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plot_cdf.py
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plot_cdf.py
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#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import argparse
from re import search
from os.path import basename, getsize
COLORS = [ str(i) for i in range(20) ]
COLOR_MAP = {
1: 'blue',
2: 'red',
3: 'green',
4: 'cyan',
5: 'violet',
6: 'magenta',
7: 'orange',
8: 'brown',
9: 'yellow',
}
# COLORS = mcolors.CSS4_COLORS.keys()
LINES = {
'1': '-',
'2': '-.',
'3': ':',
'4': ':',
'5': ':',
'6': '--',
'7': '--',
'8': '-',
'9': '--',
}
# COLORS = ['b', 'g', 'r', 'c', 'm', 'y', 'k', 'w']
# Set global font size
plt.rcParams['font.size'] = 10 # Sets the global font size to 14
plt.rcParams['axes.labelsize'] = 10 # Sets axis label size
plt.rcParams['xtick.labelsize'] = 8 # Sets x-tick label size
plt.rcParams['ytick.labelsize'] = 8 # Sets y-tick label size
plt.rcParams['legend.fontsize'] = 8 # Sets legend font size
plt.rcParams['axes.titlesize'] = 16 # Sets title font size
class LatencyHistogram(object):
_filepath = None
_filename = None
_rate = None
_data = None
_latencies = None
_percentile25 = None
_percentile50 = None
_percentile75 = None
_percentile99 = None
def __init__(self, filepath):
self._filepath = filepath
self._filename = basename(filepath)
self._rate = int(search(r'(\d+?)kpps', self._filename).group(1))
self._data = np.genfromtxt(self._filepath, delimiter=',')
self._data[:, 0] /= 1e3 # Convert to microseconds
self._latencies = []
for latency, count in self._data:
self._latencies.extend([latency] * int(count))
self._percentile25 = np.percentile(self._latencies, 25)
self._percentile50 = np.percentile(self._latencies, 50)
self._percentile75 = np.percentile(self._latencies, 75)
self._percentile99 = np.percentile(self._latencies, 99)
def filepath(self):
return self._filepath
def filename(self):
return self._filename
def rate(self):
return self._rate
def percentile25(self):
return self._percentile25
def percentile50(self):
return self._percentile50
def percentile75(self):
return self._percentile75
def percentile99(self):
return self._percentile99
class LoadLatencyPlot(object):
_latency_histograms = None
_name = None
_color = None
_line = None
_line_color = None
_plot25 = None
_plot50 = None
_plot75 = None
_plot99 = None
def __init__(self, histogram_filepaths, name, color, line, line_color):
self._latency_histograms = []
for filepath in histogram_filepaths:
if getsize(filepath) > 0:
self._latency_histograms.append(LatencyHistogram(filepath))
if len(self._latency_histograms) == 0:
print(f"WARN: list of latency histograms empty for {histogram_filepaths}")
self._name = name
self._color = color
self._line = line
self._line_color = line_color
def plot(self):
hist, bin_edges = np.histogram(self._latency_histograms[0]._latencies, bins=400, density=True)
cdf = np.cumsum(hist) * (bin_edges[1] - bin_edges[0]);
cdf *= 100; # 1.0 -> 100%
_x = [hist.rate() for hist in self._latency_histograms]
_y25 = [hist.percentile25() for hist in self._latency_histograms]
_y50 = [hist.percentile50() for hist in self._latency_histograms]
_y75 = [hist.percentile75() for hist in self._latency_histograms]
_y99 = [hist.percentile99() for hist in self._latency_histograms]
order = np.argsort(_x)
x = np.array(_x)[order]
y25 = np.array(_y25)[order]
y50 = np.array(_y50)[order]
y75 = np.array(_y75)[order]
y99 = np.array(_y99)[order]
self._plot50, = plt.plot(
bin_edges[1:],
cdf,
label=f'{self._name}',
color=self._line_color,
linestyle=self._line,
linewidth=1,
marker='',
)
def setup_parser():
parser = argparse.ArgumentParser(
description='Plot load latency percentile graph'
)
parser.add_argument('-t',
'--title',
type=str,
help='Title of the plot',
)
parser.add_argument('-W', '--width',
type=float,
default=12,
help='Width of the plot in inches'
)
parser.add_argument('-H', '--height',
type=float,
default=6,
help='Height of the plot in inches'
)
parser.add_argument('-l', '--logarithmic',
action='store_true',
help='Plot logarithmic latency axis',
)
parser.add_argument('-o', '--output',
type=argparse.FileType('w+'),
help='''Path to the output plot
(default: load_latency.pdf)''',
default='load_latency.pdf'
)
parser.add_argument('-c', '--compress',
action='store_true',
help='Compress the legend',
default=False
)
for color in COLORS:
parser.add_argument(f'--{color}',
type=argparse.FileType('r'),
nargs='+',
help=f'''Paths to latency histogram CSVs for
{color} plot''',
)
for color in COLORS:
parser.add_argument(f'--{color}-name',
type=str,
default=color,
nargs='+',
help=f'''Name of {color} plot''',
)
# for color in COLORS:
# parser.add_argument(f'--{color}-line',
# type=str,
# default="-",
# help=f'''Line style of {color} plot''',
# )
# for color in COLORS:
# parser.add_argument(f'--{color}-color',
# type=str,
# default="blue",
# help=f'''Color of {color} plot''',
# )
return parser
def parse_args(parser):
args = parser.parse_args()
if not any([args.__dict__[color] for color in COLORS]):
parser.error('At least one set of latency histogram paths must be ' +
'provided')
return args
def chain(lst: list[list]) -> list:
return [item for sublist in lst for item in sublist]
def main():
parser = setup_parser()
args = parse_args(parser)
fig = plt.figure(figsize=(args.width, args.height))
ax = fig.add_subplot(1, 1, 1)
ax.set_axisbelow(True)
if args.title:
plt.title(args.title)
plt.xlabel(' Latency ($\mu s$)')
plt.ylabel('CDF (%)')
plt.grid()
plots = []
# print(vars(args))
for color in COLORS:
if args.__dict__[color]:
if len(args.__dict__[f'{color}_name']) == 1:
name = args.__dict__[f'{color}_name'][0]
line = "-"
line_color = "blue"
elif len(args.__dict__[f'{color}_name']) == 3:
name = args.__dict__[f'{color}_name'][0]
line = args.__dict__[f'{color}_name'][1].strip("l") # allow prepending with l to avoid "-" being interpreted as a flag
line_color = args.__dict__[f'{color}_name'][2]
plot = LoadLatencyPlot(
histogram_filepaths=[h.name for h in args.__dict__[color]],
name=name,
color=color,
line=line,
line_color=line_color,
)
plot.plot()
plots.append(plot)
ax.set_xscale('log' if args.logarithmic else 'linear')
# plt.xlim(0, 1)
legend = None
if args.compress:
# empty name1 name2 ...
# 25pctl x x ...
# 50pctl x x ...
# 75pctl x x ...
# 99pctl x x ...
dummy, = plt.plot([0], marker='None', linestyle='None',
label='dummy')
legend = plt.legend(
chain([
[dummy, p._plot25, p._plot50, p._plot75, p._plot99]
for p in plots
]),
chain([
[p._name, '25.pctl', '50.pctl', '75.pctl', '99.pctl']
for p in plots
]),
ncol=len(plots),
prop={'size': 8},
loc="lower right",
)
else:
legend = plt.legend(loc="lower right", bbox_to_anchor=(1, 1),
ncol=2, title=None, frameon=False,
)
ax.annotate(
"← Lower is better", # or ↓ ← ↑ →
xycoords="axes points",
# xy=(0, 0),
xy=(0, 0),
xytext=(-45, -27),
# fontsize=FONT_SIZE,
color="navy",
weight="bold",
)
legend.get_frame().set_facecolor('white')
legend.get_frame().set_alpha(0.8)
fig.tight_layout()
plt.savefig(args.output.name)
plt.close()
if __name__ == '__main__':
main()