mpv/TOOLS/stats-conv.py

136 lines
3.9 KiB
Python
Executable File

#!/usr/bin/env python3
import matplotlib.pyplot as plot
import sys
import re
filename = sys.argv[1]
event_regex = re.compile(".*")
"""
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:
'signal' <name> singular event
'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-timed' <ts> <name> singular event at the given timestamp
'value-timed' <ts> <float> <name>
a value for an event at the given timestamp
<name> singular event (same as 'signal')
"""
class G:
events = {}
start = None
# http://matplotlib.org/api/markers_api.html#module-matplotlib.markers
markers = ["o", "8", "s", "p", "*", "h", "+", "x", "D"]
def find_marker():
if len(G.markers) == 0:
return "o"
m = G.markers[0]
G.markers = G.markers[1:]
return m
class Event:
pass
def get_event(event, evtype):
if event not in G.events:
e = Event()
e.name = event
e.vals = []
e.type = evtype
e.marker = "o"
if e.type == "event-signal":
e.marker = find_marker()
if not event_regex.match(e.name):
return e
G.events[event] = e
return G.events[event]
SCALE = 1e6 # microseconds to seconds
for line in [line.split("#")[0].strip() for line in open(filename, "r")]:
line = line.strip()
if not line:
continue
ts, event = line.split(" ", 1)
ts = int(ts) / SCALE
if G.start is None:
G.start = ts
ts = ts - G.start
if event.startswith("start "):
e = get_event(event[6:], "event")
e.vals.append((ts, 0))
e.vals.append((ts, 1))
elif event.startswith("end "):
e = get_event(event[4:], "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, "value")
e.vals.append((ts, val))
elif event.startswith("event-timed "):
_, val, name = event.split(" ", 2)
val = int(val) / SCALE - G.start
e = get_event(name, "event-signal")
e.vals.append((val, 1))
elif event.startswith("value-timed "):
_, tsval, val, name = event.split(" ", 3)
tsval = int(tsval) / SCALE - G.start
val = float(val)
e = get_event(name, "value")
e.vals.append((tsval, val))
elif event.startswith("signal "):
name = event.split(" ", 2)[1]
e = get_event(name, "event-signal")
e.vals.append((ts, 1))
else:
e = get_event(event, "event-signal")
e.vals.append((ts, 1))
# deterministically sort them; make sure the legend is sorted too
G.sevents = list(G.events.values())
G.sevents.sort(key=lambda x: x.name)
hasval = False
for e, index in zip(G.sevents, range(len(G.sevents))):
m = len(G.sevents)
if e.type == "value":
hasval = True
else:
e.vals = [(x, y * (m - index) / m) for (x, y) in e.vals]
fig = plot.figure()
fig.hold(True)
ax = [None, None]
plots = 2 if hasval else 1
ax[0] = fig.add_subplot(plots, 1, 1)
if hasval:
ax[1] = fig.add_subplot(plots, 1, 2, sharex=ax[0])
legends = [[], []]
for e in G.sevents:
cur = ax[1 if e.type == "value" else 0]
pl, = cur.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 = e.marker, linestyle = "None")
for cur in ax:
if cur is not None:
cur.legend()
plot.show()