##// END OF EJS Templates
revlog: make the index always return the same tuple...
revlog: make the index always return the same tuple It is simpler to manage the diferrence in on disk format in the internal index code itself and lets the rest of the code always handle the same object. This will become even more important when the data we store will be entirely different (for example the changelog does not need the "linkrev" field. We start with item reading, we will deal with item writing in the next changesets. Differential Revision: https://phab.mercurial-scm.org/D10568

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perf-revlog-write-plot.py
126 lines | 3.2 KiB | text/x-python | PythonLexer
/ contrib / perf-utils / perf-revlog-write-plot.py
#!/usr/bin/env python3
#
# Copyright 2018 Paul Morelle <Paul.Morelle@octobus.net>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
#
# This script use the output of `hg perfrevlogwrite -T json --details` to draw
# various plot related to write performance in a revlog
#
# usage: perf-revlog-write-plot.py details.json
from __future__ import absolute_import, print_function
import json
import re
import numpy as np
import scipy.signal
from matplotlib import (
pyplot as plt,
ticker as mticker,
)
def plot(data, title=None):
items = {}
re_title = re.compile(r'^revisions #\d+ of \d+, rev (\d+)$')
for item in data:
m = re_title.match(item['title'])
if m is None:
continue
rev = int(m.group(1))
items[rev] = item
min_rev = min(items.keys())
max_rev = max(items.keys())
ary = np.empty((2, max_rev - min_rev + 1))
for rev, item in items.items():
ary[0][rev - min_rev] = rev
ary[1][rev - min_rev] = item['wall']
fig = plt.figure()
comb_plt = fig.add_subplot(211)
other_plt = fig.add_subplot(212)
comb_plt.plot(
ary[0], np.cumsum(ary[1]), color='red', linewidth=1, label='comb'
)
plots = []
p = other_plt.plot(ary[0], ary[1], color='red', linewidth=1, label='wall')
plots.append(p)
colors = {
10: ('green', 'xkcd:grass green'),
100: ('blue', 'xkcd:bright blue'),
1000: ('purple', 'xkcd:dark pink'),
}
for n, color in colors.items():
avg_n = np.convolve(ary[1], np.full(n, 1.0 / n), 'valid')
p = other_plt.plot(
ary[0][n - 1 :],
avg_n,
color=color[0],
linewidth=1,
label='avg time last %d' % n,
)
plots.append(p)
med_n = scipy.signal.medfilt(ary[1], n + 1)
p = other_plt.plot(
ary[0],
med_n,
color=color[1],
linewidth=1,
label='median time last %d' % n,
)
plots.append(p)
formatter = mticker.ScalarFormatter()
formatter.set_scientific(False)
formatter.set_useOffset(False)
comb_plt.grid()
comb_plt.xaxis.set_major_formatter(formatter)
comb_plt.legend()
other_plt.grid()
other_plt.xaxis.set_major_formatter(formatter)
leg = other_plt.legend()
leg2plot = {}
for legline, plot in zip(leg.get_lines(), plots):
legline.set_picker(5)
leg2plot[legline] = plot
def onpick(event):
legline = event.artist
plot = leg2plot[legline]
visible = not plot[0].get_visible()
for l in plot:
l.set_visible(visible)
if visible:
legline.set_alpha(1.0)
else:
legline.set_alpha(0.2)
fig.canvas.draw()
if title is not None:
fig.canvas.set_window_title(title)
fig.canvas.mpl_connect('pick_event', onpick)
plt.show()
if __name__ == '__main__':
import sys
if len(sys.argv) > 1:
print('reading from %r' % sys.argv[1])
with open(sys.argv[1], 'r') as fp:
plot(json.load(fp), title=sys.argv[1])
else:
print('reading from stdin')
plot(json.load(sys.stdin))