refactor: flake8 corrections

brown-ccv · Oct 11, 2024 · 308ffe8 · 308ffe8
1 parent 9717ae7
commit 308ffe8
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Showing 2 changed files with 7 additions and 7 deletions.
diff --git a/hnn_core/tests/test_viz.py b/hnn_core/tests/test_viz.py
@@ -291,9 +291,10 @@ def test_spikes_raster_trial_idx(self, base_simulation_spikes):
             fig = net.cell_response.plot_spikes_raster(trial_idx=index_arg,
                                                        show=False)
             # Check that collections contain data
-            assert (all([collection.get_positions() != [-1]
-                         for collection in fig.axes[0].collections]),
-                    "No data plotted in raster plot")
+            assert all(
+                [collection.get_positions() != [-1]
+                 for collection in fig.axes[0].collections]
+            ), "No data plotted in raster plot"
 
     def test_spikes_raster_colors(self, base_simulation_spikes):
         net, _ = base_simulation_spikes

diff --git a/hnn_core/viz.py b/hnn_core/viz.py
@@ -507,8 +507,8 @@ def plot_spikes_hist(cell_response, trial_idx=None, ax=None, spike_types=None,
 
 
 def plot_spikes_raster(cell_response, trial_idx=None, ax=None, show=True,
-                       cell_types = ['L2_basket', 'L2_pyramidal',
-                                     'L5_basket','L5_pyramidal'],
+                       cell_types=['L2_basket', 'L2_pyramidal',
+                                   'L5_basket', 'L5_pyramidal'],
                        colors=None,
                        ):
     """Plot the aggregate spiking activity according to cell type.
@@ -552,7 +552,6 @@ def plot_spikes_raster(cell_response, trial_idx=None, ax=None, show=True,
                              f"cell types. {len(colors)} colors provided "
                              f"for {len(cell_types)} cell types.")
 
-
     # Extract desired trials
     spike_times = np.concatenate(
         np.array(cell_response._spike_times, dtype=object)[trial_idx])
@@ -573,7 +572,7 @@ def plot_spikes_raster(cell_response, trial_idx=None, ax=None, show=True,
     for cell_type in cell_types:
         cell_type_gids = np.unique(spike_gids[spike_types == cell_type])
         cell_type_times, cell_type_ypos = [], []
-        color =  next(color_iter)
+        color = next(color_iter)
 
         for gid in cell_type_gids:
             gid_time = spike_times[spike_gids == gid]