test -2020-01-28 19:00:00,machine-1-1_y_20,0.180911,0.0,test -2020-01-28 20:00:00,machine-1-1_y_20,0.158782,0.0,test -2020-01-28 21:00:00,machine-1-1_y_20,0.123952,0.0,test -2020-01-28 22:00:00,machine-1-1_y_20,0.104874,0.0,test -2020-01-28 23:00:00,machine-1-1_y_20,0.08093,0.0,test -2020-01-29 00:00:00,machine-1-1_y_20,0.055035,0.0,test -2020-01-29 01:00:00,machine-1-1_y_20,0.043846,0.0,test -2020-01-29 02:00:00,machine-1-1_y_20,0.040548,0.0,test -2020-01-29 03:00:00,machine-1-1_y_20,0.038651,0.0,test -2020-01-29 04:00:00,machine-1-1_y_20,0.042912,0.0,test -2020-01-29 05:00:00,machine-1-1_y_20,0.098964,0.0,test -2020-01-29 06:00:00,machine-1-1_y_20,0.31289,0.0,test -2020-01-29 07:00:00,machine-1-1_y_20,0.35473,0.0,test -2020-01-29 08:00:00,machine-1-1_y_20,0.357451,0.0,test -2020-01-29 09:00:00,machine-1-1_y_20,0.460483,0.0,test -2020-01-29 10:00:00,machine-1-1_y_20,0.418809,0.0,test -2020-01-29 11:00:00,machine-1-1_y_20,0.452401,0.0,test -2020-01-29 12:00:00,machine-1-1_y_20,0.454793,0.0,test -2020-01-29 13:00:00,machine-1-1_y_20,0.160926,0.0,test -2020-01-29 14:00:00,machine-1-1_y_20,0.121505,0.0,test -2020-01-29 15:00:00,machine-1-1_y_20,0.142728,0.0,test -2020-01-29 16:00:00,machine-1-1_y_20,0.135718,0.0,test -2020-01-29 17:00:00,machine-1-1_y_20,0.138329,0.0,test -2020-01-29 18:00:00,machine-1-1_y_20,0.140776,0.0,test -2020-01-29 19:00:00,machine-1-1_y_20,0.1358,0.0,test -2020-01-29 20:00:00,machine-1-1_y_20,0.17577,0.0,test -2020-01-29 21:00:00,machine-1-1_y_20,0.174258,0.0,test -2020-01-29 22:00:00,machine-1-1_y_20,0.123897,0.0,test -2020-01-29 23:00:00,machine-1-1_y_20,0.091514,0.0,test -2020-01-30 00:00:00,machine-1-1_y_20,0.059351,0.0,test -2020-01-30 01:00:00,machine-1-1_y_20,0.04184,0.0,test -2020-01-30 02:00:00,machine-1-1_y_20,0.036754,0.0,test -2020-01-30 03:00:00,machine-1-1_y_20,0.035022,0.0,test -2020-01-30 04:00:00,machine-1-1_y_20,0.042527,0.0,test -2020-01-30 05:00:00,machine-1-1_y_20,0.128103,0.0,test -2020-01-30 06:00:00,machine-1-1_y_20,0.408857,0.0,test -2020-01-30 07:00:00,machine-1-1_y_20,0.513979,0.0,test 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01:00:00,machine-1-1_y_20,0.042774,0.0,test -2020-01-31 02:00:00,machine-1-1_y_20,0.037001,0.0,test -2020-01-31 03:00:00,machine-1-1_y_20,0.061,0.0,test -2020-01-31 04:00:00,machine-1-1_y_20,0.151002,0.0,test -2020-01-31 05:00:00,machine-1-1_y_20,0.278967,0.0,test -2020-01-31 06:00:00,machine-1-1_y_20,0.340517,0.0,test -2020-01-31 07:00:00,machine-1-1_y_20,0.634797,0.0,test -2020-01-31 08:00:00,machine-1-1_y_20,0.619375,0.0,test -2020-01-31 09:00:00,machine-1-1_y_20,0.504027,0.0,test -2020-01-31 10:00:00,machine-1-1_y_20,0.205514,0.0,test -2020-01-31 11:00:00,machine-1-1_y_20,0.16953,0.0,test -2020-01-31 12:00:00,machine-1-1_y_20,0.295901,0.0,test -2020-01-31 13:00:00,machine-1-1_y_20,0.19133,0.0,test -2020-01-31 14:00:00,machine-1-1_y_20,0.138219,0.0,test -2020-01-31 15:00:00,machine-1-1_y_20,0.134123,0.0,test -2020-01-31 16:00:00,machine-1-1_y_20,0.157435,0.0,test -2020-01-31 17:00:00,machine-1-1_y_20,0.126921,0.0,test -2020-01-31 18:00:00,machine-1-1_y_20,0.087143,1.0,test 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12:00:00,machine-1-1_y_20,0.156472,0.0,test -2020-02-01 13:00:00,machine-1-1_y_20,0.098771,1.0,test -2020-02-01 14:00:00,machine-1-1_y_20,0.066993,1.0,test -2020-02-01 15:00:00,machine-1-1_y_20,0.050444,1.0,test -2020-02-01 16:00:00,machine-1-1_y_20,0.066663,1.0,test -2020-02-01 17:00:00,machine-1-1_y_20,0.215906,1.0,test -2020-02-01 18:00:00,machine-1-1_y_20,0.344064,1.0,test -2020-02-01 19:00:00,machine-1-1_y_20,0.643978,1.0,test -2020-02-01 20:00:00,machine-1-1_y_20,0.783902,1.0,test -2020-02-01 21:00:00,machine-1-1_y_20,0.962559,1.0,test -2020-02-01 22:00:00,machine-1-1_y_20,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_20,0.339473,0.0,test -2020-02-02 00:00:00,machine-1-1_y_20,0.199714,0.0,test -2020-02-02 01:00:00,machine-1-1_y_20,0.23108,0.0,test -2020-02-02 02:00:00,machine-1-1_y_20,0.247107,0.0,test -2020-02-02 03:00:00,machine-1-1_y_20,0.23897,0.0,test -2020-02-02 04:00:00,machine-1-1_y_20,0.26591,0.0,test -2020-02-02 05:00:00,machine-1-1_y_20,0.224428,0.0,test -2020-02-02 06:00:00,machine-1-1_y_20,0.168486,0.0,test -2020-02-02 07:00:00,machine-1-1_y_20,0.101163,1.0,test -2020-02-02 08:00:00,machine-1-1_y_20,0.072848,1.0,test -2020-02-02 09:00:00,machine-1-1_y_20,0.056959,1.0,test -2020-02-02 10:00:00,machine-1-1_y_20,0.049372,1.0,test -2020-02-02 11:00:00,machine-1-1_y_20,0.16439,1.0,test -2020-02-02 12:00:00,machine-1-1_y_20,0.348572,1.0,test -2020-02-02 13:00:00,machine-1-1_y_20,0.491327,1.0,test -2020-02-02 14:00:00,machine-1-1_y_20,0.807818,1.0,test -2020-02-02 15:00:00,machine-1-1_y_20,0.576656,1.0,test -2020-02-02 16:00:00,machine-1-1_y_20,0.270995,0.0,test -2020-02-02 17:00:00,machine-1-1_y_20,0.175605,0.0,test -2020-02-02 18:00:00,machine-1-1_y_20,0.122385,0.0,test -2020-02-02 19:00:00,machine-1-1_y_20,0.106743,0.0,test -2020-02-02 20:00:00,machine-1-1_y_20,0.101713,0.0,test -2020-02-02 21:00:00,machine-1-1_y_20,0.111059,0.0,test -2020-02-02 22:00:00,machine-1-1_y_20,0.158397,0.0,test -2020-02-02 23:00:00,machine-1-1_y_20,0.161173,0.0,test 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17:00:00,machine-1-1_y_20,0.783215,1.0,test -2020-02-03 18:00:00,machine-1-1_y_20,0.193941,0.0,test -2020-02-03 19:00:00,machine-1-1_y_20,0.167908,0.0,test -2020-02-03 20:00:00,machine-1-1_y_20,0.145779,0.0,test -2020-02-03 21:00:00,machine-1-1_y_20,0.138879,0.0,test -2020-02-03 22:00:00,machine-1-1_y_20,0.144789,0.0,test -2020-02-03 23:00:00,machine-1-1_y_20,0.192072,0.0,test -2020-02-04 00:00:00,machine-1-1_y_20,0.206257,0.0,test -2020-02-04 01:00:00,machine-1-1_y_20,0.218875,0.0,test -2020-02-04 02:00:00,machine-1-1_y_20,0.181048,0.0,test -2020-02-04 03:00:00,machine-1-1_y_20,0.141958,0.0,test -2020-02-04 04:00:00,machine-1-1_y_20,0.111279,0.0,test -2020-02-04 05:00:00,machine-1-1_y_20,0.066993,1.0,test -2020-02-04 06:00:00,machine-1-1_y_20,0.053001,1.0,test -2020-02-04 07:00:00,machine-1-1_y_20,0.044973,1.0,test -2020-02-04 08:00:00,machine-1-1_y_20,0.060038,1.0,test -2020-02-04 09:00:00,machine-1-1_y_20,0.163098,1.0,test -2020-02-04 10:00:00,machine-1-1_y_20,0.304506,1.0,test 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15:00:00,machine-1-1_y_21,0.124978,0.0,test -2020-01-26 16:00:00,machine-1-1_y_21,0.120562,0.0,test -2020-01-26 17:00:00,machine-1-1_y_21,0.103018,0.0,test -2020-01-26 18:00:00,machine-1-1_y_21,0.114574,0.0,test -2020-01-26 19:00:00,machine-1-1_y_21,0.110536,0.0,test -2020-01-26 20:00:00,machine-1-1_y_21,0.109562,0.0,test -2020-01-26 21:00:00,machine-1-1_y_21,0.133869,0.0,test -2020-01-26 22:00:00,machine-1-1_y_21,0.08792,0.0,test -2020-01-26 23:00:00,machine-1-1_y_21,0.06596,0.0,test -2020-01-27 00:00:00,machine-1-1_y_21,0.046884,0.0,test -2020-01-27 01:00:00,machine-1-1_y_21,0.032622,0.0,test -2020-01-27 02:00:00,machine-1-1_y_21,0.025938,0.0,test -2020-01-27 03:00:00,machine-1-1_y_21,0.024526,0.0,test -2020-01-27 04:00:00,machine-1-1_y_21,0.027192,0.0,test -2020-01-27 05:00:00,machine-1-1_y_21,0.059575,0.0,test -2020-01-27 06:00:00,machine-1-1_y_21,0.06769,0.0,test -2020-01-27 07:00:00,machine-1-1_y_21,0.090287,0.0,test -2020-01-27 08:00:00,machine-1-1_y_21,0.078611,0.0,test 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02:00:00,machine-1-1_y_21,0.027231,0.0,test -2020-01-28 03:00:00,machine-1-1_y_21,0.02568,0.0,test -2020-01-28 04:00:00,machine-1-1_y_21,0.026555,0.0,test -2020-01-28 05:00:00,machine-1-1_y_21,0.048097,0.0,test -2020-01-28 06:00:00,machine-1-1_y_21,0.08603,0.0,test -2020-01-28 07:00:00,machine-1-1_y_21,0.091262,0.0,test -2020-01-28 08:00:00,machine-1-1_y_21,0.074215,0.0,test -2020-01-28 09:00:00,machine-1-1_y_21,0.092873,0.0,test -2020-01-28 10:00:00,machine-1-1_y_21,0.076164,0.0,test -2020-01-28 11:00:00,machine-1-1_y_21,0.080401,0.0,test -2020-01-28 12:00:00,machine-1-1_y_21,0.081038,0.0,test -2020-01-28 13:00:00,machine-1-1_y_21,0.064428,0.0,test -2020-01-28 14:00:00,machine-1-1_y_21,0.065423,0.0,test -2020-01-28 15:00:00,machine-1-1_y_21,0.084618,0.0,test -2020-01-28 16:00:00,machine-1-1_y_21,0.086965,0.0,test -2020-01-28 17:00:00,machine-1-1_y_21,0.108488,0.0,test -2020-01-28 18:00:00,machine-1-1_y_21,0.131999,0.0,test -2020-01-28 19:00:00,machine-1-1_y_21,0.150339,0.0,test 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13:00:00,machine-1-1_y_21,0.128021,0.0,test -2020-01-29 14:00:00,machine-1-1_y_21,0.095558,0.0,test -2020-01-29 15:00:00,machine-1-1_y_21,0.112725,0.0,test -2020-01-29 16:00:00,machine-1-1_y_21,0.10803,0.0,test -2020-01-29 17:00:00,machine-1-1_y_21,0.110139,0.0,test -2020-01-29 18:00:00,machine-1-1_y_21,0.113281,0.0,test -2020-01-29 19:00:00,machine-1-1_y_21,0.107732,0.0,test -2020-01-29 20:00:00,machine-1-1_y_21,0.140294,0.0,test -2020-01-29 21:00:00,machine-1-1_y_21,0.142223,0.0,test -2020-01-29 22:00:00,machine-1-1_y_21,0.09707,0.0,test -2020-01-29 23:00:00,machine-1-1_y_21,0.069461,0.0,test -2020-01-30 00:00:00,machine-1-1_y_21,0.044199,0.0,test -2020-01-30 01:00:00,machine-1-1_y_21,0.029797,0.0,test -2020-01-30 02:00:00,machine-1-1_y_21,0.026117,0.0,test -2020-01-30 03:00:00,machine-1-1_y_21,0.02385,0.0,test -2020-01-30 04:00:00,machine-1-1_y_21,0.031369,0.0,test -2020-01-30 05:00:00,machine-1-1_y_21,0.101526,0.0,test -2020-01-30 06:00:00,machine-1-1_y_21,0.346548,0.0,test 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00:00:00,machine-1-1_y_21,0.044139,0.0,test -2020-01-31 01:00:00,machine-1-1_y_21,0.030374,0.0,test -2020-01-31 02:00:00,machine-1-1_y_21,0.025879,0.0,test -2020-01-31 03:00:00,machine-1-1_y_21,0.046387,0.0,test -2020-01-31 04:00:00,machine-1-1_y_21,0.121875,0.0,test -2020-01-31 05:00:00,machine-1-1_y_21,0.233406,0.0,test -2020-01-31 06:00:00,machine-1-1_y_21,0.288724,0.0,test -2020-01-31 07:00:00,machine-1-1_y_21,0.555209,0.0,test -2020-01-31 08:00:00,machine-1-1_y_21,0.551807,0.0,test -2020-01-31 09:00:00,machine-1-1_y_21,0.450838,0.0,test -2020-01-31 10:00:00,machine-1-1_y_21,0.167625,0.0,test -2020-01-31 11:00:00,machine-1-1_y_21,0.13556,0.0,test -2020-01-31 12:00:00,machine-1-1_y_21,0.248981,0.0,test -2020-01-31 13:00:00,machine-1-1_y_21,0.156366,0.0,test -2020-01-31 14:00:00,machine-1-1_y_21,0.108408,0.0,test -2020-01-31 15:00:00,machine-1-1_y_21,0.105007,0.0,test -2020-01-31 16:00:00,machine-1-1_y_21,0.123466,0.0,test -2020-01-31 17:00:00,machine-1-1_y_21,0.098582,0.0,test 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22:00:00,machine-1-1_y_23,0.019423,0.0,train -2020-01-17 23:00:00,machine-1-1_y_23,0.017564,0.0,train -2020-01-18 00:00:00,machine-1-1_y_23,0.012917,0.0,train -2020-01-18 01:00:00,machine-1-1_y_23,0.010833,0.0,train -2020-01-18 02:00:00,machine-1-1_y_23,0.007917,0.0,train -2020-01-18 03:00:00,machine-1-1_y_23,0.00734,0.0,train -2020-01-18 04:00:00,machine-1-1_y_23,0.005994,0.0,train -2020-01-18 05:00:00,machine-1-1_y_23,0.005865,0.0,train -2020-01-18 06:00:00,machine-1-1_y_23,0.010064,0.0,train -2020-01-18 07:00:00,machine-1-1_y_23,0.014583,0.0,train -2020-01-18 08:00:00,machine-1-1_y_23,0.017788,0.0,train -2020-01-18 09:00:00,machine-1-1_y_23,0.019038,0.0,train -2020-01-18 10:00:00,machine-1-1_y_23,0.022821,0.0,train -2020-01-18 11:00:00,machine-1-1_y_23,0.019744,0.0,train -2020-01-18 12:00:00,machine-1-1_y_23,0.019038,0.0,train -2020-01-18 13:00:00,machine-1-1_y_23,0.019231,0.0,train -2020-01-18 14:00:00,machine-1-1_y_23,0.016154,0.0,train -2020-01-18 15:00:00,machine-1-1_y_23,0.015994,0.0,train -2020-01-18 16:00:00,machine-1-1_y_23,0.016859,0.0,train -2020-01-18 17:00:00,machine-1-1_y_23,0.016731,0.0,train -2020-01-18 18:00:00,machine-1-1_y_23,0.016474,0.0,train -2020-01-18 19:00:00,machine-1-1_y_23,0.017276,0.0,train -2020-01-18 20:00:00,machine-1-1_y_23,0.017436,0.0,train -2020-01-18 21:00:00,machine-1-1_y_23,0.017756,0.0,train -2020-01-18 22:00:00,machine-1-1_y_23,0.018237,0.0,train -2020-01-18 23:00:00,machine-1-1_y_23,0.017756,0.0,train -2020-01-19 00:00:00,machine-1-1_y_23,0.016987,0.0,train -2020-01-19 01:00:00,machine-1-1_y_23,0.012372,0.0,train -2020-01-19 02:00:00,machine-1-1_y_23,0.012564,0.0,train -2020-01-19 03:00:00,machine-1-1_y_23,0.008109,0.0,train -2020-01-19 04:00:00,machine-1-1_y_23,0.006987,0.0,train -2020-01-19 05:00:00,machine-1-1_y_23,0.007692,0.0,train -2020-01-19 06:00:00,machine-1-1_y_23,0.010385,0.0,train -2020-01-19 07:00:00,machine-1-1_y_23,0.015673,0.0,train -2020-01-19 08:00:00,machine-1-1_y_23,0.018077,0.0,train -2020-01-19 09:00:00,machine-1-1_y_23,0.019744,0.0,train -2020-01-19 10:00:00,machine-1-1_y_23,0.028173,0.0,train -2020-01-19 11:00:00,machine-1-1_y_23,0.023109,0.0,train -2020-01-19 12:00:00,machine-1-1_y_23,0.019167,0.0,train -2020-01-19 13:00:00,machine-1-1_y_23,0.016635,0.0,train -2020-01-19 14:00:00,machine-1-1_y_23,0.015256,0.0,train -2020-01-19 15:00:00,machine-1-1_y_23,0.015321,0.0,train -2020-01-19 16:00:00,machine-1-1_y_23,0.018077,0.0,train -2020-01-19 17:00:00,machine-1-1_y_23,0.015641,0.0,train -2020-01-19 18:00:00,machine-1-1_y_23,0.016442,0.0,train -2020-01-19 19:00:00,machine-1-1_y_23,0.016538,0.0,train -2020-01-19 20:00:00,machine-1-1_y_23,0.017692,0.0,train -2020-01-19 21:00:00,machine-1-1_y_23,0.018109,0.0,train -2020-01-19 22:00:00,machine-1-1_y_23,0.017532,0.0,train -2020-01-19 23:00:00,machine-1-1_y_23,0.018846,0.0,train -2020-01-20 00:00:00,machine-1-1_y_23,0.015897,0.0,train -2020-01-20 01:00:00,machine-1-1_y_23,0.014103,0.0,train -2020-01-20 02:00:00,machine-1-1_y_23,0.010385,0.0,train -2020-01-20 03:00:00,machine-1-1_y_23,0.008333,0.0,train -2020-01-20 04:00:00,machine-1-1_y_23,0.008045,0.0,train -2020-01-20 05:00:00,machine-1-1_y_23,0.008782,0.0,train -2020-01-20 06:00:00,machine-1-1_y_23,0.011859,0.0,train -2020-01-20 07:00:00,machine-1-1_y_23,0.020833,0.0,train -2020-01-20 08:00:00,machine-1-1_y_23,0.01766,0.0,train -2020-01-20 09:00:00,machine-1-1_y_23,0.018686,0.0,train -2020-01-20 10:00:00,machine-1-1_y_23,0.018429,0.0,train -2020-01-20 11:00:00,machine-1-1_y_23,0.019167,0.0,train -2020-01-20 12:00:00,machine-1-1_y_23,0.020321,0.0,train -2020-01-20 13:00:00,machine-1-1_y_23,0.018686,0.0,train -2020-01-20 14:00:00,machine-1-1_y_23,0.015224,0.0,train -2020-01-20 15:00:00,machine-1-1_y_23,0.015417,0.0,train -2020-01-20 16:00:00,machine-1-1_y_23,0.015897,0.0,train -2020-01-20 17:00:00,machine-1-1_y_23,0.019615,0.0,train -2020-01-20 18:00:00,machine-1-1_y_23,0.018397,0.0,train -2020-01-20 19:00:00,machine-1-1_y_23,0.019487,0.0,test -2020-01-20 20:00:00,machine-1-1_y_23,0.017147,0.0,test -2020-01-20 21:00:00,machine-1-1_y_23,0.018526,0.0,test -2020-01-20 22:00:00,machine-1-1_y_23,0.021827,0.0,test -2020-01-20 23:00:00,machine-1-1_y_23,0.018013,0.0,test -2020-01-21 00:00:00,machine-1-1_y_23,0.015096,0.0,test -2020-01-21 01:00:00,machine-1-1_y_23,0.010545,0.0,test -2020-01-21 02:00:00,machine-1-1_y_23,0.008269,0.0,test -2020-01-21 03:00:00,machine-1-1_y_23,0.00734,0.0,test -2020-01-21 04:00:00,machine-1-1_y_23,0.005929,0.0,test -2020-01-21 05:00:00,machine-1-1_y_23,0.005929,0.0,test -2020-01-21 06:00:00,machine-1-1_y_23,0.010064,0.0,test -2020-01-21 07:00:00,machine-1-1_y_23,0.015064,0.0,test -2020-01-21 08:00:00,machine-1-1_y_23,0.018878,0.0,test -2020-01-21 09:00:00,machine-1-1_y_23,0.019551,0.0,test -2020-01-21 10:00:00,machine-1-1_y_23,0.020224,0.0,test -2020-01-21 11:00:00,machine-1-1_y_23,0.020641,0.0,test 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03:00:00,machine-1-1_y_23,0.005833,0.0,test -2020-01-25 04:00:00,machine-1-1_y_23,0.006923,0.0,test -2020-01-25 05:00:00,machine-1-1_y_23,0.011346,0.0,test -2020-01-25 06:00:00,machine-1-1_y_23,0.019071,0.0,test -2020-01-25 07:00:00,machine-1-1_y_23,0.020064,0.0,test -2020-01-25 08:00:00,machine-1-1_y_23,0.021442,0.0,test -2020-01-25 09:00:00,machine-1-1_y_23,0.033622,0.0,test -2020-01-25 10:00:00,machine-1-1_y_23,0.02266,0.0,test -2020-01-25 11:00:00,machine-1-1_y_23,0.020994,0.0,test -2020-01-25 12:00:00,machine-1-1_y_23,0.023462,0.0,test -2020-01-25 13:00:00,machine-1-1_y_23,0.016378,0.0,test -2020-01-25 14:00:00,machine-1-1_y_23,0.011571,0.0,test -2020-01-25 15:00:00,machine-1-1_y_23,0.011955,0.0,test -2020-01-25 16:00:00,machine-1-1_y_23,0.013429,0.0,test -2020-01-25 17:00:00,machine-1-1_y_23,0.014167,0.0,test -2020-01-25 18:00:00,machine-1-1_y_23,0.014135,0.0,test -2020-01-25 19:00:00,machine-1-1_y_23,0.013269,0.0,test -2020-01-25 20:00:00,machine-1-1_y_23,0.013494,0.0,test 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14:00:00,machine-1-1_y_23,0.013846,0.0,test -2020-01-26 15:00:00,machine-1-1_y_23,0.014359,0.0,test -2020-01-26 16:00:00,machine-1-1_y_23,0.01625,0.0,test -2020-01-26 17:00:00,machine-1-1_y_23,0.016282,0.0,test -2020-01-26 18:00:00,machine-1-1_y_23,0.017244,0.0,test -2020-01-26 19:00:00,machine-1-1_y_23,0.016346,0.0,test -2020-01-26 20:00:00,machine-1-1_y_23,0.017244,0.0,test -2020-01-26 21:00:00,machine-1-1_y_23,0.016987,0.0,test -2020-01-26 22:00:00,machine-1-1_y_23,0.013878,0.0,test -2020-01-26 23:00:00,machine-1-1_y_23,0.010513,0.0,test -2020-01-27 00:00:00,machine-1-1_y_23,0.008333,0.0,test -2020-01-27 01:00:00,machine-1-1_y_23,0.005994,0.0,test -2020-01-27 02:00:00,machine-1-1_y_23,0.004583,0.0,test -2020-01-27 03:00:00,machine-1-1_y_23,0.003654,0.0,test -2020-01-27 04:00:00,machine-1-1_y_23,0.004455,0.0,test -2020-01-27 05:00:00,machine-1-1_y_23,0.007821,0.0,test -2020-01-27 06:00:00,machine-1-1_y_23,0.010929,0.0,test -2020-01-27 07:00:00,machine-1-1_y_23,0.013109,0.0,test 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01:00:00,machine-1-1_y_23,0.007051,0.0,test -2020-01-28 02:00:00,machine-1-1_y_23,0.006442,0.0,test -2020-01-28 03:00:00,machine-1-1_y_23,0.006154,0.0,test -2020-01-28 04:00:00,machine-1-1_y_23,0.005673,0.0,test -2020-01-28 05:00:00,machine-1-1_y_23,0.008462,0.0,test -2020-01-28 06:00:00,machine-1-1_y_23,0.013878,0.0,test -2020-01-28 07:00:00,machine-1-1_y_23,0.018558,0.0,test -2020-01-28 08:00:00,machine-1-1_y_23,0.016186,0.0,test -2020-01-28 09:00:00,machine-1-1_y_23,0.0175,0.0,test -2020-01-28 10:00:00,machine-1-1_y_23,0.01875,0.0,test -2020-01-28 11:00:00,machine-1-1_y_23,0.017468,0.0,test -2020-01-28 12:00:00,machine-1-1_y_23,0.014808,0.0,test -2020-01-28 13:00:00,machine-1-1_y_23,0.01484,0.0,test -2020-01-28 14:00:00,machine-1-1_y_23,0.015641,0.0,test -2020-01-28 15:00:00,machine-1-1_y_23,0.019968,0.0,test -2020-01-28 16:00:00,machine-1-1_y_23,0.017596,0.0,test -2020-01-28 17:00:00,machine-1-1_y_23,0.020288,0.0,test -2020-01-28 18:00:00,machine-1-1_y_23,0.019744,0.0,test 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12:00:00,machine-1-1_y_23,0.028269,0.0,test -2020-01-29 13:00:00,machine-1-1_y_23,0.018718,0.0,test -2020-01-29 14:00:00,machine-1-1_y_23,0.017179,0.0,test -2020-01-29 15:00:00,machine-1-1_y_23,0.017949,0.0,test -2020-01-29 16:00:00,machine-1-1_y_23,0.023333,0.0,test -2020-01-29 17:00:00,machine-1-1_y_23,0.019103,0.0,test -2020-01-29 18:00:00,machine-1-1_y_23,0.019167,0.0,test -2020-01-29 19:00:00,machine-1-1_y_23,0.019423,0.0,test -2020-01-29 20:00:00,machine-1-1_y_23,0.019391,0.0,test -2020-01-29 21:00:00,machine-1-1_y_23,0.018141,0.0,test -2020-01-29 22:00:00,machine-1-1_y_23,0.017564,0.0,test -2020-01-29 23:00:00,machine-1-1_y_23,0.014295,0.0,test -2020-01-30 00:00:00,machine-1-1_y_23,0.010385,0.0,test -2020-01-30 01:00:00,machine-1-1_y_23,0.008173,0.0,test -2020-01-30 02:00:00,machine-1-1_y_23,0.006506,0.0,test -2020-01-30 03:00:00,machine-1-1_y_23,0.005833,0.0,test -2020-01-30 04:00:00,machine-1-1_y_23,0.008173,0.0,test -2020-01-30 05:00:00,machine-1-1_y_23,0.015096,0.0,test 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23:00:00,machine-1-1_y_23,0.015417,0.0,test -2020-01-31 00:00:00,machine-1-1_y_23,0.010096,0.0,test -2020-01-31 01:00:00,machine-1-1_y_23,0.007981,0.0,test -2020-01-31 02:00:00,machine-1-1_y_23,0.006763,0.0,test -2020-01-31 03:00:00,machine-1-1_y_23,0.00875,0.0,test -2020-01-31 04:00:00,machine-1-1_y_23,0.018141,0.0,test -2020-01-31 05:00:00,machine-1-1_y_23,0.024295,0.0,test -2020-01-31 06:00:00,machine-1-1_y_23,0.026154,0.0,test -2020-01-31 07:00:00,machine-1-1_y_23,0.040737,0.0,test -2020-01-31 08:00:00,machine-1-1_y_23,0.037821,0.0,test -2020-01-31 09:00:00,machine-1-1_y_23,0.030994,0.0,test -2020-01-31 10:00:00,machine-1-1_y_23,0.018333,0.0,test -2020-01-31 11:00:00,machine-1-1_y_23,0.016474,0.0,test -2020-01-31 12:00:00,machine-1-1_y_23,0.021795,0.0,test -2020-01-31 13:00:00,machine-1-1_y_23,0.019744,0.0,test -2020-01-31 14:00:00,machine-1-1_y_23,0.017692,0.0,test -2020-01-31 15:00:00,machine-1-1_y_23,0.019006,0.0,test -2020-01-31 16:00:00,machine-1-1_y_23,0.019583,0.0,test 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11:00:00,machine-1-1_y_24,0.237537,0.0,test -2020-01-29 12:00:00,machine-1-1_y_24,0.241385,0.0,test -2020-01-29 13:00:00,machine-1-1_y_24,0.06332,0.0,test -2020-01-29 14:00:00,machine-1-1_y_24,0.04198,0.0,test -2020-01-29 15:00:00,machine-1-1_y_24,0.055274,0.0,test -2020-01-29 16:00:00,machine-1-1_y_24,0.051251,0.0,test -2020-01-29 17:00:00,machine-1-1_y_24,0.05265,0.0,test -2020-01-29 18:00:00,machine-1-1_y_24,0.055624,0.0,test -2020-01-29 19:00:00,machine-1-1_y_24,0.052475,0.0,test -2020-01-29 20:00:00,machine-1-1_y_24,0.069092,0.0,test -2020-01-29 21:00:00,machine-1-1_y_24,0.072591,0.0,test -2020-01-29 22:00:00,machine-1-1_y_24,0.04163,0.0,test -2020-01-29 23:00:00,machine-1-1_y_24,0.027287,0.0,test -2020-01-30 00:00:00,machine-1-1_y_24,0.016267,0.0,test -2020-01-30 01:00:00,machine-1-1_y_24,0.01032,0.0,test -2020-01-30 02:00:00,machine-1-1_y_24,0.007871,0.0,test -2020-01-30 03:00:00,machine-1-1_y_24,0.006997,0.0,test -2020-01-30 04:00:00,machine-1-1_y_24,0.012594,0.0,test 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22:00:00,machine-1-1_y_24,0.044079,0.0,test -2020-01-30 23:00:00,machine-1-1_y_24,0.031485,0.0,test -2020-01-31 00:00:00,machine-1-1_y_24,0.015743,0.0,test -2020-01-31 01:00:00,machine-1-1_y_24,0.009446,0.0,test -2020-01-31 02:00:00,machine-1-1_y_24,0.008921,0.0,test -2020-01-31 03:00:00,machine-1-1_y_24,0.02099,0.0,test -2020-01-31 04:00:00,machine-1-1_y_24,0.06402,0.0,test -2020-01-31 05:00:00,machine-1-1_y_24,0.121917,0.0,test -2020-01-31 06:00:00,machine-1-1_y_24,0.163023,0.0,test -2020-01-31 07:00:00,machine-1-1_y_24,0.371349,0.0,test -2020-01-31 08:00:00,machine-1-1_y_24,0.364002,0.0,test -2020-01-31 09:00:00,machine-1-1_y_24,0.274969,0.0,test -2020-01-31 10:00:00,machine-1-1_y_24,0.087983,0.0,test -2020-01-31 11:00:00,machine-1-1_y_24,0.060346,0.0,test -2020-01-31 12:00:00,machine-1-1_y_24,0.139234,0.0,test -2020-01-31 13:00:00,machine-1-1_y_24,0.082911,0.0,test -2020-01-31 14:00:00,machine-1-1_y_24,0.047752,0.0,test -2020-01-31 15:00:00,machine-1-1_y_24,0.048452,0.0,test 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03:00:00,machine-1-1_y_25,0.005952,0.0,train -2020-01-17 04:00:00,machine-1-1_y_25,0.004854,0.0,train -2020-01-17 05:00:00,machine-1-1_y_25,0.005172,0.0,train -2020-01-17 06:00:00,machine-1-1_y_25,0.008003,0.0,train -2020-01-17 07:00:00,machine-1-1_y_25,0.017277,0.0,train -2020-01-17 08:00:00,machine-1-1_y_25,0.022391,0.0,train -2020-01-17 09:00:00,machine-1-1_y_25,0.020253,0.0,train -2020-01-17 10:00:00,machine-1-1_y_25,0.030047,0.0,train -2020-01-17 11:00:00,machine-1-1_y_25,0.020195,0.0,train -2020-01-17 12:00:00,machine-1-1_y_25,0.01904,0.0,train -2020-01-17 13:00:00,machine-1-1_y_25,0.025251,0.0,train -2020-01-17 14:00:00,machine-1-1_y_25,0.01537,0.0,train -2020-01-17 15:00:00,machine-1-1_y_25,0.01485,0.0,train -2020-01-17 16:00:00,machine-1-1_y_25,0.01485,0.0,train -2020-01-17 17:00:00,machine-1-1_y_25,0.014186,0.0,train -2020-01-17 18:00:00,machine-1-1_y_25,0.014446,0.0,train -2020-01-17 19:00:00,machine-1-1_y_25,0.017248,0.0,train -2020-01-17 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23:00:00,machine-1-1_y_25,0.017191,0.0,train -2020-01-20 00:00:00,machine-1-1_y_25,0.014706,0.0,train -2020-01-20 01:00:00,machine-1-1_y_25,0.012741,0.0,train -2020-01-20 02:00:00,machine-1-1_y_25,0.009476,0.0,train -2020-01-20 03:00:00,machine-1-1_y_25,0.007599,0.0,train -2020-01-20 04:00:00,machine-1-1_y_25,0.00731,0.0,train -2020-01-20 05:00:00,machine-1-1_y_25,0.008061,0.0,train -2020-01-20 06:00:00,machine-1-1_y_25,0.010892,0.0,train -2020-01-20 07:00:00,machine-1-1_y_25,0.019011,0.0,train -2020-01-20 08:00:00,machine-1-1_y_25,0.01615,0.0,train -2020-01-20 09:00:00,machine-1-1_y_25,0.017133,0.0,train -2020-01-20 10:00:00,machine-1-1_y_25,0.016757,0.0,train -2020-01-20 11:00:00,machine-1-1_y_25,0.017508,0.0,train -2020-01-20 12:00:00,machine-1-1_y_25,0.018491,0.0,train -2020-01-20 13:00:00,machine-1-1_y_25,0.017162,0.0,train -2020-01-20 14:00:00,machine-1-1_y_25,0.013839,0.0,train -2020-01-20 15:00:00,machine-1-1_y_25,0.01407,0.0,train -2020-01-20 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03:00:00,machine-1-1_y_25,0.005576,0.0,test -2020-01-22 04:00:00,machine-1-1_y_25,0.006443,0.0,test -2020-01-22 05:00:00,machine-1-1_y_25,0.011268,0.0,test -2020-01-22 06:00:00,machine-1-1_y_25,0.015602,0.0,test -2020-01-22 07:00:00,machine-1-1_y_25,0.018028,0.0,test -2020-01-22 08:00:00,machine-1-1_y_25,0.0193,0.0,test -2020-01-22 09:00:00,machine-1-1_y_25,0.025916,0.0,test -2020-01-22 10:00:00,machine-1-1_y_25,0.017971,0.0,test -2020-01-22 11:00:00,machine-1-1_y_25,0.018144,0.0,test -2020-01-22 12:00:00,machine-1-1_y_25,0.01433,0.0,test -2020-01-22 13:00:00,machine-1-1_y_25,0.015081,0.0,test -2020-01-22 14:00:00,machine-1-1_y_25,0.014879,0.0,test -2020-01-22 15:00:00,machine-1-1_y_25,0.014446,0.0,test -2020-01-22 16:00:00,machine-1-1_y_25,0.015544,0.0,test -2020-01-22 17:00:00,machine-1-1_y_25,0.016295,0.0,test -2020-01-22 18:00:00,machine-1-1_y_25,0.018288,0.0,test -2020-01-22 19:00:00,machine-1-1_y_25,0.016208,0.0,test -2020-01-22 20:00:00,machine-1-1_y_25,0.015746,0.0,test 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14:00:00,machine-1-1_y_25,0.016006,0.0,test -2020-01-23 15:00:00,machine-1-1_y_25,0.016555,0.0,test -2020-01-23 16:00:00,machine-1-1_y_25,0.016179,0.0,test -2020-01-23 17:00:00,machine-1-1_y_25,0.016526,0.0,test -2020-01-23 18:00:00,machine-1-1_y_25,0.015284,0.0,test -2020-01-23 19:00:00,machine-1-1_y_25,0.016815,0.0,test -2020-01-23 20:00:00,machine-1-1_y_25,0.017104,0.0,test -2020-01-23 21:00:00,machine-1-1_y_25,0.017191,0.0,test -2020-01-23 22:00:00,machine-1-1_y_25,0.015659,0.0,test -2020-01-23 23:00:00,machine-1-1_y_25,0.012481,0.0,test -2020-01-24 00:00:00,machine-1-1_y_25,0.008639,0.0,test -2020-01-24 01:00:00,machine-1-1_y_25,0.006732,0.0,test -2020-01-24 02:00:00,machine-1-1_y_25,0.005634,0.0,test -2020-01-24 03:00:00,machine-1-1_y_25,0.005172,0.0,test -2020-01-24 04:00:00,machine-1-1_y_25,0.005229,0.0,test -2020-01-24 05:00:00,machine-1-1_y_25,0.010603,0.0,test -2020-01-24 06:00:00,machine-1-1_y_25,0.01459,0.0,test -2020-01-24 07:00:00,machine-1-1_y_25,0.018924,0.0,test 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01:00:00,machine-1-1_y_25,0.007338,0.0,test -2020-01-25 02:00:00,machine-1-1_y_25,0.005894,0.0,test -2020-01-25 03:00:00,machine-1-1_y_25,0.005316,0.0,test -2020-01-25 04:00:00,machine-1-1_y_25,0.006298,0.0,test -2020-01-25 05:00:00,machine-1-1_y_25,0.010343,0.0,test -2020-01-25 06:00:00,machine-1-1_y_25,0.017393,0.0,test -2020-01-25 07:00:00,machine-1-1_y_25,0.018548,0.0,test -2020-01-25 08:00:00,machine-1-1_y_25,0.019531,0.0,test -2020-01-25 09:00:00,machine-1-1_y_25,0.030741,0.0,test -2020-01-25 10:00:00,machine-1-1_y_25,0.020946,0.0,test -2020-01-25 11:00:00,machine-1-1_y_25,0.018982,0.0,test -2020-01-25 12:00:00,machine-1-1_y_25,0.021784,0.0,test -2020-01-25 13:00:00,machine-1-1_y_25,0.014157,0.0,test -2020-01-25 14:00:00,machine-1-1_y_25,0.010401,0.0,test -2020-01-25 15:00:00,machine-1-1_y_25,0.010719,0.0,test -2020-01-25 16:00:00,machine-1-1_y_25,0.012192,0.0,test -2020-01-25 17:00:00,machine-1-1_y_25,0.012886,0.0,test -2020-01-25 18:00:00,machine-1-1_y_25,0.012857,0.0,test -2020-01-25 19:00:00,machine-1-1_y_25,0.012135,0.0,test -2020-01-25 20:00:00,machine-1-1_y_25,0.01225,0.0,test -2020-01-25 21:00:00,machine-1-1_y_25,0.012481,0.0,test -2020-01-25 22:00:00,machine-1-1_y_25,0.014301,0.0,test -2020-01-25 23:00:00,machine-1-1_y_25,0.01043,0.0,test -2020-01-26 00:00:00,machine-1-1_y_25,0.007772,0.0,test -2020-01-26 01:00:00,machine-1-1_y_25,0.006298,0.0,test -2020-01-26 02:00:00,machine-1-1_y_25,0.004738,0.0,test -2020-01-26 03:00:00,machine-1-1_y_25,0.004276,0.0,test -2020-01-26 04:00:00,machine-1-1_y_25,0.003929,0.0,test -2020-01-26 05:00:00,machine-1-1_y_25,0.007916,0.0,test -2020-01-26 06:00:00,machine-1-1_y_25,0.011326,0.0,test -2020-01-26 07:00:00,machine-1-1_y_25,0.015053,0.0,test -2020-01-26 08:00:00,machine-1-1_y_25,0.01459,0.0,test -2020-01-26 09:00:00,machine-1-1_y_25,0.014215,0.0,test -2020-01-26 10:00:00,machine-1-1_y_25,0.011817,0.0,test -2020-01-26 11:00:00,machine-1-1_y_25,0.012423,0.0,test -2020-01-26 12:00:00,machine-1-1_y_25,0.011297,0.0,test -2020-01-26 13:00:00,machine-1-1_y_25,0.011586,0.0,test -2020-01-26 14:00:00,machine-1-1_y_25,0.012799,0.0,test -2020-01-26 15:00:00,machine-1-1_y_25,0.012972,0.0,test -2020-01-26 16:00:00,machine-1-1_y_25,0.014879,0.0,test -2020-01-26 17:00:00,machine-1-1_y_25,0.01485,0.0,test -2020-01-26 18:00:00,machine-1-1_y_25,0.015717,0.0,test -2020-01-26 19:00:00,machine-1-1_y_25,0.014966,0.0,test -2020-01-26 20:00:00,machine-1-1_y_25,0.015833,0.0,test -2020-01-26 21:00:00,machine-1-1_y_25,0.018866,0.0,test -2020-01-26 22:00:00,machine-1-1_y_25,0.012655,0.0,test -2020-01-26 23:00:00,machine-1-1_y_25,0.009737,0.0,test -2020-01-27 00:00:00,machine-1-1_y_25,0.007656,0.0,test -2020-01-27 01:00:00,machine-1-1_y_25,0.005576,0.0,test -2020-01-27 02:00:00,machine-1-1_y_25,0.004247,0.0,test -2020-01-27 03:00:00,machine-1-1_y_25,0.003323,0.0,test -2020-01-27 04:00:00,machine-1-1_y_25,0.004103,0.0,test -2020-01-27 05:00:00,machine-1-1_y_25,0.007252,0.0,test 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23:00:00,machine-1-1_y_25,0.010343,0.0,test -2020-01-28 00:00:00,machine-1-1_y_25,0.008176,0.0,test -2020-01-28 01:00:00,machine-1-1_y_25,0.006501,0.0,test -2020-01-28 02:00:00,machine-1-1_y_25,0.005894,0.0,test -2020-01-28 03:00:00,machine-1-1_y_25,0.005489,0.0,test -2020-01-28 04:00:00,machine-1-1_y_25,0.005172,0.0,test -2020-01-28 05:00:00,machine-1-1_y_25,0.007801,0.0,test -2020-01-28 06:00:00,machine-1-1_y_25,0.012828,0.0,test -2020-01-28 07:00:00,machine-1-1_y_25,0.016873,0.0,test -2020-01-28 08:00:00,machine-1-1_y_25,0.014764,0.0,test -2020-01-28 09:00:00,machine-1-1_y_25,0.016064,0.0,test -2020-01-28 10:00:00,machine-1-1_y_25,0.017075,0.0,test -2020-01-28 11:00:00,machine-1-1_y_25,0.015833,0.0,test -2020-01-28 12:00:00,machine-1-1_y_25,0.013464,0.0,test -2020-01-28 13:00:00,machine-1-1_y_25,0.013521,0.0,test -2020-01-28 14:00:00,machine-1-1_y_25,0.014244,0.0,test -2020-01-28 15:00:00,machine-1-1_y_25,0.018202,0.0,test -2020-01-28 16:00:00,machine-1-1_y_25,0.016035,0.0,test 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10:00:00,machine-1-1_y_25,0.028025,0.0,test -2020-01-29 11:00:00,machine-1-1_y_25,0.025945,0.0,test -2020-01-29 12:00:00,machine-1-1_y_25,0.026956,0.0,test -2020-01-29 13:00:00,machine-1-1_y_25,0.016959,0.0,test -2020-01-29 14:00:00,machine-1-1_y_25,0.015717,0.0,test -2020-01-29 15:00:00,machine-1-1_y_25,0.01641,0.0,test -2020-01-29 16:00:00,machine-1-1_y_25,0.02138,0.0,test -2020-01-29 17:00:00,machine-1-1_y_25,0.017653,0.0,test -2020-01-29 18:00:00,machine-1-1_y_25,0.017566,0.0,test -2020-01-29 19:00:00,machine-1-1_y_25,0.017797,0.0,test -2020-01-29 20:00:00,machine-1-1_y_25,0.017768,0.0,test -2020-01-29 21:00:00,machine-1-1_y_25,0.016555,0.0,test -2020-01-29 22:00:00,machine-1-1_y_25,0.016035,0.0,test -2020-01-29 23:00:00,machine-1-1_y_25,0.013088,0.0,test -2020-01-30 00:00:00,machine-1-1_y_25,0.009361,0.0,test -2020-01-30 01:00:00,machine-1-1_y_25,0.007454,0.0,test -2020-01-30 02:00:00,machine-1-1_y_25,0.006009,0.0,test -2020-01-30 03:00:00,machine-1-1_y_25,0.005374,0.0,test 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06:00:00,machine-1-1_y_27,0.044643,0.0,train -2020-01-14 07:00:00,machine-1-1_y_27,0.085405,0.0,train -2020-01-14 08:00:00,machine-1-1_y_27,0.107609,0.0,train -2020-01-14 09:00:00,machine-1-1_y_27,0.136373,0.0,train -2020-01-14 10:00:00,machine-1-1_y_27,0.123508,0.0,train -2020-01-14 11:00:00,machine-1-1_y_27,0.089877,0.0,train -2020-01-14 12:00:00,machine-1-1_y_27,0.122148,0.0,train -2020-01-14 13:00:00,machine-1-1_y_27,0.09039,0.0,train -2020-01-14 14:00:00,machine-1-1_y_27,0.067635,0.0,train -2020-01-14 15:00:00,machine-1-1_y_27,0.080618,0.0,train -2020-01-14 16:00:00,machine-1-1_y_27,0.078017,0.0,train -2020-01-14 17:00:00,machine-1-1_y_27,0.065172,0.0,train -2020-01-14 18:00:00,machine-1-1_y_27,0.076146,0.0,train -2020-01-14 19:00:00,machine-1-1_y_27,0.096241,0.0,train -2020-01-14 20:00:00,machine-1-1_y_27,0.084578,0.0,train -2020-01-14 21:00:00,machine-1-1_y_27,0.080992,0.0,train -2020-01-14 22:00:00,machine-1-1_y_27,0.076382,0.0,train -2020-01-14 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16:00:00,machine-1-1_y_27,0.106998,0.0,train -2020-01-15 17:00:00,machine-1-1_y_27,0.096714,0.0,train -2020-01-15 18:00:00,machine-1-1_y_27,0.100595,0.0,train -2020-01-15 19:00:00,machine-1-1_y_27,0.098546,0.0,train -2020-01-15 20:00:00,machine-1-1_y_27,0.117124,0.0,train -2020-01-15 21:00:00,machine-1-1_y_27,0.097128,0.0,train -2020-01-15 22:00:00,machine-1-1_y_27,0.109993,0.0,train -2020-01-15 23:00:00,machine-1-1_y_27,0.093581,0.0,train -2020-01-16 00:00:00,machine-1-1_y_27,0.079337,0.0,train -2020-01-16 01:00:00,machine-1-1_y_27,0.055774,0.0,train -2020-01-16 02:00:00,machine-1-1_y_27,0.043067,0.0,train -2020-01-16 03:00:00,machine-1-1_y_27,0.034753,0.0,train -2020-01-16 04:00:00,machine-1-1_y_27,0.031404,0.0,train -2020-01-16 05:00:00,machine-1-1_y_27,0.032704,0.0,train -2020-01-16 06:00:00,machine-1-1_y_27,0.052445,0.0,train -2020-01-16 07:00:00,machine-1-1_y_27,0.096635,0.0,train -2020-01-16 08:00:00,machine-1-1_y_27,0.11809,0.0,train -2020-01-16 09:00:00,machine-1-1_y_27,0.111253,0.0,train -2020-01-16 10:00:00,machine-1-1_y_27,0.140628,0.0,train -2020-01-16 11:00:00,machine-1-1_y_27,0.129044,0.0,train -2020-01-16 12:00:00,machine-1-1_y_27,0.118011,0.0,train -2020-01-16 13:00:00,machine-1-1_y_27,0.096123,0.0,train -2020-01-16 14:00:00,machine-1-1_y_27,0.078983,0.0,train -2020-01-16 15:00:00,machine-1-1_y_27,0.084006,0.0,train -2020-01-16 16:00:00,machine-1-1_y_27,0.084637,0.0,train -2020-01-16 17:00:00,machine-1-1_y_27,0.078195,0.0,train -2020-01-16 18:00:00,machine-1-1_y_27,0.092025,0.0,train -2020-01-16 19:00:00,machine-1-1_y_27,0.107096,0.0,train -2020-01-16 20:00:00,machine-1-1_y_27,0.109283,0.0,train -2020-01-16 21:00:00,machine-1-1_y_27,0.097285,0.0,train -2020-01-16 22:00:00,machine-1-1_y_27,0.096359,0.0,train -2020-01-16 23:00:00,machine-1-1_y_27,0.085957,0.0,train -2020-01-17 00:00:00,machine-1-1_y_27,0.063813,0.0,train -2020-01-17 01:00:00,machine-1-1_y_27,0.050041,0.0,train -2020-01-17 02:00:00,machine-1-1_y_27,0.036644,0.0,train -2020-01-17 03:00:00,machine-1-1_y_27,0.030576,0.0,train -2020-01-17 04:00:00,machine-1-1_y_27,0.025356,0.0,train -2020-01-17 05:00:00,machine-1-1_y_27,0.026597,0.0,train -2020-01-17 06:00:00,machine-1-1_y_27,0.044013,0.0,train -2020-01-17 07:00:00,machine-1-1_y_27,0.109776,0.0,train -2020-01-17 08:00:00,machine-1-1_y_27,0.200106,0.0,train -2020-01-17 09:00:00,machine-1-1_y_27,0.204204,0.0,train -2020-01-17 10:00:00,machine-1-1_y_27,0.263742,0.0,train -2020-01-17 11:00:00,machine-1-1_y_27,0.194669,0.0,train -2020-01-17 12:00:00,machine-1-1_y_27,0.176741,0.0,train -2020-01-17 13:00:00,machine-1-1_y_27,0.229067,0.0,train -2020-01-17 14:00:00,machine-1-1_y_27,0.101462,0.0,train -2020-01-17 15:00:00,machine-1-1_y_27,0.109283,0.0,train -2020-01-17 16:00:00,machine-1-1_y_27,0.10491,0.0,train -2020-01-17 17:00:00,machine-1-1_y_27,0.08639,0.0,train -2020-01-17 18:00:00,machine-1-1_y_27,0.090193,0.0,train -2020-01-17 19:00:00,machine-1-1_y_27,0.169825,0.0,train -2020-01-17 20:00:00,machine-1-1_y_27,0.14711,0.0,train -2020-01-17 21:00:00,machine-1-1_y_27,0.168702,0.0,train -2020-01-17 22:00:00,machine-1-1_y_27,0.159994,0.0,train -2020-01-17 23:00:00,machine-1-1_y_27,0.101225,0.0,train -2020-01-18 00:00:00,machine-1-1_y_27,0.072737,0.0,train -2020-01-18 01:00:00,machine-1-1_y_27,0.055538,0.0,train -2020-01-18 02:00:00,machine-1-1_y_27,0.039994,0.0,train -2020-01-18 03:00:00,machine-1-1_y_27,0.033788,0.0,train -2020-01-18 04:00:00,machine-1-1_y_27,0.028862,0.0,train -2020-01-18 05:00:00,machine-1-1_y_27,0.028587,0.0,train -2020-01-18 06:00:00,machine-1-1_y_27,0.047421,0.0,train -2020-01-18 07:00:00,machine-1-1_y_27,0.084046,0.0,train -2020-01-18 08:00:00,machine-1-1_y_27,0.131605,0.0,train -2020-01-18 09:00:00,machine-1-1_y_27,0.128886,0.0,train -2020-01-18 10:00:00,machine-1-1_y_27,0.181233,0.0,train -2020-01-18 11:00:00,machine-1-1_y_27,0.152863,0.0,train -2020-01-18 12:00:00,machine-1-1_y_27,0.139032,0.0,train -2020-01-18 13:00:00,machine-1-1_y_27,0.183794,0.0,train -2020-01-18 14:00:00,machine-1-1_y_27,0.099689,0.0,train -2020-01-18 15:00:00,machine-1-1_y_27,0.082411,0.0,train -2020-01-18 16:00:00,machine-1-1_y_27,0.110446,0.0,train -2020-01-18 17:00:00,machine-1-1_y_27,0.085543,0.0,train -2020-01-18 18:00:00,machine-1-1_y_27,0.103767,0.0,train -2020-01-18 19:00:00,machine-1-1_y_27,0.090646,0.0,train -2020-01-18 20:00:00,machine-1-1_y_27,0.089464,0.0,train -2020-01-18 21:00:00,machine-1-1_y_27,0.126758,0.0,train -2020-01-18 22:00:00,machine-1-1_y_27,0.11742,0.0,train -2020-01-18 23:00:00,machine-1-1_y_27,0.094094,0.0,train -2020-01-19 00:00:00,machine-1-1_y_27,0.07851,0.0,train -2020-01-19 01:00:00,machine-1-1_y_27,0.068167,0.0,train -2020-01-19 02:00:00,machine-1-1_y_27,0.060956,0.0,train -2020-01-19 03:00:00,machine-1-1_y_27,0.039994,0.0,train -2020-01-19 04:00:00,machine-1-1_y_27,0.030045,0.0,train -2020-01-19 05:00:00,machine-1-1_y_27,0.031502,0.0,train -2020-01-19 06:00:00,machine-1-1_y_27,0.053174,0.0,train -2020-01-19 07:00:00,machine-1-1_y_27,0.097955,0.0,train -2020-01-19 08:00:00,machine-1-1_y_27,0.13921,0.0,train -2020-01-19 09:00:00,machine-1-1_y_27,0.210607,0.0,train -2020-01-19 10:00:00,machine-1-1_y_27,0.20121,0.0,train -2020-01-19 11:00:00,machine-1-1_y_27,0.138126,0.0,train -2020-01-19 12:00:00,machine-1-1_y_27,0.129497,0.0,train -2020-01-19 13:00:00,machine-1-1_y_27,0.14185,0.0,train -2020-01-19 14:00:00,machine-1-1_y_27,0.094034,0.0,train -2020-01-19 15:00:00,machine-1-1_y_27,0.095236,0.0,train -2020-01-19 16:00:00,machine-1-1_y_27,0.090744,0.0,train -2020-01-19 17:00:00,machine-1-1_y_27,0.081898,0.0,train -2020-01-19 18:00:00,machine-1-1_y_27,0.10156,0.0,train -2020-01-19 19:00:00,machine-1-1_y_27,0.116317,0.0,train -2020-01-19 20:00:00,machine-1-1_y_27,0.115923,0.0,train -2020-01-19 21:00:00,machine-1-1_y_27,0.116001,0.0,train -2020-01-19 22:00:00,machine-1-1_y_27,0.101915,0.0,train -2020-01-19 23:00:00,machine-1-1_y_27,0.100102,0.0,train -2020-01-20 00:00:00,machine-1-1_y_27,0.101442,0.0,train -2020-01-20 01:00:00,machine-1-1_y_27,0.08178,0.0,train -2020-01-20 02:00:00,machine-1-1_y_27,0.041471,0.0,train -2020-01-20 03:00:00,machine-1-1_y_27,0.03627,0.0,train -2020-01-20 04:00:00,machine-1-1_y_27,0.03432,0.0,train -2020-01-20 05:00:00,machine-1-1_y_27,0.037373,0.0,train -2020-01-20 06:00:00,machine-1-1_y_27,0.073742,0.0,train -2020-01-20 07:00:00,machine-1-1_y_27,0.127349,0.0,train -2020-01-20 08:00:00,machine-1-1_y_27,0.1293,0.0,train -2020-01-20 09:00:00,machine-1-1_y_27,0.137732,0.0,train -2020-01-20 10:00:00,machine-1-1_y_27,0.109303,0.0,train -2020-01-20 11:00:00,machine-1-1_y_27,0.153749,0.0,train -2020-01-20 12:00:00,machine-1-1_y_27,0.132511,0.0,train -2020-01-20 13:00:00,machine-1-1_y_27,0.104259,0.0,train -2020-01-20 14:00:00,machine-1-1_y_27,0.07187,0.0,train -2020-01-20 15:00:00,machine-1-1_y_27,0.092104,0.0,train -2020-01-20 16:00:00,machine-1-1_y_27,0.089759,0.0,train -2020-01-20 17:00:00,machine-1-1_y_27,0.090705,0.0,train -2020-01-20 18:00:00,machine-1-1_y_27,0.087297,0.0,train -2020-01-20 19:00:00,machine-1-1_y_27,0.148962,0.0,test -2020-01-20 20:00:00,machine-1-1_y_27,0.14906,0.0,test -2020-01-20 21:00:00,machine-1-1_y_27,0.152705,0.0,test -2020-01-20 22:00:00,machine-1-1_y_27,0.230368,0.0,test -2020-01-20 23:00:00,machine-1-1_y_27,0.116592,0.0,test -2020-01-21 00:00:00,machine-1-1_y_27,0.072816,0.0,test -2020-01-21 01:00:00,machine-1-1_y_27,0.052307,0.0,test -2020-01-21 02:00:00,machine-1-1_y_27,0.038851,0.0,test -2020-01-21 03:00:00,machine-1-1_y_27,0.032901,0.0,test -2020-01-21 04:00:00,machine-1-1_y_27,0.028606,0.0,test -2020-01-21 05:00:00,machine-1-1_y_27,0.029808,0.0,test -2020-01-21 06:00:00,machine-1-1_y_27,0.050573,0.0,test -2020-01-21 07:00:00,machine-1-1_y_27,0.089208,0.0,test -2020-01-21 08:00:00,machine-1-1_y_27,0.12272,0.0,test 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02:00:00,machine-1-1_y_27,0.029178,0.0,test -2020-01-22 03:00:00,machine-1-1_y_27,0.023996,0.0,test -2020-01-22 04:00:00,machine-1-1_y_27,0.028725,0.0,test -2020-01-22 05:00:00,machine-1-1_y_27,0.078155,0.0,test -2020-01-22 06:00:00,machine-1-1_y_27,0.144549,0.0,test -2020-01-22 07:00:00,machine-1-1_y_27,0.209898,0.0,test -2020-01-22 08:00:00,machine-1-1_y_27,0.190216,0.0,test -2020-01-22 09:00:00,machine-1-1_y_27,0.145613,0.0,test -2020-01-22 10:00:00,machine-1-1_y_27,0.118582,0.0,test -2020-01-22 11:00:00,machine-1-1_y_27,0.121597,0.0,test -2020-01-22 12:00:00,machine-1-1_y_27,0.081544,0.0,test -2020-01-22 13:00:00,machine-1-1_y_27,0.093562,0.0,test -2020-01-22 14:00:00,machine-1-1_y_27,0.08511,0.0,test -2020-01-22 15:00:00,machine-1-1_y_27,0.085839,0.0,test -2020-01-22 16:00:00,machine-1-1_y_27,0.090409,0.0,test -2020-01-22 17:00:00,machine-1-1_y_27,0.11283,0.0,test -2020-01-22 18:00:00,machine-1-1_y_27,0.122404,0.0,test -2020-01-22 19:00:00,machine-1-1_y_27,0.123941,0.0,test -2020-01-22 20:00:00,machine-1-1_y_27,0.117046,0.0,test -2020-01-22 21:00:00,machine-1-1_y_27,0.106545,0.0,test -2020-01-22 22:00:00,machine-1-1_y_27,0.083711,0.0,test -2020-01-22 23:00:00,machine-1-1_y_27,0.062729,0.0,test -2020-01-23 00:00:00,machine-1-1_y_27,0.044604,0.0,test -2020-01-23 01:00:00,machine-1-1_y_27,0.034379,0.0,test -2020-01-23 02:00:00,machine-1-1_y_27,0.027523,0.0,test -2020-01-23 03:00:00,machine-1-1_y_27,0.026262,0.0,test -2020-01-23 04:00:00,machine-1-1_y_27,0.032074,0.0,test -2020-01-23 05:00:00,machine-1-1_y_27,0.076205,0.0,test -2020-01-23 06:00:00,machine-1-1_y_27,0.115548,0.0,test -2020-01-23 07:00:00,machine-1-1_y_27,0.138579,0.0,test -2020-01-23 08:00:00,machine-1-1_y_27,0.137239,0.0,test -2020-01-23 09:00:00,machine-1-1_y_27,0.300091,0.0,test -2020-01-23 10:00:00,machine-1-1_y_27,0.234958,0.0,test -2020-01-23 11:00:00,machine-1-1_y_27,0.32917,0.0,test -2020-01-23 12:00:00,machine-1-1_y_27,0.279641,0.0,test -2020-01-23 13:00:00,machine-1-1_y_27,0.119134,0.0,test -2020-01-23 14:00:00,machine-1-1_y_27,0.098034,0.0,test -2020-01-23 15:00:00,machine-1-1_y_27,0.120316,0.0,test -2020-01-23 16:00:00,machine-1-1_y_27,0.104752,0.0,test -2020-01-23 17:00:00,machine-1-1_y_27,0.132491,0.0,test -2020-01-23 18:00:00,machine-1-1_y_27,0.123488,0.0,test -2020-01-23 19:00:00,machine-1-1_y_27,0.145002,0.0,test -2020-01-23 20:00:00,machine-1-1_y_27,0.136195,0.0,test -2020-01-23 21:00:00,machine-1-1_y_27,0.133654,0.0,test -2020-01-23 22:00:00,machine-1-1_y_27,0.10355,0.0,test -2020-01-23 23:00:00,machine-1-1_y_27,0.07457,0.0,test -2020-01-24 00:00:00,machine-1-1_y_27,0.05081,0.0,test -2020-01-24 01:00:00,machine-1-1_y_27,0.039225,0.0,test -2020-01-24 02:00:00,machine-1-1_y_27,0.032133,0.0,test -2020-01-24 03:00:00,machine-1-1_y_27,0.03032,0.0,test -2020-01-24 04:00:00,machine-1-1_y_27,0.0343,0.0,test -2020-01-24 05:00:00,machine-1-1_y_27,0.074924,0.0,test -2020-01-24 06:00:00,machine-1-1_y_27,0.099216,0.0,test 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00:00:00,machine-1-1_y_27,0.048524,0.0,test -2020-01-25 01:00:00,machine-1-1_y_27,0.036329,0.0,test -2020-01-25 02:00:00,machine-1-1_y_27,0.033768,0.0,test -2020-01-25 03:00:00,machine-1-1_y_27,0.028528,0.0,test -2020-01-25 04:00:00,machine-1-1_y_27,0.032822,0.0,test -2020-01-25 05:00:00,machine-1-1_y_27,0.073387,0.0,test -2020-01-25 06:00:00,machine-1-1_y_27,0.155148,0.0,test -2020-01-25 07:00:00,machine-1-1_y_27,0.165806,0.0,test -2020-01-25 08:00:00,machine-1-1_y_27,0.193112,0.0,test -2020-01-25 09:00:00,machine-1-1_y_27,0.299224,0.0,test -2020-01-25 10:00:00,machine-1-1_y_27,0.209662,0.0,test -2020-01-25 11:00:00,machine-1-1_y_27,0.254896,0.0,test -2020-01-25 12:00:00,machine-1-1_y_27,0.207238,0.0,test -2020-01-25 13:00:00,machine-1-1_y_27,0.122168,0.0,test -2020-01-25 14:00:00,machine-1-1_y_27,0.094606,0.0,test -2020-01-25 15:00:00,machine-1-1_y_27,0.108357,0.0,test -2020-01-25 16:00:00,machine-1-1_y_27,0.120651,0.0,test -2020-01-25 17:00:00,machine-1-1_y_27,0.13854,0.0,test -2020-01-25 18:00:00,machine-1-1_y_27,0.11348,0.0,test -2020-01-25 19:00:00,machine-1-1_y_27,0.1319,0.0,test -2020-01-25 20:00:00,machine-1-1_y_27,0.133398,0.0,test -2020-01-25 21:00:00,machine-1-1_y_27,0.117105,0.0,test -2020-01-25 22:00:00,machine-1-1_y_27,0.09565,0.0,test -2020-01-25 23:00:00,machine-1-1_y_27,0.077485,0.0,test -2020-01-26 00:00:00,machine-1-1_y_27,0.054376,0.0,test -2020-01-26 01:00:00,machine-1-1_y_27,0.040861,0.0,test -2020-01-26 02:00:00,machine-1-1_y_27,0.03757,0.0,test -2020-01-26 03:00:00,machine-1-1_y_27,0.033039,0.0,test -2020-01-26 04:00:00,machine-1-1_y_27,0.032133,0.0,test -2020-01-26 05:00:00,machine-1-1_y_27,0.062296,0.0,test -2020-01-26 06:00:00,machine-1-1_y_27,0.092439,0.0,test -2020-01-26 07:00:00,machine-1-1_y_27,0.139032,0.0,test -2020-01-26 08:00:00,machine-1-1_y_27,0.103373,0.0,test -2020-01-26 09:00:00,machine-1-1_y_27,0.109835,0.0,test -2020-01-26 10:00:00,machine-1-1_y_27,0.111234,0.0,test -2020-01-26 11:00:00,machine-1-1_y_27,0.097778,0.0,test -2020-01-26 12:00:00,machine-1-1_y_27,0.080756,0.0,test -2020-01-26 13:00:00,machine-1-1_y_27,0.09366,0.0,test -2020-01-26 14:00:00,machine-1-1_y_27,0.104634,0.0,test -2020-01-26 15:00:00,machine-1-1_y_27,0.126561,0.0,test -2020-01-26 16:00:00,machine-1-1_y_27,0.121222,0.0,test -2020-01-26 17:00:00,machine-1-1_y_27,0.106131,0.0,test -2020-01-26 18:00:00,machine-1-1_y_27,0.115745,0.0,test -2020-01-26 19:00:00,machine-1-1_y_27,0.111529,0.0,test -2020-01-26 20:00:00,machine-1-1_y_27,0.112987,0.0,test -2020-01-26 21:00:00,machine-1-1_y_27,0.137417,0.0,test -2020-01-26 22:00:00,machine-1-1_y_27,0.092281,0.0,test -2020-01-26 23:00:00,machine-1-1_y_27,0.070432,0.0,test -2020-01-27 00:00:00,machine-1-1_y_27,0.052406,0.0,test -2020-01-27 01:00:00,machine-1-1_y_27,0.038122,0.0,test -2020-01-27 02:00:00,machine-1-1_y_27,0.031148,0.0,test -2020-01-27 03:00:00,machine-1-1_y_27,0.030458,0.0,test -2020-01-27 04:00:00,machine-1-1_y_27,0.032625,0.0,test -2020-01-27 05:00:00,machine-1-1_y_27,0.062946,0.0,test -2020-01-27 06:00:00,machine-1-1_y_27,0.070294,0.0,test -2020-01-27 07:00:00,machine-1-1_y_27,0.091867,0.0,test -2020-01-27 08:00:00,machine-1-1_y_27,0.081268,0.0,test -2020-01-27 09:00:00,machine-1-1_y_27,0.076973,0.0,test -2020-01-27 10:00:00,machine-1-1_y_27,0.080716,0.0,test -2020-01-27 11:00:00,machine-1-1_y_27,0.104181,0.0,test -2020-01-27 12:00:00,machine-1-1_y_27,0.067576,0.0,test -2020-01-27 13:00:00,machine-1-1_y_27,0.057331,0.0,test -2020-01-27 14:00:00,machine-1-1_y_27,0.079869,0.0,test -2020-01-27 15:00:00,machine-1-1_y_27,0.073151,0.0,test -2020-01-27 16:00:00,machine-1-1_y_27,0.086843,0.0,test -2020-01-27 17:00:00,machine-1-1_y_27,0.087691,0.0,test -2020-01-27 18:00:00,machine-1-1_y_27,0.084775,0.0,test -2020-01-27 19:00:00,machine-1-1_y_27,0.085799,0.0,test -2020-01-27 20:00:00,machine-1-1_y_27,0.095354,0.0,test -2020-01-27 21:00:00,machine-1-1_y_27,0.08773,0.0,test -2020-01-27 22:00:00,machine-1-1_y_27,0.079101,0.0,test -2020-01-27 23:00:00,machine-1-1_y_27,0.058257,0.0,test -2020-01-28 00:00:00,machine-1-1_y_27,0.041333,0.0,test -2020-01-28 01:00:00,machine-1-1_y_27,0.035009,0.0,test -2020-01-28 02:00:00,machine-1-1_y_27,0.033098,0.0,test -2020-01-28 03:00:00,machine-1-1_y_27,0.030931,0.0,test -2020-01-28 04:00:00,machine-1-1_y_27,0.030951,0.0,test -2020-01-28 05:00:00,machine-1-1_y_27,0.051381,0.0,test -2020-01-28 06:00:00,machine-1-1_y_27,0.088124,0.0,test -2020-01-28 07:00:00,machine-1-1_y_27,0.091749,0.0,test -2020-01-28 08:00:00,machine-1-1_y_27,0.077072,0.0,test -2020-01-28 09:00:00,machine-1-1_y_27,0.093522,0.0,test -2020-01-28 10:00:00,machine-1-1_y_27,0.078372,0.0,test -2020-01-28 11:00:00,machine-1-1_y_27,0.081642,0.0,test -2020-01-28 12:00:00,machine-1-1_y_27,0.083947,0.0,test -2020-01-28 13:00:00,machine-1-1_y_27,0.067674,0.0,test -2020-01-28 14:00:00,machine-1-1_y_27,0.068245,0.0,test -2020-01-28 15:00:00,machine-1-1_y_27,0.086843,0.0,test 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09:00:00,machine-1-1_y_27,0.405847,0.0,test -2020-01-29 10:00:00,machine-1-1_y_27,0.368789,0.0,test -2020-01-29 11:00:00,machine-1-1_y_27,0.39779,0.0,test -2020-01-29 12:00:00,machine-1-1_y_27,0.408369,0.0,test -2020-01-29 13:00:00,machine-1-1_y_27,0.132728,0.0,test -2020-01-29 14:00:00,machine-1-1_y_27,0.101088,0.0,test -2020-01-29 15:00:00,machine-1-1_y_27,0.118366,0.0,test -2020-01-29 16:00:00,machine-1-1_y_27,0.112376,0.0,test -2020-01-29 17:00:00,machine-1-1_y_27,0.114248,0.0,test -2020-01-29 18:00:00,machine-1-1_y_27,0.116691,0.0,test -2020-01-29 19:00:00,machine-1-1_y_27,0.112554,0.0,test -2020-01-29 20:00:00,machine-1-1_y_27,0.146164,0.0,test -2020-01-29 21:00:00,machine-1-1_y_27,0.14512,0.0,test -2020-01-29 22:00:00,machine-1-1_y_27,0.103491,0.0,test -2020-01-29 23:00:00,machine-1-1_y_27,0.076185,0.0,test -2020-01-30 00:00:00,machine-1-1_y_27,0.049588,0.0,test -2020-01-30 01:00:00,machine-1-1_y_27,0.035364,0.0,test -2020-01-30 02:00:00,machine-1-1_y_27,0.031049,0.0,test 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20:00:00,machine-1-1_y_27,0.14447,0.0,test -2020-01-30 21:00:00,machine-1-1_y_27,0.130462,0.0,test -2020-01-30 22:00:00,machine-1-1_y_27,0.112416,0.0,test -2020-01-30 23:00:00,machine-1-1_y_27,0.08312,0.0,test -2020-01-31 00:00:00,machine-1-1_y_27,0.04945,0.0,test -2020-01-31 01:00:00,machine-1-1_y_27,0.03629,0.0,test -2020-01-31 02:00:00,machine-1-1_y_27,0.031305,0.0,test -2020-01-31 03:00:00,machine-1-1_y_27,0.050297,0.0,test -2020-01-31 04:00:00,machine-1-1_y_27,0.124197,0.0,test -2020-01-31 05:00:00,machine-1-1_y_27,0.235904,0.0,test -2020-01-31 06:00:00,machine-1-1_y_27,0.28823,0.0,test -2020-01-31 07:00:00,machine-1-1_y_27,0.555893,0.0,test -2020-01-31 08:00:00,machine-1-1_y_27,0.546535,0.0,test -2020-01-31 09:00:00,machine-1-1_y_27,0.448107,0.0,test -2020-01-31 10:00:00,machine-1-1_y_27,0.170298,0.0,test -2020-01-31 11:00:00,machine-1-1_y_27,0.143465,0.0,test -2020-01-31 12:00:00,machine-1-1_y_27,0.248079,0.0,test -2020-01-31 13:00:00,machine-1-1_y_27,0.158162,0.0,test 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20:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-26 21:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-26 22:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-26 23:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 00:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 01:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 02:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 03:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 04:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 05:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 06:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 07:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 08:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 09:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 10:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 11:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 12:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 13:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 14:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-27 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05:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 06:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 07:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 08:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 09:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 10:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 11:00:00,machine-1-1_y_28,8.2e-05,0.0,test -2020-01-29 12:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 13:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 14:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 15:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 16:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 17:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 18:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 19:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 20:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 21:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 22:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-29 23:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 00:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 01:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 02:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 03:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 04:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 05:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 06:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 07:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 08:00:00,machine-1-1_y_28,0.000117,0.0,test -2020-01-30 09:00:00,machine-1-1_y_28,0.011425,0.0,test -2020-01-30 10:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 11:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 12:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 13:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 14:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 15:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 16:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 17:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 18:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 19:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 20:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 21:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 22:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-30 23:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 00:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 01:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 02:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 03:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 04:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 05:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 06:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 07:00:00,machine-1-1_y_28,0.000191,0.0,test -2020-01-31 08:00:00,machine-1-1_y_28,6.5e-05,0.0,test -2020-01-31 09:00:00,machine-1-1_y_28,2.6e-05,0.0,test -2020-01-31 10:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 11:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 12:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 13:00:00,machine-1-1_y_28,0.0,0.0,test -2020-01-31 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12:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-13 13:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 14:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 15:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 16:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-13 17:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 18:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 19:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 20:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 21:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-13 22:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-13 23:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 00:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 01:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-14 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 07:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-14 08:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-14 09:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-14 10:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-14 11:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-14 12:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-14 13:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-14 14:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 15:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-14 16:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-14 17:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 18:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-14 19:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 20:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 21:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-14 22:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-14 23:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 00:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 01:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-15 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-15 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-15 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-15 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 07:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-15 08:00:00,machine-1-1_y_29,0.015759,0.0,train -2020-01-15 09:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-15 10:00:00,machine-1-1_y_29,0.028653,0.0,train -2020-01-15 11:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-15 12:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-15 13:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-15 14:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 15:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 16:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-15 17:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-15 18:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 19:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 20:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-15 21:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 22:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-15 23:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-16 00:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-16 01:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-16 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-16 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-16 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-16 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-16 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-16 07:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 08:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-16 09:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-16 10:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-16 11:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-16 12:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-16 13:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 14:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 15:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 16:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 17:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 18:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-16 19:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 20:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-16 21:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 22:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-16 23:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-17 00:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-17 01:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-17 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-17 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-17 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-17 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-17 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-17 07:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-17 08:00:00,machine-1-1_y_29,0.025788,0.0,train -2020-01-17 09:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-17 10:00:00,machine-1-1_y_29,0.024355,0.0,train -2020-01-17 11:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-17 12:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-17 13:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-17 14:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-17 15:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-17 16:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-17 17:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-17 18:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-17 19:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-17 20:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-17 21:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-17 22:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-17 23:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-18 00:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-18 01:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-18 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-18 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-18 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-18 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-18 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-18 07:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-18 08:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-18 09:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-18 10:00:00,machine-1-1_y_29,0.020057,0.0,train -2020-01-18 11:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-18 12:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-18 13:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-18 14:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-18 15:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-18 16:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-18 17:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-18 18:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-18 19:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-18 20:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-18 21:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-18 22:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-18 23:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-19 00:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-19 01:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-19 02:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-19 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-19 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-19 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-19 06:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-19 07:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-19 08:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-19 09:00:00,machine-1-1_y_29,0.024355,0.0,train -2020-01-19 10:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-19 11:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-19 12:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-19 13:00:00,machine-1-1_y_29,0.014327,0.0,train -2020-01-19 14:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-19 15:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-19 16:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-19 17:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-19 18:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-19 19:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-19 20:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-19 21:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-19 22:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-19 23:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-20 00:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-20 01:00:00,machine-1-1_y_29,0.007163,0.0,train -2020-01-20 02:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-20 03:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-20 04:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-20 05:00:00,machine-1-1_y_29,0.005731,0.0,train -2020-01-20 06:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-20 07:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-20 08:00:00,machine-1-1_y_29,0.012894,0.0,train -2020-01-20 09:00:00,machine-1-1_y_29,0.015759,0.0,train -2020-01-20 10:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-20 11:00:00,machine-1-1_y_29,0.017192,0.0,train -2020-01-20 12:00:00,machine-1-1_y_29,0.011461,0.0,train -2020-01-20 13:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-20 14:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-20 15:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-20 16:00:00,machine-1-1_y_29,0.008596,0.0,train -2020-01-20 17:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-20 18:00:00,machine-1-1_y_29,0.010029,0.0,train -2020-01-20 19:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-20 20:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-20 21:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-20 22:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-20 23:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-21 00:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-21 01:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-21 02:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-21 03:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-21 04:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-21 05:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-21 06:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-21 07:00:00,machine-1-1_y_29,0.010029,0.0,test 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01:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-22 02:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-22 03:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-22 04:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-22 05:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-22 06:00:00,machine-1-1_y_29,0.018625,0.0,test -2020-01-22 07:00:00,machine-1-1_y_29,0.022923,0.0,test -2020-01-22 08:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-22 09:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-22 10:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-22 11:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-22 12:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-22 13:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-22 14:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-22 15:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-22 16:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-22 17:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-22 18:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-22 19:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-22 20:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-22 21:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-22 22:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-22 23:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-23 00:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-23 01:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-23 02:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-23 03:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-23 04:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-23 05:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-23 06:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-23 07:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-23 08:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-23 09:00:00,machine-1-1_y_29,0.044413,0.0,test -2020-01-23 10:00:00,machine-1-1_y_29,0.02149,0.0,test -2020-01-23 11:00:00,machine-1-1_y_29,0.025788,0.0,test -2020-01-23 12:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-23 13:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-23 14:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-23 15:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-23 16:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-23 17:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-23 18:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-23 19:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-23 20:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-23 21:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-23 22:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-23 23:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-24 00:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-24 01:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-24 02:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-24 03:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-24 04:00:00,machine-1-1_y_29,0.005731,0.0,test -2020-01-24 05:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-24 06:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 07:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-24 08:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 09:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-24 10:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-24 11:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-24 12:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 13:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 14:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-24 15:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-24 16:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 17:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-24 18:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 19:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-24 20:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-24 21:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-24 22:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-24 23:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-25 00:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-25 01:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-25 02:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-25 03:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-25 04:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-25 05:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 06:00:00,machine-1-1_y_29,0.025788,0.0,test -2020-01-25 07:00:00,machine-1-1_y_29,0.020057,0.0,test -2020-01-25 08:00:00,machine-1-1_y_29,0.02149,0.0,test -2020-01-25 09:00:00,machine-1-1_y_29,0.035817,0.0,test -2020-01-25 10:00:00,machine-1-1_y_29,0.018625,0.0,test -2020-01-25 11:00:00,machine-1-1_y_29,0.024355,0.0,test -2020-01-25 12:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-25 13:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 14:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-25 15:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 16:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 17:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-25 18:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-25 19:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-25 20:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 21:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-25 22:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-25 23:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-26 00:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-26 01:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-26 02:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-26 03:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-26 04:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-26 05:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-26 06:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 07:00:00,machine-1-1_y_29,0.020057,0.0,test -2020-01-26 08:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-26 09:00:00,machine-1-1_y_29,0.035817,0.0,test -2020-01-26 10:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-26 11:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-26 12:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 13:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-26 14:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-26 15:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 16:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-26 17:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 18:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 19:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-26 20:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-26 21:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-26 22:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-26 23:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-27 00:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-27 01:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-27 02:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-27 03:00:00,machine-1-1_y_29,0.007163,0.0,test 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21:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-27 22:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-27 23:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-28 00:00:00,machine-1-1_y_29,0.008596,0.0,test -2020-01-28 01:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-28 02:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-28 03:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-28 04:00:00,machine-1-1_y_29,0.007163,0.0,test -2020-01-28 05:00:00,machine-1-1_y_29,0.010029,0.0,test -2020-01-28 06:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-28 07:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-28 08:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-28 09:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-28 10:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-28 11:00:00,machine-1-1_y_29,0.012894,0.0,test -2020-01-28 12:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-28 13:00:00,machine-1-1_y_29,0.011461,0.0,test -2020-01-28 14:00:00,machine-1-1_y_29,0.010029,0.0,test 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08:00:00,machine-1-1_y_29,0.031519,0.0,test -2020-01-29 09:00:00,machine-1-1_y_29,0.034384,0.0,test -2020-01-29 10:00:00,machine-1-1_y_29,0.030086,0.0,test -2020-01-29 11:00:00,machine-1-1_y_29,0.025788,0.0,test -2020-01-29 12:00:00,machine-1-1_y_29,0.022923,0.0,test -2020-01-29 13:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 14:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-29 15:00:00,machine-1-1_y_29,0.018625,0.0,test -2020-01-29 16:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 17:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 18:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 19:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 20:00:00,machine-1-1_y_29,0.020057,0.0,test -2020-01-29 21:00:00,machine-1-1_y_29,0.020057,0.0,test -2020-01-29 22:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-29 23:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-30 00:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-30 01:00:00,machine-1-1_y_29,0.014327,0.0,test 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19:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-30 20:00:00,machine-1-1_y_29,0.020057,0.0,test -2020-01-30 21:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-30 22:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-30 23:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-31 00:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-31 01:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-31 02:00:00,machine-1-1_y_29,0.014327,0.0,test -2020-01-31 03:00:00,machine-1-1_y_29,0.015759,0.0,test -2020-01-31 04:00:00,machine-1-1_y_29,0.02149,0.0,test -2020-01-31 05:00:00,machine-1-1_y_29,0.030086,0.0,test -2020-01-31 06:00:00,machine-1-1_y_29,0.034384,0.0,test -2020-01-31 07:00:00,machine-1-1_y_29,0.074499,0.0,test -2020-01-31 08:00:00,machine-1-1_y_29,0.053009,0.0,test -2020-01-31 09:00:00,machine-1-1_y_29,0.032951,0.0,test -2020-01-31 10:00:00,machine-1-1_y_29,0.018625,0.0,test -2020-01-31 11:00:00,machine-1-1_y_29,0.017192,0.0,test -2020-01-31 12:00:00,machine-1-1_y_29,0.020057,0.0,test 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11:00:00,machine-1-1_y_29,0.047278,1.0,test -2020-02-03 12:00:00,machine-1-1_y_29,0.051576,1.0,test -2020-02-03 13:00:00,machine-1-1_y_29,0.055874,1.0,test -2020-02-03 14:00:00,machine-1-1_y_29,0.077364,1.0,test -2020-02-03 15:00:00,machine-1-1_y_29,0.071633,1.0,test -2020-02-03 16:00:00,machine-1-1_y_29,0.114613,1.0,test -2020-02-03 17:00:00,machine-1-1_y_29,0.088825,1.0,test -2020-02-03 18:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-03 19:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-03 20:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-03 21:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-03 22:00:00,machine-1-1_y_29,0.051576,0.0,test -2020-02-03 23:00:00,machine-1-1_y_29,0.04298,0.0,test -2020-02-04 00:00:00,machine-1-1_y_29,0.04298,0.0,test -2020-02-04 01:00:00,machine-1-1_y_29,0.04298,0.0,test -2020-02-04 02:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-04 03:00:00,machine-1-1_y_29,0.040115,0.0,test -2020-02-04 04:00:00,machine-1-1_y_29,0.038682,0.0,test 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23:00:00,machine-1-1_y_3,0.113821,0.0,train -2020-01-19 00:00:00,machine-1-1_y_3,0.089431,0.0,train -2020-01-19 01:00:00,machine-1-1_y_3,0.066202,0.0,train -2020-01-19 02:00:00,machine-1-1_y_3,0.060395,0.0,train -2020-01-19 03:00:00,machine-1-1_y_3,0.039489,0.0,train -2020-01-19 04:00:00,machine-1-1_y_3,0.026713,0.0,train -2020-01-19 05:00:00,machine-1-1_y_3,0.031359,0.0,train -2020-01-19 06:00:00,machine-1-1_y_3,0.046458,0.0,train -2020-01-19 07:00:00,machine-1-1_y_3,0.080139,0.0,train -2020-01-19 08:00:00,machine-1-1_y_3,0.12079,0.0,train -2020-01-19 09:00:00,machine-1-1_y_3,0.132404,0.0,train -2020-01-19 10:00:00,machine-1-1_y_3,0.170732,0.0,train -2020-01-19 11:00:00,machine-1-1_y_3,0.149826,0.0,train -2020-01-19 12:00:00,machine-1-1_y_3,0.135889,0.0,train -2020-01-19 13:00:00,machine-1-1_y_3,0.12079,0.0,train -2020-01-19 14:00:00,machine-1-1_y_3,0.094077,0.0,train -2020-01-19 15:00:00,machine-1-1_y_3,0.092915,0.0,train -2020-01-19 16:00:00,machine-1-1_y_3,0.078978,0.0,train 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04:00:00,machine-1-1_y_3,0.031359,0.0,test -2020-01-21 05:00:00,machine-1-1_y_3,0.027875,0.0,test -2020-01-21 06:00:00,machine-1-1_y_3,0.04065,0.0,test -2020-01-21 07:00:00,machine-1-1_y_3,0.077816,0.0,test -2020-01-21 08:00:00,machine-1-1_y_3,0.11266,0.0,test -2020-01-21 09:00:00,machine-1-1_y_3,0.111498,0.0,test -2020-01-21 10:00:00,machine-1-1_y_3,0.125436,0.0,test -2020-01-21 11:00:00,machine-1-1_y_3,0.132404,0.0,test -2020-01-21 12:00:00,machine-1-1_y_3,0.15331,0.0,test -2020-01-21 13:00:00,machine-1-1_y_3,0.144019,0.0,test -2020-01-21 14:00:00,machine-1-1_y_3,0.0964,0.0,test -2020-01-21 15:00:00,machine-1-1_y_3,0.081301,0.0,test -2020-01-21 16:00:00,machine-1-1_y_3,0.065041,0.0,test -2020-01-21 17:00:00,machine-1-1_y_3,0.083624,0.0,test -2020-01-21 18:00:00,machine-1-1_y_3,0.084785,0.0,test -2020-01-21 19:00:00,machine-1-1_y_3,0.082462,0.0,test -2020-01-21 20:00:00,machine-1-1_y_3,0.099884,0.0,test -2020-01-21 21:00:00,machine-1-1_y_3,0.082462,0.0,test -2020-01-21 22:00:00,machine-1-1_y_3,0.0964,0.0,test -2020-01-21 23:00:00,machine-1-1_y_3,0.089431,0.0,test -2020-01-22 00:00:00,machine-1-1_y_3,0.073171,0.0,test -2020-01-22 01:00:00,machine-1-1_y_3,0.039489,0.0,test -2020-01-22 02:00:00,machine-1-1_y_3,0.030197,0.0,test -2020-01-22 03:00:00,machine-1-1_y_3,0.036005,0.0,test -2020-01-22 04:00:00,machine-1-1_y_3,0.030197,0.0,test -2020-01-22 05:00:00,machine-1-1_y_3,0.062718,0.0,test -2020-01-22 06:00:00,machine-1-1_y_3,0.110337,0.0,test -2020-01-22 07:00:00,machine-1-1_y_3,0.170732,0.0,test -2020-01-22 08:00:00,machine-1-1_y_3,0.150987,0.0,test -2020-01-22 09:00:00,machine-1-1_y_3,0.134727,0.0,test -2020-01-22 10:00:00,machine-1-1_y_3,0.116144,0.0,test -2020-01-22 11:00:00,machine-1-1_y_3,0.162602,0.0,test -2020-01-22 12:00:00,machine-1-1_y_3,0.097561,0.0,test -2020-01-22 13:00:00,machine-1-1_y_3,0.072009,0.0,test -2020-01-22 14:00:00,machine-1-1_y_3,0.067364,0.0,test -2020-01-22 15:00:00,machine-1-1_y_3,0.075494,0.0,test -2020-01-22 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22:00:00,machine-1-1_y_3,0.091754,0.0,test -2020-01-24 23:00:00,machine-1-1_y_3,0.055749,0.0,test -2020-01-25 00:00:00,machine-1-1_y_3,0.055749,0.0,test -2020-01-25 01:00:00,machine-1-1_y_3,0.039489,0.0,test -2020-01-25 02:00:00,machine-1-1_y_3,0.034843,0.0,test -2020-01-25 03:00:00,machine-1-1_y_3,0.029036,0.0,test -2020-01-25 04:00:00,machine-1-1_y_3,0.031359,0.0,test -2020-01-25 05:00:00,machine-1-1_y_3,0.04878,0.0,test -2020-01-25 06:00:00,machine-1-1_y_3,0.105691,0.0,test -2020-01-25 07:00:00,machine-1-1_y_3,0.146341,0.0,test -2020-01-25 08:00:00,machine-1-1_y_3,0.193961,0.0,test -2020-01-25 09:00:00,machine-1-1_y_3,0.210221,0.0,test -2020-01-25 10:00:00,machine-1-1_y_3,0.193961,0.0,test -2020-01-25 11:00:00,machine-1-1_y_3,0.228804,0.0,test -2020-01-25 12:00:00,machine-1-1_y_3,0.192799,0.0,test -2020-01-25 13:00:00,machine-1-1_y_3,0.132404,0.0,test -2020-01-25 14:00:00,machine-1-1_y_3,0.108014,0.0,test -2020-01-25 15:00:00,machine-1-1_y_3,0.084785,0.0,test -2020-01-25 16:00:00,machine-1-1_y_3,0.084785,0.0,test -2020-01-25 17:00:00,machine-1-1_y_3,0.105691,0.0,test -2020-01-25 18:00:00,machine-1-1_y_3,0.097561,0.0,test -2020-01-25 19:00:00,machine-1-1_y_3,0.125436,0.0,test -2020-01-25 20:00:00,machine-1-1_y_3,0.126597,0.0,test -2020-01-25 21:00:00,machine-1-1_y_3,0.102207,0.0,test -2020-01-25 22:00:00,machine-1-1_y_3,0.10453,0.0,test -2020-01-25 23:00:00,machine-1-1_y_3,0.070848,0.0,test -2020-01-26 00:00:00,machine-1-1_y_3,0.045296,0.0,test -2020-01-26 01:00:00,machine-1-1_y_3,0.026713,0.0,test -2020-01-26 02:00:00,machine-1-1_y_3,0.029036,0.0,test -2020-01-26 03:00:00,machine-1-1_y_3,0.019744,0.0,test -2020-01-26 04:00:00,machine-1-1_y_3,0.029036,0.0,test -2020-01-26 05:00:00,machine-1-1_y_3,0.030197,0.0,test -2020-01-26 06:00:00,machine-1-1_y_3,0.083624,0.0,test -2020-01-26 07:00:00,machine-1-1_y_3,0.088269,0.0,test -2020-01-26 08:00:00,machine-1-1_y_3,0.090592,0.0,test -2020-01-26 09:00:00,machine-1-1_y_3,0.094077,0.0,test -2020-01-26 10:00:00,machine-1-1_y_3,0.090592,0.0,test -2020-01-26 11:00:00,machine-1-1_y_3,0.084785,0.0,test -2020-01-26 12:00:00,machine-1-1_y_3,0.077816,0.0,test -2020-01-26 13:00:00,machine-1-1_y_3,0.061556,0.0,test -2020-01-26 14:00:00,machine-1-1_y_3,0.075494,0.0,test -2020-01-26 15:00:00,machine-1-1_y_3,0.10453,0.0,test -2020-01-26 16:00:00,machine-1-1_y_3,0.111498,0.0,test -2020-01-26 17:00:00,machine-1-1_y_3,0.105691,0.0,test -2020-01-26 18:00:00,machine-1-1_y_3,0.098722,0.0,test -2020-01-26 19:00:00,machine-1-1_y_3,0.082462,0.0,test -2020-01-26 20:00:00,machine-1-1_y_3,0.082462,0.0,test -2020-01-26 21:00:00,machine-1-1_y_3,0.102207,0.0,test -2020-01-26 22:00:00,machine-1-1_y_3,0.080139,0.0,test -2020-01-26 23:00:00,machine-1-1_y_3,0.063879,0.0,test -2020-01-27 00:00:00,machine-1-1_y_3,0.042973,0.0,test -2020-01-27 01:00:00,machine-1-1_y_3,0.034843,0.0,test -2020-01-27 02:00:00,machine-1-1_y_3,0.026713,0.0,test -2020-01-27 03:00:00,machine-1-1_y_3,0.019744,0.0,test -2020-01-27 04:00:00,machine-1-1_y_3,0.02439,0.0,test -2020-01-27 05:00:00,machine-1-1_y_3,0.03252,0.0,test -2020-01-27 06:00:00,machine-1-1_y_3,0.055749,0.0,test -2020-01-27 07:00:00,machine-1-1_y_3,0.072009,0.0,test -2020-01-27 08:00:00,machine-1-1_y_3,0.077816,0.0,test -2020-01-27 09:00:00,machine-1-1_y_3,0.072009,0.0,test -2020-01-27 10:00:00,machine-1-1_y_3,0.063879,0.0,test -2020-01-27 11:00:00,machine-1-1_y_3,0.072009,0.0,test -2020-01-27 12:00:00,machine-1-1_y_3,0.073171,0.0,test -2020-01-27 13:00:00,machine-1-1_y_3,0.047619,0.0,test -2020-01-27 14:00:00,machine-1-1_y_3,0.049942,0.0,test -2020-01-27 15:00:00,machine-1-1_y_3,0.066202,0.0,test -2020-01-27 16:00:00,machine-1-1_y_3,0.066202,0.0,test -2020-01-27 17:00:00,machine-1-1_y_3,0.076655,0.0,test -2020-01-27 18:00:00,machine-1-1_y_3,0.081301,0.0,test -2020-01-27 19:00:00,machine-1-1_y_3,0.078978,0.0,test -2020-01-27 20:00:00,machine-1-1_y_3,0.091754,0.0,test -2020-01-27 21:00:00,machine-1-1_y_3,0.10453,0.0,test -2020-01-27 22:00:00,machine-1-1_y_3,0.068525,0.0,test -2020-01-27 23:00:00,machine-1-1_y_3,0.051103,0.0,test -2020-01-28 00:00:00,machine-1-1_y_3,0.041812,0.0,test -2020-01-28 01:00:00,machine-1-1_y_3,0.037166,0.0,test -2020-01-28 02:00:00,machine-1-1_y_3,0.027875,0.0,test -2020-01-28 03:00:00,machine-1-1_y_3,0.03252,0.0,test -2020-01-28 04:00:00,machine-1-1_y_3,0.027875,0.0,test -2020-01-28 05:00:00,machine-1-1_y_3,0.047619,0.0,test -2020-01-28 06:00:00,machine-1-1_y_3,0.060395,0.0,test -2020-01-28 07:00:00,machine-1-1_y_3,0.059233,0.0,test -2020-01-28 08:00:00,machine-1-1_y_3,0.059233,0.0,test -2020-01-28 09:00:00,machine-1-1_y_3,0.087108,0.0,test -2020-01-28 10:00:00,machine-1-1_y_3,0.069686,0.0,test -2020-01-28 11:00:00,machine-1-1_y_3,0.080139,0.0,test -2020-01-28 12:00:00,machine-1-1_y_3,0.070848,0.0,test -2020-01-28 13:00:00,machine-1-1_y_3,0.059233,0.0,test -2020-01-28 14:00:00,machine-1-1_y_3,0.066202,0.0,test -2020-01-28 15:00:00,machine-1-1_y_3,0.092915,0.0,test -2020-01-28 16:00:00,machine-1-1_y_3,0.077816,0.0,test -2020-01-28 17:00:00,machine-1-1_y_3,0.0964,0.0,test -2020-01-28 18:00:00,machine-1-1_y_3,0.116144,0.0,test -2020-01-28 19:00:00,machine-1-1_y_3,0.126597,0.0,test -2020-01-28 20:00:00,machine-1-1_y_3,0.111498,0.0,test -2020-01-28 21:00:00,machine-1-1_y_3,0.116144,0.0,test -2020-01-28 22:00:00,machine-1-1_y_3,0.089431,0.0,test -2020-01-28 23:00:00,machine-1-1_y_3,0.066202,0.0,test -2020-01-29 00:00:00,machine-1-1_y_3,0.042973,0.0,test -2020-01-29 01:00:00,machine-1-1_y_3,0.025552,0.0,test -2020-01-29 02:00:00,machine-1-1_y_3,0.023229,0.0,test -2020-01-29 03:00:00,machine-1-1_y_3,0.02439,0.0,test -2020-01-29 04:00:00,machine-1-1_y_3,0.022067,0.0,test -2020-01-29 05:00:00,machine-1-1_y_3,0.061556,0.0,test -2020-01-29 06:00:00,machine-1-1_y_3,0.182346,0.0,test -2020-01-29 07:00:00,machine-1-1_y_3,0.284553,0.0,test -2020-01-29 08:00:00,machine-1-1_y_3,0.31475,0.0,test -2020-01-29 09:00:00,machine-1-1_y_3,0.457607,0.0,test -2020-01-29 10:00:00,machine-1-1_y_3,0.406504,0.0,test -2020-01-29 11:00:00,machine-1-1_y_3,0.407666,0.0,test -2020-01-29 12:00:00,machine-1-1_y_3,0.412311,0.0,test -2020-01-29 13:00:00,machine-1-1_y_3,0.146341,0.0,test -2020-01-29 14:00:00,machine-1-1_y_3,0.102207,0.0,test -2020-01-29 15:00:00,machine-1-1_y_3,0.0964,0.0,test -2020-01-29 16:00:00,machine-1-1_y_3,0.123113,0.0,test -2020-01-29 17:00:00,machine-1-1_y_3,0.119628,0.0,test -2020-01-29 18:00:00,machine-1-1_y_3,0.124274,0.0,test -2020-01-29 19:00:00,machine-1-1_y_3,0.0964,0.0,test -2020-01-29 20:00:00,machine-1-1_y_3,0.11266,0.0,test -2020-01-29 21:00:00,machine-1-1_y_3,0.133566,0.0,test -2020-01-29 22:00:00,machine-1-1_y_3,0.116144,0.0,test -2020-01-29 23:00:00,machine-1-1_y_3,0.070848,0.0,test -2020-01-30 00:00:00,machine-1-1_y_3,0.044135,0.0,test -2020-01-30 01:00:00,machine-1-1_y_3,0.041812,0.0,test -2020-01-30 02:00:00,machine-1-1_y_3,0.026713,0.0,test -2020-01-30 03:00:00,machine-1-1_y_3,0.02439,0.0,test -2020-01-30 04:00:00,machine-1-1_y_3,0.018583,0.0,test -2020-01-30 05:00:00,machine-1-1_y_3,0.088269,0.0,test -2020-01-30 06:00:00,machine-1-1_y_3,0.277584,0.0,test -2020-01-30 07:00:00,machine-1-1_y_3,0.409988,0.0,test -2020-01-30 08:00:00,machine-1-1_y_3,0.473868,0.0,test -2020-01-30 09:00:00,machine-1-1_y_3,0.490128,0.0,test -2020-01-30 10:00:00,machine-1-1_y_3,0.318235,0.0,test -2020-01-30 11:00:00,machine-1-1_y_3,0.312427,0.0,test -2020-01-30 12:00:00,machine-1-1_y_3,0.264808,0.0,test -2020-01-30 13:00:00,machine-1-1_y_3,0.13705,0.0,test -2020-01-30 14:00:00,machine-1-1_y_3,0.108014,0.0,test -2020-01-30 15:00:00,machine-1-1_y_3,0.111498,0.0,test -2020-01-30 16:00:00,machine-1-1_y_3,0.105691,0.0,test -2020-01-30 17:00:00,machine-1-1_y_3,0.130081,0.0,test -2020-01-30 18:00:00,machine-1-1_y_3,0.12892,0.0,test -2020-01-30 19:00:00,machine-1-1_y_3,0.125436,0.0,test -2020-01-30 20:00:00,machine-1-1_y_3,0.11266,0.0,test -2020-01-30 21:00:00,machine-1-1_y_3,0.130081,0.0,test -2020-01-30 22:00:00,machine-1-1_y_3,0.106852,0.0,test -2020-01-30 23:00:00,machine-1-1_y_3,0.091754,0.0,test -2020-01-31 00:00:00,machine-1-1_y_3,0.042973,0.0,test -2020-01-31 01:00:00,machine-1-1_y_3,0.042973,0.0,test -2020-01-31 02:00:00,machine-1-1_y_3,0.033682,0.0,test -2020-01-31 03:00:00,machine-1-1_y_3,0.033682,0.0,test -2020-01-31 04:00:00,machine-1-1_y_3,0.094077,0.0,test -2020-01-31 05:00:00,machine-1-1_y_3,0.200929,0.0,test -2020-01-31 06:00:00,machine-1-1_y_3,0.242741,0.0,test -2020-01-31 07:00:00,machine-1-1_y_3,0.442509,0.0,test -2020-01-31 08:00:00,machine-1-1_y_3,0.490128,0.0,test -2020-01-31 09:00:00,machine-1-1_y_3,0.499419,0.0,test -2020-01-31 10:00:00,machine-1-1_y_3,0.171893,0.0,test -2020-01-31 11:00:00,machine-1-1_y_3,0.148664,0.0,test -2020-01-31 12:00:00,machine-1-1_y_3,0.192799,0.0,test -2020-01-31 13:00:00,machine-1-1_y_3,0.16144,0.0,test -2020-01-31 14:00:00,machine-1-1_y_3,0.114983,0.0,test -2020-01-31 15:00:00,machine-1-1_y_3,0.118467,0.0,test -2020-01-31 16:00:00,machine-1-1_y_3,0.131243,0.0,test -2020-01-31 17:00:00,machine-1-1_y_3,0.097561,0.0,test -2020-01-31 18:00:00,machine-1-1_y_3,0.082462,1.0,test -2020-01-31 19:00:00,machine-1-1_y_3,0.065041,1.0,test -2020-01-31 20:00:00,machine-1-1_y_3,0.060395,1.0,test -2020-01-31 21:00:00,machine-1-1_y_3,0.055749,1.0,test -2020-01-31 22:00:00,machine-1-1_y_3,0.084785,1.0,test -2020-01-31 23:00:00,machine-1-1_y_3,0.15331,1.0,test -2020-02-01 00:00:00,machine-1-1_y_3,0.308943,1.0,test -2020-02-01 01:00:00,machine-1-1_y_3,0.534262,1.0,test -2020-02-01 02:00:00,machine-1-1_y_3,0.462253,1.0,test -2020-02-01 03:00:00,machine-1-1_y_3,0.47619,1.0,test -2020-02-01 04:00:00,machine-1-1_y_3,0.393728,0.0,test -2020-02-01 05:00:00,machine-1-1_y_3,0.175377,0.0,test -2020-02-01 06:00:00,machine-1-1_y_3,0.203252,0.0,test -2020-02-01 07:00:00,machine-1-1_y_3,0.18583,0.0,test -2020-02-01 08:00:00,machine-1-1_y_3,0.221835,0.0,test -2020-02-01 09:00:00,machine-1-1_y_3,0.234611,0.0,test -2020-02-01 10:00:00,machine-1-1_y_3,0.233449,0.0,test -2020-02-01 11:00:00,machine-1-1_y_3,0.205575,0.0,test -2020-02-01 12:00:00,machine-1-1_y_3,0.134727,0.0,test -2020-02-01 13:00:00,machine-1-1_y_3,0.116144,1.0,test -2020-02-01 14:00:00,machine-1-1_y_3,0.095238,1.0,test -2020-02-01 15:00:00,machine-1-1_y_3,0.053426,1.0,test -2020-02-01 16:00:00,machine-1-1_y_3,0.076655,1.0,test -2020-02-01 17:00:00,machine-1-1_y_3,0.192799,1.0,test -2020-02-01 18:00:00,machine-1-1_y_3,0.248548,1.0,test -2020-02-01 19:00:00,machine-1-1_y_3,0.440186,1.0,test -2020-02-01 20:00:00,machine-1-1_y_3,0.842044,1.0,test -2020-02-01 21:00:00,machine-1-1_y_3,0.97561,1.0,test -2020-02-01 22:00:00,machine-1-1_y_3,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_3,0.277584,0.0,test -2020-02-02 00:00:00,machine-1-1_y_3,0.181185,0.0,test -2020-02-02 01:00:00,machine-1-1_y_3,0.199768,0.0,test -2020-02-02 02:00:00,machine-1-1_y_3,0.197445,0.0,test -2020-02-02 03:00:00,machine-1-1_y_3,0.219512,0.0,test -2020-02-02 04:00:00,machine-1-1_y_3,0.229965,0.0,test -2020-02-02 05:00:00,machine-1-1_y_3,0.209059,0.0,test -2020-02-02 06:00:00,machine-1-1_y_3,0.154472,0.0,test -2020-02-02 07:00:00,machine-1-1_y_3,0.081301,1.0,test -2020-02-02 08:00:00,machine-1-1_y_3,0.098722,1.0,test -2020-02-02 09:00:00,machine-1-1_y_3,0.077816,1.0,test -2020-02-02 10:00:00,machine-1-1_y_3,0.056911,1.0,test -2020-02-02 11:00:00,machine-1-1_y_3,0.197445,1.0,test -2020-02-02 12:00:00,machine-1-1_y_3,0.259001,1.0,test -2020-02-02 13:00:00,machine-1-1_y_3,0.433217,1.0,test -2020-02-02 14:00:00,machine-1-1_y_3,0.628339,1.0,test -2020-02-02 15:00:00,machine-1-1_y_3,0.499419,1.0,test -2020-02-02 16:00:00,machine-1-1_y_3,0.272938,0.0,test -2020-02-02 17:00:00,machine-1-1_y_3,0.209059,0.0,test -2020-02-02 18:00:00,machine-1-1_y_3,0.099884,0.0,test -2020-02-02 19:00:00,machine-1-1_y_3,0.106852,0.0,test -2020-02-02 20:00:00,machine-1-1_y_3,0.092915,0.0,test -2020-02-02 21:00:00,machine-1-1_y_3,0.080139,0.0,test -2020-02-02 22:00:00,machine-1-1_y_3,0.11266,0.0,test -2020-02-02 23:00:00,machine-1-1_y_3,0.114983,0.0,test -2020-02-03 00:00:00,machine-1-1_y_3,0.108014,0.0,test -2020-02-03 01:00:00,machine-1-1_y_3,0.113821,0.0,test -2020-02-03 02:00:00,machine-1-1_y_3,0.101045,0.0,test -2020-02-03 03:00:00,machine-1-1_y_3,0.101045,0.0,test -2020-02-03 04:00:00,machine-1-1_y_3,0.083624,0.0,test -2020-02-03 05:00:00,machine-1-1_y_3,0.062718,1.0,test -2020-02-03 06:00:00,machine-1-1_y_3,0.052265,1.0,test -2020-02-03 07:00:00,machine-1-1_y_3,0.049942,1.0,test -2020-02-03 08:00:00,machine-1-1_y_3,0.059233,1.0,test -2020-02-03 09:00:00,machine-1-1_y_3,0.038328,1.0,test -2020-02-03 10:00:00,machine-1-1_y_3,0.061556,1.0,test -2020-02-03 11:00:00,machine-1-1_y_3,0.113821,1.0,test -2020-02-03 12:00:00,machine-1-1_y_3,0.197445,1.0,test -2020-02-03 13:00:00,machine-1-1_y_3,0.253194,1.0,test -2020-02-03 14:00:00,machine-1-1_y_3,0.40302,1.0,test -2020-02-03 15:00:00,machine-1-1_y_3,0.466899,1.0,test -2020-02-03 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22:00:00,machine-1-1_y_30,0.21363,0.0,test -2020-01-20 23:00:00,machine-1-1_y_30,0.103678,0.0,test -2020-01-21 00:00:00,machine-1-1_y_30,0.062914,0.0,test -2020-01-21 01:00:00,machine-1-1_y_30,0.044189,0.0,test -2020-01-21 02:00:00,machine-1-1_y_30,0.031529,0.0,test -2020-01-21 03:00:00,machine-1-1_y_30,0.026136,0.0,test -2020-01-21 04:00:00,machine-1-1_y_30,0.022358,0.0,test -2020-01-21 05:00:00,machine-1-1_y_30,0.023687,0.0,test -2020-01-21 06:00:00,machine-1-1_y_30,0.042892,0.0,test -2020-01-21 07:00:00,machine-1-1_y_30,0.078151,0.0,test -2020-01-21 08:00:00,machine-1-1_y_30,0.110096,0.0,test -2020-01-21 09:00:00,machine-1-1_y_30,0.095932,0.0,test -2020-01-21 10:00:00,machine-1-1_y_30,0.141273,0.0,test -2020-01-21 11:00:00,machine-1-1_y_30,0.139016,0.0,test -2020-01-21 12:00:00,machine-1-1_y_30,0.159326,0.0,test -2020-01-21 13:00:00,machine-1-1_y_30,0.130085,0.0,test -2020-01-21 14:00:00,machine-1-1_y_30,0.065587,0.0,test -2020-01-21 15:00:00,machine-1-1_y_30,0.058945,0.0,test 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09:00:00,machine-1-1_y_30,0.132454,0.0,test -2020-01-22 10:00:00,machine-1-1_y_30,0.105742,0.0,test -2020-01-22 11:00:00,machine-1-1_y_30,0.109151,0.0,test -2020-01-22 12:00:00,machine-1-1_y_30,0.071653,0.0,test -2020-01-22 13:00:00,machine-1-1_y_30,0.082248,0.0,test -2020-01-22 14:00:00,machine-1-1_y_30,0.075526,0.0,test -2020-01-22 15:00:00,machine-1-1_y_30,0.076118,0.0,test -2020-01-22 16:00:00,machine-1-1_y_30,0.080775,0.0,test -2020-01-22 17:00:00,machine-1-1_y_30,0.100301,0.0,test -2020-01-22 18:00:00,machine-1-1_y_30,0.10952,0.0,test -2020-01-22 19:00:00,machine-1-1_y_30,0.113473,0.0,test -2020-01-22 20:00:00,machine-1-1_y_30,0.103614,0.0,test -2020-01-22 21:00:00,machine-1-1_y_30,0.094571,0.0,test -2020-01-22 22:00:00,machine-1-1_y_30,0.072917,0.0,test -2020-01-22 23:00:00,machine-1-1_y_30,0.053727,0.0,test -2020-01-23 00:00:00,machine-1-1_y_30,0.037163,0.0,test -2020-01-23 01:00:00,machine-1-1_y_30,0.028008,0.0,test -2020-01-23 02:00:00,machine-1-1_y_30,0.021574,0.0,test 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20:00:00,machine-1-1_y_30,0.121203,0.0,test -2020-01-23 21:00:00,machine-1-1_y_30,0.119698,0.0,test -2020-01-23 22:00:00,machine-1-1_y_30,0.091626,0.0,test -2020-01-23 23:00:00,machine-1-1_y_30,0.064595,0.0,test -2020-01-24 00:00:00,machine-1-1_y_30,0.042508,0.0,test -2020-01-24 01:00:00,machine-1-1_y_30,0.032201,0.0,test -2020-01-24 02:00:00,machine-1-1_y_30,0.025863,0.0,test -2020-01-24 03:00:00,machine-1-1_y_30,0.023847,0.0,test -2020-01-24 04:00:00,machine-1-1_y_30,0.028344,0.0,test -2020-01-24 05:00:00,machine-1-1_y_30,0.065283,0.0,test -2020-01-24 06:00:00,machine-1-1_y_30,0.088762,0.0,test -2020-01-24 07:00:00,machine-1-1_y_30,0.105838,0.0,test -2020-01-24 08:00:00,machine-1-1_y_30,0.091594,0.0,test -2020-01-24 09:00:00,machine-1-1_y_30,0.112624,0.0,test -2020-01-24 10:00:00,machine-1-1_y_30,0.116145,0.0,test -2020-01-24 11:00:00,machine-1-1_y_30,0.108095,0.0,test -2020-01-24 12:00:00,machine-1-1_y_30,0.071861,0.0,test -2020-01-24 13:00:00,machine-1-1_y_30,0.067812,0.0,test 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07:00:00,machine-1-1_y_30,0.149803,0.0,test -2020-01-25 08:00:00,machine-1-1_y_30,0.176163,0.0,test -2020-01-25 09:00:00,machine-1-1_y_30,0.276704,0.0,test -2020-01-25 10:00:00,machine-1-1_y_30,0.192263,0.0,test -2020-01-25 11:00:00,machine-1-1_y_30,0.236516,0.0,test -2020-01-25 12:00:00,machine-1-1_y_30,0.189655,0.0,test -2020-01-25 13:00:00,machine-1-1_y_30,0.107183,0.0,test -2020-01-25 14:00:00,machine-1-1_y_30,0.082248,0.0,test -2020-01-25 15:00:00,machine-1-1_y_30,0.094923,0.0,test -2020-01-25 16:00:00,machine-1-1_y_30,0.106591,0.0,test -2020-01-25 17:00:00,machine-1-1_y_30,0.124212,0.0,test -2020-01-25 18:00:00,machine-1-1_y_30,0.099309,0.0,test -2020-01-25 19:00:00,machine-1-1_y_30,0.116241,0.0,test -2020-01-25 20:00:00,machine-1-1_y_30,0.118818,0.0,test -2020-01-25 21:00:00,machine-1-1_y_30,0.103054,0.0,test -2020-01-25 22:00:00,machine-1-1_y_30,0.08252,0.0,test -2020-01-25 23:00:00,machine-1-1_y_30,0.066691,0.0,test -2020-01-26 00:00:00,machine-1-1_y_30,0.046205,0.0,test 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18:00:00,machine-1-1_y_30,0.105214,0.0,test -2020-01-26 19:00:00,machine-1-1_y_30,0.101277,0.0,test -2020-01-26 20:00:00,machine-1-1_y_30,0.100861,0.0,test -2020-01-26 21:00:00,machine-1-1_y_30,0.125428,0.0,test -2020-01-26 22:00:00,machine-1-1_y_30,0.081399,0.0,test -2020-01-26 23:00:00,machine-1-1_y_30,0.061602,0.0,test -2020-01-27 00:00:00,machine-1-1_y_30,0.043981,0.0,test -2020-01-27 01:00:00,machine-1-1_y_30,0.031049,0.0,test -2020-01-27 02:00:00,machine-1-1_y_30,0.024663,0.0,test -2020-01-27 03:00:00,machine-1-1_y_30,0.024007,0.0,test -2020-01-27 04:00:00,machine-1-1_y_30,0.025639,0.0,test -2020-01-27 05:00:00,machine-1-1_y_30,0.054608,0.0,test -2020-01-27 06:00:00,machine-1-1_y_30,0.061858,0.0,test -2020-01-27 07:00:00,machine-1-1_y_30,0.082456,0.0,test -2020-01-27 08:00:00,machine-1-1_y_30,0.072261,0.0,test -2020-01-27 09:00:00,machine-1-1_y_30,0.067539,0.0,test -2020-01-27 10:00:00,machine-1-1_y_30,0.071781,0.0,test -2020-01-27 11:00:00,machine-1-1_y_30,0.093131,0.0,test 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05:00:00,machine-1-1_y_30,0.044093,0.0,test -2020-01-28 06:00:00,machine-1-1_y_30,0.078615,0.0,test -2020-01-28 07:00:00,machine-1-1_y_30,0.083448,0.0,test -2020-01-28 08:00:00,machine-1-1_y_30,0.06794,0.0,test -2020-01-28 09:00:00,machine-1-1_y_30,0.085048,0.0,test -2020-01-28 10:00:00,machine-1-1_y_30,0.069348,0.0,test -2020-01-28 11:00:00,machine-1-1_y_30,0.072949,0.0,test -2020-01-28 12:00:00,machine-1-1_y_30,0.074117,0.0,test -2020-01-28 13:00:00,machine-1-1_y_30,0.059361,0.0,test -2020-01-28 14:00:00,machine-1-1_y_30,0.060353,0.0,test -2020-01-28 15:00:00,machine-1-1_y_30,0.078102,0.0,test -2020-01-28 16:00:00,machine-1-1_y_30,0.079271,0.0,test -2020-01-28 17:00:00,machine-1-1_y_30,0.100653,0.0,test -2020-01-28 18:00:00,machine-1-1_y_30,0.123203,0.0,test -2020-01-28 19:00:00,machine-1-1_y_30,0.139672,0.0,test -2020-01-28 20:00:00,machine-1-1_y_30,0.120035,0.0,test -2020-01-28 21:00:00,machine-1-1_y_30,0.092043,0.0,test -2020-01-28 22:00:00,machine-1-1_y_30,0.077766,0.0,test 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16:00:00,machine-1-1_y_30,0.099165,0.0,test -2020-01-29 17:00:00,machine-1-1_y_30,0.100861,0.0,test -2020-01-29 18:00:00,machine-1-1_y_30,0.10395,0.0,test -2020-01-29 19:00:00,machine-1-1_y_30,0.099037,0.0,test -2020-01-29 20:00:00,machine-1-1_y_30,0.129269,0.0,test -2020-01-29 21:00:00,machine-1-1_y_30,0.130854,0.0,test -2020-01-29 22:00:00,machine-1-1_y_30,0.090026,0.0,test -2020-01-29 23:00:00,machine-1-1_y_30,0.064499,0.0,test -2020-01-30 00:00:00,machine-1-1_y_30,0.041276,0.0,test -2020-01-30 01:00:00,machine-1-1_y_30,0.028456,0.0,test -2020-01-30 02:00:00,machine-1-1_y_30,0.024855,0.0,test -2020-01-30 03:00:00,machine-1-1_y_30,0.022759,0.0,test -2020-01-30 04:00:00,machine-1-1_y_30,0.029208,0.0,test -2020-01-30 05:00:00,machine-1-1_y_30,0.093659,0.0,test -2020-01-30 06:00:00,machine-1-1_y_30,0.330511,0.0,test -2020-01-30 07:00:00,machine-1-1_y_30,0.434445,0.0,test -2020-01-30 08:00:00,machine-1-1_y_30,0.41668,0.0,test -2020-01-30 09:00:00,machine-1-1_y_30,0.453315,0.0,test 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03:00:00,machine-1-1_y_30,0.042668,0.0,test -2020-01-31 04:00:00,machine-1-1_y_30,0.111008,0.0,test -2020-01-31 05:00:00,machine-1-1_y_30,0.216974,0.0,test -2020-01-31 06:00:00,machine-1-1_y_30,0.268653,0.0,test -2020-01-31 07:00:00,machine-1-1_y_30,0.528632,0.0,test -2020-01-31 08:00:00,machine-1-1_y_30,0.527272,0.0,test -2020-01-31 09:00:00,machine-1-1_y_30,0.433261,0.0,test -2020-01-31 10:00:00,machine-1-1_y_30,0.153532,0.0,test -2020-01-31 11:00:00,machine-1-1_y_30,0.126901,0.0,test -2020-01-31 12:00:00,machine-1-1_y_30,0.229538,0.0,test -2020-01-31 13:00:00,machine-1-1_y_30,0.142873,0.0,test -2020-01-31 14:00:00,machine-1-1_y_30,0.100317,0.0,test -2020-01-31 15:00:00,machine-1-1_y_30,0.096652,0.0,test -2020-01-31 16:00:00,machine-1-1_y_30,0.113905,0.0,test -2020-01-31 17:00:00,machine-1-1_y_30,0.09169,0.0,test -2020-01-31 18:00:00,machine-1-1_y_30,0.061506,1.0,test -2020-01-31 19:00:00,machine-1-1_y_30,0.040428,1.0,test -2020-01-31 20:00:00,machine-1-1_y_30,0.031449,1.0,test 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14:00:00,machine-1-1_y_30,0.047486,1.0,test -2020-02-01 15:00:00,machine-1-1_y_30,0.034874,1.0,test -2020-02-01 16:00:00,machine-1-1_y_30,0.047102,1.0,test -2020-02-01 17:00:00,machine-1-1_y_30,0.162911,1.0,test -2020-02-01 18:00:00,machine-1-1_y_30,0.272446,1.0,test -2020-02-01 19:00:00,machine-1-1_y_30,0.545437,1.0,test -2020-02-01 20:00:00,machine-1-1_y_30,0.7083,1.0,test -2020-02-01 21:00:00,machine-1-1_y_30,1.0,1.0,test -2020-02-01 22:00:00,machine-1-1_y_30,0.983243,1.0,test -2020-02-01 23:00:00,machine-1-1_y_30,0.272783,0.0,test -2020-02-02 00:00:00,machine-1-1_y_30,0.153516,0.0,test -2020-02-02 01:00:00,machine-1-1_y_30,0.175987,0.0,test -2020-02-02 02:00:00,machine-1-1_y_30,0.191255,0.0,test -2020-02-02 03:00:00,machine-1-1_y_30,0.187078,0.0,test -2020-02-02 04:00:00,machine-1-1_y_30,0.208172,0.0,test -2020-02-02 05:00:00,machine-1-1_y_30,0.174258,0.0,test -2020-02-02 06:00:00,machine-1-1_y_30,0.128565,0.0,test -2020-02-02 07:00:00,machine-1-1_y_30,0.075798,1.0,test -2020-02-02 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22:00:00,machine-1-1_y_31,0.064848,0.0,train -2020-01-15 23:00:00,machine-1-1_y_31,0.049408,0.0,train -2020-01-16 00:00:00,machine-1-1_y_31,0.042717,0.0,train -2020-01-16 01:00:00,machine-1-1_y_31,0.034997,0.0,train -2020-01-16 02:00:00,machine-1-1_y_31,0.030365,0.0,train -2020-01-16 03:00:00,machine-1-1_y_31,0.027792,0.0,train -2020-01-16 04:00:00,machine-1-1_y_31,0.026763,0.0,train -2020-01-16 05:00:00,machine-1-1_y_31,0.025733,0.0,train -2020-01-16 06:00:00,machine-1-1_y_31,0.043747,0.0,train -2020-01-16 07:00:00,machine-1-1_y_31,0.079774,0.0,train -2020-01-16 08:00:00,machine-1-1_y_31,0.088523,0.0,train -2020-01-16 09:00:00,machine-1-1_y_31,0.083891,0.0,train -2020-01-16 10:00:00,machine-1-1_y_31,0.109624,0.0,train -2020-01-16 11:00:00,machine-1-1_y_31,0.082347,0.0,train -2020-01-16 12:00:00,machine-1-1_y_31,0.075656,0.0,train -2020-01-16 13:00:00,machine-1-1_y_31,0.059701,0.0,train -2020-01-16 14:00:00,machine-1-1_y_31,0.048893,0.0,train -2020-01-16 15:00:00,machine-1-1_y_31,0.067422,0.0,train -2020-01-16 16:00:00,machine-1-1_y_31,0.061245,0.0,train -2020-01-16 17:00:00,machine-1-1_y_31,0.052496,0.0,train -2020-01-16 18:00:00,machine-1-1_y_31,0.065878,0.0,train -2020-01-16 19:00:00,machine-1-1_y_31,0.067936,0.0,train -2020-01-16 20:00:00,machine-1-1_y_31,0.067936,0.0,train -2020-01-16 21:00:00,machine-1-1_y_31,0.06176,0.0,train -2020-01-16 22:00:00,machine-1-1_y_31,0.059187,0.0,train -2020-01-16 23:00:00,machine-1-1_y_31,0.050437,0.0,train -2020-01-17 00:00:00,machine-1-1_y_31,0.037056,0.0,train -2020-01-17 01:00:00,machine-1-1_y_31,0.03088,0.0,train -2020-01-17 02:00:00,machine-1-1_y_31,0.026763,0.0,train -2020-01-17 03:00:00,machine-1-1_y_31,0.025733,0.0,train -2020-01-17 04:00:00,machine-1-1_y_31,0.022131,0.0,train -2020-01-17 05:00:00,machine-1-1_y_31,0.02316,0.0,train -2020-01-17 06:00:00,machine-1-1_y_31,0.037571,0.0,train -2020-01-17 07:00:00,machine-1-1_y_31,0.096243,0.0,train -2020-01-17 08:00:00,machine-1-1_y_31,0.17756,0.0,train -2020-01-17 09:00:00,machine-1-1_y_31,0.156459,0.0,train -2020-01-17 10:00:00,machine-1-1_y_31,0.227998,0.0,train -2020-01-17 11:00:00,machine-1-1_y_31,0.136387,0.0,train -2020-01-17 12:00:00,machine-1-1_y_31,0.124035,0.0,train -2020-01-17 13:00:00,machine-1-1_y_31,0.199177,0.0,train -2020-01-17 14:00:00,machine-1-1_y_31,0.06176,0.0,train -2020-01-17 15:00:00,machine-1-1_y_31,0.081832,0.0,train -2020-01-17 16:00:00,machine-1-1_y_31,0.075656,0.0,train -2020-01-17 17:00:00,machine-1-1_y_31,0.057643,0.0,train -2020-01-17 18:00:00,machine-1-1_y_31,0.062275,0.0,train -2020-01-17 19:00:00,machine-1-1_y_31,0.149254,0.0,train -2020-01-17 20:00:00,machine-1-1_y_31,0.088523,0.0,train -2020-01-17 21:00:00,machine-1-1_y_31,0.120947,0.0,train -2020-01-17 22:00:00,machine-1-1_y_31,0.104992,0.0,train -2020-01-17 23:00:00,machine-1-1_y_31,0.059187,0.0,train -2020-01-18 00:00:00,machine-1-1_y_31,0.043747,0.0,train -2020-01-18 01:00:00,machine-1-1_y_31,0.037571,0.0,train -2020-01-18 02:00:00,machine-1-1_y_31,0.029851,0.0,train -2020-01-18 03:00:00,machine-1-1_y_31,0.027792,0.0,train -2020-01-18 04:00:00,machine-1-1_y_31,0.024704,0.0,train -2020-01-18 05:00:00,machine-1-1_y_31,0.026248,0.0,train -2020-01-18 06:00:00,machine-1-1_y_31,0.038085,0.0,train -2020-01-18 07:00:00,machine-1-1_y_31,0.07823,0.0,train -2020-01-18 08:00:00,machine-1-1_y_31,0.115286,0.0,train -2020-01-18 09:00:00,machine-1-1_y_31,0.106022,0.0,train -2020-01-18 10:00:00,machine-1-1_y_31,0.152342,0.0,train -2020-01-18 11:00:00,machine-1-1_y_31,0.113227,0.0,train -2020-01-18 12:00:00,machine-1-1_y_31,0.10036,0.0,train -2020-01-18 13:00:00,machine-1-1_y_31,0.151827,0.0,train -2020-01-18 14:00:00,machine-1-1_y_31,0.067936,0.0,train -2020-01-18 15:00:00,machine-1-1_y_31,0.055069,0.0,train -2020-01-18 16:00:00,machine-1-1_y_31,0.090067,0.0,train -2020-01-18 17:00:00,machine-1-1_y_31,0.060731,0.0,train -2020-01-18 18:00:00,machine-1-1_y_31,0.082347,0.0,train -2020-01-18 19:00:00,machine-1-1_y_31,0.063819,0.0,train -2020-01-18 20:00:00,machine-1-1_y_31,0.060731,0.0,train -2020-01-18 21:00:00,machine-1-1_y_31,0.10139,0.0,train -2020-01-18 22:00:00,machine-1-1_y_31,0.080288,0.0,train -2020-01-18 23:00:00,machine-1-1_y_31,0.058157,0.0,train -2020-01-19 00:00:00,machine-1-1_y_31,0.053525,0.0,train -2020-01-19 01:00:00,machine-1-1_y_31,0.043747,0.0,train -2020-01-19 02:00:00,machine-1-1_y_31,0.044776,0.0,train -2020-01-19 03:00:00,machine-1-1_y_31,0.027792,0.0,train -2020-01-19 04:00:00,machine-1-1_y_31,0.02316,0.0,train -2020-01-19 05:00:00,machine-1-1_y_31,0.028307,0.0,train -2020-01-19 06:00:00,machine-1-1_y_31,0.039115,0.0,train -2020-01-19 07:00:00,machine-1-1_y_31,0.078744,0.0,train -2020-01-19 08:00:00,machine-1-1_y_31,0.113742,0.0,train -2020-01-19 09:00:00,machine-1-1_y_31,0.172414,0.0,train -2020-01-19 10:00:00,machine-1-1_y_31,0.166238,0.0,train -2020-01-19 11:00:00,machine-1-1_y_31,0.099846,0.0,train -2020-01-19 12:00:00,machine-1-1_y_31,0.089038,0.0,train -2020-01-19 13:00:00,machine-1-1_y_31,0.106536,0.0,train -2020-01-19 14:00:00,machine-1-1_y_31,0.059187,0.0,train -2020-01-19 15:00:00,machine-1-1_y_31,0.076686,0.0,train -2020-01-19 16:00:00,machine-1-1_y_31,0.063304,0.0,train -2020-01-19 17:00:00,machine-1-1_y_31,0.057643,0.0,train -2020-01-19 18:00:00,machine-1-1_y_31,0.078744,0.0,train -2020-01-19 19:00:00,machine-1-1_y_31,0.088523,0.0,train -2020-01-19 20:00:00,machine-1-1_y_31,0.082347,0.0,train -2020-01-19 21:00:00,machine-1-1_y_31,0.078744,0.0,train -2020-01-19 22:00:00,machine-1-1_y_31,0.064334,0.0,train -2020-01-19 23:00:00,machine-1-1_y_31,0.067422,0.0,train -2020-01-20 00:00:00,machine-1-1_y_31,0.061245,0.0,train -2020-01-20 01:00:00,machine-1-1_y_31,0.051981,0.0,train -2020-01-20 02:00:00,machine-1-1_y_31,0.029851,0.0,train -2020-01-20 03:00:00,machine-1-1_y_31,0.030365,0.0,train -2020-01-20 04:00:00,machine-1-1_y_31,0.033453,0.0,train -2020-01-20 05:00:00,machine-1-1_y_31,0.032424,0.0,train -2020-01-20 06:00:00,machine-1-1_y_31,0.057643,0.0,train -2020-01-20 07:00:00,machine-1-1_y_31,0.106536,0.0,train -2020-01-20 08:00:00,machine-1-1_y_31,0.102419,0.0,train -2020-01-20 09:00:00,machine-1-1_y_31,0.115286,0.0,train -2020-01-20 10:00:00,machine-1-1_y_31,0.084406,0.0,train -2020-01-20 11:00:00,machine-1-1_y_31,0.13124,0.0,train -2020-01-20 12:00:00,machine-1-1_y_31,0.090067,0.0,train -2020-01-20 13:00:00,machine-1-1_y_31,0.065878,0.0,train -2020-01-20 14:00:00,machine-1-1_y_31,0.055069,0.0,train -2020-01-20 15:00:00,machine-1-1_y_31,0.075656,0.0,train -2020-01-20 16:00:00,machine-1-1_y_31,0.066392,0.0,train -2020-01-20 17:00:00,machine-1-1_y_31,0.066907,0.0,train -2020-01-20 18:00:00,machine-1-1_y_31,0.059187,0.0,train -2020-01-20 19:00:00,machine-1-1_y_31,0.130726,0.0,test -2020-01-20 20:00:00,machine-1-1_y_31,0.098302,0.0,test -2020-01-20 21:00:00,machine-1-1_y_31,0.111683,0.0,test -2020-01-20 22:00:00,machine-1-1_y_31,0.164694,0.0,test -2020-01-20 23:00:00,machine-1-1_y_31,0.06176,0.0,test -2020-01-21 00:00:00,machine-1-1_y_31,0.042717,0.0,test -2020-01-21 01:00:00,machine-1-1_y_31,0.031909,0.0,test -2020-01-21 02:00:00,machine-1-1_y_31,0.027277,0.0,test -2020-01-21 03:00:00,machine-1-1_y_31,0.026248,0.0,test -2020-01-21 04:00:00,machine-1-1_y_31,0.021616,0.0,test -2020-01-21 05:00:00,machine-1-1_y_31,0.025219,0.0,test -2020-01-21 06:00:00,machine-1-1_y_31,0.041688,0.0,test -2020-01-21 07:00:00,machine-1-1_y_31,0.07823,0.0,test -2020-01-21 08:00:00,machine-1-1_y_31,0.099331,0.0,test -2020-01-21 09:00:00,machine-1-1_y_31,0.083891,0.0,test -2020-01-21 10:00:00,machine-1-1_y_31,0.13896,0.0,test -2020-01-21 11:00:00,machine-1-1_y_31,0.133299,0.0,test -2020-01-21 12:00:00,machine-1-1_y_31,0.13999,0.0,test -2020-01-21 13:00:00,machine-1-1_y_31,0.103963,0.0,test -2020-01-21 14:00:00,machine-1-1_y_31,0.053011,0.0,test -2020-01-21 15:00:00,machine-1-1_y_31,0.051981,0.0,test -2020-01-21 16:00:00,machine-1-1_y_31,0.064848,0.0,test -2020-01-21 17:00:00,machine-1-1_y_31,0.060731,0.0,test -2020-01-21 18:00:00,machine-1-1_y_31,0.056613,0.0,test -2020-01-21 19:00:00,machine-1-1_y_31,0.057128,0.0,test -2020-01-21 20:00:00,machine-1-1_y_31,0.075142,0.0,test -2020-01-21 21:00:00,machine-1-1_y_31,0.05404,0.0,test -2020-01-21 22:00:00,machine-1-1_y_31,0.056099,0.0,test -2020-01-21 23:00:00,machine-1-1_y_31,0.047349,0.0,test -2020-01-22 00:00:00,machine-1-1_y_31,0.041688,0.0,test -2020-01-22 01:00:00,machine-1-1_y_31,0.029851,0.0,test -2020-01-22 02:00:00,machine-1-1_y_31,0.025733,0.0,test -2020-01-22 03:00:00,machine-1-1_y_31,0.023675,0.0,test -2020-01-22 04:00:00,machine-1-1_y_31,0.029336,0.0,test -2020-01-22 05:00:00,machine-1-1_y_31,0.080803,0.0,test -2020-01-22 06:00:00,machine-1-1_y_31,0.132784,0.0,test -2020-01-22 07:00:00,machine-1-1_y_31,0.162635,0.0,test -2020-01-22 08:00:00,machine-1-1_y_31,0.157488,0.0,test -2020-01-22 09:00:00,machine-1-1_y_31,0.105507,0.0,test -2020-01-22 10:00:00,machine-1-1_y_31,0.084406,0.0,test -2020-01-22 11:00:00,machine-1-1_y_31,0.082862,0.0,test -2020-01-22 12:00:00,machine-1-1_y_31,0.055069,0.0,test -2020-01-22 13:00:00,machine-1-1_y_31,0.083376,0.0,test -2020-01-22 14:00:00,machine-1-1_y_31,0.064334,0.0,test -2020-01-22 15:00:00,machine-1-1_y_31,0.063819,0.0,test -2020-01-22 16:00:00,machine-1-1_y_31,0.063819,0.0,test -2020-01-22 17:00:00,machine-1-1_y_31,0.097787,0.0,test -2020-01-22 18:00:00,machine-1-1_y_31,0.086979,0.0,test -2020-01-22 19:00:00,machine-1-1_y_31,0.071539,0.0,test -2020-01-22 20:00:00,machine-1-1_y_31,0.07823,0.0,test -2020-01-22 21:00:00,machine-1-1_y_31,0.074627,0.0,test -2020-01-22 22:00:00,machine-1-1_y_31,0.051467,0.0,test -2020-01-22 23:00:00,machine-1-1_y_31,0.042717,0.0,test -2020-01-23 00:00:00,machine-1-1_y_31,0.032939,0.0,test -2020-01-23 01:00:00,machine-1-1_y_31,0.025733,0.0,test -2020-01-23 02:00:00,machine-1-1_y_31,0.025219,0.0,test -2020-01-23 03:00:00,machine-1-1_y_31,0.025219,0.0,test -2020-01-23 04:00:00,machine-1-1_y_31,0.026248,0.0,test -2020-01-23 05:00:00,machine-1-1_y_31,0.071024,0.0,test -2020-01-23 06:00:00,machine-1-1_y_31,0.10036,0.0,test -2020-01-23 07:00:00,machine-1-1_y_31,0.114256,0.0,test -2020-01-23 08:00:00,machine-1-1_y_31,0.103448,0.0,test -2020-01-23 09:00:00,machine-1-1_y_31,0.312403,0.0,test -2020-01-23 10:00:00,machine-1-1_y_31,0.182192,0.0,test -2020-01-23 11:00:00,machine-1-1_y_31,0.311374,0.0,test -2020-01-23 12:00:00,machine-1-1_y_31,0.185795,0.0,test -2020-01-23 13:00:00,machine-1-1_y_31,0.090067,0.0,test -2020-01-23 14:00:00,machine-1-1_y_31,0.059701,0.0,test -2020-01-23 15:00:00,machine-1-1_y_31,0.081318,0.0,test -2020-01-23 16:00:00,machine-1-1_y_31,0.07051,0.0,test -2020-01-23 17:00:00,machine-1-1_y_31,0.092126,0.0,test -2020-01-23 18:00:00,machine-1-1_y_31,0.076171,0.0,test -2020-01-23 19:00:00,machine-1-1_y_31,0.097787,0.0,test -2020-01-23 20:00:00,machine-1-1_y_31,0.095214,0.0,test -2020-01-23 21:00:00,machine-1-1_y_31,0.081318,0.0,test -2020-01-23 22:00:00,machine-1-1_y_31,0.053525,0.0,test -2020-01-23 23:00:00,machine-1-1_y_31,0.042203,0.0,test -2020-01-24 00:00:00,machine-1-1_y_31,0.032939,0.0,test -2020-01-24 01:00:00,machine-1-1_y_31,0.026763,0.0,test -2020-01-24 02:00:00,machine-1-1_y_31,0.025733,0.0,test -2020-01-24 03:00:00,machine-1-1_y_31,0.028307,0.0,test -2020-01-24 04:00:00,machine-1-1_y_31,0.032424,0.0,test -2020-01-24 05:00:00,machine-1-1_y_31,0.073598,0.0,test -2020-01-24 06:00:00,machine-1-1_y_31,0.08595,0.0,test -2020-01-24 07:00:00,machine-1-1_y_31,0.088523,0.0,test -2020-01-24 08:00:00,machine-1-1_y_31,0.080803,0.0,test -2020-01-24 09:00:00,machine-1-1_y_31,0.10036,0.0,test -2020-01-24 10:00:00,machine-1-1_y_31,0.095728,0.0,test -2020-01-24 11:00:00,machine-1-1_y_31,0.084406,0.0,test -2020-01-24 12:00:00,machine-1-1_y_31,0.056099,0.0,test -2020-01-24 13:00:00,machine-1-1_y_31,0.06279,0.0,test -2020-01-24 14:00:00,machine-1-1_y_31,0.049923,0.0,test -2020-01-24 15:00:00,machine-1-1_y_31,0.069995,0.0,test -2020-01-24 16:00:00,machine-1-1_y_31,0.066392,0.0,test -2020-01-24 17:00:00,machine-1-1_y_31,0.086979,0.0,test -2020-01-24 18:00:00,machine-1-1_y_31,0.063819,0.0,test -2020-01-24 19:00:00,machine-1-1_y_31,0.082862,0.0,test -2020-01-24 20:00:00,machine-1-1_y_31,0.055069,0.0,test -2020-01-24 21:00:00,machine-1-1_y_31,0.077715,0.0,test -2020-01-24 22:00:00,machine-1-1_y_31,0.048893,0.0,test -2020-01-24 23:00:00,machine-1-1_y_31,0.039629,0.0,test -2020-01-25 00:00:00,machine-1-1_y_31,0.032424,0.0,test -2020-01-25 01:00:00,machine-1-1_y_31,0.027277,0.0,test -2020-01-25 02:00:00,machine-1-1_y_31,0.026763,0.0,test -2020-01-25 03:00:00,machine-1-1_y_31,0.025219,0.0,test -2020-01-25 04:00:00,machine-1-1_y_31,0.035512,0.0,test -2020-01-25 05:00:00,machine-1-1_y_31,0.068966,0.0,test -2020-01-25 06:00:00,machine-1-1_y_31,0.14668,0.0,test -2020-01-25 07:00:00,machine-1-1_y_31,0.134843,0.0,test -2020-01-25 08:00:00,machine-1-1_y_31,0.152342,0.0,test -2020-01-25 09:00:00,machine-1-1_y_31,0.27895,0.0,test -2020-01-25 10:00:00,machine-1-1_y_31,0.151312,0.0,test -2020-01-25 11:00:00,machine-1-1_y_31,0.224395,0.0,test -2020-01-25 12:00:00,machine-1-1_y_31,0.141019,0.0,test -2020-01-25 13:00:00,machine-1-1_y_31,0.089038,0.0,test -2020-01-25 14:00:00,machine-1-1_y_31,0.059187,0.0,test -2020-01-25 15:00:00,machine-1-1_y_31,0.080803,0.0,test -2020-01-25 16:00:00,machine-1-1_y_31,0.08492,0.0,test -2020-01-25 17:00:00,machine-1-1_y_31,0.103963,0.0,test -2020-01-25 18:00:00,machine-1-1_y_31,0.075656,0.0,test -2020-01-25 19:00:00,machine-1-1_y_31,0.095214,0.0,test -2020-01-25 20:00:00,machine-1-1_y_31,0.094699,0.0,test -2020-01-25 21:00:00,machine-1-1_y_31,0.073083,0.0,test -2020-01-25 22:00:00,machine-1-1_y_31,0.056099,0.0,test -2020-01-25 23:00:00,machine-1-1_y_31,0.044776,0.0,test -2020-01-26 00:00:00,machine-1-1_y_31,0.034997,0.0,test -2020-01-26 01:00:00,machine-1-1_y_31,0.028821,0.0,test -2020-01-26 02:00:00,machine-1-1_y_31,0.028307,0.0,test -2020-01-26 03:00:00,machine-1-1_y_31,0.027277,0.0,test -2020-01-26 04:00:00,machine-1-1_y_31,0.026763,0.0,test -2020-01-26 05:00:00,machine-1-1_y_31,0.051467,0.0,test -2020-01-26 06:00:00,machine-1-1_y_31,0.067422,0.0,test -2020-01-26 07:00:00,machine-1-1_y_31,0.107566,0.0,test -2020-01-26 08:00:00,machine-1-1_y_31,0.07051,0.0,test -2020-01-26 09:00:00,machine-1-1_y_31,0.08492,0.0,test -2020-01-26 10:00:00,machine-1-1_y_31,0.075656,0.0,test -2020-01-26 11:00:00,machine-1-1_y_31,0.060216,0.0,test -2020-01-26 12:00:00,machine-1-1_y_31,0.053525,0.0,test -2020-01-26 13:00:00,machine-1-1_y_31,0.066907,0.0,test -2020-01-26 14:00:00,machine-1-1_y_31,0.073598,0.0,test -2020-01-26 15:00:00,machine-1-1_y_31,0.088008,0.0,test -2020-01-26 16:00:00,machine-1-1_y_31,0.09367,0.0,test -2020-01-26 17:00:00,machine-1-1_y_31,0.068966,0.0,test -2020-01-26 18:00:00,machine-1-1_y_31,0.076171,0.0,test -2020-01-26 19:00:00,machine-1-1_y_31,0.071539,0.0,test -2020-01-26 20:00:00,machine-1-1_y_31,0.08595,0.0,test -2020-01-26 21:00:00,machine-1-1_y_31,0.104478,0.0,test -2020-01-26 22:00:00,machine-1-1_y_31,0.05404,0.0,test -2020-01-26 23:00:00,machine-1-1_y_31,0.042717,0.0,test -2020-01-27 00:00:00,machine-1-1_y_31,0.033453,0.0,test -2020-01-27 01:00:00,machine-1-1_y_31,0.029336,0.0,test -2020-01-27 02:00:00,machine-1-1_y_31,0.026763,0.0,test -2020-01-27 03:00:00,machine-1-1_y_31,0.026248,0.0,test -2020-01-27 04:00:00,machine-1-1_y_31,0.027277,0.0,test -2020-01-27 05:00:00,machine-1-1_y_31,0.055069,0.0,test -2020-01-27 06:00:00,machine-1-1_y_31,0.055584,0.0,test -2020-01-27 07:00:00,machine-1-1_y_31,0.064334,0.0,test -2020-01-27 08:00:00,machine-1-1_y_31,0.059187,0.0,test -2020-01-27 09:00:00,machine-1-1_y_31,0.059701,0.0,test -2020-01-27 10:00:00,machine-1-1_y_31,0.060216,0.0,test -2020-01-27 11:00:00,machine-1-1_y_31,0.081318,0.0,test -2020-01-27 12:00:00,machine-1-1_y_31,0.046835,0.0,test -2020-01-27 13:00:00,machine-1-1_y_31,0.048379,0.0,test -2020-01-27 14:00:00,machine-1-1_y_31,0.06176,0.0,test -2020-01-27 15:00:00,machine-1-1_y_31,0.050437,0.0,test -2020-01-27 16:00:00,machine-1-1_y_31,0.066907,0.0,test -2020-01-27 17:00:00,machine-1-1_y_31,0.058157,0.0,test -2020-01-27 18:00:00,machine-1-1_y_31,0.052496,0.0,test -2020-01-27 19:00:00,machine-1-1_y_31,0.059701,0.0,test -2020-01-27 20:00:00,machine-1-1_y_31,0.068966,0.0,test -2020-01-27 21:00:00,machine-1-1_y_31,0.059701,0.0,test -2020-01-27 22:00:00,machine-1-1_y_31,0.047349,0.0,test -2020-01-27 23:00:00,machine-1-1_y_31,0.036541,0.0,test -2020-01-28 00:00:00,machine-1-1_y_31,0.028307,0.0,test -2020-01-28 01:00:00,machine-1-1_y_31,0.030365,0.0,test -2020-01-28 02:00:00,machine-1-1_y_31,0.027792,0.0,test -2020-01-28 03:00:00,machine-1-1_y_31,0.026248,0.0,test -2020-01-28 04:00:00,machine-1-1_y_31,0.028821,0.0,test -2020-01-28 05:00:00,machine-1-1_y_31,0.042717,0.0,test -2020-01-28 06:00:00,machine-1-1_y_31,0.069995,0.0,test -2020-01-28 07:00:00,machine-1-1_y_31,0.068966,0.0,test -2020-01-28 08:00:00,machine-1-1_y_31,0.056613,0.0,test -2020-01-28 09:00:00,machine-1-1_y_31,0.071539,0.0,test -2020-01-28 10:00:00,machine-1-1_y_31,0.059187,0.0,test -2020-01-28 11:00:00,machine-1-1_y_31,0.056613,0.0,test -2020-01-28 12:00:00,machine-1-1_y_31,0.071024,0.0,test -2020-01-28 13:00:00,machine-1-1_y_31,0.051981,0.0,test -2020-01-28 14:00:00,machine-1-1_y_31,0.048379,0.0,test -2020-01-28 15:00:00,machine-1-1_y_31,0.068966,0.0,test -2020-01-28 16:00:00,machine-1-1_y_31,0.064848,0.0,test -2020-01-28 17:00:00,machine-1-1_y_31,0.091096,0.0,test -2020-01-28 18:00:00,machine-1-1_y_31,0.097272,0.0,test -2020-01-28 19:00:00,machine-1-1_y_31,0.101904,0.0,test -2020-01-28 20:00:00,machine-1-1_y_31,0.089038,0.0,test -2020-01-28 21:00:00,machine-1-1_y_31,0.060731,0.0,test -2020-01-28 22:00:00,machine-1-1_y_31,0.055584,0.0,test -2020-01-28 23:00:00,machine-1-1_y_31,0.044776,0.0,test -2020-01-29 00:00:00,machine-1-1_y_31,0.036541,0.0,test -2020-01-29 01:00:00,machine-1-1_y_31,0.035512,0.0,test -2020-01-29 02:00:00,machine-1-1_y_31,0.031909,0.0,test -2020-01-29 03:00:00,machine-1-1_y_31,0.032939,0.0,test -2020-01-29 04:00:00,machine-1-1_y_31,0.036541,0.0,test -2020-01-29 05:00:00,machine-1-1_y_31,0.07823,0.0,test -2020-01-29 06:00:00,machine-1-1_y_31,0.243438,0.0,test -2020-01-29 07:00:00,machine-1-1_y_31,0.217705,0.0,test -2020-01-29 08:00:00,machine-1-1_y_31,0.190427,0.0,test -2020-01-29 09:00:00,machine-1-1_y_31,0.310345,0.0,test -2020-01-29 10:00:00,machine-1-1_y_31,0.227483,0.0,test -2020-01-29 11:00:00,machine-1-1_y_31,0.230571,0.0,test -2020-01-29 12:00:00,machine-1-1_y_31,0.223366,0.0,test -2020-01-29 13:00:00,machine-1-1_y_31,0.099846,0.0,test -2020-01-29 14:00:00,machine-1-1_y_31,0.061245,0.0,test -2020-01-29 15:00:00,machine-1-1_y_31,0.097272,0.0,test -2020-01-29 16:00:00,machine-1-1_y_31,0.075142,0.0,test -2020-01-29 17:00:00,machine-1-1_y_31,0.075656,0.0,test -2020-01-29 18:00:00,machine-1-1_y_31,0.079259,0.0,test -2020-01-29 19:00:00,machine-1-1_y_31,0.077715,0.0,test -2020-01-29 20:00:00,machine-1-1_y_31,0.110654,0.0,test -2020-01-29 21:00:00,machine-1-1_y_31,0.097787,0.0,test -2020-01-29 22:00:00,machine-1-1_y_31,0.06176,0.0,test -2020-01-29 23:00:00,machine-1-1_y_31,0.046835,0.0,test -2020-01-30 00:00:00,machine-1-1_y_31,0.035512,0.0,test -2020-01-30 01:00:00,machine-1-1_y_31,0.032424,0.0,test -2020-01-30 02:00:00,machine-1-1_y_31,0.030365,0.0,test -2020-01-30 03:00:00,machine-1-1_y_31,0.029851,0.0,test -2020-01-30 04:00:00,machine-1-1_y_31,0.033453,0.0,test -2020-01-30 05:00:00,machine-1-1_y_31,0.104478,0.0,test -2020-01-30 06:00:00,machine-1-1_y_31,0.304683,0.0,test -2020-01-30 07:00:00,machine-1-1_y_31,0.370046,0.0,test -2020-01-30 08:00:00,machine-1-1_y_31,0.376737,0.0,test -2020-01-30 09:00:00,machine-1-1_y_31,0.435409,0.0,test -2020-01-30 10:00:00,machine-1-1_y_31,0.213073,0.0,test -2020-01-30 11:00:00,machine-1-1_y_31,0.225425,0.0,test -2020-01-30 12:00:00,machine-1-1_y_31,0.126094,0.0,test -2020-01-30 13:00:00,machine-1-1_y_31,0.09264,0.0,test -2020-01-30 14:00:00,machine-1-1_y_31,0.073083,0.0,test -2020-01-30 15:00:00,machine-1-1_y_31,0.100875,0.0,test -2020-01-30 16:00:00,machine-1-1_y_31,0.07823,0.0,test -2020-01-30 17:00:00,machine-1-1_y_31,0.108595,0.0,test -2020-01-30 18:00:00,machine-1-1_y_31,0.08492,0.0,test -2020-01-30 19:00:00,machine-1-1_y_31,0.079259,0.0,test -2020-01-30 20:00:00,machine-1-1_y_31,0.111168,0.0,test -2020-01-30 21:00:00,machine-1-1_y_31,0.081318,0.0,test -2020-01-30 22:00:00,machine-1-1_y_31,0.072568,0.0,test -2020-01-30 23:00:00,machine-1-1_y_31,0.053011,0.0,test -2020-01-31 00:00:00,machine-1-1_y_31,0.036541,0.0,test -2020-01-31 01:00:00,machine-1-1_y_31,0.032939,0.0,test -2020-01-31 02:00:00,machine-1-1_y_31,0.033968,0.0,test -2020-01-31 03:00:00,machine-1-1_y_31,0.04632,0.0,test -2020-01-31 04:00:00,machine-1-1_y_31,0.103963,0.0,test -2020-01-31 05:00:00,machine-1-1_y_31,0.16984,0.0,test -2020-01-31 06:00:00,machine-1-1_y_31,0.219763,0.0,test -2020-01-31 07:00:00,machine-1-1_y_31,0.543489,0.0,test -2020-01-31 08:00:00,machine-1-1_y_31,0.445703,0.0,test -2020-01-31 09:00:00,machine-1-1_y_31,0.324756,0.0,test -2020-01-31 10:00:00,machine-1-1_y_31,0.133814,0.0,test -2020-01-31 11:00:00,machine-1-1_y_31,0.093155,0.0,test -2020-01-31 12:00:00,machine-1-1_y_31,0.181678,0.0,test -2020-01-31 13:00:00,machine-1-1_y_31,0.113742,0.0,test -2020-01-31 14:00:00,machine-1-1_y_31,0.075142,0.0,test -2020-01-31 15:00:00,machine-1-1_y_31,0.074112,0.0,test -2020-01-31 16:00:00,machine-1-1_y_31,0.095728,0.0,test -2020-01-31 17:00:00,machine-1-1_y_31,0.063819,0.0,test -2020-01-31 18:00:00,machine-1-1_y_31,0.045805,1.0,test -2020-01-31 19:00:00,machine-1-1_y_31,0.037056,1.0,test 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20:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-13 21:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-13 22:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-13 23:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 00:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 01:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 02:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 03:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 04:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 05:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 06:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 07:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 08:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 09:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-14 10:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-14 11:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-14 12:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-14 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06:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 07:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 08:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-15 09:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-15 10:00:00,machine-1-1_y_32,0.001159,0.0,train -2020-01-15 11:00:00,machine-1-1_y_32,0.001159,0.0,train -2020-01-15 12:00:00,machine-1-1_y_32,0.001159,0.0,train -2020-01-15 13:00:00,machine-1-1_y_32,0.001159,0.0,train -2020-01-15 14:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-15 15:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-15 16:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 17:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 18:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 19:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 20:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 21:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 22:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-15 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12:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-19 13:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 14:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 15:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 16:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 17:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 18:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 19:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 20:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 21:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 22:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-19 23:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 00:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 01:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 02:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 03:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 04:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 05:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 06:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-20 07:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 08:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-20 09:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 10:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 11:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 12:00:00,machine-1-1_y_32,0.000773,0.0,train -2020-01-20 13:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 14:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 15:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 16:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 17:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 18:00:00,machine-1-1_y_32,0.000386,0.0,train -2020-01-20 19:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-20 20:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-20 21:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-20 22:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-20 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 00:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 01:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 02:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 03:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-21 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 05:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-21 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 07:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 08:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 09:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 10:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-21 11:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 12:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-21 13:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-21 14:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 15:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 16:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 17:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 18:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 19:00:00,machine-1-1_y_32,0.001159,0.0,test -2020-01-21 20:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-21 21:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 22:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-21 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 00:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 01:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 02:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 03:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-22 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 05:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 07:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-22 08:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-22 09:00:00,machine-1-1_y_32,0.000773,0.0,test 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21:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-23 22:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-23 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 00:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 01:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-24 02:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 03:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 05:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 07:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 08:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-24 09:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 10:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 11:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 12:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 13:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-24 14:00:00,machine-1-1_y_32,0.000386,0.0,test 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01:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-29 02:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-29 03:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-29 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 05:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 07:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-29 08:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 09:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-29 10:00:00,machine-1-1_y_32,0.001159,0.0,test -2020-01-29 11:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-29 12:00:00,machine-1-1_y_32,0.001159,0.0,test -2020-01-29 13:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 14:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 15:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 16:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 17:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 18:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 19:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 20:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 21:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 22:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-29 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 00:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 01:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 02:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-30 03:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-30 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 05:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 07:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 08:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 09:00:00,machine-1-1_y_32,0.014683,0.0,test -2020-01-30 10:00:00,machine-1-1_y_32,0.001159,0.0,test -2020-01-30 11:00:00,machine-1-1_y_32,0.001932,0.0,test -2020-01-30 12:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 13:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 14:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 15:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 16:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-30 17:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 18:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 19:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 20:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 21:00:00,machine-1-1_y_32,0.001546,0.0,test -2020-01-30 22:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-30 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-31 00:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-31 01:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-31 02:00:00,machine-1-1_y_32,0.0,0.0,test -2020-01-31 03:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-31 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-01-31 05:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-31 06:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-01-31 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18:00:00,machine-1-1_y_32,0.000386,1.0,test -2020-02-01 19:00:00,machine-1-1_y_32,0.000773,1.0,test -2020-02-01 20:00:00,machine-1-1_y_32,0.010819,1.0,test -2020-02-01 21:00:00,machine-1-1_y_32,0.766229,1.0,test -2020-02-01 22:00:00,machine-1-1_y_32,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-02-02 00:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-02-02 01:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-02-02 02:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-02-02 03:00:00,machine-1-1_y_32,0.000773,0.0,test -2020-02-02 04:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-02-02 05:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-02-02 06:00:00,machine-1-1_y_32,0.000386,0.0,test -2020-02-02 07:00:00,machine-1-1_y_32,0.000386,1.0,test -2020-02-02 08:00:00,machine-1-1_y_32,0.000386,1.0,test -2020-02-02 09:00:00,machine-1-1_y_32,0.000386,1.0,test -2020-02-02 10:00:00,machine-1-1_y_32,0.0,1.0,test -2020-02-02 11:00:00,machine-1-1_y_32,0.000386,1.0,test -2020-02-02 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23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 00:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-21 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 03:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-21 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 07:00:00,machine-1-1_y_33,0.000112,0.0,test -2020-01-21 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-21 09:00:00,machine-1-1_y_33,0.000146,0.0,test -2020-01-21 10:00:00,machine-1-1_y_33,0.000427,0.0,test -2020-01-21 11:00:00,machine-1-1_y_33,0.000157,0.0,test -2020-01-21 12:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 13:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-21 14:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-21 15:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-21 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 17:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 19:00:00,machine-1-1_y_33,0.000731,0.0,test -2020-01-21 20:00:00,machine-1-1_y_33,0.000517,0.0,test -2020-01-21 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-21 22:00:00,machine-1-1_y_33,0.000169,0.0,test -2020-01-21 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 00:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 07:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 09:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 10:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 11:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 12:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 13:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 14:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 17:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-22 21:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-22 22:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-22 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 01:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-23 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 03:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 05:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 07:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-23 08:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-23 09:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 10:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 11:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 12:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-01-23 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 14:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 17:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 19:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 20:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-23 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-23 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-24 07:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-01-24 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-24 09:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 10:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 11:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 12:00:00,machine-1-1_y_33,0.000124,0.0,test -2020-01-24 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 17:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-24 18:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-24 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 20:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-24 21:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-24 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-24 23:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-25 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-25 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-25 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-25 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-25 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-25 05:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-25 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-25 07:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-25 08:00:00,machine-1-1_y_33,0.000112,0.0,test -2020-01-25 09:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-01-25 10:00:00,machine-1-1_y_33,0.00018,0.0,test -2020-01-25 11:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-01-25 12:00:00,machine-1-1_y_33,0.000259,0.0,test -2020-01-25 13:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-01-25 14:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 15:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-25 16:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 17:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 18:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-01-25 19:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 20:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-01-25 21:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 22:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-25 23:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 01:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-26 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 07:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 09:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 10:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 11:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-01-26 12:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-26 16:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-26 18:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-01-26 19:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 20:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-26 21:00:00,machine-1-1_y_33,0.000124,0.0,test -2020-01-26 22:00:00,machine-1-1_y_33,0.000112,0.0,test -2020-01-26 23:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-27 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 05:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 07:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 08:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-01-27 09:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-27 10:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-01-27 11:00:00,machine-1-1_y_33,0.000933,0.0,test -2020-01-27 12:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-27 13:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-01-27 14:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-27 22:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-27 23:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-28 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 05:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-28 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 07:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-28 08:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 09:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 10:00:00,machine-1-1_y_33,0.000146,0.0,test -2020-01-28 11:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 12:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-28 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 15:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-28 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-28 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 19:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-28 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-28 23:00:00,machine-1-1_y_33,0.000495,0.0,test -2020-01-29 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 01:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-29 02:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-29 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 05:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-29 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 07:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 08:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 09:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 10:00:00,machine-1-1_y_33,0.00063,0.0,test -2020-01-29 11:00:00,machine-1-1_y_33,0.000191,0.0,test -2020-01-29 12:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-01-29 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 14:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-29 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 16:00:00,machine-1-1_y_33,0.00018,0.0,test -2020-01-29 17:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 18:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-29 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-29 23:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-30 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 01:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-30 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-30 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 07:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-30 08:00:00,machine-1-1_y_33,0.000281,0.0,test -2020-01-30 09:00:00,machine-1-1_y_33,0.016382,0.0,test -2020-01-30 10:00:00,machine-1-1_y_33,0.000416,0.0,test -2020-01-30 11:00:00,machine-1-1_y_33,0.000663,0.0,test -2020-01-30 12:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-30 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 19:00:00,machine-1-1_y_33,0.000326,0.0,test -2020-01-30 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 21:00:00,machine-1-1_y_33,0.000899,0.0,test -2020-01-30 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-30 23:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-31 00:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-31 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-01-31 05:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-31 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 07:00:00,machine-1-1_y_33,0.000382,0.0,test -2020-01-31 08:00:00,machine-1-1_y_33,0.000326,0.0,test -2020-01-31 09:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 10:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-31 11:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 12:00:00,machine-1-1_y_33,0.000438,0.0,test -2020-01-31 13:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 15:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-01-31 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-01-31 17:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-01-31 18:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-01-31 19:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-01-31 20:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-01-31 21:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-01-31 22:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-01-31 23:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-01 00:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-01 01:00:00,machine-1-1_y_33,0.000753,1.0,test -2020-02-01 02:00:00,machine-1-1_y_33,0.00018,1.0,test -2020-02-01 03:00:00,machine-1-1_y_33,0.000472,1.0,test -2020-02-01 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-01 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-01 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-01 07:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-01 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-01 09:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-02-01 10:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-01 11:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-01 12:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-01 13:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-01 14:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-01 15:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-01 16:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-01 17:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-01 18:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-01 19:00:00,machine-1-1_y_33,0.000416,1.0,test -2020-02-01 20:00:00,machine-1-1_y_33,0.018541,1.0,test -2020-02-01 21:00:00,machine-1-1_y_33,0.779031,1.0,test -2020-02-01 22:00:00,machine-1-1_y_33,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 00:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 01:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 03:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 06:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 07:00:00,machine-1-1_y_33,9e-05,1.0,test -2020-02-02 08:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-02 09:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-02 10:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-02 11:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-02 12:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-02 13:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-02 14:00:00,machine-1-1_y_33,0.029379,1.0,test -2020-02-02 15:00:00,machine-1-1_y_33,0.00054,1.0,test -2020-02-02 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 17:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 18:00:00,machine-1-1_y_33,0.000124,0.0,test -2020-02-02 19:00:00,machine-1-1_y_33,0.000146,0.0,test -2020-02-02 20:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 21:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-02 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-02 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-03 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-03 01:00:00,machine-1-1_y_33,0.000259,0.0,test -2020-02-03 02:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-02-03 03:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-03 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-03 05:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 06:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 07:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 08:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 09:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 10:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 11:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 12:00:00,machine-1-1_y_33,7.9e-05,1.0,test -2020-02-03 13:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-03 14:00:00,machine-1-1_y_33,0.001765,1.0,test -2020-02-03 15:00:00,machine-1-1_y_33,0.000618,1.0,test -2020-02-03 16:00:00,machine-1-1_y_33,0.010929,1.0,test -2020-02-03 17:00:00,machine-1-1_y_33,0.001754,1.0,test -2020-02-03 18:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-03 19:00:00,machine-1-1_y_33,0.000101,0.0,test -2020-02-03 20:00:00,machine-1-1_y_33,0.000596,0.0,test -2020-02-03 21:00:00,machine-1-1_y_33,0.000697,0.0,test -2020-02-03 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-03 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 03:00:00,machine-1-1_y_33,4.5e-05,0.0,test -2020-02-04 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-04 05:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-04 06:00:00,machine-1-1_y_33,4.5e-05,1.0,test -2020-02-04 07:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-04 08:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-04 09:00:00,machine-1-1_y_33,0.000169,1.0,test -2020-02-04 10:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-04 11:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-04 12:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 13:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-04 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 15:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-02-04 16:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-04 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-04 18:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-04 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 20:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-02-04 21:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-04 22:00:00,machine-1-1_y_33,0.000911,0.0,test -2020-02-04 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 03:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 04:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 05:00:00,machine-1-1_y_33,0.000169,0.0,test -2020-02-05 06:00:00,machine-1-1_y_33,0.000438,0.0,test -2020-02-05 07:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-02-05 08:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 09:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 10:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 11:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 12:00:00,machine-1-1_y_33,0.000124,0.0,test -2020-02-05 13:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 15:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-05 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 18:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 19:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 20:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-05 21:00:00,machine-1-1_y_33,0.000405,0.0,test -2020-02-05 22:00:00,machine-1-1_y_33,0.000292,0.0,test -2020-02-05 23:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-06 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 01:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 02:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 04:00:00,machine-1-1_y_33,0.000461,0.0,test -2020-02-06 05:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-06 06:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-06 07:00:00,machine-1-1_y_33,0.001203,0.0,test -2020-02-06 08:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 09:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 10:00:00,machine-1-1_y_33,0.000135,0.0,test -2020-02-06 11:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 12:00:00,machine-1-1_y_33,0.000169,0.0,test -2020-02-06 13:00:00,machine-1-1_y_33,0.000124,0.0,test -2020-02-06 14:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 15:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 16:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 17:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-06 18:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-06 19:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-06 21:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-06 22:00:00,machine-1-1_y_33,5.6e-05,1.0,test -2020-02-06 23:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 00:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 01:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 02:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-02-07 03:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 04:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 05:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 06:00:00,machine-1-1_y_33,0.003339,0.0,test -2020-02-07 07:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-02-07 08:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 09:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 10:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 11:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 12:00:00,machine-1-1_y_33,0.000416,0.0,test -2020-02-07 13:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 14:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 15:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 16:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 17:00:00,machine-1-1_y_33,9e-05,0.0,test -2020-02-07 18:00:00,machine-1-1_y_33,6.7e-05,0.0,test -2020-02-07 19:00:00,machine-1-1_y_33,7.9e-05,0.0,test -2020-02-07 20:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 21:00:00,machine-1-1_y_33,6.7e-05,1.0,test -2020-02-07 22:00:00,machine-1-1_y_33,5.6e-05,0.0,test -2020-02-07 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11:00:00,machine-1-1_y_34,0.107218,0.0,train -2020-01-16 12:00:00,machine-1-1_y_34,0.09672,0.0,train -2020-01-16 13:00:00,machine-1-1_y_34,0.07768,0.0,train -2020-01-16 14:00:00,machine-1-1_y_34,0.060161,0.0,train -2020-01-16 15:00:00,machine-1-1_y_34,0.068848,0.0,train -2020-01-16 16:00:00,machine-1-1_y_34,0.070151,0.0,train -2020-01-16 17:00:00,machine-1-1_y_34,0.065301,0.0,train -2020-01-16 18:00:00,machine-1-1_y_34,0.083617,0.0,train -2020-01-16 19:00:00,machine-1-1_y_34,0.097517,0.0,train -2020-01-16 20:00:00,machine-1-1_y_34,0.100992,0.0,train -2020-01-16 21:00:00,machine-1-1_y_34,0.087671,0.0,train -2020-01-16 22:00:00,machine-1-1_y_34,0.087526,0.0,train -2020-01-16 23:00:00,machine-1-1_y_34,0.083544,0.0,train -2020-01-17 00:00:00,machine-1-1_y_34,0.061898,0.0,train -2020-01-17 01:00:00,machine-1-1_y_34,0.046333,0.0,train -2020-01-17 02:00:00,machine-1-1_y_34,0.036415,0.0,train -2020-01-17 03:00:00,machine-1-1_y_34,0.030189,0.0,train -2020-01-17 04:00:00,machine-1-1_y_34,0.024614,0.0,train -2020-01-17 05:00:00,machine-1-1_y_34,0.023891,0.0,train -2020-01-17 06:00:00,machine-1-1_y_34,0.034171,0.0,train -2020-01-17 07:00:00,machine-1-1_y_34,0.083906,0.0,train -2020-01-17 08:00:00,machine-1-1_y_34,0.191776,0.0,train -2020-01-17 09:00:00,machine-1-1_y_34,0.20097,0.0,train -2020-01-17 10:00:00,machine-1-1_y_34,0.233114,0.0,train -2020-01-17 11:00:00,machine-1-1_y_34,0.186563,0.0,train -2020-01-17 12:00:00,machine-1-1_y_34,0.168247,0.0,train -2020-01-17 13:00:00,machine-1-1_y_34,0.177804,0.0,train -2020-01-17 14:00:00,machine-1-1_y_34,0.093318,0.0,train -2020-01-17 15:00:00,machine-1-1_y_34,0.092377,0.0,train -2020-01-17 16:00:00,machine-1-1_y_34,0.09006,0.0,train -2020-01-17 17:00:00,machine-1-1_y_34,0.077318,0.0,train -2020-01-17 18:00:00,machine-1-1_y_34,0.076595,0.0,train -2020-01-17 19:00:00,machine-1-1_y_34,0.1626,0.0,train -2020-01-17 20:00:00,machine-1-1_y_34,0.172591,0.0,train -2020-01-17 21:00:00,machine-1-1_y_34,0.176428,0.0,train -2020-01-17 22:00:00,machine-1-1_y_34,0.167017,0.0,train -2020-01-17 23:00:00,machine-1-1_y_34,0.097372,0.0,train -2020-01-18 00:00:00,machine-1-1_y_34,0.071816,0.0,train -2020-01-18 01:00:00,machine-1-1_y_34,0.052994,0.0,train -2020-01-18 02:00:00,machine-1-1_y_34,0.039456,0.0,train -2020-01-18 03:00:00,machine-1-1_y_34,0.033447,0.0,train -2020-01-18 04:00:00,machine-1-1_y_34,0.028017,0.0,train -2020-01-18 05:00:00,machine-1-1_y_34,0.025845,0.0,train -2020-01-18 06:00:00,machine-1-1_y_34,0.036849,0.0,train -2020-01-18 07:00:00,machine-1-1_y_34,0.070513,0.0,train -2020-01-18 08:00:00,machine-1-1_y_34,0.110258,0.0,train -2020-01-18 09:00:00,machine-1-1_y_34,0.108666,0.0,train -2020-01-18 10:00:00,machine-1-1_y_34,0.158546,0.0,train -2020-01-18 11:00:00,machine-1-1_y_34,0.139361,0.0,train -2020-01-18 12:00:00,machine-1-1_y_34,0.122276,0.0,train -2020-01-18 13:00:00,machine-1-1_y_34,0.14537,0.0,train -2020-01-18 14:00:00,machine-1-1_y_34,0.085934,0.0,train -2020-01-18 15:00:00,machine-1-1_y_34,0.076884,0.0,train -2020-01-18 16:00:00,machine-1-1_y_34,0.093969,0.0,train -2020-01-18 17:00:00,machine-1-1_y_34,0.076667,0.0,train -2020-01-18 18:00:00,machine-1-1_y_34,0.086947,0.0,train -2020-01-18 19:00:00,machine-1-1_y_34,0.080287,0.0,train -2020-01-18 20:00:00,machine-1-1_y_34,0.078694,0.0,train -2020-01-18 21:00:00,machine-1-1_y_34,0.10215,0.0,train -2020-01-18 22:00:00,machine-1-1_y_34,0.107942,0.0,train -2020-01-18 23:00:00,machine-1-1_y_34,0.088395,0.0,train -2020-01-19 00:00:00,machine-1-1_y_34,0.072902,0.0,train -2020-01-19 01:00:00,machine-1-1_y_34,0.067328,0.0,train -2020-01-19 02:00:00,machine-1-1_y_34,0.056613,0.0,train -2020-01-19 03:00:00,machine-1-1_y_34,0.035691,0.0,train -2020-01-19 04:00:00,machine-1-1_y_34,0.027366,0.0,train -2020-01-19 05:00:00,machine-1-1_y_34,0.027366,0.0,train -2020-01-19 06:00:00,machine-1-1_y_34,0.039238,0.0,train -2020-01-19 07:00:00,machine-1-1_y_34,0.083544,0.0,train -2020-01-19 08:00:00,machine-1-1_y_34,0.11634,0.0,train -2020-01-19 09:00:00,machine-1-1_y_34,0.171433,0.0,train -2020-01-19 10:00:00,machine-1-1_y_34,0.166799,0.0,train -2020-01-19 11:00:00,machine-1-1_y_34,0.119236,0.0,train -2020-01-19 12:00:00,machine-1-1_y_34,0.109752,0.0,train -2020-01-19 13:00:00,machine-1-1_y_34,0.11815,0.0,train -2020-01-19 14:00:00,machine-1-1_y_34,0.089626,0.0,train -2020-01-19 15:00:00,machine-1-1_y_34,0.084848,0.0,train -2020-01-19 16:00:00,machine-1-1_y_34,0.076377,0.0,train -2020-01-19 17:00:00,machine-1-1_y_34,0.071454,0.0,train -2020-01-19 18:00:00,machine-1-1_y_34,0.092811,0.0,train -2020-01-19 19:00:00,machine-1-1_y_34,0.109173,0.0,train -2020-01-19 20:00:00,machine-1-1_y_34,0.109679,0.0,train -2020-01-19 21:00:00,machine-1-1_y_34,0.115616,0.0,train -2020-01-19 22:00:00,machine-1-1_y_34,0.102657,0.0,train -2020-01-19 23:00:00,machine-1-1_y_34,0.103091,0.0,train -2020-01-20 00:00:00,machine-1-1_y_34,0.099037,0.0,train -2020-01-20 01:00:00,machine-1-1_y_34,0.078187,0.0,train -2020-01-20 02:00:00,machine-1-1_y_34,0.038804,0.0,train -2020-01-20 03:00:00,machine-1-1_y_34,0.034605,0.0,train -2020-01-20 04:00:00,machine-1-1_y_34,0.032071,0.0,train -2020-01-20 05:00:00,machine-1-1_y_34,0.032361,0.0,train -2020-01-20 06:00:00,machine-1-1_y_34,0.053935,0.0,train -2020-01-20 07:00:00,machine-1-1_y_34,0.102295,0.0,train -2020-01-20 08:00:00,machine-1-1_y_34,0.102946,0.0,train -2020-01-20 09:00:00,machine-1-1_y_34,0.115761,0.0,train -2020-01-20 10:00:00,machine-1-1_y_34,0.094114,0.0,train -2020-01-20 11:00:00,machine-1-1_y_34,0.122131,0.0,train -2020-01-20 12:00:00,machine-1-1_y_34,0.112648,0.0,train -2020-01-20 13:00:00,machine-1-1_y_34,0.091508,0.0,train -2020-01-20 14:00:00,machine-1-1_y_34,0.060233,0.0,train -2020-01-20 15:00:00,machine-1-1_y_34,0.073771,0.0,train -2020-01-20 16:00:00,machine-1-1_y_34,0.074423,0.0,train -2020-01-20 17:00:00,machine-1-1_y_34,0.075147,0.0,train -2020-01-20 18:00:00,machine-1-1_y_34,0.070151,0.0,train -2020-01-20 19:00:00,machine-1-1_y_34,0.12452,0.0,test -2020-01-20 20:00:00,machine-1-1_y_34,0.172229,0.0,test -2020-01-20 21:00:00,machine-1-1_y_34,0.188373,0.0,test -2020-01-20 22:00:00,machine-1-1_y_34,0.233403,0.0,test -2020-01-20 23:00:00,machine-1-1_y_34,0.11424,0.0,test -2020-01-21 00:00:00,machine-1-1_y_34,0.075798,0.0,test -2020-01-21 01:00:00,machine-1-1_y_34,0.053862,0.0,test -2020-01-21 02:00:00,machine-1-1_y_34,0.040035,0.0,test -2020-01-21 03:00:00,machine-1-1_y_34,0.031999,0.0,test -2020-01-21 04:00:00,machine-1-1_y_34,0.0278,0.0,test -2020-01-21 05:00:00,machine-1-1_y_34,0.028017,0.0,test -2020-01-21 06:00:00,machine-1-1_y_34,0.040614,0.0,test -2020-01-21 07:00:00,machine-1-1_y_34,0.073843,0.0,test -2020-01-21 08:00:00,machine-1-1_y_34,0.102729,0.0,test -2020-01-21 09:00:00,machine-1-1_y_34,0.092232,0.0,test -2020-01-21 10:00:00,machine-1-1_y_34,0.126692,0.0,test 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04:00:00,machine-1-1_y_34,0.023384,0.0,test -2020-01-22 05:00:00,machine-1-1_y_34,0.057844,0.0,test -2020-01-22 06:00:00,machine-1-1_y_34,0.154637,0.0,test -2020-01-22 07:00:00,machine-1-1_y_34,0.21849,0.0,test -2020-01-22 08:00:00,machine-1-1_y_34,0.16955,0.0,test -2020-01-22 09:00:00,machine-1-1_y_34,0.132339,0.0,test -2020-01-22 10:00:00,machine-1-1_y_34,0.104105,0.0,test -2020-01-22 11:00:00,machine-1-1_y_34,0.105915,0.0,test -2020-01-22 12:00:00,machine-1-1_y_34,0.071889,0.0,test -2020-01-22 13:00:00,machine-1-1_y_34,0.07645,0.0,test -2020-01-22 14:00:00,machine-1-1_y_34,0.076088,0.0,test -2020-01-22 15:00:00,machine-1-1_y_34,0.077898,0.0,test -2020-01-22 16:00:00,machine-1-1_y_34,0.080069,0.0,test -2020-01-22 17:00:00,machine-1-1_y_34,0.107145,0.0,test -2020-01-22 18:00:00,machine-1-1_y_34,0.120466,0.0,test -2020-01-22 19:00:00,machine-1-1_y_34,0.118946,0.0,test -2020-01-22 20:00:00,machine-1-1_y_34,0.110041,0.0,test -2020-01-22 21:00:00,machine-1-1_y_34,0.103381,0.0,test 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15:00:00,machine-1-1_y_34,0.103888,0.0,test -2020-01-23 16:00:00,machine-1-1_y_34,0.092522,0.0,test -2020-01-23 17:00:00,machine-1-1_y_34,0.136466,0.0,test -2020-01-23 18:00:00,machine-1-1_y_34,0.133208,0.0,test -2020-01-23 19:00:00,machine-1-1_y_34,0.138348,0.0,test -2020-01-23 20:00:00,machine-1-1_y_34,0.132991,0.0,test -2020-01-23 21:00:00,machine-1-1_y_34,0.128792,0.0,test -2020-01-23 22:00:00,machine-1-1_y_34,0.104829,0.0,test -2020-01-23 23:00:00,machine-1-1_y_34,0.075291,0.0,test -2020-01-24 00:00:00,machine-1-1_y_34,0.050894,0.0,test -2020-01-24 01:00:00,machine-1-1_y_34,0.038876,0.0,test -2020-01-24 02:00:00,machine-1-1_y_34,0.034315,0.0,test -2020-01-24 03:00:00,machine-1-1_y_34,0.030117,0.0,test -2020-01-24 04:00:00,machine-1-1_y_34,0.032071,0.0,test -2020-01-24 05:00:00,machine-1-1_y_34,0.057265,0.0,test -2020-01-24 06:00:00,machine-1-1_y_34,0.078622,0.0,test -2020-01-24 07:00:00,machine-1-1_y_34,0.094911,0.0,test -2020-01-24 08:00:00,machine-1-1_y_34,0.084051,0.0,test 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02:00:00,machine-1-1_y_34,0.034243,0.0,test -2020-01-25 03:00:00,machine-1-1_y_34,0.029465,0.0,test -2020-01-25 04:00:00,machine-1-1_y_34,0.030479,0.0,test -2020-01-25 05:00:00,machine-1-1_y_34,0.054731,0.0,test -2020-01-25 06:00:00,machine-1-1_y_34,0.125606,0.0,test -2020-01-25 07:00:00,machine-1-1_y_34,0.158257,0.0,test -2020-01-25 08:00:00,machine-1-1_y_34,0.185188,0.0,test -2020-01-25 09:00:00,machine-1-1_y_34,0.25657,0.0,test -2020-01-25 10:00:00,machine-1-1_y_34,0.191269,0.0,test -2020-01-25 11:00:00,machine-1-1_y_34,0.208499,0.0,test -2020-01-25 12:00:00,machine-1-1_y_34,0.179251,0.0,test -2020-01-25 13:00:00,machine-1-1_y_34,0.105336,0.0,test -2020-01-25 14:00:00,machine-1-1_y_34,0.086657,0.0,test -2020-01-25 15:00:00,machine-1-1_y_34,0.092304,0.0,test -2020-01-25 16:00:00,machine-1-1_y_34,0.105408,0.0,test -2020-01-25 17:00:00,machine-1-1_y_34,0.116484,0.0,test -2020-01-25 18:00:00,machine-1-1_y_34,0.111706,0.0,test -2020-01-25 19:00:00,machine-1-1_y_34,0.134439,0.0,test -2020-01-25 20:00:00,machine-1-1_y_34,0.126258,0.0,test -2020-01-25 21:00:00,machine-1-1_y_34,0.115181,0.0,test -2020-01-25 22:00:00,machine-1-1_y_34,0.095924,0.0,test -2020-01-25 23:00:00,machine-1-1_y_34,0.075074,0.0,test -2020-01-26 00:00:00,machine-1-1_y_34,0.055455,0.0,test -2020-01-26 01:00:00,machine-1-1_y_34,0.041193,0.0,test -2020-01-26 02:00:00,machine-1-1_y_34,0.038442,0.0,test -2020-01-26 03:00:00,machine-1-1_y_34,0.033954,0.0,test -2020-01-26 04:00:00,machine-1-1_y_34,0.030044,0.0,test -2020-01-26 05:00:00,machine-1-1_y_34,0.050677,0.0,test -2020-01-26 06:00:00,machine-1-1_y_34,0.074857,0.0,test -2020-01-26 07:00:00,machine-1-1_y_34,0.110765,0.0,test -2020-01-26 08:00:00,machine-1-1_y_34,0.08854,0.0,test -2020-01-26 09:00:00,machine-1-1_y_34,0.091363,0.0,test -2020-01-26 10:00:00,machine-1-1_y_34,0.092884,0.0,test -2020-01-26 11:00:00,machine-1-1_y_34,0.086875,0.0,test -2020-01-26 12:00:00,machine-1-1_y_34,0.067038,0.0,test -2020-01-26 13:00:00,machine-1-1_y_34,0.082314,0.0,test -2020-01-26 14:00:00,machine-1-1_y_34,0.107652,0.0,test -2020-01-26 15:00:00,machine-1-1_y_34,0.118946,0.0,test -2020-01-26 16:00:00,machine-1-1_y_34,0.120611,0.0,test -2020-01-26 17:00:00,machine-1-1_y_34,0.100268,0.0,test -2020-01-26 18:00:00,machine-1-1_y_34,0.110041,0.0,test -2020-01-26 19:00:00,machine-1-1_y_34,0.101064,0.0,test -2020-01-26 20:00:00,machine-1-1_y_34,0.097734,0.0,test -2020-01-26 21:00:00,machine-1-1_y_34,0.126982,0.0,test -2020-01-26 22:00:00,machine-1-1_y_34,0.089771,0.0,test -2020-01-26 23:00:00,machine-1-1_y_34,0.069065,0.0,test -2020-01-27 00:00:00,machine-1-1_y_34,0.051835,0.0,test -2020-01-27 01:00:00,machine-1-1_y_34,0.038587,0.0,test -2020-01-27 02:00:00,machine-1-1_y_34,0.032795,0.0,test -2020-01-27 03:00:00,machine-1-1_y_34,0.030479,0.0,test -2020-01-27 04:00:00,machine-1-1_y_34,0.028379,0.0,test -2020-01-27 05:00:00,machine-1-1_y_34,0.051546,0.0,test -2020-01-27 06:00:00,machine-1-1_y_34,0.058206,0.0,test -2020-01-27 07:00:00,machine-1-1_y_34,0.076595,0.0,test -2020-01-27 08:00:00,machine-1-1_y_34,0.071165,0.0,test -2020-01-27 09:00:00,machine-1-1_y_34,0.064504,0.0,test -2020-01-27 10:00:00,machine-1-1_y_34,0.063491,0.0,test -2020-01-27 11:00:00,machine-1-1_y_34,0.083617,0.0,test -2020-01-27 12:00:00,machine-1-1_y_34,0.061609,0.0,test -2020-01-27 13:00:00,machine-1-1_y_34,0.050822,0.0,test -2020-01-27 14:00:00,machine-1-1_y_34,0.073482,0.0,test -2020-01-27 15:00:00,machine-1-1_y_34,0.069427,0.0,test -2020-01-27 16:00:00,machine-1-1_y_34,0.078549,0.0,test -2020-01-27 17:00:00,machine-1-1_y_34,0.085137,0.0,test -2020-01-27 18:00:00,machine-1-1_y_34,0.082821,0.0,test -2020-01-27 19:00:00,machine-1-1_y_34,0.088974,0.0,test -2020-01-27 20:00:00,machine-1-1_y_34,0.089481,0.0,test -2020-01-27 21:00:00,machine-1-1_y_34,0.083906,0.0,test -2020-01-27 22:00:00,machine-1-1_y_34,0.079056,0.0,test -2020-01-27 23:00:00,machine-1-1_y_34,0.058713,0.0,test -2020-01-28 00:00:00,machine-1-1_y_34,0.043075,0.0,test -2020-01-28 01:00:00,machine-1-1_y_34,0.035474,0.0,test -2020-01-28 02:00:00,machine-1-1_y_34,0.035474,0.0,test -2020-01-28 03:00:00,machine-1-1_y_34,0.032578,0.0,test -2020-01-28 04:00:00,machine-1-1_y_34,0.028524,0.0,test -2020-01-28 05:00:00,machine-1-1_y_34,0.040542,0.0,test -2020-01-28 06:00:00,machine-1-1_y_34,0.071092,0.0,test -2020-01-28 07:00:00,machine-1-1_y_34,0.075653,0.0,test -2020-01-28 08:00:00,machine-1-1_y_34,0.064722,0.0,test -2020-01-28 09:00:00,machine-1-1_y_34,0.076739,0.0,test -2020-01-28 10:00:00,machine-1-1_y_34,0.064504,0.0,test -2020-01-28 11:00:00,machine-1-1_y_34,0.0674,0.0,test -2020-01-28 12:00:00,machine-1-1_y_34,0.067473,0.0,test -2020-01-28 13:00:00,machine-1-1_y_34,0.058134,0.0,test -2020-01-28 14:00:00,machine-1-1_y_34,0.062477,0.0,test -2020-01-28 15:00:00,machine-1-1_y_34,0.078766,0.0,test -2020-01-28 16:00:00,machine-1-1_y_34,0.076088,0.0,test -2020-01-28 17:00:00,machine-1-1_y_34,0.118294,0.0,test -2020-01-28 18:00:00,machine-1-1_y_34,0.155795,0.0,test -2020-01-28 19:00:00,machine-1-1_y_34,0.160429,0.0,test -2020-01-28 20:00:00,machine-1-1_y_34,0.129081,0.0,test -2020-01-28 21:00:00,machine-1-1_y_34,0.10063,0.0,test -2020-01-28 22:00:00,machine-1-1_y_34,0.083834,0.0,test -2020-01-28 23:00:00,machine-1-1_y_34,0.06226,0.0,test -2020-01-29 00:00:00,machine-1-1_y_34,0.044596,0.0,test -2020-01-29 01:00:00,machine-1-1_y_34,0.036487,0.0,test -2020-01-29 02:00:00,machine-1-1_y_34,0.035112,0.0,test -2020-01-29 03:00:00,machine-1-1_y_34,0.032216,0.0,test -2020-01-29 04:00:00,machine-1-1_y_34,0.029899,0.0,test -2020-01-29 05:00:00,machine-1-1_y_34,0.06588,0.0,test -2020-01-29 06:00:00,machine-1-1_y_34,0.2877,0.0,test -2020-01-29 07:00:00,machine-1-1_y_34,0.364656,0.0,test -2020-01-29 08:00:00,machine-1-1_y_34,0.379642,0.0,test -2020-01-29 09:00:00,machine-1-1_y_34,0.468689,0.0,test -2020-01-29 10:00:00,machine-1-1_y_34,0.440455,0.0,test -2020-01-29 11:00:00,machine-1-1_y_34,0.497213,0.0,test -2020-01-29 12:00:00,machine-1-1_y_34,0.500109,0.0,test -2020-01-29 13:00:00,machine-1-1_y_34,0.114095,0.0,test -2020-01-29 14:00:00,machine-1-1_y_34,0.094259,0.0,test -2020-01-29 15:00:00,machine-1-1_y_34,0.102223,0.0,test -2020-01-29 16:00:00,machine-1-1_y_34,0.100775,0.0,test -2020-01-29 17:00:00,machine-1-1_y_34,0.100557,0.0,test -2020-01-29 18:00:00,machine-1-1_y_34,0.101499,0.0,test -2020-01-29 19:00:00,machine-1-1_y_34,0.101426,0.0,test -2020-01-29 20:00:00,machine-1-1_y_34,0.134077,0.0,test -2020-01-29 21:00:00,machine-1-1_y_34,0.135814,0.0,test -2020-01-29 22:00:00,machine-1-1_y_34,0.100123,0.0,test -2020-01-29 23:00:00,machine-1-1_y_34,0.071744,0.0,test -2020-01-30 00:00:00,machine-1-1_y_34,0.047419,0.0,test -2020-01-30 01:00:00,machine-1-1_y_34,0.036053,0.0,test -2020-01-30 02:00:00,machine-1-1_y_34,0.030841,0.0,test -2020-01-30 03:00:00,machine-1-1_y_34,0.027655,0.0,test -2020-01-30 04:00:00,machine-1-1_y_34,0.030189,0.0,test -2020-01-30 05:00:00,machine-1-1_y_34,0.090929,0.0,test -2020-01-30 06:00:00,machine-1-1_y_34,0.367625,0.0,test -2020-01-30 07:00:00,machine-1-1_y_34,0.508362,0.0,test -2020-01-30 08:00:00,machine-1-1_y_34,0.488742,0.0,test -2020-01-30 09:00:00,machine-1-1_y_34,0.500615,0.0,test -2020-01-30 10:00:00,machine-1-1_y_34,0.276696,0.0,test -2020-01-30 11:00:00,machine-1-1_y_34,0.290596,0.0,test -2020-01-30 12:00:00,machine-1-1_y_34,0.154275,0.0,test -2020-01-30 13:00:00,machine-1-1_y_34,0.120032,0.0,test -2020-01-30 14:00:00,machine-1-1_y_34,0.097879,0.0,test -2020-01-30 15:00:00,machine-1-1_y_34,0.106277,0.0,test -2020-01-30 16:00:00,machine-1-1_y_34,0.10063,0.0,test -2020-01-30 17:00:00,machine-1-1_y_34,0.119236,0.0,test -2020-01-30 18:00:00,machine-1-1_y_34,0.114313,0.0,test -2020-01-30 19:00:00,machine-1-1_y_34,0.101499,0.0,test -2020-01-30 20:00:00,machine-1-1_y_34,0.123,0.0,test -2020-01-30 21:00:00,machine-1-1_y_34,0.122421,0.0,test -2020-01-30 22:00:00,machine-1-1_y_34,0.10606,0.0,test -2020-01-30 23:00:00,machine-1-1_y_34,0.076667,0.0,test -2020-01-31 00:00:00,machine-1-1_y_34,0.048215,0.0,test -2020-01-31 01:00:00,machine-1-1_y_34,0.035619,0.0,test -2020-01-31 02:00:00,machine-1-1_y_34,0.030189,0.0,test -2020-01-31 03:00:00,machine-1-1_y_34,0.040469,0.0,test -2020-01-31 04:00:00,machine-1-1_y_34,0.100123,0.0,test -2020-01-31 05:00:00,machine-1-1_y_34,0.242525,0.0,test -2020-01-31 06:00:00,machine-1-1_y_34,0.268805,0.0,test -2020-01-31 07:00:00,machine-1-1_y_34,0.49772,0.0,test -2020-01-31 08:00:00,machine-1-1_y_34,0.523782,0.0,test -2020-01-31 09:00:00,machine-1-1_y_34,0.493955,0.0,test -2020-01-31 10:00:00,machine-1-1_y_34,0.152682,0.0,test -2020-01-31 11:00:00,machine-1-1_y_34,0.159632,0.0,test -2020-01-31 12:00:00,machine-1-1_y_34,0.234417,0.0,test -2020-01-31 13:00:00,machine-1-1_y_34,0.138203,0.0,test -2020-01-31 14:00:00,machine-1-1_y_34,0.109245,0.0,test -2020-01-31 15:00:00,machine-1-1_y_34,0.096286,0.0,test -2020-01-31 16:00:00,machine-1-1_y_34,0.120611,0.0,test -2020-01-31 17:00:00,machine-1-1_y_34,0.102585,0.0,test -2020-01-31 18:00:00,machine-1-1_y_34,0.070948,1.0,test -2020-01-31 19:00:00,machine-1-1_y_34,0.050677,1.0,test -2020-01-31 20:00:00,machine-1-1_y_34,0.04018,1.0,test -2020-01-31 21:00:00,machine-1-1_y_34,0.034243,1.0,test -2020-01-31 22:00:00,machine-1-1_y_34,0.055093,1.0,test -2020-01-31 23:00:00,machine-1-1_y_34,0.212047,1.0,test -2020-02-01 00:00:00,machine-1-1_y_34,0.355173,1.0,test -2020-02-01 01:00:00,machine-1-1_y_34,0.547021,1.0,test -2020-02-01 02:00:00,machine-1-1_y_34,0.397596,1.0,test -2020-02-01 03:00:00,machine-1-1_y_34,0.481793,1.0,test -2020-02-01 04:00:00,machine-1-1_y_34,0.254036,0.0,test -2020-02-01 05:00:00,machine-1-1_y_34,0.17527,0.0,test -2020-02-01 06:00:00,machine-1-1_y_34,0.184753,0.0,test -2020-02-01 07:00:00,machine-1-1_y_34,0.177442,0.0,test -2020-02-01 08:00:00,machine-1-1_y_34,0.210599,0.0,test -2020-02-01 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23:00:00,machine-1-1_y_35,0.103084,0.0,train -2020-01-20 00:00:00,machine-1-1_y_35,0.099102,0.0,train -2020-01-20 01:00:00,machine-1-1_y_35,0.078254,0.0,train -2020-01-20 02:00:00,machine-1-1_y_35,0.038874,0.0,train -2020-01-20 03:00:00,machine-1-1_y_35,0.034675,0.0,train -2020-01-20 04:00:00,machine-1-1_y_35,0.032141,0.0,train -2020-01-20 05:00:00,machine-1-1_y_35,0.032358,0.0,train -2020-01-20 06:00:00,machine-1-1_y_35,0.053931,0.0,train -2020-01-20 07:00:00,machine-1-1_y_35,0.10236,0.0,train -2020-01-20 08:00:00,machine-1-1_y_35,0.103011,0.0,train -2020-01-20 09:00:00,machine-1-1_y_35,0.115825,0.0,train -2020-01-20 10:00:00,machine-1-1_y_35,0.09418,0.0,train -2020-01-20 11:00:00,machine-1-1_y_35,0.122195,0.0,train -2020-01-20 12:00:00,machine-1-1_y_35,0.112712,0.0,train -2020-01-20 13:00:00,machine-1-1_y_35,0.091574,0.0,train -2020-01-20 14:00:00,machine-1-1_y_35,0.060301,0.0,train -2020-01-20 15:00:00,machine-1-1_y_35,0.073766,0.0,train -2020-01-20 16:00:00,machine-1-1_y_35,0.074417,0.0,train -2020-01-20 17:00:00,machine-1-1_y_35,0.075214,0.0,train -2020-01-20 18:00:00,machine-1-1_y_35,0.070219,0.0,train -2020-01-20 19:00:00,machine-1-1_y_35,0.124584,0.0,test -2020-01-20 20:00:00,machine-1-1_y_35,0.172217,0.0,test -2020-01-20 21:00:00,machine-1-1_y_35,0.188432,0.0,test -2020-01-20 22:00:00,machine-1-1_y_35,0.233459,0.0,test -2020-01-20 23:00:00,machine-1-1_y_35,0.114232,0.0,test -2020-01-21 00:00:00,machine-1-1_y_35,0.075865,0.0,test -2020-01-21 01:00:00,machine-1-1_y_35,0.053931,0.0,test -2020-01-21 02:00:00,machine-1-1_y_35,0.040104,0.0,test -2020-01-21 03:00:00,machine-1-1_y_35,0.031997,0.0,test -2020-01-21 04:00:00,machine-1-1_y_35,0.02787,0.0,test -2020-01-21 05:00:00,machine-1-1_y_35,0.028015,0.0,test -2020-01-21 06:00:00,machine-1-1_y_35,0.040683,0.0,test -2020-01-21 07:00:00,machine-1-1_y_35,0.073911,0.0,test -2020-01-21 08:00:00,machine-1-1_y_35,0.102794,0.0,test -2020-01-21 09:00:00,machine-1-1_y_35,0.092225,0.0,test 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03:00:00,machine-1-1_y_35,0.022658,0.0,test -2020-01-22 04:00:00,machine-1-1_y_35,0.023382,0.0,test -2020-01-22 05:00:00,machine-1-1_y_35,0.057912,0.0,test -2020-01-22 06:00:00,machine-1-1_y_35,0.154698,0.0,test -2020-01-22 07:00:00,machine-1-1_y_35,0.218546,0.0,test -2020-01-22 08:00:00,machine-1-1_y_35,0.169611,0.0,test -2020-01-22 09:00:00,machine-1-1_y_35,0.13233,0.0,test -2020-01-22 10:00:00,machine-1-1_y_35,0.104097,0.0,test -2020-01-22 11:00:00,machine-1-1_y_35,0.105907,0.0,test -2020-01-22 12:00:00,machine-1-1_y_35,0.071884,0.0,test -2020-01-22 13:00:00,machine-1-1_y_35,0.076517,0.0,test -2020-01-22 14:00:00,machine-1-1_y_35,0.076155,0.0,test -2020-01-22 15:00:00,machine-1-1_y_35,0.077964,0.0,test -2020-01-22 16:00:00,machine-1-1_y_35,0.080136,0.0,test -2020-01-22 17:00:00,machine-1-1_y_35,0.10721,0.0,test -2020-01-22 18:00:00,machine-1-1_y_35,0.12053,0.0,test -2020-01-22 19:00:00,machine-1-1_y_35,0.118937,0.0,test -2020-01-22 20:00:00,machine-1-1_y_35,0.110033,0.0,test 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14:00:00,machine-1-1_y_35,0.088823,0.0,test -2020-01-23 15:00:00,machine-1-1_y_35,0.10388,0.0,test -2020-01-23 16:00:00,machine-1-1_y_35,0.092587,0.0,test -2020-01-23 17:00:00,machine-1-1_y_35,0.136456,0.0,test -2020-01-23 18:00:00,machine-1-1_y_35,0.133271,0.0,test -2020-01-23 19:00:00,machine-1-1_y_35,0.138338,0.0,test -2020-01-23 20:00:00,machine-1-1_y_35,0.132981,0.0,test -2020-01-23 21:00:00,machine-1-1_y_35,0.128855,0.0,test -2020-01-23 22:00:00,machine-1-1_y_35,0.104894,0.0,test -2020-01-23 23:00:00,machine-1-1_y_35,0.075358,0.0,test -2020-01-24 00:00:00,machine-1-1_y_35,0.050963,0.0,test -2020-01-24 01:00:00,machine-1-1_y_35,0.038946,0.0,test -2020-01-24 02:00:00,machine-1-1_y_35,0.034385,0.0,test -2020-01-24 03:00:00,machine-1-1_y_35,0.030114,0.0,test -2020-01-24 04:00:00,machine-1-1_y_35,0.032141,0.0,test -2020-01-24 05:00:00,machine-1-1_y_35,0.057261,0.0,test -2020-01-24 06:00:00,machine-1-1_y_35,0.078616,0.0,test -2020-01-24 07:00:00,machine-1-1_y_35,0.094904,0.0,test 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01:00:00,machine-1-1_y_35,0.03634,0.0,test -2020-01-25 02:00:00,machine-1-1_y_35,0.034313,0.0,test -2020-01-25 03:00:00,machine-1-1_y_35,0.029535,0.0,test -2020-01-25 04:00:00,machine-1-1_y_35,0.030549,0.0,test -2020-01-25 05:00:00,machine-1-1_y_35,0.054727,0.0,test -2020-01-25 06:00:00,machine-1-1_y_35,0.12567,0.0,test -2020-01-25 07:00:00,machine-1-1_y_35,0.158318,0.0,test -2020-01-25 08:00:00,machine-1-1_y_35,0.185174,0.0,test -2020-01-25 09:00:00,machine-1-1_y_35,0.256624,0.0,test -2020-01-25 10:00:00,machine-1-1_y_35,0.191328,0.0,test -2020-01-25 11:00:00,machine-1-1_y_35,0.208557,0.0,test -2020-01-25 12:00:00,machine-1-1_y_35,0.179311,0.0,test -2020-01-25 13:00:00,machine-1-1_y_35,0.1054,0.0,test -2020-01-25 14:00:00,machine-1-1_y_35,0.086724,0.0,test -2020-01-25 15:00:00,machine-1-1_y_35,0.09237,0.0,test -2020-01-25 16:00:00,machine-1-1_y_35,0.1054,0.0,test -2020-01-25 17:00:00,machine-1-1_y_35,0.116548,0.0,test -2020-01-25 18:00:00,machine-1-1_y_35,0.111698,0.0,test -2020-01-25 19:00:00,machine-1-1_y_35,0.134501,0.0,test -2020-01-25 20:00:00,machine-1-1_y_35,0.126321,0.0,test -2020-01-25 21:00:00,machine-1-1_y_35,0.115173,0.0,test -2020-01-25 22:00:00,machine-1-1_y_35,0.09599,0.0,test -2020-01-25 23:00:00,machine-1-1_y_35,0.075141,0.0,test -2020-01-26 00:00:00,machine-1-1_y_35,0.055523,0.0,test -2020-01-26 01:00:00,machine-1-1_y_35,0.041262,0.0,test -2020-01-26 02:00:00,machine-1-1_y_35,0.038512,0.0,test -2020-01-26 03:00:00,machine-1-1_y_35,0.034023,0.0,test -2020-01-26 04:00:00,machine-1-1_y_35,0.030042,0.0,test -2020-01-26 05:00:00,machine-1-1_y_35,0.050746,0.0,test -2020-01-26 06:00:00,machine-1-1_y_35,0.074924,0.0,test -2020-01-26 07:00:00,machine-1-1_y_35,0.11083,0.0,test -2020-01-26 08:00:00,machine-1-1_y_35,0.088606,0.0,test -2020-01-26 09:00:00,machine-1-1_y_35,0.091429,0.0,test -2020-01-26 10:00:00,machine-1-1_y_35,0.092949,0.0,test -2020-01-26 11:00:00,machine-1-1_y_35,0.086941,0.0,test -2020-01-26 12:00:00,machine-1-1_y_35,0.067033,0.0,test 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06:00:00,machine-1-1_y_35,0.058274,0.0,test -2020-01-27 07:00:00,machine-1-1_y_35,0.076661,0.0,test -2020-01-27 08:00:00,machine-1-1_y_35,0.07116,0.0,test -2020-01-27 09:00:00,machine-1-1_y_35,0.064572,0.0,test -2020-01-27 10:00:00,machine-1-1_y_35,0.063559,0.0,test -2020-01-27 11:00:00,machine-1-1_y_35,0.083683,0.0,test -2020-01-27 12:00:00,machine-1-1_y_35,0.061604,0.0,test -2020-01-27 13:00:00,machine-1-1_y_35,0.05089,0.0,test -2020-01-27 14:00:00,machine-1-1_y_35,0.073476,0.0,test -2020-01-27 15:00:00,machine-1-1_y_35,0.069422,0.0,test -2020-01-27 16:00:00,machine-1-1_y_35,0.078544,0.0,test -2020-01-27 17:00:00,machine-1-1_y_35,0.085131,0.0,test -2020-01-27 18:00:00,machine-1-1_y_35,0.082815,0.0,test -2020-01-27 19:00:00,machine-1-1_y_35,0.088968,0.0,test -2020-01-27 20:00:00,machine-1-1_y_35,0.089547,0.0,test -2020-01-27 21:00:00,machine-1-1_y_35,0.083973,0.0,test -2020-01-27 22:00:00,machine-1-1_y_35,0.079123,0.0,test -2020-01-27 23:00:00,machine-1-1_y_35,0.058781,0.0,test 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17:00:00,machine-1-1_y_35,0.118358,0.0,test -2020-01-28 18:00:00,machine-1-1_y_35,0.155784,0.0,test -2020-01-28 19:00:00,machine-1-1_y_35,0.160489,0.0,test -2020-01-28 20:00:00,machine-1-1_y_35,0.129072,0.0,test -2020-01-28 21:00:00,machine-1-1_y_35,0.100623,0.0,test -2020-01-28 22:00:00,machine-1-1_y_35,0.0839,0.0,test -2020-01-28 23:00:00,machine-1-1_y_35,0.062328,0.0,test -2020-01-29 00:00:00,machine-1-1_y_35,0.044592,0.0,test -2020-01-29 01:00:00,machine-1-1_y_35,0.036557,0.0,test -2020-01-29 02:00:00,machine-1-1_y_35,0.035182,0.0,test -2020-01-29 03:00:00,machine-1-1_y_35,0.032286,0.0,test -2020-01-29 04:00:00,machine-1-1_y_35,0.029897,0.0,test -2020-01-29 05:00:00,machine-1-1_y_35,0.065948,0.0,test -2020-01-29 06:00:00,machine-1-1_y_35,0.287679,0.0,test -2020-01-29 07:00:00,machine-1-1_y_35,0.364702,0.0,test -2020-01-29 08:00:00,machine-1-1_y_35,0.379687,0.0,test -2020-01-29 09:00:00,machine-1-1_y_35,0.468655,0.0,test -2020-01-29 10:00:00,machine-1-1_y_35,0.440495,0.0,test 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15:00:00,machine-1-1_y_35,0.096352,0.0,test -2020-01-31 16:00:00,machine-1-1_y_35,0.120675,0.0,test -2020-01-31 17:00:00,machine-1-1_y_35,0.102577,0.0,test -2020-01-31 18:00:00,machine-1-1_y_35,0.070943,1.0,test -2020-01-31 19:00:00,machine-1-1_y_35,0.050746,1.0,test -2020-01-31 20:00:00,machine-1-1_y_35,0.040249,1.0,test -2020-01-31 21:00:00,machine-1-1_y_35,0.034313,1.0,test -2020-01-31 22:00:00,machine-1-1_y_35,0.055161,1.0,test -2020-01-31 23:00:00,machine-1-1_y_35,0.212104,1.0,test -2020-02-01 00:00:00,machine-1-1_y_35,0.355219,1.0,test -2020-02-01 01:00:00,machine-1-1_y_35,0.546981,1.0,test -2020-02-01 02:00:00,machine-1-1_y_35,0.397568,1.0,test -2020-02-01 03:00:00,machine-1-1_y_35,0.48183,1.0,test -2020-02-01 04:00:00,machine-1-1_y_35,0.25409,0.0,test -2020-02-01 05:00:00,machine-1-1_y_35,0.175329,0.0,test -2020-02-01 06:00:00,machine-1-1_y_35,0.184813,0.0,test -2020-02-01 07:00:00,machine-1-1_y_35,0.177429,0.0,test -2020-02-01 08:00:00,machine-1-1_y_35,0.210656,0.0,test 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23:00:00,machine-1-1_y_5,0.925641,0.0,train -2020-01-20 00:00:00,machine-1-1_y_5,0.966667,0.0,train -2020-01-20 01:00:00,machine-1-1_y_5,0.938462,0.0,train -2020-01-20 02:00:00,machine-1-1_y_5,0.912821,0.0,train -2020-01-20 03:00:00,machine-1-1_y_5,0.917949,0.0,train -2020-01-20 04:00:00,machine-1-1_y_5,0.915385,0.0,train -2020-01-20 05:00:00,machine-1-1_y_5,0.907692,0.0,train -2020-01-20 06:00:00,machine-1-1_y_5,0.938462,0.0,train -2020-01-20 07:00:00,machine-1-1_y_5,0.928205,0.0,train -2020-01-20 08:00:00,machine-1-1_y_5,0.920513,0.0,train -2020-01-20 09:00:00,machine-1-1_y_5,0.971795,0.0,train -2020-01-20 10:00:00,machine-1-1_y_5,0.946154,0.0,train -2020-01-20 11:00:00,machine-1-1_y_5,0.923077,0.0,train -2020-01-20 12:00:00,machine-1-1_y_5,0.974359,0.0,train -2020-01-20 13:00:00,machine-1-1_y_5,0.94359,0.0,train -2020-01-20 14:00:00,machine-1-1_y_5,0.915385,0.0,train -2020-01-20 15:00:00,machine-1-1_y_5,0.958974,0.0,train -2020-01-20 16:00:00,machine-1-1_y_5,0.933333,0.0,train 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23:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-23 00:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-23 01:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-01-23 02:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-23 03:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-23 04:00:00,machine-1-1_y_5,0.951282,0.0,test -2020-01-23 05:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-23 06:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-23 07:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-23 08:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-01-23 09:00:00,machine-1-1_y_5,0.930769,0.0,test -2020-01-23 10:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-23 11:00:00,machine-1-1_y_5,0.992308,0.0,test -2020-01-23 12:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-23 13:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-23 14:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-23 15:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-23 16:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-23 17:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-23 18:00:00,machine-1-1_y_5,0.976923,0.0,test -2020-01-23 19:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-01-23 20:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-23 21:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-01-23 22:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-23 23:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-24 00:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-24 01:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-24 02:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-24 03:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-01-24 04:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-24 05:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-24 06:00:00,machine-1-1_y_5,0.948718,0.0,test -2020-01-24 07:00:00,machine-1-1_y_5,0.930769,0.0,test -2020-01-24 08:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-24 09:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-24 10:00:00,machine-1-1_y_5,0.930769,0.0,test -2020-01-24 11:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-24 12:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-24 13:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-24 14:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-24 15:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-01-24 16:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-24 17:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-24 18:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-01-24 19:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-24 20:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-01-24 21:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-01-24 22:00:00,machine-1-1_y_5,0.923077,0.0,test -2020-01-24 23:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-25 00:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-25 01:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-25 02:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-25 03:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-25 04:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-25 05:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-25 06:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-01-25 07:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-01-25 08:00:00,machine-1-1_y_5,0.992308,0.0,test -2020-01-25 09:00:00,machine-1-1_y_5,0.979487,0.0,test -2020-01-25 10:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-01-25 11:00:00,machine-1-1_y_5,0.994872,0.0,test -2020-01-25 12:00:00,machine-1-1_y_5,0.987179,0.0,test -2020-01-25 13:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-25 14:00:00,machine-1-1_y_5,0.958974,0.0,test -2020-01-25 15:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-25 16:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-25 17:00:00,machine-1-1_y_5,0.969231,0.0,test -2020-01-25 18:00:00,machine-1-1_y_5,0.930769,0.0,test -2020-01-25 19:00:00,machine-1-1_y_5,0.984615,0.0,test -2020-01-25 20:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-25 21:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-25 22:00:00,machine-1-1_y_5,0.969231,0.0,test -2020-01-25 23:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-26 00:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-26 01:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-26 02:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-26 03:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-26 04:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-26 05:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-26 06:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-26 07:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-01-26 08:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-26 09:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-26 10:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-01-26 11:00:00,machine-1-1_y_5,0.933333,0.0,test -2020-01-26 12:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-26 13:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-26 14:00:00,machine-1-1_y_5,0.930769,0.0,test -2020-01-26 15:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-26 16:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-26 17:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-26 18:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-01-26 19:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-01-26 20:00:00,machine-1-1_y_5,0.923077,0.0,test -2020-01-26 21:00:00,machine-1-1_y_5,0.951282,0.0,test -2020-01-26 22:00:00,machine-1-1_y_5,0.951282,0.0,test -2020-01-26 23:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-27 00:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-27 01:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-27 02:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-27 03:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-27 04:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-27 05:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-27 06:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-01-27 07:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-27 08:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-27 09:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-27 10:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-27 11:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-27 12:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-01-27 13:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-27 14:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-27 15:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-27 16:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-27 17:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-27 18:00:00,machine-1-1_y_5,0.969231,0.0,test -2020-01-27 19:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-27 20:00:00,machine-1-1_y_5,0.969231,0.0,test -2020-01-27 21:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-27 22:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-27 23:00:00,machine-1-1_y_5,0.958974,0.0,test -2020-01-28 00:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-28 01:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-28 02:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-01-28 03:00:00,machine-1-1_y_5,0.910256,0.0,test -2020-01-28 04:00:00,machine-1-1_y_5,0.9,0.0,test -2020-01-28 05:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-28 06:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-28 07:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-28 08:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-01-28 09:00:00,machine-1-1_y_5,0.923077,0.0,test -2020-01-28 10:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-28 11:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-28 12:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-28 13:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-28 14:00:00,machine-1-1_y_5,0.958974,0.0,test -2020-01-28 15:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-28 16:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-28 17:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-28 18:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-01-28 19:00:00,machine-1-1_y_5,0.976923,0.0,test -2020-01-28 20:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-01-28 21:00:00,machine-1-1_y_5,0.923077,0.0,test -2020-01-28 22:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-01-28 23:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-29 00:00:00,machine-1-1_y_5,0.905128,0.0,test -2020-01-29 01:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-29 02:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-29 03:00:00,machine-1-1_y_5,0.9,0.0,test -2020-01-29 04:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-29 05:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-29 06:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-01-29 07:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-01-29 08:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-29 09:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-29 10:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-29 11:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-29 12:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-29 13:00:00,machine-1-1_y_5,0.974359,0.0,test -2020-01-29 14:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-01-29 15:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-29 16:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-01-29 17:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-29 18:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-29 19:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-29 20:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-29 21:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-29 22:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-29 23:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-30 00:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-01-30 01:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-01-30 02:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-30 03:00:00,machine-1-1_y_5,0.948718,0.0,test -2020-01-30 04:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-01-30 05:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-30 06:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-30 07:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-30 08:00:00,machine-1-1_y_5,0.997436,0.0,test -2020-01-30 09:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-30 10:00:00,machine-1-1_y_5,0.979487,0.0,test -2020-01-30 11:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-30 12:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-30 13:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-01-30 14:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-01-30 15:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-30 16:00:00,machine-1-1_y_5,0.974359,0.0,test -2020-01-30 17:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-30 18:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-01-30 19:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-30 20:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-01-30 21:00:00,machine-1-1_y_5,0.923077,0.0,test -2020-01-30 22:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-01-30 23:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-01-31 00:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-01-31 01:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-01-31 02:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-01-31 03:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-01-31 04:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-01-31 05:00:00,machine-1-1_y_5,0.997436,0.0,test -2020-01-31 06:00:00,machine-1-1_y_5,0.969231,0.0,test -2020-01-31 07:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-31 08:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-31 09:00:00,machine-1-1_y_5,1.0,0.0,test -2020-01-31 10:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-01-31 11:00:00,machine-1-1_y_5,0.979487,0.0,test -2020-01-31 12:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-01-31 13:00:00,machine-1-1_y_5,0.958974,0.0,test -2020-01-31 14:00:00,machine-1-1_y_5,0.974359,0.0,test -2020-01-31 15:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-01-31 16:00:00,machine-1-1_y_5,0.946154,0.0,test -2020-01-31 17:00:00,machine-1-1_y_5,0.948718,0.0,test -2020-01-31 18:00:00,machine-1-1_y_5,0.910256,1.0,test -2020-01-31 19:00:00,machine-1-1_y_5,0.946154,1.0,test -2020-01-31 20:00:00,machine-1-1_y_5,0.9,1.0,test -2020-01-31 21:00:00,machine-1-1_y_5,0.953846,1.0,test -2020-01-31 22:00:00,machine-1-1_y_5,0.9,1.0,test -2020-01-31 23:00:00,machine-1-1_y_5,0.964103,1.0,test -2020-02-01 00:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 01:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 02:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 03:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 04:00:00,machine-1-1_y_5,0.984615,0.0,test -2020-02-01 05:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-02-01 06:00:00,machine-1-1_y_5,0.989744,0.0,test -2020-02-01 07:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-02-01 08:00:00,machine-1-1_y_5,0.997436,0.0,test -2020-02-01 09:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-02-01 10:00:00,machine-1-1_y_5,0.992308,0.0,test -2020-02-01 11:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-02-01 12:00:00,machine-1-1_y_5,0.951282,0.0,test -2020-02-01 13:00:00,machine-1-1_y_5,0.920513,1.0,test -2020-02-01 14:00:00,machine-1-1_y_5,0.958974,1.0,test -2020-02-01 15:00:00,machine-1-1_y_5,0.905128,1.0,test -2020-02-01 16:00:00,machine-1-1_y_5,0.951282,1.0,test -2020-02-01 17:00:00,machine-1-1_y_5,0.905128,1.0,test -2020-02-01 18:00:00,machine-1-1_y_5,0.992308,1.0,test -2020-02-01 19:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 20:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 21:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 22:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_5,0.997436,0.0,test -2020-02-02 00:00:00,machine-1-1_y_5,0.989744,0.0,test -2020-02-02 01:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-02-02 02:00:00,machine-1-1_y_5,0.982051,0.0,test -2020-02-02 03:00:00,machine-1-1_y_5,0.984615,0.0,test -2020-02-02 04:00:00,machine-1-1_y_5,1.0,0.0,test -2020-02-02 05:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-02-02 06:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-02-02 07:00:00,machine-1-1_y_5,0.923077,1.0,test -2020-02-02 08:00:00,machine-1-1_y_5,0.941026,1.0,test -2020-02-02 09:00:00,machine-1-1_y_5,0.912821,1.0,test -2020-02-02 10:00:00,machine-1-1_y_5,0.923077,1.0,test -2020-02-02 11:00:00,machine-1-1_y_5,0.905128,1.0,test -2020-02-02 12:00:00,machine-1-1_y_5,0.989744,1.0,test -2020-02-02 13:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-02 14:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-02 15:00:00,machine-1-1_y_5,0.989744,1.0,test -2020-02-02 16:00:00,machine-1-1_y_5,1.0,0.0,test -2020-02-02 17:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-02-02 18:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-02-02 19:00:00,machine-1-1_y_5,0.933333,0.0,test -2020-02-02 20:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-02-02 21:00:00,machine-1-1_y_5,0.964103,0.0,test -2020-02-02 22:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-02-02 23:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-02-03 00:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-02-03 01:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-02-03 02:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-02-03 03:00:00,machine-1-1_y_5,0.935897,0.0,test -2020-02-03 04:00:00,machine-1-1_y_5,0.907692,0.0,test -2020-02-03 05:00:00,machine-1-1_y_5,0.917949,1.0,test -2020-02-03 06:00:00,machine-1-1_y_5,0.907692,1.0,test -2020-02-03 07:00:00,machine-1-1_y_5,0.941026,1.0,test -2020-02-03 08:00:00,machine-1-1_y_5,0.910256,1.0,test -2020-02-03 09:00:00,machine-1-1_y_5,0.897436,1.0,test -2020-02-03 10:00:00,machine-1-1_y_5,0.946154,1.0,test -2020-02-03 11:00:00,machine-1-1_y_5,0.912821,1.0,test -2020-02-03 12:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-03 13:00:00,machine-1-1_y_5,0.992308,1.0,test -2020-02-03 14:00:00,machine-1-1_y_5,0.951282,1.0,test -2020-02-03 15:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-03 16:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-03 17:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-03 18:00:00,machine-1-1_y_5,0.94359,0.0,test -2020-02-03 19:00:00,machine-1-1_y_5,0.948718,0.0,test -2020-02-03 20:00:00,machine-1-1_y_5,0.938462,0.0,test -2020-02-03 21:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-02-03 22:00:00,machine-1-1_y_5,0.948718,0.0,test -2020-02-03 23:00:00,machine-1-1_y_5,0.933333,0.0,test -2020-02-04 00:00:00,machine-1-1_y_5,0.992308,0.0,test -2020-02-04 01:00:00,machine-1-1_y_5,0.989744,0.0,test -2020-02-04 02:00:00,machine-1-1_y_5,0.941026,0.0,test -2020-02-04 03:00:00,machine-1-1_y_5,0.976923,0.0,test -2020-02-04 04:00:00,machine-1-1_y_5,0.933333,0.0,test -2020-02-04 05:00:00,machine-1-1_y_5,0.95641,1.0,test -2020-02-04 06:00:00,machine-1-1_y_5,0.910256,1.0,test -2020-02-04 07:00:00,machine-1-1_y_5,0.910256,1.0,test -2020-02-04 08:00:00,machine-1-1_y_5,0.902564,1.0,test -2020-02-04 09:00:00,machine-1-1_y_5,0.958974,1.0,test -2020-02-04 10:00:00,machine-1-1_y_5,0.941026,1.0,test -2020-02-04 11:00:00,machine-1-1_y_5,1.0,1.0,test -2020-02-04 12:00:00,machine-1-1_y_5,0.958974,0.0,test -2020-02-04 13:00:00,machine-1-1_y_5,0.974359,0.0,test -2020-02-04 14:00:00,machine-1-1_y_5,0.920513,0.0,test -2020-02-04 15:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-02-04 16:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-02-04 17:00:00,machine-1-1_y_5,0.928205,0.0,test -2020-02-04 18:00:00,machine-1-1_y_5,0.915385,0.0,test -2020-02-04 19:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-02-04 20:00:00,machine-1-1_y_5,0.925641,0.0,test -2020-02-04 21:00:00,machine-1-1_y_5,0.971795,0.0,test -2020-02-04 22:00:00,machine-1-1_y_5,0.917949,0.0,test -2020-02-04 23:00:00,machine-1-1_y_5,0.912821,0.0,test -2020-02-05 00:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-02-05 01:00:00,machine-1-1_y_5,0.951282,0.0,test -2020-02-05 02:00:00,machine-1-1_y_5,0.902564,0.0,test -2020-02-05 03:00:00,machine-1-1_y_5,0.953846,0.0,test -2020-02-05 04:00:00,machine-1-1_y_5,0.961538,0.0,test -2020-02-05 05:00:00,machine-1-1_y_5,1.0,0.0,test -2020-02-05 06:00:00,machine-1-1_y_5,1.0,0.0,test -2020-02-05 07:00:00,machine-1-1_y_5,0.95641,0.0,test -2020-02-05 08:00:00,machine-1-1_y_5,1.0,0.0,test -2020-02-05 09:00:00,machine-1-1_y_5,0.976923,0.0,test -2020-02-05 10:00:00,machine-1-1_y_5,0.966667,0.0,test -2020-02-05 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03:00:00,machine-1-1_y_6,0.286252,0.0,test -2020-01-21 04:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-21 05:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-01-21 06:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-01-21 07:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-21 08:00:00,machine-1-1_y_6,0.283427,0.0,test -2020-01-21 09:00:00,machine-1-1_y_6,0.285311,0.0,test -2020-01-21 10:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-21 11:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-21 12:00:00,machine-1-1_y_6,0.299435,0.0,test -2020-01-21 13:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-21 14:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-21 15:00:00,machine-1-1_y_6,0.297552,0.0,test -2020-01-21 16:00:00,machine-1-1_y_6,0.282486,0.0,test -2020-01-21 17:00:00,machine-1-1_y_6,0.285311,0.0,test -2020-01-21 18:00:00,machine-1-1_y_6,0.305085,0.0,test -2020-01-21 19:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-21 20:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-21 21:00:00,machine-1-1_y_6,0.295669,0.0,test -2020-01-21 22:00:00,machine-1-1_y_6,0.283427,0.0,test -2020-01-21 23:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-01-22 00:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-22 01:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-01-22 02:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-22 03:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-22 04:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-01-22 05:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-01-22 06:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-22 07:00:00,machine-1-1_y_6,0.298493,0.0,test -2020-01-22 08:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-22 09:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-22 10:00:00,machine-1-1_y_6,0.298493,0.0,test -2020-01-22 11:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-22 12:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-22 13:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-01-22 14:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-01-22 15:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-22 16:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-01-22 17:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-22 18:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-01-22 19:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-01-22 20:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-22 21:00:00,machine-1-1_y_6,0.286252,0.0,test -2020-01-22 22:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-22 23:00:00,machine-1-1_y_6,0.283427,0.0,test -2020-01-23 00:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-23 01:00:00,machine-1-1_y_6,0.297552,0.0,test -2020-01-23 02:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-23 03:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-23 04:00:00,machine-1-1_y_6,0.297552,0.0,test -2020-01-23 05:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-23 06:00:00,machine-1-1_y_6,0.284369,0.0,test -2020-01-23 07:00:00,machine-1-1_y_6,0.30226,0.0,test -2020-01-23 08:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-01-23 09:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-01-23 10:00:00,machine-1-1_y_6,0.294727,0.0,test -2020-01-23 11:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-23 12:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-01-23 13:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-01-23 14:00:00,machine-1-1_y_6,0.26742,0.0,test -2020-01-23 15:00:00,machine-1-1_y_6,0.274953,0.0,test -2020-01-23 16:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-01-23 17:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-01-23 18:00:00,machine-1-1_y_6,0.289077,0.0,test -2020-01-23 19:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-23 20:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-23 21:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-01-23 22:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-01-23 23:00:00,machine-1-1_y_6,0.270245,0.0,test -2020-01-24 00:00:00,machine-1-1_y_6,0.274011,0.0,test -2020-01-24 01:00:00,machine-1-1_y_6,0.264595,0.0,test -2020-01-24 02:00:00,machine-1-1_y_6,0.266478,0.0,test -2020-01-24 03:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-24 04:00:00,machine-1-1_y_6,0.266478,0.0,test -2020-01-24 05:00:00,machine-1-1_y_6,0.269303,0.0,test -2020-01-24 06:00:00,machine-1-1_y_6,0.286252,0.0,test -2020-01-24 07:00:00,machine-1-1_y_6,0.274011,0.0,test -2020-01-24 08:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-01-24 09:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-24 10:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-01-24 11:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-01-24 12:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-01-24 13:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-24 14:00:00,machine-1-1_y_6,0.285311,0.0,test -2020-01-24 15:00:00,machine-1-1_y_6,0.303202,0.0,test -2020-01-24 16:00:00,machine-1-1_y_6,0.292844,0.0,test -2020-01-24 17:00:00,machine-1-1_y_6,0.297552,0.0,test -2020-01-24 18:00:00,machine-1-1_y_6,0.313559,0.0,test -2020-01-24 19:00:00,machine-1-1_y_6,0.299435,0.0,test -2020-01-24 20:00:00,machine-1-1_y_6,0.308851,0.0,test -2020-01-24 21:00:00,machine-1-1_y_6,0.298493,0.0,test -2020-01-24 22:00:00,machine-1-1_y_6,0.300377,0.0,test -2020-01-24 23:00:00,machine-1-1_y_6,0.306026,0.0,test -2020-01-25 00:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-01-25 01:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-01-25 02:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-01-25 03:00:00,machine-1-1_y_6,0.292844,0.0,test -2020-01-25 04:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-01-25 05:00:00,machine-1-1_y_6,0.306968,0.0,test -2020-01-25 06:00:00,machine-1-1_y_6,0.301318,0.0,test -2020-01-25 07:00:00,machine-1-1_y_6,0.305085,0.0,test -2020-01-25 08:00:00,machine-1-1_y_6,0.312618,0.0,test -2020-01-25 09:00:00,machine-1-1_y_6,0.298493,0.0,test -2020-01-25 10:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-25 11:00:00,machine-1-1_y_6,0.289077,0.0,test -2020-01-25 12:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-25 13:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-01-25 14:00:00,machine-1-1_y_6,0.253296,0.0,test -2020-01-25 15:00:00,machine-1-1_y_6,0.063089,0.0,test -2020-01-25 16:00:00,machine-1-1_y_6,0.078154,0.0,test -2020-01-25 17:00:00,machine-1-1_y_6,0.097928,0.0,test -2020-01-25 18:00:00,machine-1-1_y_6,0.096987,0.0,test -2020-01-25 19:00:00,machine-1-1_y_6,0.080038,0.0,test -2020-01-25 20:00:00,machine-1-1_y_6,0.082863,0.0,test -2020-01-25 21:00:00,machine-1-1_y_6,0.097928,0.0,test -2020-01-25 22:00:00,machine-1-1_y_6,0.127119,0.0,test -2020-01-25 23:00:00,machine-1-1_y_6,0.116761,0.0,test -2020-01-26 00:00:00,machine-1-1_y_6,0.117702,0.0,test -2020-01-26 01:00:00,machine-1-1_y_6,0.120527,0.0,test -2020-01-26 02:00:00,machine-1-1_y_6,0.123352,0.0,test -2020-01-26 03:00:00,machine-1-1_y_6,0.125235,0.0,test -2020-01-26 04:00:00,machine-1-1_y_6,0.138418,0.0,test -2020-01-26 05:00:00,machine-1-1_y_6,0.130885,0.0,test -2020-01-26 06:00:00,machine-1-1_y_6,0.148776,0.0,test -2020-01-26 07:00:00,machine-1-1_y_6,0.1742,0.0,test -2020-01-26 08:00:00,machine-1-1_y_6,0.173258,0.0,test -2020-01-26 09:00:00,machine-1-1_y_6,0.180791,0.0,test -2020-01-26 10:00:00,machine-1-1_y_6,0.077213,0.0,test -2020-01-26 11:00:00,machine-1-1_y_6,0.083804,0.0,test -2020-01-26 12:00:00,machine-1-1_y_6,0.101695,0.0,test -2020-01-26 13:00:00,machine-1-1_y_6,0.121469,0.0,test -2020-01-26 14:00:00,machine-1-1_y_6,0.121469,0.0,test -2020-01-26 15:00:00,machine-1-1_y_6,0.129944,0.0,test -2020-01-26 16:00:00,machine-1-1_y_6,0.150659,0.0,test -2020-01-26 17:00:00,machine-1-1_y_6,0.156309,0.0,test -2020-01-26 18:00:00,machine-1-1_y_6,0.181733,0.0,test -2020-01-26 19:00:00,machine-1-1_y_6,0.175141,0.0,test -2020-01-26 20:00:00,machine-1-1_y_6,0.180791,0.0,test -2020-01-26 21:00:00,machine-1-1_y_6,0.064972,0.0,test -2020-01-26 22:00:00,machine-1-1_y_6,0.081921,0.0,test -2020-01-26 23:00:00,machine-1-1_y_6,0.092279,0.0,test -2020-01-27 00:00:00,machine-1-1_y_6,0.09887,0.0,test -2020-01-27 01:00:00,machine-1-1_y_6,0.096987,0.0,test -2020-01-27 02:00:00,machine-1-1_y_6,0.096045,0.0,test -2020-01-27 03:00:00,machine-1-1_y_6,0.099812,0.0,test -2020-01-27 04:00:00,machine-1-1_y_6,0.099812,0.0,test -2020-01-27 05:00:00,machine-1-1_y_6,0.108286,0.0,test -2020-01-27 06:00:00,machine-1-1_y_6,0.131827,0.0,test -2020-01-27 07:00:00,machine-1-1_y_6,0.129944,0.0,test -2020-01-27 08:00:00,machine-1-1_y_6,0.145009,0.0,test -2020-01-27 09:00:00,machine-1-1_y_6,0.165725,0.0,test -2020-01-27 10:00:00,machine-1-1_y_6,0.160075,0.0,test -2020-01-27 11:00:00,machine-1-1_y_6,0.175141,0.0,test -2020-01-27 12:00:00,machine-1-1_y_6,0.056497,0.0,test -2020-01-27 13:00:00,machine-1-1_y_6,0.057439,0.0,test -2020-01-27 14:00:00,machine-1-1_y_6,0.073446,0.0,test -2020-01-27 15:00:00,machine-1-1_y_6,0.089454,0.0,test -2020-01-27 16:00:00,machine-1-1_y_6,0.096987,0.0,test -2020-01-27 17:00:00,machine-1-1_y_6,0.110169,0.0,test -2020-01-27 18:00:00,machine-1-1_y_6,0.129944,0.0,test -2020-01-27 19:00:00,machine-1-1_y_6,0.135593,0.0,test -2020-01-27 20:00:00,machine-1-1_y_6,0.159134,0.0,test -2020-01-27 21:00:00,machine-1-1_y_6,0.1629,0.0,test -2020-01-27 22:00:00,machine-1-1_y_6,0.171375,0.0,test -2020-01-27 23:00:00,machine-1-1_y_6,0.187382,0.0,test -2020-01-28 00:00:00,machine-1-1_y_6,0.177966,0.0,test -2020-01-28 01:00:00,machine-1-1_y_6,0.178908,0.0,test -2020-01-28 02:00:00,machine-1-1_y_6,0.196798,0.0,test -2020-01-28 03:00:00,machine-1-1_y_6,0.184557,0.0,test -2020-01-28 04:00:00,machine-1-1_y_6,0.185499,0.0,test -2020-01-28 05:00:00,machine-1-1_y_6,0.20339,0.0,test -2020-01-28 06:00:00,machine-1-1_y_6,0.202448,0.0,test -2020-01-28 07:00:00,machine-1-1_y_6,0.211864,0.0,test -2020-01-28 08:00:00,machine-1-1_y_6,0.228814,0.0,test -2020-01-28 09:00:00,machine-1-1_y_6,0.236347,0.0,test -2020-01-28 10:00:00,machine-1-1_y_6,0.241055,0.0,test -2020-01-28 11:00:00,machine-1-1_y_6,0.244821,0.0,test -2020-01-28 12:00:00,machine-1-1_y_6,0.241996,0.0,test -2020-01-28 13:00:00,machine-1-1_y_6,0.247646,0.0,test -2020-01-28 14:00:00,machine-1-1_y_6,0.268362,0.0,test -2020-01-28 15:00:00,machine-1-1_y_6,0.251412,0.0,test -2020-01-28 16:00:00,machine-1-1_y_6,0.253296,0.0,test -2020-01-28 17:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-01-28 18:00:00,machine-1-1_y_6,0.256121,0.0,test -2020-01-28 19:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-01-28 20:00:00,machine-1-1_y_6,0.255179,0.0,test -2020-01-28 21:00:00,machine-1-1_y_6,0.253296,0.0,test -2020-01-28 22:00:00,machine-1-1_y_6,0.269303,0.0,test -2020-01-28 23:00:00,machine-1-1_y_6,0.252354,0.0,test -2020-01-29 00:00:00,machine-1-1_y_6,0.251412,0.0,test -2020-01-29 01:00:00,machine-1-1_y_6,0.250471,0.0,test -2020-01-29 02:00:00,machine-1-1_y_6,0.249529,0.0,test -2020-01-29 03:00:00,machine-1-1_y_6,0.248588,0.0,test -2020-01-29 04:00:00,machine-1-1_y_6,0.250471,0.0,test -2020-01-29 05:00:00,machine-1-1_y_6,0.247646,0.0,test -2020-01-29 06:00:00,machine-1-1_y_6,0.251412,0.0,test -2020-01-29 07:00:00,machine-1-1_y_6,0.258004,0.0,test -2020-01-29 08:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-01-29 09:00:00,machine-1-1_y_6,0.260829,0.0,test -2020-01-29 10:00:00,machine-1-1_y_6,0.255179,0.0,test -2020-01-29 11:00:00,machine-1-1_y_6,0.252354,0.0,test -2020-01-29 12:00:00,machine-1-1_y_6,0.247646,0.0,test -2020-01-29 13:00:00,machine-1-1_y_6,0.246704,0.0,test -2020-01-29 14:00:00,machine-1-1_y_6,0.230697,0.0,test -2020-01-29 15:00:00,machine-1-1_y_6,0.235405,0.0,test -2020-01-29 16:00:00,machine-1-1_y_6,0.258945,0.0,test -2020-01-29 17:00:00,machine-1-1_y_6,0.243879,0.0,test -2020-01-29 18:00:00,machine-1-1_y_6,0.246704,0.0,test -2020-01-29 19:00:00,machine-1-1_y_6,0.26177,0.0,test -2020-01-29 20:00:00,machine-1-1_y_6,0.248588,0.0,test -2020-01-29 21:00:00,machine-1-1_y_6,0.251412,0.0,test -2020-01-29 22:00:00,machine-1-1_y_6,0.252354,0.0,test -2020-01-29 23:00:00,machine-1-1_y_6,0.247646,0.0,test -2020-01-30 00:00:00,machine-1-1_y_6,0.258945,0.0,test -2020-01-30 01:00:00,machine-1-1_y_6,0.246704,0.0,test -2020-01-30 02:00:00,machine-1-1_y_6,0.246704,0.0,test -2020-01-30 03:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-01-30 04:00:00,machine-1-1_y_6,0.246704,0.0,test -2020-01-30 05:00:00,machine-1-1_y_6,0.250471,0.0,test -2020-01-30 06:00:00,machine-1-1_y_6,0.26177,0.0,test -2020-01-30 07:00:00,machine-1-1_y_6,0.260829,0.0,test -2020-01-30 08:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-01-30 09:00:00,machine-1-1_y_6,0.351224,0.0,test -2020-01-30 10:00:00,machine-1-1_y_6,0.26742,0.0,test -2020-01-30 11:00:00,machine-1-1_y_6,0.268362,0.0,test -2020-01-30 12:00:00,machine-1-1_y_6,0.244821,0.0,test -2020-01-30 13:00:00,machine-1-1_y_6,0.250471,0.0,test -2020-01-30 14:00:00,machine-1-1_y_6,0.255179,0.0,test -2020-01-30 15:00:00,machine-1-1_y_6,0.255179,0.0,test -2020-01-30 16:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-01-30 17:00:00,machine-1-1_y_6,0.264595,0.0,test -2020-01-30 18:00:00,machine-1-1_y_6,0.270245,0.0,test -2020-01-30 19:00:00,machine-1-1_y_6,0.276836,0.0,test -2020-01-30 20:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-01-30 21:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-30 22:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-01-30 23:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-01-31 00:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-31 01:00:00,machine-1-1_y_6,0.26742,0.0,test -2020-01-31 02:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-01-31 03:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-31 04:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-01-31 05:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-31 06:00:00,machine-1-1_y_6,0.290019,0.0,test -2020-01-31 07:00:00,machine-1-1_y_6,0.313559,0.0,test -2020-01-31 08:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-01-31 09:00:00,machine-1-1_y_6,0.276836,0.0,test -2020-01-31 10:00:00,machine-1-1_y_6,0.262712,0.0,test -2020-01-31 11:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-01-31 12:00:00,machine-1-1_y_6,0.282486,0.0,test -2020-01-31 13:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-01-31 14:00:00,machine-1-1_y_6,0.303202,0.0,test -2020-01-31 15:00:00,machine-1-1_y_6,0.286252,0.0,test -2020-01-31 16:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-01-31 17:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-01-31 18:00:00,machine-1-1_y_6,0.286252,1.0,test -2020-01-31 19:00:00,machine-1-1_y_6,0.293785,1.0,test -2020-01-31 20:00:00,machine-1-1_y_6,0.284369,1.0,test -2020-01-31 21:00:00,machine-1-1_y_6,0.303202,1.0,test -2020-01-31 22:00:00,machine-1-1_y_6,0.286252,1.0,test -2020-01-31 23:00:00,machine-1-1_y_6,0.306968,1.0,test -2020-02-01 00:00:00,machine-1-1_y_6,0.298493,1.0,test -2020-02-01 01:00:00,machine-1-1_y_6,0.380414,1.0,test -2020-02-01 02:00:00,machine-1-1_y_6,0.327684,1.0,test -2020-02-01 03:00:00,machine-1-1_y_6,0.312618,1.0,test -2020-02-01 04:00:00,machine-1-1_y_6,0.285311,0.0,test -2020-02-01 05:00:00,machine-1-1_y_6,0.268362,0.0,test -2020-02-01 06:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-02-01 07:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-02-01 08:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-02-01 09:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-02-01 10:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-02-01 11:00:00,machine-1-1_y_6,0.270245,0.0,test -2020-02-01 12:00:00,machine-1-1_y_6,0.276836,0.0,test -2020-02-01 13:00:00,machine-1-1_y_6,0.265537,1.0,test -2020-02-01 14:00:00,machine-1-1_y_6,0.282486,1.0,test -2020-02-01 15:00:00,machine-1-1_y_6,0.264595,1.0,test -2020-02-01 16:00:00,machine-1-1_y_6,0.283427,1.0,test -2020-02-01 17:00:00,machine-1-1_y_6,0.274011,1.0,test -2020-02-01 18:00:00,machine-1-1_y_6,0.294727,1.0,test -2020-02-01 19:00:00,machine-1-1_y_6,0.314501,1.0,test -2020-02-01 20:00:00,machine-1-1_y_6,0.298493,1.0,test -2020-02-01 21:00:00,machine-1-1_y_6,0.89548,1.0,test -2020-02-01 22:00:00,machine-1-1_y_6,1.0,1.0,test -2020-02-01 23:00:00,machine-1-1_y_6,0.426554,0.0,test -2020-02-02 00:00:00,machine-1-1_y_6,0.437853,0.0,test -2020-02-02 01:00:00,machine-1-1_y_6,0.426554,0.0,test -2020-02-02 02:00:00,machine-1-1_y_6,0.387006,0.0,test -2020-02-02 03:00:00,machine-1-1_y_6,0.369115,0.0,test -2020-02-02 04:00:00,machine-1-1_y_6,0.374765,0.0,test -2020-02-02 05:00:00,machine-1-1_y_6,0.359699,0.0,test -2020-02-02 06:00:00,machine-1-1_y_6,0.365348,0.0,test -2020-02-02 07:00:00,machine-1-1_y_6,0.354991,1.0,test -2020-02-02 08:00:00,machine-1-1_y_6,0.363465,1.0,test -2020-02-02 09:00:00,machine-1-1_y_6,0.349341,1.0,test -2020-02-02 10:00:00,machine-1-1_y_6,0.36064,1.0,test -2020-02-02 11:00:00,machine-1-1_y_6,0.355932,1.0,test -2020-02-02 12:00:00,machine-1-1_y_6,0.370056,1.0,test -2020-02-02 13:00:00,machine-1-1_y_6,0.380414,1.0,test -2020-02-02 14:00:00,machine-1-1_y_6,0.391714,1.0,test -2020-02-02 15:00:00,machine-1-1_y_6,0.361582,1.0,test -2020-02-02 16:00:00,machine-1-1_y_6,0.332392,0.0,test -2020-02-02 17:00:00,machine-1-1_y_6,0.336158,0.0,test -2020-02-02 18:00:00,machine-1-1_y_6,0.3371,0.0,test -2020-02-02 19:00:00,machine-1-1_y_6,0.336158,0.0,test -2020-02-02 20:00:00,machine-1-1_y_6,0.335217,0.0,test -2020-02-02 21:00:00,machine-1-1_y_6,0.350282,0.0,test -2020-02-02 22:00:00,machine-1-1_y_6,0.350282,0.0,test -2020-02-02 23:00:00,machine-1-1_y_6,0.368173,0.0,test -2020-02-03 00:00:00,machine-1-1_y_6,0.368173,0.0,test -2020-02-03 01:00:00,machine-1-1_y_6,0.359699,0.0,test -2020-02-03 02:00:00,machine-1-1_y_6,0.370056,0.0,test -2020-02-03 03:00:00,machine-1-1_y_6,0.365348,0.0,test -2020-02-03 04:00:00,machine-1-1_y_6,0.358757,0.0,test -2020-02-03 05:00:00,machine-1-1_y_6,0.362524,1.0,test -2020-02-03 06:00:00,machine-1-1_y_6,0.357815,1.0,test -2020-02-03 07:00:00,machine-1-1_y_6,0.369115,1.0,test -2020-02-03 08:00:00,machine-1-1_y_6,0.355932,1.0,test -2020-02-03 09:00:00,machine-1-1_y_6,0.354991,1.0,test -2020-02-03 10:00:00,machine-1-1_y_6,0.370056,1.0,test -2020-02-03 11:00:00,machine-1-1_y_6,0.368173,1.0,test -2020-02-03 12:00:00,machine-1-1_y_6,0.37194,1.0,test -2020-02-03 13:00:00,machine-1-1_y_6,0.364407,1.0,test -2020-02-03 14:00:00,machine-1-1_y_6,0.361582,1.0,test -2020-02-03 15:00:00,machine-1-1_y_6,0.373823,1.0,test -2020-02-03 16:00:00,machine-1-1_y_6,0.349341,1.0,test -2020-02-03 17:00:00,machine-1-1_y_6,0.356874,1.0,test -2020-02-03 18:00:00,machine-1-1_y_6,0.328625,0.0,test -2020-02-03 19:00:00,machine-1-1_y_6,0.334275,0.0,test -2020-02-03 20:00:00,machine-1-1_y_6,0.330508,0.0,test -2020-02-03 21:00:00,machine-1-1_y_6,0.330508,0.0,test -2020-02-03 22:00:00,machine-1-1_y_6,0.334275,0.0,test -2020-02-03 23:00:00,machine-1-1_y_6,0.089454,0.0,test -2020-02-04 00:00:00,machine-1-1_y_6,0.136535,0.0,test -2020-02-04 01:00:00,machine-1-1_y_6,0.13371,0.0,test -2020-02-04 02:00:00,machine-1-1_y_6,0.150659,0.0,test -2020-02-04 03:00:00,machine-1-1_y_6,0.182674,0.0,test -2020-02-04 04:00:00,machine-1-1_y_6,0.176083,0.0,test -2020-02-04 05:00:00,machine-1-1_y_6,0.199623,1.0,test -2020-02-04 06:00:00,machine-1-1_y_6,0.186441,1.0,test -2020-02-04 07:00:00,machine-1-1_y_6,0.187382,1.0,test -2020-02-04 08:00:00,machine-1-1_y_6,0.19209,1.0,test -2020-02-04 09:00:00,machine-1-1_y_6,0.216573,1.0,test -2020-02-04 10:00:00,machine-1-1_y_6,0.245763,1.0,test -2020-02-04 11:00:00,machine-1-1_y_6,0.258945,1.0,test -2020-02-04 12:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-02-04 13:00:00,machine-1-1_y_6,0.272128,0.0,test -2020-02-04 14:00:00,machine-1-1_y_6,0.258004,0.0,test -2020-02-04 15:00:00,machine-1-1_y_6,0.272128,0.0,test -2020-02-04 16:00:00,machine-1-1_y_6,0.256121,0.0,test -2020-02-04 17:00:00,machine-1-1_y_6,0.265537,0.0,test -2020-02-04 18:00:00,machine-1-1_y_6,0.260829,0.0,test -2020-02-04 19:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-02-04 20:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-02-04 21:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-02-04 22:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-02-04 23:00:00,machine-1-1_y_6,0.263653,0.0,test -2020-02-05 00:00:00,machine-1-1_y_6,0.26177,0.0,test -2020-02-05 01:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-02-05 02:00:00,machine-1-1_y_6,0.26177,0.0,test -2020-02-05 03:00:00,machine-1-1_y_6,0.280603,0.0,test -2020-02-05 04:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-02-05 05:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-02-05 06:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-02-05 07:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-02-05 08:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-02-05 09:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-02-05 10:00:00,machine-1-1_y_6,0.268362,0.0,test -2020-02-05 11:00:00,machine-1-1_y_6,0.265537,0.0,test -2020-02-05 12:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-02-05 13:00:00,machine-1-1_y_6,0.272128,0.0,test -2020-02-05 14:00:00,machine-1-1_y_6,0.268362,0.0,test -2020-02-05 15:00:00,machine-1-1_y_6,0.288136,0.0,test -2020-02-05 16:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-02-05 17:00:00,machine-1-1_y_6,0.276836,0.0,test -2020-02-05 18:00:00,machine-1-1_y_6,0.274011,0.0,test -2020-02-05 19:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-02-05 20:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-02-05 21:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-02-05 22:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-02-05 23:00:00,machine-1-1_y_6,0.289077,0.0,test -2020-02-06 00:00:00,machine-1-1_y_6,0.274011,0.0,test -2020-02-06 01:00:00,machine-1-1_y_6,0.274011,0.0,test -2020-02-06 02:00:00,machine-1-1_y_6,0.291902,0.0,test -2020-02-06 03:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-02-06 04:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-02-06 05:00:00,machine-1-1_y_6,0.301318,0.0,test -2020-02-06 06:00:00,machine-1-1_y_6,0.282486,0.0,test -2020-02-06 07:00:00,machine-1-1_y_6,0.300377,0.0,test -2020-02-06 08:00:00,machine-1-1_y_6,0.279661,0.0,test -2020-02-06 09:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-02-06 10:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-02-06 11:00:00,machine-1-1_y_6,0.26177,0.0,test -2020-02-06 12:00:00,machine-1-1_y_6,0.275895,0.0,test -2020-02-06 13:00:00,machine-1-1_y_6,0.259887,0.0,test -2020-02-06 14:00:00,machine-1-1_y_6,0.271186,0.0,test -2020-02-06 15:00:00,machine-1-1_y_6,0.264595,0.0,test -2020-02-06 16:00:00,machine-1-1_y_6,0.269303,0.0,test -2020-02-06 17:00:00,machine-1-1_y_6,0.27307,0.0,test -2020-02-06 18:00:00,machine-1-1_y_6,0.292844,0.0,test -2020-02-06 19:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-02-06 20:00:00,machine-1-1_y_6,0.293785,0.0,test -2020-02-06 21:00:00,machine-1-1_y_6,0.276836,1.0,test -2020-02-06 22:00:00,machine-1-1_y_6,0.275895,1.0,test -2020-02-06 23:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-02-07 00:00:00,machine-1-1_y_6,0.277778,0.0,test -2020-02-07 01:00:00,machine-1-1_y_6,0.297552,0.0,test -2020-02-07 02:00:00,machine-1-1_y_6,0.278719,0.0,test -2020-02-07 03:00:00,machine-1-1_y_6,0.281544,0.0,test -2020-02-07 04:00:00,machine-1-1_y_6,0.289077,0.0,test -2020-02-07 05:00:00,machine-1-1_y_6,0.287194,0.0,test -2020-02-07 06:00:00,machine-1-1_y_6,0.354049,0.0,test -2020-02-07 07:00:00,machine-1-1_y_6,0.29096,0.0,test -2020-02-07 08:00:00,machine-1-1_y_6,0.286252,0.0,test -2020-02-07 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11:00:00,machine-1-1_y_8,0.04059,0.0,test -2020-01-22 12:00:00,machine-1-1_y_8,0.036758,0.0,test -2020-01-22 13:00:00,machine-1-1_y_8,0.030798,0.0,test -2020-01-22 14:00:00,machine-1-1_y_8,0.029804,0.0,test -2020-01-22 15:00:00,machine-1-1_y_8,0.043429,0.0,test -2020-01-22 16:00:00,machine-1-1_y_8,0.040448,0.0,test -2020-01-22 17:00:00,machine-1-1_y_8,0.038603,0.0,test -2020-01-22 18:00:00,machine-1-1_y_8,0.056628,0.0,test -2020-01-22 19:00:00,machine-1-1_y_8,0.048254,0.0,test -2020-01-22 20:00:00,machine-1-1_y_8,0.047119,0.0,test -2020-01-22 21:00:00,machine-1-1_y_8,0.036475,0.0,test -2020-01-22 22:00:00,machine-1-1_y_8,0.048964,0.0,test -2020-01-22 23:00:00,machine-1-1_y_8,0.018024,0.0,test -2020-01-23 00:00:00,machine-1-1_y_8,0.011212,0.0,test -2020-01-23 01:00:00,machine-1-1_y_8,0.007806,0.0,test -2020-01-23 02:00:00,machine-1-1_y_8,0.005677,0.0,test -2020-01-23 03:00:00,machine-1-1_y_8,0.007522,0.0,test -2020-01-23 04:00:00,machine-1-1_y_8,0.013199,0.0,test -2020-01-23 05:00:00,machine-1-1_y_8,0.025404,0.0,test -2020-01-23 06:00:00,machine-1-1_y_8,0.048538,0.0,test -2020-01-23 07:00:00,machine-1-1_y_8,0.030372,0.0,test -2020-01-23 08:00:00,machine-1-1_y_8,0.023276,0.0,test -2020-01-23 09:00:00,machine-1-1_y_8,0.023559,0.0,test -2020-01-23 10:00:00,machine-1-1_y_8,0.029236,0.0,test -2020-01-23 11:00:00,machine-1-1_y_8,0.034346,0.0,test -2020-01-23 12:00:00,machine-1-1_y_8,0.026114,0.0,test -2020-01-23 13:00:00,machine-1-1_y_8,0.033352,0.0,test -2020-01-23 14:00:00,machine-1-1_y_8,0.033778,0.0,test -2020-01-23 15:00:00,machine-1-1_y_8,0.065995,0.0,test -2020-01-23 16:00:00,machine-1-1_y_8,0.047687,0.0,test -2020-01-23 17:00:00,machine-1-1_y_8,0.031649,0.0,test -2020-01-23 18:00:00,machine-1-1_y_8,0.038036,0.0,test -2020-01-23 19:00:00,machine-1-1_y_8,0.03321,0.0,test -2020-01-23 20:00:00,machine-1-1_y_8,0.033636,0.0,test -2020-01-23 21:00:00,machine-1-1_y_8,0.03832,0.0,test -2020-01-23 22:00:00,machine-1-1_y_8,0.039597,0.0,test -2020-01-23 23:00:00,machine-1-1_y_8,0.01845,0.0,test -2020-01-24 00:00:00,machine-1-1_y_8,0.01178,0.0,test -2020-01-24 01:00:00,machine-1-1_y_8,0.009083,0.0,test -2020-01-24 02:00:00,machine-1-1_y_8,0.00667,0.0,test -2020-01-24 03:00:00,machine-1-1_y_8,0.007948,0.0,test -2020-01-24 04:00:00,machine-1-1_y_8,0.014618,0.0,test -2020-01-24 05:00:00,machine-1-1_y_8,0.038178,0.0,test -2020-01-24 06:00:00,machine-1-1_y_8,0.060318,0.0,test -2020-01-24 07:00:00,machine-1-1_y_8,0.04428,0.0,test -2020-01-24 08:00:00,machine-1-1_y_8,0.035765,0.0,test -2020-01-24 09:00:00,machine-1-1_y_8,0.062021,0.0,test -2020-01-24 10:00:00,machine-1-1_y_8,0.034346,0.0,test -2020-01-24 11:00:00,machine-1-1_y_8,0.051235,0.0,test -2020-01-24 12:00:00,machine-1-1_y_8,0.034204,0.0,test -2020-01-24 13:00:00,machine-1-1_y_8,0.038745,0.0,test -2020-01-24 14:00:00,machine-1-1_y_8,0.028953,0.0,test -2020-01-24 15:00:00,machine-1-1_y_8,0.04499,0.0,test -2020-01-24 16:00:00,machine-1-1_y_8,0.042861,0.0,test -2020-01-24 17:00:00,machine-1-1_y_8,0.039455,0.0,test -2020-01-24 18:00:00,machine-1-1_y_8,0.036191,0.0,test -2020-01-24 19:00:00,machine-1-1_y_8,0.043713,0.0,test -2020-01-24 20:00:00,machine-1-1_y_8,0.044848,0.0,test -2020-01-24 21:00:00,machine-1-1_y_8,0.038887,0.0,test -2020-01-24 22:00:00,machine-1-1_y_8,0.028527,0.0,test -2020-01-24 23:00:00,machine-1-1_y_8,0.020295,0.0,test -2020-01-25 00:00:00,machine-1-1_y_8,0.014051,0.0,test -2020-01-25 01:00:00,machine-1-1_y_8,0.01547,0.0,test -2020-01-25 02:00:00,machine-1-1_y_8,0.159665,0.0,test -2020-01-25 03:00:00,machine-1-1_y_8,0.007522,0.0,test -2020-01-25 04:00:00,machine-1-1_y_8,0.014334,0.0,test -2020-01-25 05:00:00,machine-1-1_y_8,0.028953,0.0,test -2020-01-25 06:00:00,machine-1-1_y_8,0.043429,0.0,test -2020-01-25 07:00:00,machine-1-1_y_8,0.045984,0.0,test -2020-01-25 08:00:00,machine-1-1_y_8,0.048396,0.0,test -2020-01-25 09:00:00,machine-1-1_y_8,0.035623,0.0,test -2020-01-25 10:00:00,machine-1-1_y_8,0.035765,0.0,test -2020-01-25 11:00:00,machine-1-1_y_8,0.038178,0.0,test -2020-01-25 12:00:00,machine-1-1_y_8,0.033352,0.0,test -2020-01-25 13:00:00,machine-1-1_y_8,0.030656,0.0,test -2020-01-25 14:00:00,machine-1-1_y_8,0.027533,0.0,test -2020-01-25 15:00:00,machine-1-1_y_8,0.048396,0.0,test -2020-01-25 16:00:00,machine-1-1_y_8,0.040307,0.0,test -2020-01-25 17:00:00,machine-1-1_y_8,0.043287,0.0,test -2020-01-25 18:00:00,machine-1-1_y_8,0.048254,0.0,test -2020-01-25 19:00:00,machine-1-1_y_8,0.040874,0.0,test -2020-01-25 20:00:00,machine-1-1_y_8,0.047119,0.0,test -2020-01-25 21:00:00,machine-1-1_y_8,0.041584,0.0,test -2020-01-25 22:00:00,machine-1-1_y_8,0.02952,0.0,test -2020-01-25 23:00:00,machine-1-1_y_8,0.021289,0.0,test -2020-01-26 00:00:00,machine-1-1_y_8,0.014618,0.0,test -2020-01-26 01:00:00,machine-1-1_y_8,0.061879,0.0,test -2020-01-26 02:00:00,machine-1-1_y_8,0.008374,0.0,test -2020-01-26 03:00:00,machine-1-1_y_8,0.007664,0.0,test -2020-01-26 04:00:00,machine-1-1_y_8,0.012915,0.0,test -2020-01-26 05:00:00,machine-1-1_y_8,0.026114,0.0,test -2020-01-26 06:00:00,machine-1-1_y_8,0.047687,0.0,test -2020-01-26 07:00:00,machine-1-1_y_8,0.06855,0.0,test -2020-01-26 08:00:00,machine-1-1_y_8,0.030798,0.0,test -2020-01-26 09:00:00,machine-1-1_y_8,0.030656,0.0,test -2020-01-26 10:00:00,machine-1-1_y_8,0.034913,0.0,test -2020-01-26 11:00:00,machine-1-1_y_8,0.031507,0.0,test -2020-01-26 12:00:00,machine-1-1_y_8,0.023843,0.0,test -2020-01-26 13:00:00,machine-1-1_y_8,0.028669,0.0,test -2020-01-26 14:00:00,machine-1-1_y_8,0.036049,0.0,test -2020-01-26 15:00:00,machine-1-1_y_8,0.073375,0.0,test -2020-01-26 16:00:00,machine-1-1_y_8,0.061453,0.0,test -2020-01-26 17:00:00,machine-1-1_y_8,0.051377,0.0,test -2020-01-26 18:00:00,machine-1-1_y_8,0.053931,0.0,test -2020-01-26 19:00:00,machine-1-1_y_8,0.05237,0.0,test -2020-01-26 20:00:00,machine-1-1_y_8,0.052086,0.0,test -2020-01-26 21:00:00,machine-1-1_y_8,0.031081,0.0,test -2020-01-26 22:00:00,machine-1-1_y_8,0.022282,0.0,test -2020-01-26 23:00:00,machine-1-1_y_8,0.021147,0.0,test -2020-01-27 00:00:00,machine-1-1_y_8,0.014476,0.0,test -2020-01-27 01:00:00,machine-1-1_y_8,0.008657,0.0,test -2020-01-27 02:00:00,machine-1-1_y_8,0.007664,0.0,test -2020-01-27 03:00:00,machine-1-1_y_8,0.008799,0.0,test -2020-01-27 04:00:00,machine-1-1_y_8,0.013483,0.0,test -2020-01-27 05:00:00,machine-1-1_y_8,0.024695,0.0,test -2020-01-27 06:00:00,machine-1-1_y_8,0.040307,0.0,test -2020-01-27 07:00:00,machine-1-1_y_8,0.066137,0.0,test -2020-01-27 08:00:00,machine-1-1_y_8,0.041016,0.0,test -2020-01-27 09:00:00,machine-1-1_y_8,0.028669,0.0,test -2020-01-27 10:00:00,machine-1-1_y_8,0.032643,0.0,test -2020-01-27 11:00:00,machine-1-1_y_8,0.053931,0.0,test -2020-01-27 12:00:00,machine-1-1_y_8,0.031365,0.0,test -2020-01-27 13:00:00,machine-1-1_y_8,0.032075,0.0,test -2020-01-27 14:00:00,machine-1-1_y_8,0.033778,0.0,test -2020-01-27 15:00:00,machine-1-1_y_8,0.046977,0.0,test -2020-01-27 16:00:00,machine-1-1_y_8,0.038745,0.0,test -2020-01-27 17:00:00,machine-1-1_y_8,0.038887,0.0,test -2020-01-27 18:00:00,machine-1-1_y_8,0.039597,0.0,test -2020-01-27 19:00:00,machine-1-1_y_8,0.040165,0.0,test -2020-01-27 20:00:00,machine-1-1_y_8,0.039597,0.0,test -2020-01-27 21:00:00,machine-1-1_y_8,0.030514,0.0,test -2020-01-27 22:00:00,machine-1-1_y_8,0.021714,0.0,test -2020-01-27 23:00:00,machine-1-1_y_8,0.019018,0.0,test -2020-01-28 00:00:00,machine-1-1_y_8,0.01178,0.0,test -2020-01-28 01:00:00,machine-1-1_y_8,0.008515,0.0,test -2020-01-28 02:00:00,machine-1-1_y_8,0.00667,0.0,test -2020-01-28 03:00:00,machine-1-1_y_8,0.00809,0.0,test -2020-01-28 04:00:00,machine-1-1_y_8,0.013625,0.0,test -2020-01-28 05:00:00,machine-1-1_y_8,0.026824,0.0,test -2020-01-28 06:00:00,machine-1-1_y_8,0.042435,0.0,test -2020-01-28 07:00:00,machine-1-1_y_8,0.043429,0.0,test -2020-01-28 08:00:00,machine-1-1_y_8,0.02654,0.0,test -2020-01-28 09:00:00,machine-1-1_y_8,0.042435,0.0,test -2020-01-28 10:00:00,machine-1-1_y_8,0.039029,0.0,test -2020-01-28 11:00:00,machine-1-1_y_8,0.039739,0.0,test -2020-01-28 12:00:00,machine-1-1_y_8,0.022992,0.0,test -2020-01-28 13:00:00,machine-1-1_y_8,0.022992,0.0,test -2020-01-28 14:00:00,machine-1-1_y_8,0.033778,0.0,test -2020-01-28 15:00:00,machine-1-1_y_8,0.041584,0.0,test -2020-01-28 16:00:00,machine-1-1_y_8,0.0369,0.0,test -2020-01-28 17:00:00,machine-1-1_y_8,0.040023,0.0,test -2020-01-28 18:00:00,machine-1-1_y_8,0.051235,0.0,test -2020-01-28 19:00:00,machine-1-1_y_8,0.054215,0.0,test -2020-01-28 20:00:00,machine-1-1_y_8,0.048538,0.0,test -2020-01-28 21:00:00,machine-1-1_y_8,0.042152,0.0,test -2020-01-28 22:00:00,machine-1-1_y_8,0.031081,0.0,test -2020-01-28 23:00:00,machine-1-1_y_8,0.021289,0.0,test -2020-01-29 00:00:00,machine-1-1_y_8,0.012206,0.0,test -2020-01-29 01:00:00,machine-1-1_y_8,0.009225,0.0,test -2020-01-29 02:00:00,machine-1-1_y_8,0.006812,0.0,test -2020-01-29 03:00:00,machine-1-1_y_8,0.008941,0.0,test -2020-01-29 04:00:00,machine-1-1_y_8,0.013909,0.0,test -2020-01-29 05:00:00,machine-1-1_y_8,0.02725,0.0,test -2020-01-29 06:00:00,machine-1-1_y_8,0.04868,0.0,test -2020-01-29 07:00:00,machine-1-1_y_8,0.070253,0.0,test -2020-01-29 08:00:00,machine-1-1_y_8,0.042861,0.0,test -2020-01-29 09:00:00,machine-1-1_y_8,0.046125,0.0,test -2020-01-29 10:00:00,machine-1-1_y_8,0.105734,0.0,test -2020-01-29 11:00:00,machine-1-1_y_8,0.046693,0.0,test -2020-01-29 12:00:00,machine-1-1_y_8,0.040165,0.0,test -2020-01-29 13:00:00,machine-1-1_y_8,0.027108,0.0,test -2020-01-29 14:00:00,machine-1-1_y_8,0.031507,0.0,test -2020-01-29 15:00:00,machine-1-1_y_8,0.059324,0.0,test -2020-01-29 16:00:00,machine-1-1_y_8,0.068691,0.0,test -2020-01-29 17:00:00,machine-1-1_y_8,0.046693,0.0,test -2020-01-29 18:00:00,machine-1-1_y_8,0.043997,0.0,test -2020-01-29 19:00:00,machine-1-1_y_8,0.041726,0.0,test -2020-01-29 20:00:00,machine-1-1_y_8,0.048396,0.0,test -2020-01-29 21:00:00,machine-1-1_y_8,0.049957,0.0,test -2020-01-29 22:00:00,machine-1-1_y_8,0.026824,0.0,test -2020-01-29 23:00:00,machine-1-1_y_8,0.020863,0.0,test -2020-01-30 00:00:00,machine-1-1_y_8,0.012347,0.0,test -2020-01-30 01:00:00,machine-1-1_y_8,0.01107,0.0,test -2020-01-30 02:00:00,machine-1-1_y_8,0.008799,0.0,test -2020-01-30 03:00:00,machine-1-1_y_8,0.009367,0.0,test -2020-01-30 04:00:00,machine-1-1_y_8,0.013909,0.0,test -2020-01-30 05:00:00,machine-1-1_y_8,0.02583,0.0,test -2020-01-30 06:00:00,machine-1-1_y_8,0.069401,0.0,test -2020-01-30 07:00:00,machine-1-1_y_8,0.057479,0.0,test -2020-01-30 08:00:00,machine-1-1_y_8,0.0457,0.0,test -2020-01-30 09:00:00,machine-1-1_y_8,0.046693,0.0,test -2020-01-30 10:00:00,machine-1-1_y_8,0.032501,0.0,test -2020-01-30 11:00:00,machine-1-1_y_8,0.036333,0.0,test -2020-01-30 12:00:00,machine-1-1_y_8,0.027108,0.0,test -2020-01-30 13:00:00,machine-1-1_y_8,0.022424,0.0,test -2020-01-30 14:00:00,machine-1-1_y_8,0.020153,0.0,test -2020-01-30 15:00:00,machine-1-1_y_8,0.04868,0.0,test -2020-01-30 16:00:00,machine-1-1_y_8,0.040874,0.0,test -2020-01-30 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02:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-25 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-25 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-25 05:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-25 06:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-25 07:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-25 08:00:00,machine-1-1_y_9,0.000855,0.0,test -2020-01-25 09:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-25 10:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-25 11:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-25 12:00:00,machine-1-1_y_9,0.002589,0.0,test -2020-01-25 13:00:00,machine-1-1_y_9,0.002589,0.0,test -2020-01-25 14:00:00,machine-1-1_y_9,0.003823,0.0,test -2020-01-25 15:00:00,machine-1-1_y_9,0.002602,0.0,test -2020-01-25 16:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-25 17:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-25 18:00:00,machine-1-1_y_9,0.003457,0.0,test -2020-01-25 19:00:00,machine-1-1_y_9,0.002846,0.0,test -2020-01-25 20:00:00,machine-1-1_y_9,0.003957,0.0,test -2020-01-25 21:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-25 22:00:00,machine-1-1_y_9,0.016403,0.0,test -2020-01-25 23:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-26 00:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-26 01:00:00,machine-1-1_y_9,0.078083,0.0,test -2020-01-26 02:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-26 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-26 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-26 05:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-26 06:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-26 07:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-26 08:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-26 09:00:00,machine-1-1_y_9,0.001234,0.0,test -2020-01-26 10:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-26 11:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-26 12:00:00,machine-1-1_y_9,0.002956,0.0,test -2020-01-26 13:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-26 14:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-26 15:00:00,machine-1-1_y_9,0.002235,0.0,test -2020-01-26 16:00:00,machine-1-1_y_9,0.032684,0.0,test -2020-01-26 17:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-26 18:00:00,machine-1-1_y_9,0.002711,0.0,test -2020-01-26 19:00:00,machine-1-1_y_9,0.000855,0.0,test -2020-01-26 20:00:00,machine-1-1_y_9,0.002846,0.0,test -2020-01-26 21:00:00,machine-1-1_y_9,0.002846,0.0,test -2020-01-26 22:00:00,machine-1-1_y_9,0.016159,0.0,test -2020-01-26 23:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-27 00:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-27 01:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-27 02:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-27 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-27 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-27 05:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-27 06:00:00,machine-1-1_y_9,0.001221,0.0,test -2020-01-27 07:00:00,machine-1-1_y_9,0.002211,0.0,test -2020-01-27 08:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-27 09:00:00,machine-1-1_y_9,0.002711,0.0,test -2020-01-27 10:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-27 11:00:00,machine-1-1_y_9,0.003457,0.0,test -2020-01-27 12:00:00,machine-1-1_y_9,0.002834,0.0,test -2020-01-27 13:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-27 14:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-27 15:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-27 16:00:00,machine-1-1_y_9,0.00309,0.0,test -2020-01-27 17:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-27 18:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-27 19:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-27 20:00:00,machine-1-1_y_9,0.002834,0.0,test -2020-01-27 21:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-27 22:00:00,machine-1-1_y_9,0.015793,0.0,test -2020-01-27 23:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-28 00:00:00,machine-1-1_y_9,0.002211,0.0,test -2020-01-28 01:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-28 02:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-28 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-28 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-28 05:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-28 06:00:00,machine-1-1_y_9,0.001478,0.0,test -2020-01-28 07:00:00,machine-1-1_y_9,0.002211,0.0,test -2020-01-28 08:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-28 09:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-28 10:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-28 11:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-28 12:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-28 13:00:00,machine-1-1_y_9,0.001234,0.0,test -2020-01-28 14:00:00,machine-1-1_y_9,0.002589,0.0,test -2020-01-28 15:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-28 16:00:00,machine-1-1_y_9,0.002956,0.0,test -2020-01-28 17:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-28 18:00:00,machine-1-1_y_9,0.002724,0.0,test -2020-01-28 19:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-28 20:00:00,machine-1-1_y_9,0.002846,0.0,test -2020-01-28 21:00:00,machine-1-1_y_9,0.002711,0.0,test -2020-01-28 22:00:00,machine-1-1_y_9,0.016293,0.0,test -2020-01-28 23:00:00,machine-1-1_y_9,0.002455,0.0,test -2020-01-29 00:00:00,machine-1-1_y_9,0.002699,0.0,test -2020-01-29 01:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-29 02:00:00,machine-1-1_y_9,0.002199,0.0,test -2020-01-29 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-29 04:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-29 05:00:00,machine-1-1_y_9,0.000122,0.0,test -2020-01-29 06:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-29 07:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-29 08:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-29 09:00:00,machine-1-1_y_9,0.001356,0.0,test -2020-01-29 10:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-29 11:00:00,machine-1-1_y_9,0.003347,0.0,test -2020-01-29 12:00:00,machine-1-1_y_9,0.002711,0.0,test -2020-01-29 13:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-29 14:00:00,machine-1-1_y_9,0.000977,0.0,test -2020-01-29 15:00:00,machine-1-1_y_9,0.002602,0.0,test -2020-01-29 16:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-29 17:00:00,machine-1-1_y_9,0.002724,0.0,test -2020-01-29 18:00:00,machine-1-1_y_9,0.001857,0.0,test -2020-01-29 19:00:00,machine-1-1_y_9,0.002589,0.0,test -2020-01-29 20:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-29 21:00:00,machine-1-1_y_9,0.002846,0.0,test -2020-01-29 22:00:00,machine-1-1_y_9,0.016513,0.0,test -2020-01-29 23:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-30 00:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-30 01:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-30 02:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-30 03:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-30 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-30 05:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-30 06:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-30 07:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-30 08:00:00,machine-1-1_y_9,0.000855,0.0,test -2020-01-30 09:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-30 10:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-30 11:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-01-30 12:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-30 13:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-30 14:00:00,machine-1-1_y_9,0.002711,0.0,test -2020-01-30 15:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-30 16:00:00,machine-1-1_y_9,0.002968,0.0,test -2020-01-30 17:00:00,machine-1-1_y_9,0.003334,0.0,test -2020-01-30 18:00:00,machine-1-1_y_9,0.000989,0.0,test -2020-01-30 19:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-30 20:00:00,machine-1-1_y_9,0.002724,0.0,test -2020-01-30 21:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-30 22:00:00,machine-1-1_y_9,0.016403,0.0,test -2020-01-30 23:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-31 00:00:00,machine-1-1_y_9,0.002333,0.0,test -2020-01-31 01:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-31 02:00:00,machine-1-1_y_9,0.000855,0.0,test -2020-01-31 03:00:00,machine-1-1_y_9,0.00171,0.0,test -2020-01-31 04:00:00,machine-1-1_y_9,0.000244,0.0,test -2020-01-31 05:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-31 06:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-31 07:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-01-31 08:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-31 09:00:00,machine-1-1_y_9,0.009405,0.0,test -2020-01-31 10:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-01-31 11:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-31 12:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-01-31 13:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-01-31 14:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-01-31 15:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-31 16:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-01-31 17:00:00,machine-1-1_y_9,0.016159,0.0,test -2020-01-31 18:00:00,machine-1-1_y_9,0.002211,1.0,test -2020-01-31 19:00:00,machine-1-1_y_9,0.589674,1.0,test -2020-01-31 20:00:00,machine-1-1_y_9,0.722647,1.0,test -2020-01-31 21:00:00,machine-1-1_y_9,1.0,1.0,test -2020-01-31 22:00:00,machine-1-1_y_9,0.062755,1.0,test -2020-01-31 23:00:00,machine-1-1_y_9,0.043616,1.0,test -2020-02-01 00:00:00,machine-1-1_y_9,0.002467,1.0,test -2020-02-01 01:00:00,machine-1-1_y_9,0.000611,1.0,test -2020-02-01 02:00:00,machine-1-1_y_9,0.050785,1.0,test -2020-02-01 03:00:00,machine-1-1_y_9,0.017967,1.0,test -2020-02-01 04:00:00,machine-1-1_y_9,0.002602,0.0,test -2020-02-01 05:00:00,machine-1-1_y_9,0.000489,0.0,test -2020-02-01 06:00:00,machine-1-1_y_9,0.002602,0.0,test -2020-02-01 07:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-02-01 08:00:00,machine-1-1_y_9,0.002479,0.0,test -2020-02-01 09:00:00,machine-1-1_y_9,0.0016,0.0,test -2020-02-01 10:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-02-01 11:00:00,machine-1-1_y_9,0.017209,0.0,test -2020-02-01 12:00:00,machine-1-1_y_9,0.000366,0.0,test -2020-02-01 13:00:00,machine-1-1_y_9,0.709456,1.0,test -2020-02-01 14:00:00,machine-1-1_y_9,0.399174,1.0,test -2020-02-01 15:00:00,machine-1-1_y_9,0.063598,1.0,test -2020-02-01 16:00:00,machine-1-1_y_9,0.063317,1.0,test -2020-02-01 17:00:00,machine-1-1_y_9,0.555085,1.0,test -2020-02-01 18:00:00,machine-1-1_y_9,0.002724,1.0,test -2020-02-01 19:00:00,machine-1-1_y_9,0.007548,1.0,test -2020-02-01 20:00:00,machine-1-1_y_9,0.000855,1.0,test -2020-02-01 21:00:00,machine-1-1_y_9,0.017881,1.0,test -2020-02-01 22:00:00,machine-1-1_y_9,0.048233,1.0,test -2020-02-01 23:00:00,machine-1-1_y_9,0.002589,0.0,test -2020-02-02 00:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-02-02 01:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-02-02 02:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-02 03:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-02 04:00:00,machine-1-1_y_9,0.002602,0.0,test -2020-02-02 05:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-02 06:00:00,machine-1-1_y_9,0.016513,0.0,test -2020-02-02 07:00:00,machine-1-1_y_9,0.002211,1.0,test -2020-02-02 08:00:00,machine-1-1_y_9,0.567347,1.0,test -2020-02-02 09:00:00,machine-1-1_y_9,0.206512,1.0,test -2020-02-02 10:00:00,machine-1-1_y_9,0.097186,1.0,test -2020-02-02 11:00:00,machine-1-1_y_9,0.86147,1.0,test -2020-02-02 12:00:00,machine-1-1_y_9,0.001808,1.0,test -2020-02-02 13:00:00,machine-1-1_y_9,0.002602,1.0,test -2020-02-02 14:00:00,machine-1-1_y_9,0.000733,1.0,test -2020-02-02 15:00:00,machine-1-1_y_9,0.000733,1.0,test -2020-02-02 16:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-02 17:00:00,machine-1-1_y_9,0.000611,0.0,test -2020-02-02 18:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-02-02 19:00:00,machine-1-1_y_9,0.002467,0.0,test -2020-02-02 20:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-02-02 21:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-02 22:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-02-02 23:00:00,machine-1-1_y_9,0.002223,0.0,test -2020-02-03 00:00:00,machine-1-1_y_9,0.000733,0.0,test -2020-02-03 01:00:00,machine-1-1_y_9,0.002345,0.0,test -2020-02-03 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-machine-1-1_y_29,2020-02-01 22:15:00,0.044413 From 4291b2a837974f3936205f28b33fb8e9b6a21997 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Wed, 18 Dec 2024 10:24:40 -0500 Subject: [PATCH 36/38] type hint functions --- nbs/src/nixtla_client.ipynb | 11 +++++------ nixtla/nixtla_client.py | 13 ++++--------- 2 files changed, 9 insertions(+), 15 deletions(-) diff --git a/nbs/src/nixtla_client.ipynb b/nbs/src/nixtla_client.ipynb index 247d30d5..33ed5540 100644 --- a/nbs/src/nixtla_client.ipynb +++ b/nbs/src/nixtla_client.ipynb @@ -658,7 +658,7 @@ " new_input_size = input_size\n", " return new_input_size\n", "\n", - "def _extract_target_array(df, target_col) -> np.ndarray:\n", + "def _extract_target_array(df: DataFrame, target_col: str) -> np.ndarray:\n", " # in pandas<2.2 to_numpy can lead to an object array if\n", " # the type is a pandas nullable type, e.g. pd.Float64Dtype\n", " # we thus use the dtype's type as the target dtype\n", @@ -672,9 +672,8 @@ "def _process_exog_features(\n", " processed_data: np.ndarray,\n", " x_cols: list[str],\n", - " hist_exog_list: Optional[list[str]] = None,\n", - " logger: Optional[logging.Logger] = None\n", - "):\n", + " hist_exog_list: Optional[list[str]] = None\n", + ") -> tuple[Optional[np.ndarray], Optional[list[int]]]:\n", " X = None\n", " hist_exog = None\n", " if processed_data.shape[1] > 1:\n", @@ -2033,7 +2032,7 @@ " if processed.sort_idxs is not None:\n", " targets = targets[processed.sort_idxs]\n", " times = times[processed.sort_idxs]\n", - " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list, logger)\n", + " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list)\n", " sizes = np.diff(processed.indptr)\n", " if np.all(sizes <= 6 * detection_size):\n", " logger.warn('Detection size is large. Using the entire series to compute the anomaly threshold...')\n", @@ -2336,7 +2335,7 @@ " processed = _tail(processed, new_input_size)\n", " times = _array_tails(times, orig_indptr, np.diff(processed.indptr))\n", " targets = _array_tails(targets, orig_indptr, np.diff(processed.indptr))\n", - " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list, logger)\n", + " X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list)\n", "\n", " logger.info('Calling Cross Validation Endpoint...')\n", " payload = {\n", diff --git a/nixtla/nixtla_client.py b/nixtla/nixtla_client.py index 077061b2..9f97018a 100644 --- a/nixtla/nixtla_client.py +++ b/nixtla/nixtla_client.py @@ -592,7 +592,7 @@ def _restrict_input_samples(level, input_size, model_horizon, h) -> int: return new_input_size -def _extract_target_array(df, target_col) -> np.ndarray: +def _extract_target_array(df: DataFrame, target_col: str) -> np.ndarray: # in pandas<2.2 to_numpy can lead to an object array if # the type is a pandas nullable type, e.g. pd.Float64Dtype # we thus use the dtype's type as the target dtype @@ -608,8 +608,7 @@ def _process_exog_features( processed_data: np.ndarray, x_cols: list[str], hist_exog_list: Optional[list[str]] = None, - logger: Optional[logging.Logger] = None, -): +) -> tuple[Optional[np.ndarray], Optional[list[int]]]: X = None hist_exog = None if processed_data.shape[1] > 1: @@ -1975,9 +1974,7 @@ def detect_anomalies_online( if processed.sort_idxs is not None: targets = targets[processed.sort_idxs] times = times[processed.sort_idxs] - X, hist_exog = _process_exog_features( - processed.data, x_cols, hist_exog_list, logger - ) + X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list) sizes = np.diff(processed.indptr) if np.all(sizes <= 6 * detection_size): logger.warn( @@ -2286,9 +2283,7 @@ def cross_validation( processed = _tail(processed, new_input_size) times = _array_tails(times, orig_indptr, np.diff(processed.indptr)) targets = _array_tails(targets, orig_indptr, np.diff(processed.indptr)) - X, hist_exog = _process_exog_features( - processed.data, x_cols, hist_exog_list, logger - ) + X, hist_exog = _process_exog_features(processed.data, x_cols, hist_exog_list) logger.info("Calling Cross Validation Endpoint...") payload = { From 0d7815701c4177ecf6acfaf80cc6393481885b51 Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 20 Dec 2024 11:15:47 -0500 Subject: [PATCH 37/38] Change google colab url --- .../historical-anomaly-detection/01_quickstart.ipynb | 2 +- .../historical-anomaly-detection/02_anomaly_exogenous.ipynb | 2 +- .../03_anomaly_detection_date_features.ipynb | 2 +- .../historical-anomaly-detection/04_confidence_levels.ipynb | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb index 6de7820a..46bc5b63 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/01_quickstart.ipynb @@ -73,7 +73,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/anomaly-detection/01_quickstart')" + " colab_badge('docs/capabilities/historical-anomaly-detection/01_quickstart')" ] }, { diff --git a/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb index 0c01bb9d..0f8d46b3 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous.ipynb @@ -73,7 +73,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/anomaly-detection/02_anomaly_exogenous')" + " colab_badge('docs/capabilities/historical-anomaly-detection/02_anomaly_exogenous')" ] }, { diff --git a/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb index 36688a6f..cadb60a3 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features.ipynb @@ -73,7 +73,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/anomaly-detection/03_anomaly_detection_date_features')" + " colab_badge('docs/capabilities/historical-anomaly-detection/03_anomaly_detection_date_features')" ] }, { diff --git a/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb b/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb index f44fae6a..ea469904 100644 --- a/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb +++ b/nbs/docs/capabilities/historical-anomaly-detection/04_confidence_levels.ipynb @@ -77,7 +77,7 @@ "#| echo: false\n", "if not IN_COLAB:\n", " load_dotenv()\n", - " colab_badge('docs/capabilities/anomaly-detection/04_confidence_levels')" + " colab_badge('docs/capabilities/historical-anomaly-detection/04_confidence_levels')" ] }, { From 0dcdc45ba06f0f1c6ff2e3ffd44fb536e13f0e7d Mon Sep 17 00:00:00 2001 From: marcopeix Date: Fri, 20 Dec 2024 11:27:31 -0500 Subject: [PATCH 38/38] Adjust online anomaly detection tutorials --- .../00_online_anomaly_detection.ipynb | 9 ++++- .../01_quickstart.ipynb | 6 +-- ...te_vs_multivariate_anomaly_detection.ipynb | 40 ------------------- 3 files changed, 10 insertions(+), 45 deletions(-) diff --git a/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb b/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb index ee2f227a..d6729483 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/00_online_anomaly_detection.ipynb @@ -4,14 +4,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Online Anomaly Detection" + "# Online (Real-Time) Anomaly Detection" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Online anomaly detection dynamically identifies anomalies as data streams in, allowing users to specify the number of steps to monitor. This method is well-suited for immediate applications, such as fraud detection, live sensor monitoring, or tracking real-time demand changes. By focusing on recent data and continuously generating forecasts, it enables timely responses to anomalies in critical scenarios.\n", + "Online anomaly detection dynamically identifies anomalies as data streams in, allowing users to specify the number of timestamps to monitor. This method is well-suited for immediate applications, such as fraud detection, live sensor monitoring, or tracking real-time demand changes. By focusing on recent data and continuously generating forecasts, it enables timely responses to anomalies in critical scenarios.\n", "\n", "This section provides various recipes for performing real-time anomaly detection using TimeGPT, offering users the ability to detect outliers and unusual patterns as they emerge, ensuring prompt intervention in time-sensitive situations.\n", "\n", @@ -23,6 +23,11 @@ "\n", "* [Univariate vs. multiseries anomaly detection](https://docs.nixtla.io/docs/capabilities-online-anomaly-detection-univariate_vs_multivariate_anomaly_detection)\n" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] } ], "metadata": {}, diff --git a/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb index a0089e00..cdcb0c88 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/01_quickstart.ipynb @@ -46,7 +46,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to Online Anomaly Detection\n", + "# Introduction to Online (Real-Time) Anomaly Detection\n", "In this notebook, we introduce the `detect_anomalies_online` method. You will learn how to quickly start using this new endpoint and understand its key differences from the historical anomaly detection endpoint. New features include:\n", "* More flexibility and control over the anomaly detection process\n", "* Perform univariate and multivariate anomaly detection\n", @@ -177,7 +177,7 @@ "metadata": {}, "source": [ "## 2. Detect anomalies in real time\n", - "The `detect_anomalies_online` method detect anomalies in a time series leveraging TimeGPT's forecast power. It uses the forecast error in deciding the anomalous step. Therefore, you need to specify and tune the parameters like that of the forecast method. This function will return a dataframe that contains anomaly flags and anomaly score (its absolute value indicates quantifies the abnormality of the value).\n", + "The `detect_anomalies_online` method detect anomalies in a time series leveraging TimeGPT's forecast power. It uses the forecast error in deciding the anomalous step so you can specify and tune the parameters like that of the `forecast` method. This function will return a dataframe that contains anomaly flags and anomaly score (its absolute value quantifies the abnormality of the value).\n", "\n", "To perfom real-time anomaly detection, set the following parameters:\n", "\n", @@ -186,7 +186,7 @@ "- `target_col`: The variable to forecast.\n", "- `h`: Horizon is the number of steps ahead to make forecast.\n", "- `freq`: The frequency of the time series in Pandas format.\n", - "- `level`: The confidence level for anomaly detection, default is 99%\n", + "- `level`: Percentile of scores distribution at which the threshold is set, controlling how strictly anomalies are flagged. Default at 99%.\n", "- `detection_size`: The number of steps to analyze for anomaly at the end of time series." ] }, diff --git a/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb index 7e367c9c..e168c131 100644 --- a/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb +++ b/nbs/docs/capabilities/online-anomaly-detection/03_univariate_vs_multivariate_anomaly_detection.ipynb @@ -309,46 +309,6 @@ "> 📘 In multiseries anomaly detection, error scores from all time series are aggregated at each time step, and a threshold is applied to identify significant deviations. If the aggregated error exceeds the threshold, the time step is flagged as anomalous across all series, capturing system-wide patterns." ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#| echo: false\n", - "filtered_df = anomaly_online_multi[anomaly_online_multi['unique_id'] == 'machine-1-1_y_0']\n", - "threshold = np.percentile(filtered_df['accumulated_anomaly_score'], 95)\n", - "plt.figure(figsize=(12, 3))\n", - "plt.plot(filtered_df['ts'], filtered_df['accumulated_anomaly_score'], label='Score', color='navy', alpha=0.8)\n", - "plt.axhline(y=threshold, color='red', linestyle='--', label='95% Threshold')\n", - "plt.scatter(filtered_df.loc[filtered_df['anomaly'] == 1, 'ts'], \n", - " filtered_df.loc[filtered_df['anomaly'] == 1, 'accumulated_anomaly_score'], \n", - " color='orchid', label='Anomaly Detected', alpha=0.8)\n", - "plt.title(\"Accumulated Anomaly Scores for machine-1-1\", fontsize=10)\n", - "plt.xlabel(\"Timestamp\")\n", - "plt.ylabel(\"Score\")\n", - "plt.legend(labels=['Score', '95% Threshold', 'Anomaly Detected'])\n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "From the figure above, we can see that even though some points fall below the 95% confidence interval, they are still flagged as anomalies because, in other series, a value at the same time step exceeded the threshold." - ] - }, { "cell_type": "markdown", "metadata": {},