/

figures/MAM2EBRAINS/M2E_visualize_time_ave_pop_rates.py

@@ -70,7 +70,6 @@ def plot_time_averaged_population_rates(M, area_list=None, **keywords):
     x_ticks = [int(a + 0.5) for a in x_index]
     y_index = list(range(len(A.network.structure['V1'])))
     y_index = [a + 0.5 for a in y_index]
-    # print(A.network.structure['V1'])
     # ax.set_xticks(x_index)
     ax.set_xticks([i + 0.5 for i in np.arange(0, len(area_list), 1)])
     # ax.set_xticklabels(x_ticks)

multiarea_model/analysis.py

@@ -899,11 +899,8 @@ class Analysis:
         ax = fig.add_subplot(111)
 
         for i, area in enumerate(area_list):
-            # print(i, area)
-            # self.network has no attribute structure_reversed
-            # for j, pop in enumerate(self.network.structure_reversed['V1']):
-            # for j, pop in enumerate(list(reversed(self.network.structure['V1']))):
-            for j, pop in enumerate(self.network.structure['V1']):
+            print(i, area)
+            for j, pop in enumerate(self.network.structure_reversed['V1']):
                 if pop in self.network.structure[area]:
                     rate = self.pop_rates[area][pop][0]
                     if rate == 0.0:
@@ -932,14 +929,10 @@ class Analysis:
         x_ticks = [int(a + 0.5) for a in x_index]
         y_index = list(range(len(self.network.structure['V1'])))
         y_index = [a + 0.5 for a in y_index]
-        # print(self.network.structure['V1'])
         ax.set_xticks(x_index)
         ax.set_xticklabels(x_ticks)
         ax.set_yticks(y_index)
-        # self.network has no attribute structure_reversed
-        # ax.set_yticklabels(self.network.structure_reversed['V1'])
-        # ax.set_yticklabels(list(reversed(self.network.structure['V1'])))
-        # ax.set_yticklabels(self.network.structure['V1'])
+        ax.set_yticklabels(self.network.structure_reversed['V1'])
         ax.set_ylabel('Population', size=18)
         ax.set_xlabel('Area index', size=18)
         t = FixedLocator([0.01, 0.1, 1., 10., 100.])