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

for more information, see https://pre-commit.ci

src/spikeinterface/comparison/groundtruthstudy.py

@@ -176,12 +176,13 @@ def remove_sorting(self, key):
         for f in (log_file, comparison_file):
             if f.exists():
                 f.unlink()
-    
+
     def set_colors(self, colors=None, map_name="tab20"):
         if colors is None:
             case_keys = list(self.cases.keys())
-            self.colors = get_some_colors(case_keys, map_name=map_name, 
-                                          color_engine = "matplotlib", shuffle=False, margin=0)
+            self.colors = get_some_colors(
+                case_keys, map_name=map_name, color_engine="matplotlib", shuffle=False, margin=0
+            )
         else:
             self.colors = colors
 

src/spikeinterface/sortingcomponents/benchmark/benchmark_clustering.py

@@ -239,7 +239,7 @@ def plot_error_metrics(self, metric="cosine", case_keys=None, figsize=(15, 5)):
             fig.colorbar(im, ax=axes[0, count])
             label = self.cases[key]["label"]
             axes[0, count].set_title(label)
-        
+
         return fig
 
     def plot_metrics_vs_snr(self, metric="agreement", case_keys=None, figsize=(15, 5), axes=None):
@@ -298,7 +298,7 @@ def plot_metrics_vs_snr(self, metric="agreement", case_keys=None, figsize=(15, 5
             label = self.cases[key]["label"]
             axes[count].set_title(label)
             axes[count].legend()
-        
+
         if fig is not None:
             return fig
 
@@ -355,7 +355,7 @@ def plot_metrics_vs_depth_and_snr(self, metric="agreement", case_keys=None, figs
             elif metric == "agreement":
                 for found, real in zip(matched_ids2[mask], unit_ids1[mask]):
                     to_plot += [scores.at[real, found]]
-            elif metric in ['recall', 'precision', 'accuracy']:
+            elif metric in ["recall", "precision", "accuracy"]:
                 to_plot = result["gt_comparison"].get_performance()[metric].values
                 depth_matched = depth
                 snr_matched = metrics["snr"]
@@ -368,14 +368,14 @@ def plot_metrics_vs_depth_and_snr(self, metric="agreement", case_keys=None, figs
             label = self.cases[key]["label"]
             axes[0, count].set_title(label)
             if count > 0:
-                axes[0, count].set_ylabel('')
+                axes[0, count].set_ylabel("")
                 axes[0, count].set_yticks([], [])
             # axs[0, count].legend()
-        
+
         fig.subplots_adjust(right=0.85)
         cbar_ax = fig.add_axes([0.9, 0.1, 0.025, 0.75])
         fig.colorbar(im, cax=cbar_ax, label=metric)
-        
+
         return fig
 
     def plot_unit_losses(self, cases_before, cases_after, metric="agreement", figsize=None):
@@ -398,19 +398,17 @@ def plot_unit_losses(self, cases_before, cases_after, metric="agreement", figsiz
             ax.set_ylabel("depth (um)")
             ax.set_ylabel("snr")
             if count > 0:
-                ax.set_ylabel('')
+                ax.set_ylabel("")
                 ax.set_yticks([], [])
             im = ax.scatter(positions[:, 1], x, c=(y_after - y_before), cmap="coolwarm")
             im.set_clim(-1, 1)
-            #fig.colorbar(im, ax=ax)
-            #ax.set_title(k)
-
+            # fig.colorbar(im, ax=ax)
+            # ax.set_title(k)
 
         fig.subplots_adjust(right=0.85)
         cbar_ax = fig.add_axes([0.9, 0.1, 0.025, 0.75])
         cbar = fig.colorbar(im, cax=cbar_ax, label=metric)
-        #cbar.set_clim(-1, 1)
-
+        # cbar.set_clim(-1, 1)
 
         return fig
 

src/spikeinterface/sortingcomponents/benchmark/benchmark_matching.py

@@ -15,6 +15,7 @@
 from spikeinterface.core.recording_tools import get_noise_levels
 from spikeinterface.core.sparsity import compute_sparsity
 
+
 class MatchingBenchmark(Benchmark):
 
     def __init__(self, recording, gt_sorting, params):
@@ -241,19 +242,19 @@ def plot_unit_losses(self, before, after, metric=["precision"], figsize=None):
 
             y_before = self.get_result(before)["gt_comparison"].get_performance()[k].values
             y_after = self.get_result(after)["gt_comparison"].get_performance()[k].values
-            #if count < 2:
-            #ax.set_xticks([], [])
-            #elif count == 2:
+            # if count < 2:
+            # ax.set_xticks([], [])
+            # elif count == 2:
             ax.set_xlabel("depth (um)")
             im = ax.scatter(positions[:, 1], x, c=(y_after - y_before), cmap="coolwarm")
             fig.colorbar(im, ax=ax, label=k)
             im.set_clim(-1, 1)
             ax.set_title(k)
             ax.set_ylabel("snr")
-    
-        #fig.subplots_adjust(right=0.85)
-        #cbar_ax = fig.add_axes([0.9, 0.1, 0.025, 0.75])
-        #cbar = fig.colorbar(im, cax=cbar_ax, label=metric)
+
+        # fig.subplots_adjust(right=0.85)
+        # cbar_ax = fig.add_axes([0.9, 0.1, 0.025, 0.75])
+        # cbar = fig.colorbar(im, cax=cbar_ax, label=metric)
 
         # if count == 2:
         #    ax.legend()

src/spikeinterface/sortingcomponents/benchmark/benchmark_peak_detection.py

@@ -195,7 +195,7 @@ def plot_detected_amplitudes(self, case_keys=None, figsize=(15, 5), detect_thres
                 ymin, ymax = ax.get_ylim()
                 abs_threshold = -detect_threshold * noise_levels
                 ax.plot([abs_threshold, abs_threshold], [ymin, ymax], "k--")
-        
+
         return fig
 
     def plot_deltas_per_cells(self, case_keys=None, figsize=(15, 5)):

src/spikeinterface/sortingcomponents/tools.py

@@ -140,10 +140,13 @@ def remove_empty_templates(templates):
         is_scaled=templates.is_scaled,
     )
 
+
 def sigmoid(x, x0, k, b):
-    return (1 / (1+np.exp(-k*(x-x0)))) + b
+    return (1 / (1 + np.exp(-k * (x - x0)))) + b
+
 
 def fit_sigmoid(xdata, ydata, p0=None):
     from scipy.optimize import curve_fit
+
     popt, pcov = curve_fit(sigmoid, xdata, ydata, p0)
-    return popt
+    return popt

src/spikeinterface/widgets/gtstudy.py

@@ -50,7 +50,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
             label = dp.study.cases[key]["label"]
             rt = dp.run_times.loc[key]
             self.ax.bar(i, rt, width=0.8, label=label, facecolor=self.colors[key])
-        self.ax.set_ylabel('run time (s)')
+        self.ax.set_ylabel("run time (s)")
         self.ax.legend()