#!/usr/bin/env python

#

#  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,

)

    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. / 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()

    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:

    else:

        print('reading from stdin')

        plot(json.load(sys.stdin))