Resolve "Experiment pipeline"

Closes #12 (closed)

code/bolsonaro/visualization/plotter.py

@@ -57,7 +57,56 @@ class Plotter(object):
         ax.plot(x_value, mean, c=color_mean, label=label)
 
     @staticmethod
-    def plot_losses(file_path, all_experiment_scores, x_value, xlabel, ylabel, all_labels, title):
+    def plot_stage1_losses(file_path, all_experiment_scores_with_params,
+        all_experiment_scores_wo_params, x_value, xlabel, ylabel, all_labels, title):
+
+        fig, axes = plt.subplots(nrows=1, ncols=2, sharey=True)
+
+        n = len(all_experiment_scores_with_params)
+
+        if n != len(all_experiment_scores_wo_params):
+            raise ValueError('all_experiment_scores_with_params and all_experiment_scores_wo_params must have the same len to be compared.')
+
+        """
+        Get as many different colors from the specified cmap (here nipy_spectral)
+        as there are curve to plot.
+        """
+        colors = Plotter.get_colors_from_cmap(n)
+
+        for j, all_experiment_scores in enumerate([all_experiment_scores_with_params,
+            all_experiment_scores_wo_params]):
+            # For each curve to plot
+            for i in range(n):
+                # Retreive the scores in a list for each seed
+                experiment_scores = list(all_experiment_scores[i].values())
+                # Compute the mean and the std for the CI
+                mean_experiment_scores = np.average(experiment_scores, axis=0)
+                std_experiment_scores = np.std(experiment_scores, axis=0)
+                # Plot the score curve with the CI
+                Plotter.plot_mean_and_CI(
+                    ax=axes[j],
+                    mean=mean_experiment_scores,
+                    lb=mean_experiment_scores + std_experiment_scores,
+                    ub=mean_experiment_scores - std_experiment_scores,
+                    x_value=x_value,
+                    color_mean=colors[i],
+                    facecolor=colors[i],
+                    label=all_labels[i]
+                )
+
+        axes[0].set_xlabel(xlabel)
+        axes[1].set_xlabel(xlabel)
+        axes[0].set_ylabel(ylabel)
+        axes[1].set_title(title)
+        handles, labels = axes[0].get_legend_handles_labels()
+        legend = axes[0].legend(handles, labels, loc='upper center', bbox_to_anchor=(1.1, -0.15))
+        fig.savefig(file_path, dpi=fig.dpi, bbox_extra_artists=(legend,), bbox_inches='tight')
+        plt.close(fig)
+
+    @staticmethod
+    def plot_stage2_losses(file_path, all_experiment_scores, x_value,
+        xlabel, ylabel, all_labels, title):
+
         fig, ax = plt.subplots()
 
         n = len(all_experiment_scores)
@@ -91,7 +140,7 @@ class Plotter(object):
         plt.ylabel(ylabel)
         plt.title(title)
         plt.legend(loc='upper right')
-        fig.savefig(file_path, dpi=fig.dpi)
+        fig.savefig(file_path, dpi=fig.dpi, bbox_inches='tight')
         plt.close(fig)
 
     @staticmethod