diff --git a/notebooks/intro-search.ipynb b/notebooks/intro-search.ipynb index 549d0f2..6e743d0 100644 --- a/notebooks/intro-search.ipynb +++ b/notebooks/intro-search.ipynb @@ -65,7 +65,7 @@ } ], "source": [ - "cat = ESGFCatalog(esgf1_indices=\"esgf-node.llnl.gov\")\n", + "cat = ESGFCatalog()\n", "print(cat) # <-- nothing to see here yet" ] }, @@ -78,14 +78,14 @@ "name": "stderr", "output_type": "stream", "text": [ - " Searching indices: 0%| |0/2 [ ?index/s]" + " Searching indices: 0%| |0/1 [ ?index/s]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - " Searching indices: 100%|██████████|2/2 [ 1.02s/index]\n" + " Searching indices: 100%|██████████|1/1 [ 1.92s/index]\n" ] }, { @@ -132,7 +132,7 @@ "name": "stderr", "output_type": "stream", "text": [ - " Searching indices: 100%|██████████|2/2 [ 2.01index/s]" + " Searching indices: 100%|██████████|1/1 [ 1.73s/index]" ] }, { @@ -146,8 +146,8 @@ "source_id [CanESM5]\n", "experiment_id [historical]\n", "member_id [r1i1p1f1]\n", - "table_id [Lmon, Amon]\n", - "variable_id [gpp, tas, pr]\n", + "table_id [Amon, Lmon]\n", + "variable_id [tas, pr, gpp]\n", "grid_label [gn]\n", "dtype: object\n" ] @@ -193,8 +193,15 @@ "name": "stderr", "output_type": "stream", "text": [ - " Obtaining file info: 100%|██████████|3/3 [ 1.49s/dataset]\n", - "Adding cell measures: 100%|██████████|3/3 [ 4.15s/dataset]\n" + " Obtaining file info: 0%| |0/3 [ ?dataset/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " Obtaining file info: 100%|██████████|3/3 [ 1.23s/dataset]\n", + "Adding cell measures: 100%|██████████|3/3 [ 3.00s/dataset]\n" ] } ], @@ -648,14 +655,14 @@ " variant_label: r1i1p1f1\n", " version: v20190429\n", " license: CMIP6 model data produced by The Government ...\n", - " cmor_version: 3.4.0
array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n", + " cmor_version: 3.4.0
array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n", " ...,\n", " cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n", - " dtype=object)
array([-87.863799, -85.096527, -82.312913, -79.525607, -76.7369 , -73.947515,\n", + " dtype=object)
array([-87.863799, -85.096527, -82.312913, -79.525607, -76.7369 , -73.947515,\n", " -71.157752, -68.367756, -65.577607, -62.787352, -59.99702 , -57.206632,\n", " -54.4162 , -51.625734, -48.835241, -46.044727, -43.254195, -40.463648,\n", " -37.67309 , -34.882521, -32.091944, -29.30136 , -26.510769, -23.720174,\n", @@ -665,7 +672,7 @@ " 29.30136 , 32.091944, 34.882521, 37.67309 , 40.463648, 43.254195,\n", " 46.044727, 48.835241, 51.625734, 54.4162 , 57.206632, 59.99702 ,\n", " 62.787352, 65.577607, 68.367756, 71.157752, 73.947515, 76.7369 ,\n", - " 79.525607, 82.312913, 85.096527, 87.863799])
array([ 0. , 2.8125, 5.625 , 8.4375, 11.25 , 14.0625, 16.875 ,\n", + " 79.525607, 82.312913, 85.096527, 87.863799])
array([ 0. , 2.8125, 5.625 , 8.4375, 11.25 , 14.0625, 16.875 ,\n", " 19.6875, 22.5 , 25.3125, 28.125 , 30.9375, 33.75 , 36.5625,\n", " 39.375 , 42.1875, 45. , 47.8125, 50.625 , 53.4375, 56.25 ,\n", " 59.0625, 61.875 , 64.6875, 67.5 , 70.3125, 73.125 , 75.9375,\n", @@ -683,7 +690,7 @@ " 295.3125, 298.125 , 300.9375, 303.75 , 306.5625, 309.375 , 312.1875,\n", " 315. , 317.8125, 320.625 , 323.4375, 326.25 , 329.0625, 331.875 ,\n", " 334.6875, 337.5 , 340.3125, 343.125 , 345.9375, 348.75 , 351.5625,\n", - " 354.375 , 357.1875])
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[256 values with dtype=float64]
[16220160 values with dtype=float32]
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PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n", + " 354.375 , 357.1875])
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PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n", " 1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n", " 1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n", " 1850-10-16 12:00:00,\n", @@ -692,7 +699,7 @@ " 2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,\n", " 2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,\n", " 2014-12-16 12:00:00],\n", - " dtype='object', length=1980, calendar='noleap', freq='None'))
PandasIndex(Float64Index([ -87.86379883923273, -85.09652698831745, -82.31291294788636,\n", + " dtype='object', length=1980, calendar='noleap', freq='None'))
PandasIndex(Float64Index([ -87.86379883923273, -85.09652698831745, -82.31291294788636,\n", " -79.52560657265951, -76.7368996803684, -73.94751515398974,\n", " -71.15775201158739, -68.36775610831324, -65.57760701082788,\n", " -62.78735179896313, -59.997020108491355, -57.2066315276433,\n", @@ -714,12 +721,12 @@ " 71.15775201158739, 73.94751515398974, 76.7368996803684,\n", " 79.52560657265951, 82.31291294788636, 85.09652698831745,\n", " 87.86379883923273],\n", - " dtype='float64', name='lat'))
PandasIndex(Float64Index([ 0.0, 2.8125, 5.625, 8.4375, 11.25, 14.0625,\n", + " dtype='float64', name='lat'))
PandasIndex(Float64Index([ 0.0, 2.8125, 5.625, 8.4375, 11.25, 14.0625,\n", " 16.875, 19.6875, 22.5, 25.3125,\n", " ...\n", " 331.875, 334.6875, 337.5, 340.3125, 343.125, 345.9375,\n", " 348.75, 351.5625, 354.375, 357.1875],\n", - " dtype='float64', name='lon', length=128))
array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n", + " cmor_version: 3.4.0
array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n", " ...,\n", " cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n", " cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n", - " dtype=object)
array([-87.863799, -85.096527, -82.312913, -79.525607, -76.7369 , -73.947515,\n", + " dtype=object)
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array([ 0. , 2.8125, 5.625 , 8.4375, 11.25 , 14.0625, 16.875 ,\n", + " 79.525607, 82.312913, 85.096527, 87.863799])
array([ 0. , 2.8125, 5.625 , 8.4375, 11.25 , 14.0625, 16.875 ,\n", " 19.6875, 22.5 , 25.3125, 28.125 , 30.9375, 33.75 , 36.5625,\n", " 39.375 , 42.1875, 45. , 47.8125, 50.625 , 53.4375, 56.25 ,\n", " 59.0625, 61.875 , 64.6875, 67.5 , 70.3125, 73.125 , 75.9375,\n", @@ -1211,7 +1218,7 @@ " 295.3125, 298.125 , 300.9375, 303.75 , 306.5625, 309.375 , 312.1875,\n", " 315. , 317.8125, 320.625 , 323.4375, 326.25 , 329.0625, 331.875 ,\n", " 334.6875, 337.5 , 340.3125, 343.125 , 345.9375, 348.75 , 351.5625,\n", - " 354.375 , 357.1875])
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PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n", + " 354.375 , 357.1875])
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PandasIndex(Float64Index([ -87.86379883923273, -85.09652698831745, -82.31291294788636,\n", + " dtype='object', length=1980, calendar='noleap', freq='None'))
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PandasIndex(Float64Index([ 0.0, 2.8125, 5.625, 8.4375, 11.25, 14.0625,\n", + " dtype='float64', name='lat'))
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