- Fix weight_density. TODO: add legend (colored by seed)

- Add a TODO for the subset in train
- Remove an useless new line

code/bolsonaro/trainer.py

@@ -30,6 +30,8 @@ class Trainer(object):
             y_omp = y_forest
             self._logger.debug('Fitting both the forest and OMP on train+dev subsets.')
 
+        # TODO: add an option to train forest to train+dev and OMP to dev
+
         model.fit(
             X_forest=X_forest,
             y_forest=y_forest,

code/bolsonaro/visualization/plotter.py

@@ -12,14 +12,19 @@ class Plotter(object):
         :param all_experiment_weights: The weights for the different experiments
         :param file path: str, path where the figure will be saved
         '''
+
+        all_experiment_weights = np.array(list(all_experiment_weights.values()))
+        n = len(all_experiment_weights)
+        colors = Plotter.get_colors_from_cmap(n)
+
         fig, ax = plt.subplots()
-        for weights in all_experiment_weights.values():
-            pd.Series([weight for weight in weights if weight != 0]).plot.kde(figsize=(15, 10), ax=ax)
+        for i in range(n):
+            for weights in all_experiment_weights[i]:
+                pd.Series([weight for weight in weights if weight != 0]).plot.kde(
+                    figsize=(15, 10), ax=ax, color=colors[i])
 
-        legends = ['Experience ' + str(i+1) for i in range(len(all_experiment_weights))]
-        ax.legend(legends)
+        ax.set_title('Density weights of the OMP')
         fig.savefig(file_path, dpi=fig.dpi)
-        fig.title('Density weights of the OMP')
         plt.close(fig)
 
     @staticmethod

code/compute_results.py

@@ -117,7 +117,6 @@ if __name__ == "__main__":
         )
 
         # Plot the density of the weights
-
         Plotter.weight_density(
             file_path=args.results_dir + os.sep + experiment_id + os.sep + 'density_weight.png',
             all_experiment_weights=experiment_weights