Joint-ISI dithering: fixed a bug regarding first ISI bin (NeuralEnsem…

…ble#396) * fixing boundaries of joint-isi * possible fix of the first-bin-error * changed values of padding
INM-6 · Oct 1, 2021 · 25c746a · 25c746a
1 parent abbb548
commit 25c746a
Showing 1 changed file with 14 additions and 11 deletions.
diff --git a/elephant/spike_train_surrogates.py b/elephant/spike_train_surrogates.py
@@ -1004,7 +1004,7 @@ def _determine_cumulative_functions(self):
                 diagonal = np.diagonal(
                     rotated_jisih, offset=-self.n_bins + double_index + 1)
                 jisih_cum = self._normalize_cumulative_distribution(
-                    np.cumsum(diagonal))
+                    np.r_[0., np.cumsum(diagonal)])
                 self._jisih_cumulatives.append(jisih_cum)
             self._jisih_cumulatives = np.array(
                 self._jisih_cumulatives, dtype=object)
@@ -1039,19 +1039,21 @@ def _window_diagonal_cumulatives(self, rotated_jisih):
         # double_index corresponds to the sum of the indices for the previous
         # and the subsequent ISI.
         for double_index in range(self.n_bins):
-            cum_diag = np.cumsum(np.diagonal(rotated_jisih,
-                                             - self.n_bins
-                                             + double_index + 1))
+            anti_diagonal = np.diagonal(
+                rotated_jisih, - self.n_bins + double_index + 1)
 
             right_padding = jisih_diag_cums.shape[1] - \
-                len(cum_diag) - self._max_change_index
+                len(anti_diagonal) - self._max_change_index
 
-            jisih_diag_cums[double_index] = np.pad(
-                cum_diag,
+            cumulated_diagonal = np.cumsum(anti_diagonal)
+
+            padded_cumulated_diagonal = np.pad(
+                cumulated_diagonal,
                 pad_width=(self._max_change_index, right_padding),
                 mode='constant',
-                constant_values=(cum_diag[0], cum_diag[-1])
-            )
+                constant_values=(0., cumulated_diagonal[-1]))
+
+            jisih_diag_cums[double_index] = padded_cumulated_diagonal
 
         return jisih_diag_cums
 
@@ -1089,7 +1091,7 @@ def _get_dithering_step(self,
             if self.method == 'fast':
                 cum_dist_func = self._jisih_cumulatives[
                     double_index]
-                compare_isi = self._index_to_isi(curr_isi_id)
+                compare_isi = self._index_to_isi(curr_isi_id + 1)
             else:
                 cum_dist_func = self._jisih_cumulatives[
                     curr_isi_id][next_isi_id]
@@ -1099,7 +1101,8 @@ def _get_dithering_step(self,
                 # when the method is 'fast', new_isi_id is where the current
                 # ISI id should go to.
                 new_isi_id = np.searchsorted(cum_dist_func, random.random())
-                step = self._index_to_isi(new_isi_id) - compare_isi
+                step = self._index_to_isi(new_isi_id)\
+                    - compare_isi
                 return step
 
         return self._uniform_dither_not_jisi_movable_spikes(