[pre-commit.ci] auto fixes from pre-commit.com hooks

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src/neuroconv/datainterfaces/behavior/facemap/facemapdatainterface.py

@@ -2,11 +2,12 @@
 
 import h5py
 import numpy as np
+from ndx_facemap_motionsvd import MotionSVDMasks, MotionSVDSeries
 from pynwb.base import TimeSeries
 from pynwb.behavior import EyeTracking, PupilTracking, SpatialSeries
-from pynwb.file import NWBFile
-from ndx_facemap_motionsvd import MotionSVDMasks, MotionSVDSeries
 from pynwb.core import DynamicTableRegion
+from pynwb.file import NWBFile
+
 from ..video.video_utils import get_video_timestamps
 from ....basetemporalalignmentinterface import BaseTemporalAlignmentInterface
 from ....tools import get_module
@@ -113,8 +114,8 @@
 
             # Extract mask_coordinates
             mask_coordinates = file[file[file["proc"]["ROI"][0][0]][0][0]]
-            y1 = int(np.round(mask_coordinates[0][0])-1) # correct matlab indexing
-            x1 = int(np.round(mask_coordinates[1][0])-1) # correct matlab indexing
+            y1 = int(np.round(mask_coordinates[0][0]) - 1)  # correct matlab indexing
+            x1 = int(np.round(mask_coordinates[1][0]) - 1)  # correct matlab indexing
             y2 = y1 + int(np.round(mask_coordinates[2][0]))
             x2 = x1 + int(np.round(mask_coordinates[3][0]))
             mask_coordinates = [x1, y1, x2, y2]
@@ -133,7 +134,7 @@
             for c, component in enumerate(file[mask_ref]):
                 if c == self.first_n_components:
                     break
-                componendt_2d = component.reshape((y2-y1, x2-x1))
+                componendt_2d = component.reshape((y2 - y1, x2 - x1))
                 motion_masks_table.add_row(image_mask=componendt_2d.T)
 
             motion_masks = DynamicTableRegion(
@@ -180,18 +181,18 @@
             behavior_module = get_module(nwbfile=nwbfile, name="behavior", description="behavioral data")
 
             timestamps = self.get_timestamps()
-            downsampling_factor=self._get_downsamplig_factor()
-            processed_frame_dimension=self._get_processed_frame_dimension()
+            downsampling_factor = self._get_downsamplig_factor()
+            processed_frame_dimension = self._get_processed_frame_dimension()
             # store ROIs motion mask and motion series
             n = 1
             for series_ref, mask_ref in zip(file["proc"]["motSVD"][1:], file["proc"]["uMotMask"][1:]):
                 series_ref = series_ref[0]
                 mask_ref = mask_ref[0]
 
                 # skipping the first ROI because it referes to "running" mask, from Facemap doc
                 mask_coordinates = file[file["proc"]["locROI"][n][0]]
-                y1 = int(np.round(mask_coordinates[0][0])-1) # correct matlab indexing
-                x1 = int(np.round(mask_coordinates[1][0])-1) # correct matlab indexing
+                y1 = int(np.round(mask_coordinates[0][0]) - 1)  # correct matlab indexing
+                x1 = int(np.round(mask_coordinates[1][0]) - 1)  # correct matlab indexing
                 y2 = y1 + int(np.round(mask_coordinates[2][0]))
                 x2 = x1 + int(np.round(mask_coordinates[3][0]))
                 mask_coordinates = [x1, y1, x2, y2]
@@ -247,19 +248,18 @@
 
     def set_aligned_timestamps(self, aligned_timestamps: np.ndarray) -> None:
         self.timestamps = aligned_timestamps
-    
+
     def _get_downsamplig_factor(self) -> float:
         with h5py.File(self.source_data["mat_file_path"], "r") as file:
             downsamplig_factor = file["proc"]["sc"][0][0]
         return downsamplig_factor
-    
+
     def _get_processed_frame_dimension(self) -> np.ndarray:
         with h5py.File(self.source_data["mat_file_path"], "r") as file:
             processed_frame_ref = file["proc"]["wpix"][0][0]
             frame = file[processed_frame_ref]
-            return [frame.shape[1],frame.shape[0]]
-
-
+            return [frame.shape[1], frame.shape[0]]
+
     def add_to_nwbfile(
         self,
         nwbfile: NWBFile,