ENH: add new property to access spike times by cell type

hnn_core/cell_response.py

@@ -153,6 +153,24 @@ def __eq__(self, other):
     def spike_times(self):
         return self._spike_times
 
+    @property
+    def cell_types(self):
+        """Get unique cell types."""
+        spike_types_data = np.concatenate(np.array(self.spike_types, dtype=object))
+        return np.unique(spike_types_data).tolist()
+
+    @property
+    def spike_times_by_type(self):
+        """Get a dictionary of spike times by cell type"""
+        spike_times = dict()
+        for cell_type in self.cell_types:
+            spike_times[cell_type] = list()
+            for trial_spike_times, trial_spike_types in zip(self.spike_times, self.spike_types):
+                mask = np.isin(trial_spike_types, cell_type)
+                trial_cell_spike_times = np.array(trial_spike_times)[mask].tolist()
+                spike_times[cell_type].append(trial_cell_spike_times)
+        return spike_times
+
     @property
     def spike_gids(self):
         return self._spike_gids

hnn_core/tests/test_cell_response.py

@@ -24,6 +24,11 @@ def test_cell_response(tmp_path):
                                  spike_gids=spike_gids,
                                  spike_types=spike_types,
                                  times=sim_times)
+
+    assert set(cell_response.cell_types) == set(gid_ranges.keys())
+    assert cell_response.spike_times_by_type['L2_basket'] == [[7.89], []]
+    assert cell_response.spike_times_by_type['L5_pyramidal'] == [[], [4.2812]]
+
     kwargs_hist = dict(alpha=0.25)
     fig = cell_response.plot_spikes_hist(show=False, **kwargs_hist)
     assert all(patch.get_alpha() == kwargs_hist['alpha']