Fixing typos and alignments/spacings

cobrawap/pipeline/Snakefile

@@ -14,7 +14,7 @@ temp_config = 'working_config.yaml'
 config_path = Path(get_setting('config_path'))
 output_path = Path(get_setting('output_path'))
 
-configfile: config_path /'configs' / 'config.yaml'
+configfile: config_path / 'configs' / 'config.yaml'
 report: "report.rst"
 
 # Setting the profile

cobrawap/pipeline/stage01_data_entry/scripts/enter_data_template.py

@@ -1,5 +1,5 @@
 """
-Loads a dataset a brings it into the required data representation (using Neo).
+Loads a dataset and brings it into the required data representation (using Neo).
 """
 
 import argparse
@@ -14,55 +14,55 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data", nargs='?', type=Path, required=True,
-                    help="path to input data")
+                 help="path to input data")
 CLI.add_argument("--output", nargs='?', type=Path, required=True,
-                    help="path of output file")
+                 help="path of output file")
 CLI.add_argument("--data_name", nargs='?', type=str, default='None',
-                    help="chosen name of the dataset")
+                 help="chosen name of the dataset")
 CLI.add_argument("--sampling_rate", nargs='?', type=none_or_float,
-                    default=None, help="sampling rate in Hz")
+                 default=None, help="sampling rate in Hz")
 CLI.add_argument("--spatial_scale", nargs='?', type=float, required=True,
-                    help="distance between electrodes or pixels in mm")
+                 help="distance between electrodes or pixels in mm")
 CLI.add_argument("--t_start", nargs='?', type=none_or_float, default=None,
-                    help="start time, in s, delimits the interval of recordings to be analyzed")
+                 help="start time, in s, delimits the interval of recordings to be analyzed")
 CLI.add_argument("--t_stop", nargs='?', type=none_or_float, default=None,
-                    help="stop time, in s, delimits the interval of recordings to be analyzed")
+                 help="stop time, in s, delimits the interval of recordings to be analyzed")
 CLI.add_argument("--orientation_top", nargs='?', type=str, required=True,
-                    help="upward orientation of the recorded cortical region")
+                 help="upward orientation of the recorded cortical region")
 CLI.add_argument("--orientation_right", nargs='?', type=str, required=True,
-                    help="right-facing orientation of the recorded cortical region")
+                 help="right-facing orientation of the recorded cortical region")
 CLI.add_argument("--annotations", nargs='+', type=none_or_str, default=None,
-                    help="metadata of the dataset")
+                 help="metadata of the dataset")
 CLI.add_argument("--array_annotations", nargs='+', type=none_or_str,
-                    default=None, help="channel-wise metadata")
+                 default=None, help="channel-wise metadata")
 CLI.add_argument("--kwargs", nargs='+', type=none_or_str, default=None,
-                    help="additional optional arguments")
+                 help="additional optional arguments")
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()
 
     # Load data with Neo IO or custom loading routine
     block = load_neo(args.data)
     # If there is no Neo IO for the data type available,
-    # the data must be loaded conventioally and added to a newly constructed
+    # the data must be loaded conventionally and added to a newly constructed
     # Neo block. For building a Neo objects, have a look into the documentation
     # https://neo.readthedocs.io/
 
-    # In case the dataset is imagaging data and therefore stored as an
+    # In case the dataset is imaging data and therefore stored as an
     # ImageSequence object, it needs to be transformed into an AnalogSignal
-    # object. To do this use the function imagesequence_to_analogsignal in utils/neo.py
+    # object. To do this use the function imagesequence_to_analogsignal in utils/neo_utils.py
 
     asig = block.segments[0].analogsignals[0]
 
     asig = time_slice(asig, args.t_start, args.t_stop)
 
-    # Add metadata from ANNOTIATION dict
+    # Add metadata from ANNOTATION dict
     asig.annotations.update(parse_string2dict(args.annotations))
     asig.annotations.update(spatial_scale=args.spatial_scale*pq.mm)
     asig.annotations.update(orientation_top=args.orientation_top)
     asig.annotations.update(orientation_right=args.orientation_right)
 
-    # Add metadata from ARRAY_ANNOTIATION dict
+    # Add metadata from ARRAY_ANNOTATION dict
     asig.array_annotations.update(parse_string2dict(args.array_annotations))
 
     # Do custom metadata processing from KWARGS dict (optional)

cobrawap/pipeline/stage01_data_entry/scripts/plot_traces.py

@@ -13,15 +13,15 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data",    nargs='?', type=Path, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--output",  nargs='?', type=Path, required=True,
-                    help="path of output figure")
+                 help="path of output figure")
 CLI.add_argument("--t_start", nargs='?', type=float, default=0,
-                    help="start time in seconds")
+                 help="start time in seconds")
 CLI.add_argument("--t_stop",  nargs='?', type=float, default=10,
-                    help="stop time in seconds")
+                 help="stop time in seconds")
 CLI.add_argument("--channels", nargs='+', type=none_or_int, default=0,
-                    help="list of channels to plot")
+                 help="list of channels to plot")
 
 def plot_traces(asig, channels):
     sns.set(style='ticks', palette="deep", context="notebook")

cobrawap/pipeline/stage02_processing/Snakefile

@@ -122,7 +122,7 @@ use rule template as frequency_filter with:
         params('highpass_frequency', 'lowpass_frequency', 'filter_function',
                 order=config.FILTER_ORDER, config=config)
     output:
-       Path('{dir}') / '{rule_name}' /  f'frequency_filter.{config.NEO_FORMAT}'
+        Path('{dir}') / '{rule_name}' /  f'frequency_filter.{config.NEO_FORMAT}'
 
 
 use rule template as roi_selection with:

cobrawap/pipeline/stage02_processing/configs/config_template.yaml

@@ -44,7 +44,7 @@ RERUN_MODE: True
 #################################
 # No parameters needed
 
-# BLOCK - spatial_smoothig
+# BLOCK - spatial_smoothing
 #################################
 MACRO_PIXEL_DIM: 2
 

cobrawap/pipeline/stage02_processing/scripts/background_subtraction.py

@@ -11,14 +11,14 @@
 from utils.parse import none_or_str
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=Path, required=True,
-                    help="path to input data in neo format")
-CLI.add_argument("--output",  nargs='?', type=Path, required=True,
-                    help="path of output file")
-CLI.add_argument("--output_img",  nargs='?', type=none_or_str,
-                    help="path of output image", default=None)
-CLI.add_argument("--output_array",  nargs='?', type=none_or_str,
-                    help="path of output numpy array", default=None)
+CLI.add_argument("--data", nargs='?', type=Path, required=True,
+                 help="path to input data in neo format")
+CLI.add_argument("--output", nargs='?', type=Path, required=True,
+                 help="path of output file")
+CLI.add_argument("--output_img", nargs='?', type=none_or_str,
+                 help="path of output image", default=None)
+CLI.add_argument("--output_array", nargs='?', type=none_or_str,
+                 help="path of output numpy array", default=None)
 
 def shape_frame(value_array, xy_coords):
     dim_x = np.max(xy_coords[:,0]) + 1

cobrawap/pipeline/stage02_processing/scripts/check_input.py

@@ -11,7 +11,7 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data", nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()

cobrawap/pipeline/stage02_processing/scripts/detrending.py

@@ -13,18 +13,18 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data",    nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--output",  nargs='?', type=str, required=True,
-                    help="path of output file")
+                 help="path of output file")
 CLI.add_argument("--order", nargs='?', type=int, default=1,
-                    help="detrending order")
+                 help="detrending order")
 CLI.add_argument("--img_dir",  nargs='?', type=str, required=True,
-                    help="path of output figure directory")
+                 help="path of output figure directory")
 CLI.add_argument("--img_name", nargs='?', type=str,
-                    default='processed_trace_channel0.png',
-                    help='example filename for channel 0')
+                 default='processed_trace_channel0.png',
+                 help='example filename for channel 0')
 CLI.add_argument("--plot_channels", nargs='+', type=none_or_int, default=None,
-                    help="list of channels to plot")
+                 help="list of channels to plot")
 
 def detrend(asig, order):
     if (order != 0) and (order != 1):
@@ -72,7 +72,7 @@ def plot_detrend(asig, detrend_asig, channel):
         for channel in args.plot_channels:
             plot_detrend(asig, detrend_asig, channel)
             output_path = os.path.join(args.img_dir,
-                                    args.img_name.replace('_channel0', f'_channel{channel}'))
+                                       args.img_name.replace('_channel0', f'_channel{channel}'))
             save_plot(output_path)
 
     detrend_asig.name += ""

cobrawap/pipeline/stage02_processing/scripts/frequency_filter.py

@@ -10,18 +10,18 @@
 from utils.parse import none_or_float
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
-                help="path to input data in neo format")
-CLI.add_argument("--output",  nargs='?', type=str, required=True,
-                help="path of output file")
+CLI.add_argument("--data", nargs='?', type=str, required=True,
+                 help="path to input data in neo format")
+CLI.add_argument("--output", nargs='?', type=str, required=True,
+                 help="path of output file")
 CLI.add_argument("--highpass_frequency", nargs='?', type=none_or_float,
-                default=None, help="lower bound of frequency band in Hz")
+                 default=None, help="lower bound of frequency band in Hz")
 CLI.add_argument("--lowpass_frequency", nargs='?', type=none_or_float,
-                default=None, help="upper bound of frequency band in Hz")
+                 default=None, help="upper bound of frequency band in Hz")
 CLI.add_argument("--order", nargs='?', type=int, default=2,
-                help="order of the filter function")
+                 help="order of the filter function")
 CLI.add_argument("--filter_function", nargs='?', type=str, default='filtfilt',
-                help="filterfunction used in the scipy backend")
+                 help="filter function used in the scipy backend")
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()

cobrawap/pipeline/stage02_processing/scripts/logMUA_estimation.py

@@ -19,30 +19,30 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data", nargs='?', type=Path, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--output", nargs='?', type=Path, required=True,
-                    help="path of output file")
+                 help="path of output file")
 CLI.add_argument("--img_dir", nargs='?', type=Path,
-                    default=None, help="path of figure directory")
+                 default=None, help="path of figure directory")
 CLI.add_argument("--img_name", nargs='?', type=str,
-                    default='minima_channel0.png',
-                    help='example image filename for channel 0')
+                 default='minima_channel0.png',
+                 help='example image filename for channel 0')
 CLI.add_argument("--highpass_frequency", nargs='?', type=float, default=200,
-                    help="lower bound of frequency band in Hz")
+                 help="lower bound of frequency band in Hz")
 CLI.add_argument("--lowpass_frequency", nargs='?', type=float, default=1500,
-                    help="upper bound of frequency band in Hz")
+                 help="upper bound of frequency band in Hz")
 CLI.add_argument("--logMUA_rate", nargs='?', type=none_or_float, default=None,
-                    help="rate of the signal after transformation")
+                 help="rate of the signal after transformation")
 CLI.add_argument("--psd_overlap", nargs='?', type=float, default=0.5,
-                    help="overlap parameter for Welch's algorithm [0-1]")
+                 help="overlap parameter for Welch's algorithm [0-1]")
 CLI.add_argument("--fft_slice", nargs='?', type=none_or_float, default=None,
-                    help="time window length used for power spectrum estimate, in s")
+                 help="time window length used for power spectrum estimate, in s")
 CLI.add_argument("--plot_tstart", nargs='?', type=float, default=0,
-                    help="start time in seconds")
+                 help="start time in seconds")
 CLI.add_argument("--plot_tstop",  nargs='?', type=float, default=10,
-                    help="stop time in seconds")
+                 help="stop time in seconds")
 CLI.add_argument("--plot_channels", nargs='+', type=none_or_int, default=None,
-                    help="list of channels to plot")
+                 help="list of channels to plot")
 
 
 def logMUA_estimation(asig, highpass_frequency, lowpass_frequency, logMUA_rate,
@@ -175,12 +175,12 @@ def plot_logMUA_estimation(asig, logMUA_asig, highpass_frequency, lowpass_freque
     if args.plot_channels is not None:
         for channel in args.plot_channels:
             plot_logMUA_estimation(asig=block.segments[0].analogsignals[0],
-                                logMUA_asig=asig,
-                                highpass_frequency=args.highpass_frequency*pq.Hz,
-                                lowpass_frequency=args.lowpass_frequency*pq.Hz,
-                                t_start=args.plot_tstart,
-                                t_stop=args.plot_tstop,
-                                channel=channel)
+                                   logMUA_asig=asig,
+                                   highpass_frequency=args.highpass_frequency*pq.Hz,
+                                   lowpass_frequency=args.lowpass_frequency*pq.Hz,
+                                   t_start=args.plot_tstart,
+                                   t_stop=args.plot_tstop,
+                                   channel=channel)
             output_path = args.img_dir \
                         / args.img_name.replace('_channel0', f'_channel{channel}')
             save_plot(output_path)

cobrawap/pipeline/stage02_processing/scripts/normalization.py

@@ -11,12 +11,12 @@
 from utils.io_utils import write_neo, load_neo
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
-CLI.add_argument("--output",  nargs='?', type=str, required=True,
-                    help="path of output file")
+CLI.add_argument("--data", nargs='?', type=str, required=True,
+                 help="path to input data in neo format")
+CLI.add_argument("--output", nargs='?', type=str, required=True,
+                 help="path of output file")
 CLI.add_argument("--normalize_by", nargs='?', type=str, default='mean',
-                    help="division factor: 'max', 'mean', or 'median'")
+                 help="division factor: 'max', 'mean', or 'median'")
 
 def normalize(asig, normalize_by):
     if normalize_by == 'median':

cobrawap/pipeline/stage02_processing/scripts/phase_transform.py

@@ -10,9 +10,9 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--data", nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--output", nargs='?', type=str, required=True,
-                    help="path of output file")
+                 help="path of output file")
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()

cobrawap/pipeline/stage02_processing/scripts/plot_power_spectrum.py

@@ -12,18 +12,18 @@
 from utils.parse import none_or_float
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
-CLI.add_argument("--output",  nargs='?', type=str, required=True,
-                    help="path of output figure")
+CLI.add_argument("--data", nargs='?', type=str, required=True,
+                 help="path to input data in neo format")
+CLI.add_argument("--output", nargs='?', type=str, required=True,
+                 help="path of output figure")
 CLI.add_argument("--highpass_frequency", nargs='?', type=none_or_float,
-                    default='None', help="lower bound of frequency band in Hz")
+                 default='None', help="lower bound of frequency band in Hz")
 CLI.add_argument("--lowpass_frequency", nargs='?', type=none_or_float,
-                    default='None', help="upper bound of frequency band in Hz")
+                 default='None', help="upper bound of frequency band in Hz")
 CLI.add_argument("--psd_frequency_resolution", nargs='?', type=float, default=5,
-                    help="frequency resolution of the power spectrum in Hz")
+                 help="frequency resolution of the power spectrum in Hz")
 CLI.add_argument("--psd_overlap", nargs='?', type=float, default=0.5,
-                    help="overlap parameter for Welch's algorithm [0-1]")
+                 help="overlap parameter for Welch's algorithm [0-1]")
 
 def plot_psd(frequencies, psd, highpass_frequency, lowpass_frequency):
     sns.set(style='ticks', palette="deep", context="notebook")

cobrawap/pipeline/stage02_processing/scripts/plot_processed_trace.py

@@ -11,20 +11,20 @@
 
 CLI = argparse.ArgumentParser()
 CLI.add_argument("--original_data", nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--data", nargs='?', type=str, required=True,
-                    help="path to input data in neo format")
+                 help="path to input data in neo format")
 CLI.add_argument("--img_dir",  nargs='?', type=str, required=True,
-                    help="path of output figure directory")
+                 help="path of output figure directory")
 CLI.add_argument("--img_name", nargs='?', type=str,
-                    default='processed_trace_channel0.png',
-                    help='example filename for channel 0')
+                 default='processed_trace_channel0.png',
+                 help='example filename for channel 0')
 CLI.add_argument("--t_start", nargs='?', type=float, default=0,
-                    help="start time in seconds")
+                 help="start time in seconds")
 CLI.add_argument("--t_stop",  nargs='?', type=float, default=10,
-                    help="stop time in seconds")
+                 help="stop time in seconds")
 CLI.add_argument("--channels", nargs='+', type=int, default=0,
-                    help="channel to plot")
+                 help="channel to plot")
 
 def plot_traces(original_asig, processed_asig, channel):
     sns.set(style='ticks', palette="deep", context="notebook")