mpv/TOOLS/stats-conv.py

89 lines
2.3 KiB
Python
Executable File

#!/usr/bin/env python3
import matplotlib.pyplot as plot
import sys
filename = sys.argv[1]
"""
This script is meant to display stats written by mpv --dump-stats=filename.
In general, each line in that file is an event of the form:
<timestamp in microseconds> <text> '#' <comment>
e.g.:
10474959 start flip #cplayer
<text> is what MP_STATS(log, "...") writes. The rest is added by msg.c.
Currently, the following event types are supported:
'start' <name> start of the named event
'end' <name> end of the named event
'value' <float> <name> a normal value (as opposed to event)
<event> singular event
"""
class G:
events = {}
sevents = [] # events, deterministically sorted
start = None
class Event:
pass
def get_event(event):
if event not in G.events:
e = Event()
G.events[event] = e
e.name = event
e.vals = []
e.type = "unknown"
G.sevents = list(G.events.values())
G.sevents.sort(key=lambda x: x.name)
return G.events[event]
for line in [line.split("#")[0].strip() for line in open(filename, "r")]:
ts, event = line.split(" ", 1)
ts = int(ts) / 1000 # milliseconds
if G.start is None:
G.start = ts
ts = ts - G.start
if event.startswith("start "):
e = get_event(event[6:])
e.type = "event"
e.vals.append((ts, 0))
e.vals.append((ts, 1))
elif event.startswith("end "):
e = get_event(event[4:])
e.type = "event"
e.vals.append((ts, 1))
e.vals.append((ts, 0))
elif event.startswith("value "):
_, val, name = event.split(" ", 2)
val = float(val)
e = get_event(name)
e.type = "value"
e.vals.append((ts, val))
else:
e = get_event(event)
e.type = "event-signal"
e.vals.append((ts, 1))
plot.hold(True)
mainpl = plot.subplot(2, 1, 1)
legend = []
for e in G.sevents:
if e.type == "value":
plot.subplot(2, 1, 2, sharex=mainpl)
else:
plot.subplot(2, 1, 1)
pl, = plot.plot([x for x,y in e.vals], [y for x,y in e.vals], label=e.name)
if e.type == "event-signal":
plot.setp(pl, marker = "o", linestyle = "None")
legend.append(pl)
plot.subplot(2, 1, 1)
plot.legend(legend, [pl.get_label() for pl in legend])
plot.show()