From 51ba4727bf69a5370a12a42bbb0adb2f33170d5f Mon Sep 17 00:00:00 2001
From: florijan <florijan@memgraph.io>
Date: Wed, 6 Sep 2017 10:31:26 +0200
Subject: [PATCH] Gbench plot tool added
Summary: See script docs.
Reviewers: buda, teon.banek, mislav.bradac
Reviewed By: teon.banek
Subscribers: pullbot
Differential Revision: https://phabricator.memgraph.io/D755
---
tools/plot_gbench_json | 128 +++++++++++++++++++++++++++++++++++++++++
1 file changed, 128 insertions(+)
create mode 100755 tools/plot_gbench_json
diff --git a/tools/plot_gbench_json b/tools/plot_gbench_json
new file mode 100755
index 000000000..0b34b5121
--- /dev/null
+++ b/tools/plot_gbench_json
@@ -0,0 +1,128 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+"""
+A tool for plotting Google benchmark results using matplotlib. Requires
+Python3, matplotlib and gbench data in JSON format.
+
+Does a few nice things for you:
+ 1. Can be used with file input (cmd line arg) or reading from stdin
+ 2. Groups benchmarks into multiple plots based on benchmark name.
+ This is currently implemented to work well with template based
+ benchmarks, it might required mods.
+ 3. Automatically detects the need for log-scale on both axes.
+
+Missing features:
+ 1. Proper support for benchmarks that use two arguments.
+ 2. Proper handling for all types of benchmark structures, name parsing
+ in this implementation is made for template-based benches.
+ 3. Plotting to image files. This implementation plots to the GUI (you can
+ save images there).
+
+Usage:
+ # Generate benchmark data in json format using:
+ > ./my_bench --benchmark_out_format=json --benchmark_out=data.json
+ # Use that data with plotter:
+ > ./plot_bench_json data.json
+
+Alternatively you can route stuff and avoid using an intermediary file:
+ sh > ./my_bench --benchmark_out_format=json --benchmark_out=/dev/stderr 2>&1 >/dev/null | grep "^[{} ]" | plot_gbench_json
+
+Maybe there is a nicer way to route it?
+"""
+
+import re
+import fileinput
+import json
+from collections import defaultdict
+
+from matplotlib import pyplot as plt
+
+
+def convert_num(string):
+ """
+ Converts stuff like "100" and "3k" to numbers.
+ """
+ suffix_re = re.search("\D+$", string)
+
+ if not suffix_re:
+ return float(string)
+
+ suffix = string[suffix_re.start():]
+ number = float(string[:suffix_re.start()])
+
+ if suffix == "k":
+ number *= 1000
+ else:
+ raise ValueError("Unknown number suffix: " + suffix)
+
+ return number
+
+
+def is_exponential_growth(numbers):
+ """
+ Tries to determine if the given numbers progress more in logarithmic then
+ in linear fashion. Assumes numbers increase monotonically.
+ """
+ diffs = [n2 - n1 for (n1, n2) in zip(numbers, numbers[1:])]
+ factors = [n2 / n1 for (n1, n2) in zip(numbers, numbers[1:])]
+
+ # constant diff implies linear increase, constant factor implies exp
+ # which is more constant?
+ diff_rms = [(d - (sum(diffs) / len(diffs))) ** 2 for d in diffs]
+ factor_rms = [(f - (sum(factors) / len(factors))) ** 2 for f in factors]
+ return sum(factor_rms) < sum(diff_rms)
+
+
+def main():
+ data = json.loads("".join(fileinput.input()).strip())
+
+ # structure: {bench_name: [(x, y, time_unit), ...]
+ benchmarks = defaultdict(list)
+
+ for bench in data["benchmarks"]:
+ name, x = bench["name"].rsplit("/", 1)
+ benchmarks[name].append((convert_num(x), bench["real_time"],
+ bench["time_unit"]))
+
+ # group benchmarks on name prefix
+ # one group will be one plot with possibly multiple lines
+ benchmarks_groups = defaultdict(dict)
+ for name, data in benchmarks.items():
+ name_split = re.split("\W", name, 1)
+ if len(name_split) == 2:
+ group, element = name_split
+ benchmarks_groups[group][element] = data
+ else:
+ benchmarks_groups["__all_benchmarks__"][name] = data
+
+ # validate all the time units per group (one plot)
+ for measurements in benchmarks_groups.values():
+ units = set()
+ for measurement in measurements.values():
+ units.update(k[2] for k in measurement)
+ if len(units) > 1:
+ raise ValueError(
+ "Multiple time units in a single plot: %r" % units)
+
+ # plot all groups
+ for group_name, measurements in benchmarks_groups.items():
+ plt.figure()
+ log_x, log_y = False, False
+ for line, values in measurements.items():
+ x, y, _ = zip(*values)
+ log_x |= is_exponential_growth(x)
+ log_y |= is_exponential_growth(y)
+ plt.plot(x, y, label=line)
+ if log_x:
+ plt.xscale("log")
+ if log_y:
+ plt.yscale("log")
+ plt.title(group_name)
+ plt.legend()
+ plt.grid()
+ plt.show()
+
+
+if __name__ == "__main__":
+ main()