changeset 9:53ee437b5ba3

added a proper piano roll; fixed a bug with plotting the final scene, added another verbosity level

--- a/simscene.py	Tue Oct 03 13:56:15 2017 +0100
+++ b/simscene.py	Tue Oct 03 15:18:08 2017 +0100
@@ -26,6 +26,8 @@
 import librosa.output
 
 # Matplotlib
+from matplotlib import rc
+# rc('text', usetex=True)
 import matplotlib.pyplot as plt
 import matplotlib.patches as patches
 from cycler import cycler
@@ -222,7 +224,6 @@
             while new_start_time < track_end_time:
                 offset = float(mean_time_between_instances) +\
                             float(events_df['time_between_instances_stddev'].loc[n]*np.random.randn())
-                logging.debug(offset)
                 new_start_time += offset
                 new_end_time += offset
                 
@@ -267,7 +268,8 @@
             Fdb = librosa.amplitude_to_db(F)
             plt.subplot(2,1,2)
             librosa.display.specshow(Fdb, sr=SR, x_axis='time', y_axis='hz')
-            plt.savefig('{}/{}.{}'.format(output_path, label, image_format))
+            plt.tight_layout()
+            plt.savefig('{}/{}.{}'.format(output_path, label, image_format),dpi=300)
 
             
         scene_starting_times.append((label, start_times))
@@ -275,42 +277,44 @@
 
     if figure_verbosity > 0:
         plt.figure()
-        plt.subplot(3,1,1)
-        plt.title('Waveform and spectrogram for the full track')
-        librosa.display.waveplot(scene_arr)
+        ax0 = plt.subplot(3,1,1)
+        plt.title('Synthesized Scene')
+        librosa.display.waveplot(scene_arr, sr=SR)
         F = librosa.stft(scene_arr)
         Fdb = librosa.amplitude_to_db(F)
-        plt.subplot(3,1,2)
+        ax1 = plt.subplot(3,1,2)
         librosa.display.specshow(Fdb, sr=SR, x_axis='time', y_axis='hz')
-        ax = plt.subplot(3,1,3)
-        ax.set_xlim([0,scene_duration])
-        ax.set_ylim([-0.5, len(scene_starting_times)-0.5])
+        ax2 = plt.subplot(3,1,3)
+        ax2.set_xlim([0,scene_duration])
+        ax2.set_ylim([-0.5, len(scene_starting_times)-0.5])
 
         # Get labels
         labels = [s[0] for s in scene_starting_times]
 
         plt.yticks(range(len(scene_starting_times)), labels)
 
-        plt.rc('lines', linewidth=4)
-        plt.rc('axes', prop_cycle=(cycler('color', ['r', 'g', 'b', 'y']) +
-            cycler('linestyle', ['-', '--', ':', '-.'])))
-        
         for n in range(len(scene_starting_times)):
             label = scene_starting_times[n][0]
             start_times = scene_starting_times[n][1]
             end_times = scene_ending_times[n][1]
+            color = ['r', 'g', 'y'][n % 3]
+
             for m in range(len(start_times)):
-                plt.axhline(float(n), start_times[m], start_times[m]+1.0)
-            # for m in range(len(start_times)):
-            #     plt.text(
-            #         start_times[m],
-            #         n,
-            #         label,
-            #         size=9,ha='center',va='center',
-            #         bbox=dict(boxstyle='square', ec=(1., 0.5, 0.5), fc=(1., 1-n/float(len(scene_starting_times)), n/float(len(scene_starting_times)))),
-            #     )
-        
-        plt.savefig('{}/full-scene.{}'.format(output_path, image_format))     
+                plt.hlines(y=float(n), xmin=start_times[m], xmax=end_times[m], alpha=0.5, color=color, linewidth=4)
+                if figure_verbosity > 2:
+                    ax0.axvline(start_times[m], color=color, alpha=0.1)
+                    ax0.axvline(end_times[m], color=color, alpha=0.1)
+                    ax0.axvspan(start_times[m], end_times[m], color=color, alpha=0.1)
+                    ax1.axvline(start_times[m], color=color, alpha=0.1)
+                    ax1.axvline(end_times[m], color=color, alpha=0.1)
+                    ax1.axvline(end_times[m], color=color, alpha=0.1)
+                    ax1.axvspan(start_times[m], end_times[m], color=color, alpha=0.1)                
+                    ax2.axvline(start_times[m], color=color, alpha=0.1)
+                    ax2.axvline(end_times[m], color=color, alpha=0.1)
+                    ax2.axvline(end_times[m], color=color, alpha=0.1)
+                    ax2.axvspan(start_times[m], end_times[m], color=color, alpha=0.1)                
+        plt.tight_layout()
+        plt.savefig('{}/full-scene.{}'.format(output_path, image_format),dpi=300)     
     if figure_verbosity > 1:
         plt.show()
 
@@ -396,7 +400,7 @@
     
     argparser.add_argument(
         '-v', '--figure-verbosity', action='count',
-        help="Increase figure verbosity. (Default) 0 - Don't save or display figures, 1 - Save pictures but do not display them, 2 - Save and display figures"
+        help="Increase figure verbosity. (Default) 0 - Don't save or display figures, 1 - Save pictures but do not display them, 2 - Save and display figures, 3 - Add shades over the events in the final plot"
     )
     figure_verbosity = None