diff --git a/figures/MAM2EBRAINS/M2E_visualize_time_ave_pop_rates.py b/figures/MAM2EBRAINS/M2E_visualize_time_ave_pop_rates.py index 89b991acfd40842b4bcb9a32839330f0a2a13a03..63b9f8b87f2ece2a762b1183fd8bfe9dd08b485e 100644 --- a/figures/MAM2EBRAINS/M2E_visualize_time_ave_pop_rates.py +++ b/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) diff --git a/multiarea_model/analysis.py b/multiarea_model/analysis.py index 10a5c0564b630cdce288521e904659dcfe3f7322..d2960fabca8336a1f4379a452c0d06a1dd6f2af4 100644 --- a/multiarea_model/analysis.py +++ b/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.])