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Merge branch 'osg_stats_hist_threshold' into 'master'

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Stacked histogram for frames with duration over given threshold for osg_stats

See merge request OpenMW/openmw!1230
This commit is contained in:
psi29a 2021-09-27 19:06:35 +00:00
commit c7f668457c
1 changed files with 65 additions and 21 deletions
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86
scripts/osg_stats.py
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@ -38,27 +38,41 @@ import termtables
@click.option('--timeseries_sum', is_flag=True,
help='Add a graph to timeseries for a sum per frame of all given timeseries metrics.')
@click.option('--commulative_timeseries_sum', is_flag=True,
help='Add a graph to timeseries for a sum per frame of all given commulative timeseries.')
help='Add a graph to timeseries for a sum per frame of all given commulative timeseries.')
@click.option('--stats_sum', is_flag=True,
help='Add a row to stats table for a sum per frame of all given stats metrics.')
@click.option('--begin_frame', type=int, default=0,
help='Start processing from this frame.')
@click.option('--end_frame', type=int, default=sys.maxsize,
help='End processing at this frame.')
@click.option('--frame_number_name', type=str, default='FrameNumber',
help='Frame number metric name.')
@click.option('--hist_threshold', type=str, multiple=True,
help='Show a histogram for given metric only for frames with threshold_name metric over threshold_value.')
@click.option('--threshold_name', type=str, default='Frame duration',
help='Frame duration metric name.')
@click.option('--threshold_value', type=float, default=1.05/60,
help='Threshold for hist_over.')
@click.argument('path', type=click.Path(), nargs=-1)
def main(print_keys, timeseries, hist, hist_ratio, stdev_hist, plot, stats,
timeseries_sum, stats_sum, begin_frame, end_frame, path,
commulative_timeseries, commulative_timeseries_sum):
commulative_timeseries, commulative_timeseries_sum, frame_number_name,
hist_threshold, threshold_name, threshold_value):
sources = {v: list(read_data(v)) for v in path} if path else {'stdin': list(read_data(None))}
keys = collect_unique_keys(sources)
frames = collect_per_frame(sources=sources, keys=keys, begin_frame=begin_frame, end_frame=end_frame)
frames, begin_frame, end_frame = collect_per_frame(
sources=sources, keys=keys, begin_frame=begin_frame,
end_frame=end_frame, frame_number_name=frame_number_name,
)
if print_keys:
for v in keys:
print(v)
if timeseries:
draw_timeseries(sources=frames, keys=timeseries, add_sum=timeseries_sum)
draw_timeseries(sources=frames, keys=timeseries, add_sum=timeseries_sum,
begin_frame=begin_frame, end_frame=end_frame)
if commulative_timeseries:
draw_commulative_timeseries(sources=frames, keys=commulative_timeseries, add_sum=commulative_timeseries_sum)
draw_commulative_timeseries(sources=frames, keys=commulative_timeseries, add_sum=commulative_timeseries_sum,
begin_frame=begin_frame, end_frame=end_frame)
if hist:
draw_hists(sources=frames, keys=hist)
if hist_ratio:
@ -69,6 +83,9 @@ def main(print_keys, timeseries, hist, hist_ratio, stdev_hist, plot, stats,
draw_plots(sources=frames, plots=plot)
if stats:
print_stats(sources=frames, keys=stats, stats_sum=stats_sum)
if hist_threshold:
draw_hist_threshold(sources=frames, keys=hist_threshold, begin_frame=begin_frame,
threshold_name=threshold_name, threshold_value=threshold_value)
matplotlib.pyplot.show()
@ -92,19 +109,26 @@ def read_data(path):
frame[key] = to_number(value)
def collect_per_frame(sources, keys, begin_frame, end_frame):
def collect_per_frame(sources, keys, begin_frame, end_frame, frame_number_name):
assert begin_frame < end_frame
result = collections.defaultdict(lambda: collections.defaultdict(list))
begin_frame = max(begin_frame, min(v[0][frame_number_name] for v in sources.values()))
end_frame = min(end_frame, begin_frame + max(len(v) for v in sources.values()))
for name in sources.keys():
for key in keys:
result[name][key] = [0] * (end_frame - begin_frame)
for name, frames in sources.items():
for frame in frames:
for key in keys:
if key in frame:
result[name][key].append(frame[key])
else:
result[name][key].append(None)
for name, sources in result.items():
for key, values in sources.items():
result[name][key] = numpy.array(values[begin_frame:end_frame])
return result
number = frame[frame_number_name]
if begin_frame <= number < end_frame:
index = number - begin_frame
for key in keys:
if key in frame:
result[name][key][index] = frame[key]
for name in result.keys():
for key in keys:
result[name][key] = numpy.array(result[name][key])
return result, begin_frame, end_frame
def collect_unique_keys(sources):
@ -116,12 +140,11 @@ def collect_unique_keys(sources):
return sorted(result)
def draw_timeseries(sources, keys, add_sum):
def draw_timeseries(sources, keys, add_sum, begin_frame, end_frame):
fig, ax = matplotlib.pyplot.subplots()
x = numpy.array(range(begin_frame, end_frame))
for name, frames in sources.items():
x = numpy.array(range(max(len(v) for k, v in frames.items() if k in keys)))
for key in keys:
print(key, name)
ax.plot(x, frames[key], 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}')
@ -130,10 +153,10 @@ def draw_timeseries(sources, keys, add_sum):
fig.canvas.set_window_title('timeseries')
def draw_commulative_timeseries(sources, keys, add_sum):
def draw_commulative_timeseries(sources, keys, add_sum, begin_frame, end_frame):
fig, ax = matplotlib.pyplot.subplots()
x = numpy.array(range(begin_frame, end_frame))
for name, frames in sources.items():
x = numpy.array(range(max(len(v) for k, v in frames.items() if k in keys)))
for key in keys:
ax.plot(x, numpy.cumsum(frames[key]), label=f'{key}:{name}')
if add_sum:
@ -227,7 +250,6 @@ def print_stats(sources, keys, stats_sum):
if stats_sum:
stats.append(make_stats(source=name, key='sum', values=sum_multiple(frames, keys)))
metrics = list(stats[0].keys())
max_key_size = max(len(tuple(v.values())[0]) for v in stats)
termtables.print(
[list(v.values()) for v in stats],
header=metrics,
@ -235,6 +257,27 @@ def print_stats(sources, keys, stats_sum):
)
def draw_hist_threshold(sources, keys, begin_frame, threshold_name, threshold_value):
for name, frames in sources.items():
indices = [n for n, v in enumerate(frames[threshold_name]) if v > threshold_value]
numbers = [v + begin_frame for v in indices]
x = [v for v in range(0, len(indices))]
fig, ax = matplotlib.pyplot.subplots()
ax.set_title(f'Frames with "{threshold_name}" > {threshold_value} ({len(indices)})')
ax.bar(x, [frames[threshold_name][v] for v in indices], label=threshold_name, color='black', alpha=0.2)
prev = 0
for key in keys:
values = [frames[key][v] for v in indices]
ax.bar(x, values, bottom=prev, label=key)
prev = values
ax.hlines(threshold_value, x[0] - 1, x[-1] + 1, color='black', label='threshold', linestyles='dashed')
ax.xaxis.set_major_locator(matplotlib.pyplot.FixedLocator(x))
ax.xaxis.set_major_formatter(matplotlib.pyplot.FixedFormatter(numbers))
ax.grid(True)
ax.legend()
fig.canvas.set_window_title(f'hist_threshold:{name}')
def filter_not_none(values):
return [v for v in values if v is not None]
@ -269,5 +312,6 @@ def to_number(value):
except ValueError:
return float(value)
if __name__ == '__main__':
main()