Allow grouping based on filenames

This commit is contained in:
Nimrod Gilboa Markevich 2022-05-15 09:16:46 +03:00
parent 4355c58e4a
commit b27a87a168

View File

@ -1,4 +1,5 @@
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pathlib
import re
@ -10,6 +11,7 @@ COLORMAP = plt.get_cmap('turbo')
# Extract cpu and rss samples from log files and plot them
# Input: List of log files
def append_sample(name: str, line: str, samples: typing.List[float]):
pattern = name + r': ?(\d+(\.\d+)?)'
maybe_sample = re.findall(pattern, line)
@ -35,13 +37,30 @@ def extract_samples(f: typing.IO) -> typing.Tuple[pd.Series, pd.Series, pd.Serie
return cpu_samples, rss_samples, count_samples
def plot(df: pd.DataFrame, title: str, xlabel: str, ylabel: str):
def plot(df: pd.DataFrame, title: str, xlabel: str, ylabel: str, group_pattern: typing.Optional[str]):
if group_pattern:
color = get_group_color(df.columns, group_pattern)
df.plot(color=color, ax=ax)
else:
df.plot(cmap=COLORMAP, ax=ax)
plt.title(title)
plt.legend()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
def get_group_color(names, pattern):
props = [int(re.findall(pattern, pathlib.Path(name).name)[0]) for name in names]
key = dict(zip(sorted(list(set(props))), range(len(set(props)))))
n_colors = len(key)
color_options = plt.get_cmap('jet')(np.linspace(0, 1, n_colors))
groups = [key[prop] for prop in props]
color = color_options[groups] # type: ignore
return color
if __name__ == '__main__':
filenames = sys.argv[1:]
@ -65,13 +84,15 @@ if __name__ == '__main__':
rss_samples_df = pd.concat(rss_samples_all_files, axis=1)
count_samples_df = pd.concat(count_samples_all_files, axis=1)
group_pattern = r'^\d+'
ax = plt.subplot(3, 1, 1)
plot(cpu_samples_df, 'cpu', '# sample', 'cpu (%)')
plot(cpu_samples_df, 'cpu', '# sample', 'cpu (%)', group_pattern)
ax = plt.subplot(3, 1, 2)
plot(rss_samples_df, 'rss', '# sample', 'mem (MB)')
plot(rss_samples_df, 'rss', '# sample', 'mem (MB)', group_pattern)
ax = plt.subplot(3, 1, 3)
plot(count_samples_df, 'packetsCount', '# sample', 'packetsCount')
plot(count_samples_df, 'packetsCount', '# sample', 'packetsCount', group_pattern)
plt.show()