Imported Upstream version 1.72.0

[platform/upstream/boost.git] / libs / histogram / doc / fill_performance.py

diff --git a/libs/histogram/doc/fill_performance.py b/libs/histogram/doc/fill_performance.py
index 661a1f2..4645963 100755 (executable)
--- a/libs/histogram/doc/fill_performance.py
+++ b/libs/histogram/doc/fill_performance.py
@@ -1,9 +1,16 @@
 #!/usr/bin/env python3
+
+#            Copyright Hans Dembinski 2018 - 2019.
+#   Distributed under the Boost Software License, Version 1.0.
+#      (See accompanying file LICENSE_1_0.txt or copy at
+#            https://www.boost.org/LICENSE_1_0.txt)
+
 import os
 import numpy as np
 import glob
 import re
 import json
+import sys
 from collections import defaultdict, OrderedDict
 from matplotlib.patches import Rectangle
 from matplotlib.lines import Line2D
@@ -11,72 +18,101 @@ from matplotlib.text import Text
 from matplotlib.font_manager import FontProperties
 import matplotlib.pyplot as plt
 import matplotlib as mpl
+
 mpl.rcParams.update(mpl.rcParamsDefault)
 
-data = defaultdict(lambda:[])
-for fn in glob.glob("fill_*.json"):
-    for bench in json.load(open(fn))["benchmarks"]:
+cpu_frequency = 0
+
+data = defaultdict(lambda: [])
+for fn in sys.argv[1:]:
+    d = json.load(open(fn))
+    cpu_frequency = d["context"]["mhz_per_cpu"]
+    for bench in d["benchmarks"]:
         name = bench["name"]
         time = min(bench["cpu_time"], bench["real_time"])
-        m = re.match("fill_([0-9])d<([^>]+)>", name)
-        tags = m.group(2).split(", ")
-        dim = int(m.group(1))
-        label = re.search("fill_([a-z]+).json", fn).group(1)
+        m = re.match("fill_(n_)?([0-9])d<([^>]+)>", name)
+        if m.group(1):
+            time /= 1 << 15
+        tags = m.group(3).split(", ")
+        dim = int(m.group(2))
+        label = re.search(
+            "fill_([a-z]+)", os.path.splitext(os.path.split(fn)[1])[0]
+        ).group(1)
         dist = tags[0]
-        if label == "boost":
-            label += "-" + {"dynamic_tag":"D", "static_tag":"S"}[tags[1]] + tags[2][0]
+        if len(tags) > 1 and tags[1] in ("dynamic_tag", "static_tag"):
+            if len(tags) == 3 and "DStore" in tags[2]:
+                continue
+            label += "-" + {"dynamic_tag": "dyn", "static_tag": "sta"}[tags[1]]
+            label += "-fill" if m.group(1) else "-call"
         data[dim].append((label, dist, time / dim))
 
-plt.figure()
-if os.path.exists("/proc/cpuinfo"):
-    cpuinfo = open("/proc/cpuinfo").read()
-    m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
-    if m:
-        plt.title(m.group(1))
+time_per_cycle_in_ns = 1.0 / (cpu_frequency * 1e6) / 1e-9
+
+plt.figure(figsize=(7, 6))
 i = 0
 for dim in sorted(data):
     v = data[dim]
     labels = OrderedDict()
     for label, dist, time in v:
         if label in labels:
-            labels[label][dist] = time
+            labels[label][dist] = time / time_per_cycle_in_ns
         else:
-            labels[label] = {dist: time}
+            labels[label] = {dist: time / time_per_cycle_in_ns}
     j = 0
     for label, d in labels.items():
         t1 = d["uniform"]
         t2 = d["normal"]
         i -= 1
         z = float(j) / len(labels)
-        col = ((1.0-z) * np.array((1.0, 0.0, 0.0))
-               + z * np.array((1.0, 1.0, 0.0)))
+        col = (1.0 - z) * np.array((1.0, 0.0, 0.0)) + z * np.array((1.0, 1.0, 0.0))
         if label == "root":
             col = "k"
+            label = "ROOT 6"
         if "numpy" in label:
             col = "0.6"
         if "gsl" in label:
             col = "0.3"
+            label = "GSL"
         tmin = min(t1, t2)
         tmax = max(t1, t2)
         r1 = Rectangle((0, i), tmax, 1, facecolor=col)
-        r2 = Rectangle((tmin, i), tmax-tmin, 1, facecolor="none", edgecolor="w", hatch="//////")
+        r2 = Rectangle(
+            (tmin, i), tmax - tmin, 1, facecolor="none", edgecolor="w", hatch="//////"
+        )
         plt.gca().add_artist(r1)
         plt.gca().add_artist(r2)
-        tx = Text(-0.1, i+0.5, "%s" % label,
-                  va="center", ha="right", clip_on=False)
+        font = FontProperties(size=9)
+        tx = Text(
+            -0.5,
+            i + 0.5,
+            "%s" % label,
+            fontproperties=font,
+            va="center",
+            ha="right",
+            clip_on=False,
+        )
         plt.gca().add_artist(tx)
         j += 1
     i -= 1
-    font0 = FontProperties()
-    font0.set_weight("bold")
-    tx = Text(-0.1, i+0.6, "%iD" % dim,
-              fontproperties=font0, va="center", ha="right", clip_on=False)
+    font = FontProperties()
+    font.set_weight("bold")
+    tx = Text(
+        -0.5,
+        i + 0.6,
+        "%iD" % dim,
+        fontproperties=font,
+        va="center",
+        ha="right",
+        clip_on=False,
+    )
     plt.gca().add_artist(tx)
 plt.ylim(0, i)
-plt.xlim(0, 20)
+plt.xlim(0, 80)
 
 plt.tick_params("y", left=False, labelleft=False)
-plt.xlabel("fill time per random input value in nanoseconds (smaller is better)")
+plt.xlabel("average CPU cycles per random input value (smaller is better)")
+
+plt.tight_layout()
 
 plt.savefig("fill_performance.svg")
 plt.show()