Consider absent value in a frame as none

There are frames with missing values because of loading screens. They should not
be replaced with zeroes or other values. Otherwise showed graphs and calculated
statistics are wrong.

scripts/osg_stats.py

@@ -159,13 +159,7 @@ def collect_per_frame(sources, keys, begin_frame, end_frame, frame_number_name):
                     if key in frame:
                         result[name][key][index] = frame[key]
         for key in keys:
-            prev = 0.0
             values = result[name][key][:max_index + 1]
-            for i in range(len(values)):
-                if values[i] is not None:
-                    prev = values[i]
-                else:
-                    values[i] = prev
             result[name][key] = numpy.array(values)
     return result, begin_frame, end_frame
 
@@ -187,7 +181,7 @@ def draw_timeseries(sources, keys, add_sum, begin_frame, end_frame):
             y = frames[key]
             ax.plot(x[:len(y)], y, label=f'{key}:{name}')
         if add_sum:
-            y = numpy.sum(list(frames[k] for k in keys), axis=0)
+            y = sum_arrays_with_none([frames[k] for k in keys])
             ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
@@ -199,10 +193,10 @@ def draw_cumulative_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:
-            y = numpy.cumsum(frames[key])
+            y = cumsum_with_none(frames[key])
             ax.plot(x[:len(y)], y, label=f'{key}:{name}')
         if add_sum:
-            y = numpy.cumsum(numpy.sum(list(frames[k] for k in keys), axis=0))
+            y = sum_arrays_with_none([cumsum_with_none(frames[k]) for k in keys])
             ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
@@ -214,10 +208,10 @@ 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:
-            y = numpy.diff(frames[key])
-            ax.plot(x[:len(y)], numpy.diff(frames[key]), label=f'{key}:{name}')
+            y = diff_with_none(frames[key])
+            ax.plot(x[:len(y)], y, label=f'{key}:{name}')
         if add_sum:
-            y = numpy.diff(numpy.sum(list(frames[k] for k in keys), axis=0))
+            y = sum_arrays_with_none([diff_with_none(frames[k]) for k in keys])
             ax.plot(x[:len(y)], y, label=f'sum:{name}', linestyle='--')
     ax.grid(True)
     ax.legend()
@@ -367,13 +361,13 @@ def make_stats(source, key, values, precision):
         source=source,
         key=key,
         number=len(values),
-        min=fixed_float(min(values), precision),
-        max=fixed_float(max(values), precision),
-        sum=fixed_float(sum(values), precision),
-        mean=fixed_float(statistics.mean(values), precision),
-        median=fixed_float(statistics.median(values), precision),
-        stdev=fixed_float(statistics.stdev(float(v) for v in values), precision),
-        q95=fixed_float(numpy.quantile(values, 0.95), precision),
+        min=fixed_float(min(values), precision) if values else '-',
+        max=fixed_float(max(values), precision) if values else '-',
+        sum=fixed_float(sum(values), precision) if values else '-',
+        mean=fixed_float(statistics.mean(values), precision) if values else '-',
+        median=fixed_float(statistics.median(values), precision) if values else '-',
+        stdev=fixed_float(statistics.stdev(float(v) for v in values), precision) if values else '-',
+        q95=fixed_float(numpy.quantile(values, 0.95), precision) if values else '-',
     )
 
 
@@ -384,5 +378,49 @@ def to_number(value):
         return float(value)
 
 
+def cumsum_with_none(values):
+    cumsum = None
+    result = list()
+    for v in values:
+        if v is None:
+            result.append(None)
+        elif cumsum is None:
+            cumsum = v
+            result.append(cumsum)
+        else:
+            cumsum += v
+            result.append(cumsum)
+    return numpy.array(result)
+
+
+def diff_with_none(values):
+    if len(values) < 2:
+        return numpy.array([])
+    prev = values[0]
+    result = list()
+    for v in values[1:]:
+        if prev is None:
+            result.append(v)
+            prev = v
+        elif v is None:
+            result.append(v)
+        else:
+            result.append(v - prev)
+            prev = v
+    return numpy.array(result)
+
+
+def sum_arrays_with_none(arrays):
+    size = max(len(v) for v in arrays)
+    result = list()
+    for i in range(size):
+        not_none_values = [v[i] for v in arrays if v[i] is not None]
+        if not_none_values:
+            result.append(sum(not_none_values))
+        else:
+            result.append(None)
+    return numpy.array(result)
+
+
 if __name__ == '__main__':
     main()