Do not align arrays by duplicating last value

To produce the same stats for single and multiple sources.

If there are multiple sources with different number of frames, leave the number
of values per each metric as is. For example:

source 1: [1, None, 2]
source 2: [3, None, 4, 5]

before this change becomes:

source 1: [1, 1, 2, 2]
source 2: [3, 3, 4, 5]

and after this change:

source 1: [1, 1, 2]
source 2: [3, 3, 4, 5]

scripts/osg_stats.py

@@ -149,17 +149,18 @@ def collect_per_frame(sources, keys, begin_frame, end_frame, frame_number_name):
         for key in keys:
             result[name][key] = [None] * (end_frame - begin_frame)
     for name, frames in sources.items():
+        max_index = 0
         for frame in frames:
             number = frame[frame_number_name]
             if begin_frame <= number < end_frame:
                 index = number - begin_frame
+                max_index = max(max_index, index)
                 for key in keys:
                     if key in frame:
                         result[name][key][index] = frame[key]
-    for name in result.keys():
         for key in keys:
             prev = 0.0
-            values = result[name][key]
+            values = result[name][key][:max_index + 1]
             for i in range(len(values)):
                 if values[i] is not None:
                     prev = values[i]
@@ -183,9 +184,11 @@ def draw_timeseries(sources, keys, add_sum, begin_frame, end_frame):
     x = numpy.array(range(begin_frame, end_frame))
     for name, frames in sources.items():
         for key in keys:
-            ax.plot(x, frames[key], label=f'{key}:{name}')
+            y = frames[key]
+            ax.plot(x[:len(y)], y, label=f'{key}:{name}')
         if add_sum:
-            ax.plot(x, numpy.sum(list(frames[k] for k in keys), axis=0), label=f'sum:{name}', linestyle='--')
+            y = numpy.sum(list(frames[k] for k in keys), axis=0)
+            ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
     fig.canvas.manager.set_window_title('timeseries')
@@ -196,10 +199,11 @@ def draw_commulative_timeseries(sources, keys, add_sum, begin_frame, end_frame):
     x = numpy.array(range(begin_frame, end_frame))
     for name, frames in sources.items():
         for key in keys:
-            ax.plot(x, numpy.cumsum(frames[key]), label=f'{key}:{name}')
+            y = numpy.cumsum(frames[key])
+            ax.plot(x[:len(y)], y, label=f'{key}:{name}')
         if add_sum:
-            ax.plot(x, numpy.cumsum(numpy.sum(list(frames[k] for k in keys), axis=0)), label=f'sum:{name}',
+            y = numpy.cumsum(numpy.sum(list(frames[k] for k in keys), axis=0))
-                    linestyle='--')
+            ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
     fig.canvas.manager.set_window_title('commulative_timeseries')
@@ -210,10 +214,11 @@ def draw_timeseries_delta(sources, keys, add_sum, begin_frame, end_frame):
     x = numpy.array(range(begin_frame + 1, end_frame))
     for name, frames in sources.items():
         for key in keys:
-            ax.plot(x, numpy.diff(frames[key]), label=f'{key}:{name}')
+            y = numpy.diff(frames[key])
+            ax.plot(x[:len(y)], numpy.diff(frames[key]), label=f'{key}:{name}')
         if add_sum:
-            ax.plot(x, numpy.diff(numpy.sum(list(frames[k] for k in keys), axis=0)), label=f'sum:{name}',
+            y = numpy.diff(numpy.sum(list(frames[k] for k in keys), axis=0))
-                    linestyle='--')
+            ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
     fig.canvas.manager.set_window_title('timeseries_delta')
@@ -312,12 +317,7 @@ def print_stats(sources, keys, stats_sum, precision, sort_by, table_format):
             style=termtables.styles.markdown,
         )
     elif table_format == 'json':
-        table = list()
+        table = [dict(zip(metrics, row.values())) for row in stats]
-        for row in stats:
-            row_table = dict()
-            for key, value in zip(metrics, row.values()):
-                row_table[key] = value
-            table.append(row_table)
         print(json.dumps(table))
     else:
         print(f'Unsupported table format: {table_format}')