linting

src/spikeanalysis/spike_plotter.py

@@ -702,7 +702,6 @@ def plot_latencies(self):
                 plt.figure(dpi=self.dpi)
                 plt.show()
 
-
     def plot_isi(self):
         """
         Function for plotting ISI distributions
@@ -726,10 +725,15 @@ def plot_isi(self):
             plt.figure(dpi=self.dpi)
             plt.show()
 
-
-    def plot_response_trace(self, type: Literal['zscore', 'raw'] = 'zscore', by_neuron: bool = False, by_trial:bool = False, ebar: bool = False, color='black'):
-
-        assert type in ['zscore', 'raw'], 'type of data must be zscore or raw'
+    def plot_response_trace(
+        self,
+        type: Literal["zscore", "raw"] = "zscore",
+        by_neuron: bool = False,
+        by_trial: bool = False,
+        ebar: bool = False,
+        color="black",
+    ):
+        assert type in ["zscore", "raw"], "type of data must be zscore or raw"
 
         if type == "zscore":
             data = self.data.z_scores
@@ -743,41 +747,39 @@ def plot_response_trace(self, type: Literal['zscore', 'raw'] = 'zscore', by_neur
             if by_trial and by_neuron:
                 for neuron in range(np.shape(response)[0]):
                     for trial in range(np.shape(response)[1]):
-                        self._plot_one_trace(current_bins, response[neuron, trial, :], ebars=None, color=color, stim=stimulus)
+                        self._plot_one_trace(
+                            current_bins, response[neuron, trial, :], ebars=None, color=color, stim=stimulus
+                        )
             elif by_neuron:
                 for neuron in range(np.shape(response)[0]):
                     avg_response = np.mean(response[neuron], axis=0)
                     ebars = np.std(response[neuron], axis=0)
                     if ebar:
-                        self._plot_one_trace(current_bins, avg_response, ebars=ebars, color=color,stim=stimulus)
+                        self._plot_one_trace(current_bins, avg_response, ebars=ebars, color=color, stim=stimulus)
                     else:
-                        self._plot_one_trace(current_bins, avg_response, ebars=None, color=color,stim=stimulus)
+                        self._plot_one_trace(current_bins, avg_response, ebars=None, color=color, stim=stimulus)
             elif by_trial:
                 for trial in range(np.shape(response)[1]):
-                    avg_response= np.mean(response[:, trial, :], axis=0)
+                    avg_response = np.mean(response[:, trial, :], axis=0)
                     ebars = np.std(response[:, trial, :], axis=0)
                     if ebar:
-                        self._plot_one_trace(current_bins, avg_response, ebars=ebars, color=color,stim=stimulus)
+                        self._plot_one_trace(current_bins, avg_response, ebars=ebars, color=color, stim=stimulus)
                     else:
                         self._plot_one_trace(current_bins, avg_response, ebars=None, color=color, stim=stimulus)
             else:
                 avg_response = np.mean(np.mean(response, axis=1), axis=0)
                 if ebar:
                     self._plot_one_trace(current_bins, avg_response, ebars=ebars, color=color, stim=stimulus)
                 else:
-                    self._plot_one_trace(current_bins, avg_response, ebars=None, color=color,stim=stimulus)
-
-
-
-
-    def _plot_one_trace(self, bins, trace, ebars=None, color='black', stim=''):
+                    self._plot_one_trace(current_bins, avg_response, ebars=None, color=color, stim=stimulus)
 
+    def _plot_one_trace(self, bins, trace, ebars=None, color="black", stim=""):
         fig, ax = plt.subplots(figsize=self.figsize)
         ax.plot(bins, trace, color=color)
         if ebars is not None:
-            ax.plot(bins, trace+ebars, color=color)
-            ax.plot(bins, trace-ebars, color=color)
-            ax.fill_between(bins, trace-ebars, trace+ebars, color=color, alpha=0.02)
+            ax.plot(bins, trace + ebars, color=color)
+            ax.plot(bins, trace - ebars, color=color)
+            ax.fill_between(bins, trace - ebars, trace + ebars, color=color, alpha=0.02)
 
         ax.set_xlabel("Time (s)")
         ax.set_ylabel(self.y_axis)
@@ -787,7 +789,6 @@ def _plot_one_trace(self, bins, trace, ebars=None, color='black', stim=''):
         plt.figure(dpi=self.dpi)
         plt.show()
 
-
     def _get_event_lengths(self) -> dict:
         """
         Utility function to get the event lengths and convert from samples to seconds on a trial