Merge pull request #262 from NeurodataWithoutBorders/pre-commit-ci-up…

…date-config

[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -6,7 +6,7 @@ repos:
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
 -   repo: https://github.com/psf/black
-    rev: 22.12.0
+    rev: 23.1.0
     hooks:
     -   id: black
         exclude: ^docs/

nwbwidgets/allen.py

@@ -31,7 +31,6 @@ class AllenTuningCurveWidget(TimeIntervalsSelector):
 
 class AllenRasterGroupAndSortController(GroupAndSortController):
     def get_groups(self):
-
         self.electrodes = self.dynamic_table.get_ancestor("NWBFile").electrodes
 
         groups = super().get_groups()

nwbwidgets/brains.py

@@ -34,7 +34,6 @@ def make_cylinder_mesh(radius, height, sections=32, position=(0, 0, 0), directio
 
 
 def make_cylinders(positions, directions, radius=1, height=1, sections=32, name="cylinders", **kwargs):
-
     return [
         make_cylinder_mesh(
             position=position,
@@ -54,7 +53,6 @@ def make_cylinders(positions, directions, radius=1, height=1, sections=32, name=
 @check_widget_dependencies({"nilearn": nilearn, "skspatial": skspatial, "trimesh": trimesh})
 class HumanElectrodesPlotlyWidget(widgets.VBox):
     def __init__(self, electrodes: DynamicTable, **kwargs):
-
         super().__init__()
         self.electrodes = electrodes
 
@@ -85,7 +83,6 @@ def __init__(self, electrodes: DynamicTable, **kwargs):
     def find_normals(points, k=3):
         normals = []
         for point in points:
-
             distance = np.linalg.norm(points - point, axis=1)
             # closest_inds = np.argpartition(distance, 3)
             # x0, x1, x2 = points[closest_inds[:3]]
@@ -97,7 +94,6 @@ def find_normals(points, k=3):
         return normals
 
     def show_electrodes(self, electrodes: DynamicTable, color_by):
-
         positions = np.c_[electrodes.x[:], electrodes.y[:], electrodes.z[:]]
 
         if isinstance(electrodes[color_by][0], (bytes, str, np.bool_)):
@@ -172,7 +168,6 @@ def show_electrodes(self, electrodes: DynamicTable, color_by):
         )
 
     def plot_human_brain(self, left_opacity=1.0, right_opacity=1.0):
-
         mesh = nilearn.datasets.fetch_surf_fsaverage("fsaverage5")
 
         def create_mesh(name, **kwargs):

nwbwidgets/controllers/group_and_sort_controllers.py

@@ -358,6 +358,5 @@ def group_and_sort(self):
         return order, group_inds, labels
 
     def update_value(self):
-
         order, group_inds, labels = self.group_and_sort()
         self.value = dict(order=order, group_inds=group_inds, labels=labels)

nwbwidgets/controllers/time_window_controllers.py

@@ -8,7 +8,6 @@ class WindowController(HBox, ValueWidget, DescriptionWidget):
     def __init__(
         self, vmin, vmax, start_value=(None, None), description="window (s)", orientation="horizontal", **kwargs
     ):
-
         if orientation not in ("horizontal", "vertical"):
             ValueError("Unrecognized orientation: {}".format(orientation))
 
@@ -144,7 +143,6 @@ def move_end(self, change):
         self.value = (self.vmax - value_range, self.vmax)
 
     def get_children(self):
-
         if self.orientation == "horizontal":
             return [
                 self.slider,
@@ -275,7 +273,6 @@ def move_end(self, change):
         self.slider.value = self.vmax - self.duration.value
 
     def get_children(self):
-
         if self.orientation == "horizontal":
             return [
                 self.slider,

nwbwidgets/ecephys.py

@@ -98,7 +98,6 @@ def show_electrodes(electrodes_table):
 
 @check_widget_dependencies({"ccfwidget": ccfwidget, "aiohttp": safe_import("aiohttp")})
 def show_ccf(electrodes_table=None, **kwargs):
-
     input_kwargs = {}
     if electrodes_table is not None:
         df = electrodes_table.to_dataframe()

nwbwidgets/image.py

@@ -60,7 +60,6 @@ def get_frame(self, idx):
             return self.image_series.data[idx].T
 
     def set_out_fig(self):
-
         self.out_fig = go.FigureWidget(
             data=go.Heatmap(
                 z=self.get_frame(0),

nwbwidgets/misc.py

@@ -257,7 +257,6 @@ def __init__(
         unit_controller=None,
         ntt=1000,
     ):
-
         self.units = input_data
 
         super().__init__()

nwbwidgets/timeseries.py

@@ -351,7 +351,6 @@ def on_change(change):
 
 class SeparateTracesPlotlyWidget(AbstractTraceWidget):
     def set_out_fig(self):
-
         timeseries = self.controls["timeseries"].value
 
         time_window = self.controls["time_window"].value
@@ -633,7 +632,6 @@ def __init__(
             else:
                 self.children = [self.range_controller, right_panel]
         else:
-
             self.children = [self.gas, right_panel]
 
         # self.layout = widgets.Layout(width="100%")
@@ -676,7 +674,6 @@ def __init__(
         trace_controller_kwargs=None,
         sem=True,
     ):
-
         self.time_series = time_series
         self.time_series_data = time_series.data[()]
         self.time_series_timestamps = None
@@ -791,7 +788,6 @@ def __init__(
         trace_controller=None,
         trace_controller_kwargs=None,
     ):
-
         self.time_series = time_series
 
         super().__init__(
@@ -889,7 +885,6 @@ def __init__(
         trace_controller=None,
         trace_controller_kwargs=None,
     ):
-
         self.time_series = time_series
 
         super().__init__(
@@ -930,7 +925,6 @@ def update(
         align_to_zero=False,
         fig: go.FigureWidget = None,
     ):
-
         data, time_ts_aligned = self.align_data(start_label, before, after, index)
         if group_inds is None:
             group_inds = np.zeros(len(self.trials), dtype=int)
@@ -952,7 +946,6 @@ def trialize_time_series(
     duration: float = 1,
     alignment_column: str = "start_time",
 ) -> pd.DataFrame:
-
     if isinstance(trials_table, DynamicTable):
         trials_table_df = trials_table.to_dataframe()
     else:
@@ -1020,15 +1013,13 @@ def create_empty_figure(text="No data"):
 
 
 def calculate_moving_average_over_trials(df, moving_average_window):
-
     df_sort = df.sort_values(by="centered_timestamps")
     df_sort["moving_average"] = df_sort["data"].rolling(moving_average_window).mean()
 
     return df_sort
 
 
 def add_moving_average_traces(figure, df, facet_col, facet_row):
-
     if facet_col is None and facet_row is None:
         num_trials = df["trial"].unique().size
         moving_average_window = 2 * num_trials
@@ -1041,7 +1032,6 @@ def add_moving_average_traces(figure, df, facet_col, facet_row):
             line=dict(color="black", width=4),
         )
     elif facet_col is not None and facet_row is None:
-
         col_faceting_values = natsorted(df[facet_col].dropna().unique())
 
         for col_index, col_face_value in enumerate(col_faceting_values):
@@ -1067,7 +1057,6 @@ def add_moving_average_traces(figure, df, facet_col, facet_row):
             )
 
     elif facet_col is None and facet_row is not None:
-
         row_faceting_values = natsorted(df[facet_row].dropna().unique())
 
         for row_index, row_face_value in enumerate(reversed(row_faceting_values)):
@@ -1097,7 +1086,6 @@ def add_moving_average_traces(figure, df, facet_col, facet_row):
 
         for row_index, row_face_value in enumerate(reversed(row_faceting_values)):
             for col_index, col_face_value in enumerate(col_faceting_values):
-
                 if isinstance(col_face_value, str):
                     col_query_string = f"{facet_col}=='{col_face_value}'"
                 else:
@@ -1130,7 +1118,6 @@ def add_moving_average_traces(figure, df, facet_col, facet_row):
 
 
 def build_faceting_figure(df, facet_col, facet_row, data_label="data", trial_label="trial"):
-
     if df.empty:
         empty_figure = create_empty_figure()
         return empty_figure
@@ -1397,7 +1384,6 @@ def query_expresion(self, children):
             return f" {children.description} == {children.value} "
 
     def update_data_state(self):
-
         if self.controller.filtering_active:
             query_string = "and".join(
                 [self.query_expresion(children) for children in self.controller.filter_menu.children]
@@ -1416,7 +1402,6 @@ def update_data_state(self):
         )
 
     def update_plot_widget(self, button_instance):
-
         # Update data
         self.update_data_state()
 

nwbwidgets/utils/dependencies.py

@@ -60,7 +60,6 @@ def check_widget_dependencies(dependencies):
     def wrap(func):
         @wraps(func)
         def wrapped_func(*args, **kwargs):
-
             missing = [name for name, dependency in dependencies.items() if not dependency]
             if not missing:
                 return func(*args, **kwargs)

nwbwidgets/utils/timeseries.py

@@ -102,7 +102,6 @@ def get_timeseries_in_units(node: TimeSeries, istart=None, istop=None, data_colu
         data = time_series.data[istart:istop]
 
     if time_series.conversion and np.isfinite(time_series.conversion):
-
         offset_scalar = time_series.offset
         conversion_factor_scalar = time_series.conversion
         channel_conversion_vector = (

nwbwidgets/utils/units.py

@@ -157,7 +157,6 @@ def align_by_time_intervals(
 
 
 def get_unobserved_intervals(units, time_window, units_select=()):
-
     if "obs_intervals" not in units:
         return []
 

test/test_ophys.py

@@ -178,7 +178,6 @@ def test_show_image_segmentation(self):
 
 
 def test_plane_segmentation_many_categories():
-
     ps = mock_PlaneSegmentation(n_rois=0)
     ps.add_column("category", "category")
 

test/test_timeseries.py

@@ -37,7 +37,6 @@ def test_timeseries_widget():
 
 
 def test_show_timeseries_mpl():
-
     ts = TimeSeries(
         name="name",
         description="no description",