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
@@ -44,25 +44,25 @@
     # 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/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

@@ -11,13 +11,13 @@
 from utils.parse import none_or_str
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=Path, required=True,
+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,
+CLI.add_argument("--output", nargs='?', type=Path, required=True,
                     help="path of output file")
-CLI.add_argument("--output_img",  nargs='?', type=none_or_str,
+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,
+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):

cobrawap/pipeline/stage02_processing/scripts/detrending.py

@@ -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="filterfunction used in the scipy backend")
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()

cobrawap/pipeline/stage02_processing/scripts/logMUA_estimation.py

@@ -175,14 +175,13 @@ 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)
-            output_path = args.img_dir \
-                        / args.img_name.replace('_channel0', f'_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)
 
     asig.name += ""

cobrawap/pipeline/stage02_processing/scripts/normalization.py

@@ -11,9 +11,9 @@
 from utils.io_utils import write_neo, load_neo
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
+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,
+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'")

cobrawap/pipeline/stage02_processing/scripts/plot_power_spectrum.py

@@ -12,9 +12,9 @@
 from utils.parse import none_or_float
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
+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,
+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")

cobrawap/pipeline/stage02_processing/scripts/roi_selection.py

@@ -14,11 +14,11 @@
 from utils.neo_utils import analogsignal_to_imagesequence, imagesequence_to_analogsignal
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
+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,
+CLI.add_argument("--output", nargs='?', type=str, required=True,
                     help="path of output file")
-CLI.add_argument("--output_img",  nargs='?', type=none_or_str,
+CLI.add_argument("--output_img", nargs='?', type=none_or_str,
                     help="path of output image", default=None)
 CLI.add_argument("--intensity_threshold", nargs='?', type=float,
                     help="threshold for mask [0,1]", default=0.5)
@@ -125,7 +125,7 @@ def plot_roi(img, contour):
     ax.axis('image')
     ax.set_xticks([])
     ax.set_yticks([])
-    ax.plot(contour[:, 0], contour[:, 1], linewidth=2)
+    ax.plot(contour[:,0], contour[:,1], linewidth=2)
     plt.draw()
     return ax
 

cobrawap/pipeline/stage02_processing/scripts/spatial_downsampling.py

@@ -13,13 +13,13 @@
 from utils.neo_utils import analogsignal_to_imagesequence, imagesequence_to_analogsignal
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
+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,
+CLI.add_argument("--output", nargs='?', type=str, required=True,
                     help="path of output file")
-CLI.add_argument("--output_img",  nargs='?', type=none_or_str,
+CLI.add_argument("--output_img", nargs='?', type=none_or_str,
                     help="path of output image", default=None)
-CLI.add_argument("--macro_pixel_dim",  nargs='?', type=int,
+CLI.add_argument("--macro_pixel_dim", nargs='?', type=int,
                     help="smoothing factor", default=2)
 
 def spatial_smoothing(imgseq, macro_pixel_dim):

cobrawap/pipeline/stage02_processing/scripts/subsampling.py

@@ -11,9 +11,9 @@
 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,
+CLI.add_argument("--output", nargs='?', type=str, required=True,
                     help="path of output file")
-CLI.add_argument("--target_rate",  nargs='?', type=float, required=True,
+CLI.add_argument("--target_rate", nargs='?', type=float, required=True,
                     help="rate to subsample to in Hz")
 
 if __name__ == '__main__':

cobrawap/pipeline/stage02_processing/scripts/z_score.py

@@ -10,7 +10,7 @@
 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,
+CLI.add_argument("--output", nargs='?', type=Path, required=True,
                     help="path of output file")
 
 if __name__ == '__main__':

cobrawap/pipeline/stage03_trigger_detection/Snakefile

@@ -1,4 +1,4 @@
-""" 
+"""
 # Stage 03 Trigger Detection
 """
 
@@ -13,7 +13,7 @@ def filtered_triggers(wildcards):
     return prev_rule_output(wildcards, rule_list=config.TRIGGER_FILTER,
                             default_input=default_input)
 
-#### UTILTY BLOCKS ####
+#### UTILITY BLOCKS ####
 
 use rule template_all as all with:
     input:
@@ -102,6 +102,7 @@ use rule template as minima with:
                'plot_channels', 'plot_tstart', 'plot_tstop',
                 img_name='minima_channel0.'+config.PLOT_FORMAT, config=config)
 
+
 #### FILTER BLOCKS (choose any) ####
 
 use rule template as remove_short_states with:
@@ -112,4 +113,4 @@ use rule template as remove_short_states with:
         Path('{dir}') / '{rule_name}' / f'remove_short_states.{config.NEO_FORMAT}'
     params:
         params('min_up_duration', 'min_down_duration', 'remove_down_first', 
-                config=config)
+                config=config)

cobrawap/pipeline/stage03_trigger_detection/scripts/calc_thresholds_fitted.py

@@ -1,4 +1,4 @@
-"""w
+"""
 Determine the threshold between Up and Down states for each channel
 by fitting the respective amplitude distributions.
 """
@@ -153,4 +153,4 @@ def fit_amplitude_distribution(signal, sigma_factor, fit_function,
                                        args.img_name.replace('_channel0', f'_channel{channel}'))
             save_plot(output_path)
 
-    np.save(args.output, thresholds)
+    np.save(args.output, thresholds)

cobrawap/pipeline/stage03_trigger_detection/scripts/check_input.py

@@ -10,7 +10,7 @@
 from utils.io_utils import load_neo
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--data",    nargs='?', type=str, required=True,
+CLI.add_argument("--data", nargs='?', type=str, required=True,
                     help="path to input data in neo format")
 
 if __name__ == '__main__':

cobrawap/pipeline/stage03_trigger_detection/scripts/hilbert_phase.py

@@ -1,4 +1,4 @@
-"""w
+"""
 Detect trigger times (i.e., state transition / local wavefronts onsets) 
 by finding crossing of a set phase-value in the channel signals.
 """

cobrawap/pipeline/stage04_wave_detection/Snakefile

@@ -40,7 +40,7 @@ rule merge_wave_definitions:
 use rule template_plus_plot_script as trigger_clustering with:
     input:
         data = config.STAGE_INPUT,
-        script = SCRIPTS  / 'trigger_clustering.py',
+        script = SCRIPTS / 'trigger_clustering.py',
         plot_script = SCRIPTS / 'plot_clustering.py'
     params:
         params('metric', 'time_space_ratio', 'neighbour_distance',
@@ -71,7 +71,7 @@ use rule template_plus_plot_script as critical_points with:
         script = SCRIPTS / 'critical_points.py',
         plot_script = SCRIPTS / 'plot_critical_points.py',
     params:
-        params(frame_id = 0, skip_step = 1)
+        params(frame_id=0, skip_step=1)
     output:
         Path('{dir}') / 'critical_points' / f'critical_points.{config.NEO_FORMAT}',
         img = Path('{dir}') / 'critical_points' / f'critical_points.{config.PLOT_FORMAT}'
@@ -112,7 +112,7 @@ use rule template as plot_waves with:
     params:
         params(time_window = 0.4,  # in s
                colormap='viridis',
-               img_name = 'wave_plot_id0.'+config.PLOT_FORMAT)
+               img_name='wave_plot_id0.'+config.PLOT_FORMAT)
     output:
         directory(Path('{dir}') / 'wave_plots')
 
@@ -135,9 +135,9 @@ use rule template as plot_movie_frames with:
         script = SCRIPTS / 'plot_movie_frames.py'
     params:
         params('colormap', 'frame_rate', 'marker_color', 'plot_event',
-                config=config, frame_name='frame', frame_format='png')
+               config=config, frame_name='frame', frame_format='png')
     output:
-        frame_folder = directory(Path('{dir}') / '{data_name}_frames'),
+        frame_folder = directory(Path('{dir}') / '{data_name}_frames')
 
 
 rule plot_movie:

cobrawap/pipeline/stage04_wave_detection/configs/config_template.yaml

@@ -24,7 +24,7 @@ PLOT_CHANNELS: 'None'  # int or None. default 'None' -> randomly selected
 PLOT_FORMAT: 'png'
 
 
-# DETECTIION BLOCK
+# DETECTION BLOCK
 ##################
 # Available Blocks: 'trigger_clustering'
 DETECTION_BLOCK: 'trigger_clustering'

cobrawap/pipeline/stage04_wave_detection/scripts/check_input.py

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

cobrawap/pipeline/stage04_wave_detection/scripts/merge_wave_definitions.py

@@ -17,6 +17,7 @@
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()
+
     waves_block = load_neo(args.data)
 
     asig_names = [asig.name for asig in waves_block.segments[0].analogsignals]

cobrawap/pipeline/stage04_wave_detection/scripts/optical_flow.py

@@ -230,6 +230,7 @@ def is_phase_signal(signal, use_phases):
 
 if __name__ == '__main__':
     args, unknown = CLI.parse_known_args()
+
     block = load_neo(args.data)
 
     asig = block.segments[0].analogsignals[0]

cobrawap/pipeline/stage04_wave_detection/scripts/plot_clustering.py

@@ -16,11 +16,13 @@
 from utils.neo_utils import time_slice
 
 CLI = argparse.ArgumentParser()
-CLI.add_argument("--output",    nargs='?', type=str)
-CLI.add_argument("--data",      nargs='?', type=str)
+CLI.add_argument("--data", nargs='?', type=str,
+                    help="path to input data in neo format")
+CLI.add_argument("--output", nargs='?', type=str,
+                    help="path of output file")
 CLI.add_argument("--time_slice", nargs='?', type=none_or_float, default=None,
                     help="length of time_slice in seconds.")
-                    
+
 def plot_clustering(events, ax=None):
     if ax is None:
         fig = plt.figure()