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#!/usr/bin/env python3
# See LICENSE file for copyright and license details.
# Invoke using `env XKCD_STYLE=` to for more a comical plot style.
# Invoke using `env PER_BIT=` to divide all time values by the number
# of bits that where processed. This applies to 2-dimensional data only.
# Invoke using `env VIOLIN_STYLE=` to draw violin plots rather than
# box plots. This applies to multisample 1-dimensional data only.
# If used, used `env SHOW_MEAN=` will show that mean value in place
# of the median value.
# For multisample 1-dimensional, if `env VIOLIN_STYLE=` is not used
# `env NOTCH_STYLE=`, `env PATCH_ARTIST`, and `env SHOW_MEAN` may be
# applied.
import sys, os
import matplotlib.pyplot as plot
xkcdstyle = 'XKCD_STYLE' in os.environ
if xkcdstyle:
plot.xkcd()
fig = plot.figure()
xint = lambda x : (float(x) if '.' in x else int(x))
multiple = 1
smultiple = ''
multiples = [1] * len(sys.argv[1:])
smultiples = [''] * len(sys.argv[1:])
paths = [None] * len(sys.argv[1:])
i = 0
for arg in sys.argv[1:]:
if arg.startswith('*'):
multiples[i] = float(arg[1:])
smultiples[i] = ' * ' + arg[1:]
else:
paths[i] = arg
i += 1
multiples = multiples[:i]
smultiples = smultiples[:i]
paths = paths[:i]
xpoints = [None] * i
ypoints = [None] * i
values = [None] * i
labels = [None] * i
for i, path in enumerate(paths):
with open(path, 'rb') as file:
lines = file.read()
lines = lines.decode('utf-8', 'strict').split('\n')
labels[i], dim, values[i] = lines[0] + smultiples[i], int(lines[1]), lines[2:]
if dim > 1:
xpoints[i], values[i] = values[i][0], values[i][1:]
xpoints[i] = [int(x) for x in xpoints[i].split(' ')]
xpoints[i][1] += 1
xpoints[i] = list(range(*xpoints[i]))
if dim > 2:
ypoints[i], values[i] = values[i][0], values[i][1:]
ypoints[i] = [int(x) for x in ypoints[i].split(' ')]
ypoints[i][1] += 1
ypoints[i] = list(range(*ypoints[i]))
values[i] = [xint(v) * multiples[i] for v in values[i] if v != '']
if dim == 2:
if 'PER_BIT' in os.environ:
values[i] = [y / x for y, x in zip(values[i], xpoints[i])]
data = [[[i], (values[i], xpoints[i], ypoints[i])] for i in range(len(values))]
data.sort(key = lambda x : x[1])
merged, data = [data[0]], data[1:]
for ([i], d) in data:
if d == merged[-1][1]:
merged[-1][0].append(i)
else:
merged.append(([i], d))
xpoints = [xpoints[i[0]] for (i, _) in merged]
ypoints = [ypoints[i[0]] for (i, _) in merged]
values = [values[i[0]] for (i, _) in merged]
labels = [' & '.join(labels[j] for j in i) for (i, _) in merged]
vmin = min(min(min(v) for v in values), 0)
vmax = max(max(max(v) for v in values), 0)
if dim == 1:
plot.ylabel('time')
if len(values[0]) == 1:
plot.bar(range(len(values)),
[vs[0] for vs in values],
align = 'center',
orientation = 'vertical',
tick_label = labels)
labels = None
elif 'VIOLIN_STYLE' in os.environ:
plot.violinplot(values,
vert = True,
showmeans = 'SHOW_MEAN' in os.environ,
showmedians = 'SHOW_MEAN' not in os.environ,
showextrema = True)
else:
plot.boxplot(values,
vert = True,
notch = 'NOTCH_STYLE' in os.environ,
patch_artist = 'PATCH_ARTIST' in os.environ)
if 'SHOW_MEAN' in os.environ:
for i in range(len(values)):
mean = sum(values[i]) / len(values[i])
plot.plot([i + 0.75, i + 1.25], [mean, mean]);
if labels is not None:
plot.setp(fig.axes,
xticks = [x + 1 for x in range(len(values))],
xticklabels = labels)
elif dim == 2:
for i in range(len(values)):
plot.plot(xpoints[i], values[i], label = labels[i])
plot.legend(loc = 'best')
plot.xlabel('bits')
plot.ylabel('time')
elif dim == 3:
pass
plot.ylim((vmin * 1.1, vmax * 1.1))
if not xkcdstyle:
plot.grid(True)
plot.show()
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