mirror of https://github.com/mpv-player/mpv
136 lines
3.9 KiB
Python
Executable File
136 lines
3.9 KiB
Python
Executable File
#!/usr/bin/env python3
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import matplotlib.pyplot as plot
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import sys
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import re
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filename = sys.argv[1]
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event_regex = re.compile(".*")
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"""
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This script is meant to display stats written by mpv --dump-stats=filename.
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In general, each line in that file is an event of the form:
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<timestamp in microseconds> <text> '#' <comment>
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e.g.:
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10474959 start flip #cplayer
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<text> is what MP_STATS(log, "...") writes. The rest is added by msg.c.
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Currently, the following event types are supported:
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'signal' <name> singular event
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'start' <name> start of the named event
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'end' <name> end of the named event
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'value' <float> <name> a normal value (as opposed to event)
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'event-timed' <ts> <name> singular event at the given timestamp
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'value-timed' <ts> <float> <name>
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a value for an event at the given timestamp
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<name> singular event (same as 'signal')
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"""
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class G:
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events = {}
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start = None
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# http://matplotlib.org/api/markers_api.html#module-matplotlib.markers
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markers = ["o", "8", "s", "p", "*", "h", "+", "x", "D"]
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def find_marker():
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if len(G.markers) == 0:
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return "o"
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m = G.markers[0]
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G.markers = G.markers[1:]
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return m
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class Event:
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pass
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def get_event(event, evtype):
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if event not in G.events:
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e = Event()
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e.name = event
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e.vals = []
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e.type = evtype
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e.marker = "o"
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if e.type == "event-signal":
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e.marker = find_marker()
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if not event_regex.match(e.name):
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return e
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G.events[event] = e
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return G.events[event]
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SCALE = 1e6 # microseconds to seconds
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for line in [line.split("#")[0].strip() for line in open(filename, "r")]:
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line = line.strip()
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if not line:
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continue
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ts, event = line.split(" ", 1)
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ts = int(ts) / SCALE
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if G.start is None:
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G.start = ts
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ts = ts - G.start
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if event.startswith("start "):
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e = get_event(event[6:], "event")
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e.vals.append((ts, 0))
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e.vals.append((ts, 1))
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elif event.startswith("end "):
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e = get_event(event[4:], "event")
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e.vals.append((ts, 1))
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e.vals.append((ts, 0))
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elif event.startswith("value "):
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_, val, name = event.split(" ", 2)
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val = float(val)
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e = get_event(name, "value")
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e.vals.append((ts, val))
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elif event.startswith("event-timed "):
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_, val, name = event.split(" ", 2)
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val = int(val) / SCALE - G.start
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e = get_event(name, "event-signal")
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e.vals.append((val, 1))
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elif event.startswith("value-timed "):
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_, tsval, val, name = event.split(" ", 3)
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tsval = int(tsval) / SCALE - G.start
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val = float(val)
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e = get_event(name, "value")
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e.vals.append((tsval, val))
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elif event.startswith("signal "):
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name = event.split(" ", 2)[1]
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e = get_event(name, "event-signal")
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e.vals.append((ts, 1))
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else:
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e = get_event(event, "event-signal")
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e.vals.append((ts, 1))
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# deterministically sort them; make sure the legend is sorted too
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G.sevents = list(G.events.values())
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G.sevents.sort(key=lambda x: x.name)
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hasval = False
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for e, index in zip(G.sevents, range(len(G.sevents))):
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m = len(G.sevents)
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if e.type == "value":
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hasval = True
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else:
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e.vals = [(x, y * (m - index) / m) for (x, y) in e.vals]
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fig = plot.figure()
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fig.hold(True)
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ax = [None, None]
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plots = 2 if hasval else 1
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ax[0] = fig.add_subplot(plots, 1, 1)
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if hasval:
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ax[1] = fig.add_subplot(plots, 1, 2, sharex=ax[0])
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legends = [[], []]
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for e in G.sevents:
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cur = ax[1 if e.type == "value" else 0]
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pl, = cur.plot([x for x,y in e.vals], [y for x,y in e.vals], label=e.name)
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if e.type == "event-signal":
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plot.setp(pl, marker = e.marker, linestyle = "None")
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for cur in ax:
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if cur is not None:
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cur.legend()
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plot.show()
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