mirror of
https://github.com/boostorg/histogram.git
synced 2025-05-10 07:14:05 +00:00
55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
import numpy as np
|
|
import json
|
|
from collections import defaultdict
|
|
import os
|
|
import re
|
|
import sys
|
|
import matplotlib.pyplot as plt
|
|
import matplotlib as mpl
|
|
mpl.rcParams.update(mpl.rcParamsDefault)
|
|
|
|
bench = defaultdict(lambda:[])
|
|
for iline, line in enumerate(open(sys.argv[1])):
|
|
if iline < 3:
|
|
continue
|
|
# Naive/(tuple, 3, inner)/4 3.44 ns
|
|
m = re.match("(\S+)/\((\S+), (\d), (\S+)\)/(\d+)\s*([0-9\.]+) ns", line)
|
|
name = m.group(1)
|
|
hist = m.group(2)
|
|
dim = int(m.group(3))
|
|
cov = m.group(4)
|
|
nbins = int(m.group(5))
|
|
time = float(m.group(6))
|
|
bench[(name, hist, dim, cov)].append((int(nbins) ** dim, time))
|
|
|
|
fig, ax = plt.subplots(1, 3, figsize=(10, 5), sharex=True, sharey=True)
|
|
if os.path.exists("/proc/cpuinfo"):
|
|
cpuinfo = open("/proc/cpuinfo").read()
|
|
m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
|
|
if m:
|
|
plt.suptitle(m.group(1))
|
|
plt.subplots_adjust(bottom=0.18, wspace=0, top=0.85, right=0.98, left=0.07)
|
|
for iaxis, axis_type in enumerate(("tuple", "vector", "vector_of_variant")):
|
|
plt.sca(ax[iaxis])
|
|
plt.title(axis_type.replace("_", " "), y=1.02)
|
|
handles = []
|
|
for (name, axis_t, dim, cov), v in bench.items():
|
|
if axis_t != axis_type: continue
|
|
if cov != "inner": continue
|
|
v = np.sort(v, axis=0).T
|
|
# if "semi_dynamic" in axis: continue
|
|
name2, col, ls = {
|
|
"Naive": ("nested for", "r", "--"),
|
|
"Indexed": ("indexed", "b", ":")}.get(name, (name, "k", "-"))
|
|
h = plt.plot(v[0], v[1] / v[0], color=col, ls=ls, lw=dim,
|
|
label=r"%s: $D=%i$" % (name2, dim))[0]
|
|
handles.append(h)
|
|
handles.sort(key=lambda x: x.get_label())
|
|
plt.loglog()
|
|
plt.sca(ax[0])
|
|
plt.ylabel("CPU time in ns per bin")
|
|
plt.legend(handles=handles, fontsize="x-small", frameon=False, handlelength=4, ncol=2)
|
|
plt.figtext(0.5, 0.05, "number of bins", ha="center")
|
|
plt.savefig("iteration_performance.svg")
|
|
plt.show()
|