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tl-barplot.py
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tl-barplot.py
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#!/usr/bin/env python3
# plot toplev -I... -x, -o ...csv output as bar plot
#
from __future__ import print_function
import os
import re
import argparse
from math import isnan, trunc
from collections import defaultdict
import matplotlib
if os.getenv('DISPLAY') is None:
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import gen_level
import tldata
def parse_args():
p = argparse.ArgumentParser(usage='plot toplev -I... -x, output as bar plot')
p.add_argument('file', help='CSV file to plot')
p.add_argument('--output', '-o', help='Save figure to file (.pdf/.png/etc). Otherwise show.',
nargs='?')
p.add_argument('--verbose', '-v', help='Plot all data values even if below threshold', action='store_true')
p.add_argument('--xkcd', help='Enable XKCD mode (with new matplotlib). Please install Humor Sans.', action='store_true')
p.add_argument('--title', help='Set title of plot', nargs='?')
p.add_argument('--quiet', help='Be quiet', action='store_true')
p.add_argument('--cpu', help='CPU to plot (by default first)') # XXX
return p.parse_args()
args = parse_args()
try:
import brewer2mpl
except ImportError:
if not args.quiet:
print("pip install brewer2mpl for better colors")
if args.xkcd:
plt.xkcd()
data = tldata.TLData(args.file, args.verbose)
data.update()
levels = data.levels
timestamps = data.times
ratios = defaultdict(list)
# XXX plot multiple cpus instead
cpu = None
if args.cpu:
cpu = args.cpu
elif 'CLKS' in data.headers and len(data.vals) > 0:
# pick CPU with highest utilization. XXX look at all time series
util = sorted([(data.vals[0][x], x[1]) for x in data.vals[0].keys() if x[0] == 'CLKS'],
reverse=True)
cpu = util[0][1]
elif len(data.cpus) > 0:
cpu = sorted(sorted(data.cpus), key=len, reverse=True)[0]
def cpumatch(x, cpu, base):
return x.startswith(cpu) or x == base
if cpu:
base = None
m = re.match(r'C\d+', cpu)
if m:
base = m.group(0)
aliases = [x for x in data.cpus if cpumatch(x, cpu, base)]
print("plotting cpus:", " ".join(sorted(aliases)))
else:
aliases = []
if len(aliases) == 0:
aliases = [None]
for h in data.headers:
def findval(d):
for c in aliases:
if (h, c) in d:
return d[(h, c)]
return float('nan')
ratios[h] = list(map(findval, data.vals))
def valid_row(r):
s = sum(r)
#if sum([0 if isnan(x) else 1 for x in r]) < len(r)/80.:
# return False
return s != 0.0 and not isnan(s)
def get_colors(non_null):
if 'brewer2mpl' in globals():
num_color = max(min(len(non_null), 11), 3)
all_colors = brewer2mpl.get_map('Spectral', 'Diverging', num_color).hex_colors
else:
all_colors = None
return all_colors
def set_title(ax, t):
try:
ax.set_title(t, {'fontsize': 6}, loc='right')
except AttributeError:
ax.set_title(t)
def suffix(x):
dot = x.rfind('.')
if dot >= 0:
return x[dot + 1:]
return x
n = 0
numplots = len(levels.keys())
ax = None
yset = False
max_legend = 0
xaxis = None
legend_bbox = (0., 0., -0.07, -0.03)
legend_loc = 2
for l in tldata.level_order(data):
non_null = [x for x in levels[l] if valid_row(ratios[x])]
if not non_null:
n += 1
continue
all_colors = get_colors(non_null)
ax = plt.subplot2grid((numplots, 1), (n, 0), sharex=xaxis)
plt.tight_layout()
set_title(ax, l)
r = [[y if not isnan(y) else 0.0 for y in ratios[x]] for x in non_null]
if gen_level.is_metric(non_null[0]):
for j, name in zip(r, non_null):
stack = ax.plot(timestamps, j, label=name)
leg = plt.legend(ncol=6,
loc=legend_loc,
bbox_to_anchor=legend_bbox,
prop={'size':6})
low = min([min(ratios[x]) for x in non_null])
high = max([max(ratios[x]) for x in non_null])
if not isnan(low) and not isnan(high):
ax.yaxis.set_ticks([low, trunc(((high - low) / 2.0) / 100.) * 100., high])
else:
stack = ax.stackplot(timestamps, *r, colors=all_colors)
ax.set_ylim(0, 100)
ax.yaxis.set_ticks([0., 50., 100.])
p = [plt.Rectangle((0, 0), 1, 1, fc=pc.get_facecolor()[0]) for pc in stack]
leg = plt.legend(p, list(map(suffix, non_null)),
ncol=6,
bbox_to_anchor=legend_bbox,
loc=legend_loc,
prop={'size':6})
leg.get_frame().set_alpha(0.5)
for j in ax.get_xticklabels() + ax.get_yticklabels():
j.set_fontsize(6)
if not xaxis:
xaxis = ax
#if n >= 2 and not yset and l != -1:
# ax.set_ylabel('(% of execution time)')
# yset = True
if n != numplots:
max_legend = max(len(non_null), max_legend)
#ax.margins(0, 0)
n += 1
if len(timestamps) == 1:
plt.gca().axes.get_xaxis().set_visible(False)
plt.subplots_adjust(hspace=1.5 if max_legend > 6 else 0.9, bottom=0.20,
top=0.95)
if args.title:
#plt.subplot(numplots, 1, 1)
plt.title(args.title)
if args.output:
plt.savefig(args.output)
else:
plt.show()