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iperf3_plot.py
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iperf3_plot.py
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#!/usr/bin/env python
"""
Plot iperf data
"""
import json
import os
import sys
import pprint
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from optparse import OptionParser
pp = pprint.PrettyPrinter(indent=4, stream=sys.stderr)
class Plotter(object):
def __init__(self, upperLimit, lowerLimit,bound):
sns.set_style("white")
self.upperbond=upperLimit
self.lowerbond=lowerLimit
self.bound=bound
def defTableu(self):
tableau20 = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120),
(44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150),
(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),
(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),
(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
for i in range(len(tableau20)):
r, g, b = tableau20[i]
tableau20[i] = (r / 255., g / 255., b / 255.)
return tableau20
def plotBox(self, dataset,filename, desc, title):
fig, ax = plt.subplots()
# # the size of A4 paper
fig.set_size_inches(12,14)
# create our boxplot which is drawn on an Axes object
sns.boxplot(data=dataset,orient="h", palette="Set2")
filename = filename.replace(".png","_box.png")
plt.title(title)
plt.savefig(filename, bbox_inches="tight")
def plotLine(self, dataset, filename, desc, title, figureN):
sns.set_style("white")
f, axs = plt.subplots(figureN, sharex=True, sharey=True)
f.set_size_inches(12,14)
i=0
tableau20 = self.defTableu()
upperbond=self.upperbond
lowerbond=self.lowerbond
for c in dataset.columns:
axs[i].spines["left"].set_visible(False)
axs[i].spines["right"].set_visible(False)
axs[i].get_xaxis().tick_bottom()
axs[i].get_yaxis().tick_left()
axs[i].set_title(c)
axs[i].plot(dataset.index, dataset[c],color=tableau20[i])
if self.upperbond >0 : axs[i].plot(dataset.index,[upperbond]* len(dataset.index),"--", lw=2, color="red", alpha=0.5)
if self.upperbond >0 : axs[i].plot(dataset.index,[lowerbond]* len(dataset.index),"--", lw=2, color="red", alpha=0.5)
i=i+1
if i==5: break
# plt.title(title)
plt.savefig(filename, bbox_inches="tight")
def plotLinePretty(self, dataset,filename, desc, title):
tableau20 = self.defTableu()
y_level = int((int(dataset.values.max()) - int(dataset.values.min()))/20)
if y_level==0:
y_level = (dataset.values.max()-dataset.values.min())/20
y_max = dataset.values.max()+y_level
y_min = dataset.values.min()
x_max = dataset.index[-1]
x_min = dataset.index[0]
x_level = (x_max - x_min)/6
plt.figure(figsize=(12, 14))
ax = plt.subplot(111)
ax.spines["top"].set_visible(False)
ax.spines["bottom"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.get_xaxis().tick_bottom()
ax.get_yaxis().tick_left()
plt.ylim(y_min, y_max)
plt.xlim(x_min, x_max)
plt.yticks(np.arange(y_min, y_max, y_level), [str(round(x,3)) for x in np.arange(y_min, y_max, y_level)], fontsize=14)
plt.xticks(fontsize=14)
for y in np.arange(y_min, y_max, y_level):
plt.plot(np.arange(x_min, x_max), [y] * len(np.arange(x_min, x_max)), "--", lw=1, color="black", alpha=0.3)
plt.tick_params(axis="both", which="both", bottom="off", top="off",
labelbottom="on", left="off", right="off", labelleft="on")
clients = dataset.columns
i=0;
for rank, column in enumerate(clients):
plt.plot(dataset.index, dataset[column].values, lw=1,color=tableau20[rank%20])
# y_pos = dataset[column].values[-1]
y_pos = dataset[column].mean()
# print(column,dataset[column].values[-1], dataset[column].mean() )
plt.text(x_max + x_level/2, y_pos, column, fontsize=12, color=tableau20[rank % 20])
i=i+1
j=0;
for (upper_bound, lower_bound, tags) in self.bound:
# print(str(upper_bound), str(lower_bound), tags)
if upper_bound >0 : plt.plot(dataset.index,[upper_bound]* len(dataset.index), lw=2, color=tableau20[j%20] )
plt.text(x_max, upper_bound, tags, fontsize=12, color=tableau20[j % 20])
if lower_bound >0 : plt.plot(dataset.index,[lower_bound]* len(dataset.index), lw=2, color=tableau20[j%20] )
plt.text(x_max, lower_bound, tags, fontsize=12, color=tableau20[j % 20])
j=j+1
plt.title(title, fontsize=17)
# plt.text(x_min+(x_max-x_min)/2, y_max, title, fontsize=17, ha="center")
plt.text(x_max, y_max, desc, fontsize=10)
plt.savefig(filename, bbox_inches="tight")
class Parser(object):
def getOptionParser(self):
usage = '%prog [ -f FOLDER | -o OUT | -p PLOTFILES | -n NOPLOTFILES | -v ]'
return OptionParser(usage=usage)
def parseOptions(self, args):
parser = self.getOptionParser()
parser.add_option('-f', '--folder', metavar='FILE',
type='string', dest='foldername',
help='Input folder absolute path. [Input Format: /Users/iperfExp]')
parser.add_option('-o', '--output', metavar='OUT',
type='string', dest='output', default="out",
help='Output folder')
parser.add_option('-p', '--plotfiles', metavar='PLOT_FILES',
type='string', dest='plotFiles', default="",
help='Choose files to be plotted. If no specified, all files in folder. [Input Format: f1,f2,f3]')
parser.add_option('-n', '--noPlotFiles', metavar='NO_PLOT_FILES',
type='string', dest='noPlotFiles', default="",
help='Choose files not to be plotted. [Input Format: f1,f2,f3]')
parser.add_option('-u', '--upperLimit', metavar='UPPER_LIMIT',
type='float', dest='upperLimit', default=0,
help='The expected upper boundary. [Input Format: 0.5]')
parser.add_option('-l', '--lowerLimit', metavar='LOWER_LIMIT',
type='float', dest='lowerLimit', default=0,
help='The expected lower boundary. [Input Format: 0.5]')
parser.add_option('-b', '--bound', metavar='BOUND',
type='string', dest='bound', default="",
help='Provide multiple bound in pairs. [Input Format: [upperbound, lowerbound, tag]')
parser.add_option('-v', '--verbose',
dest='verbose', action='store_true', default=False,
help='Verbose debug output to stderr.')
options, _ = parser.parse_args(args)
# print(options)
if not options.foldername:
parser.error('Foldername is required.')
else:
self.foldername = options.foldername
if options.plotFiles=="":
self.plotFiles=[]
else:
self.plotFiles = map(lambda x:x.strip(), options.plotFiles.split(",")) if "," in options.plotFiles else [options.plotFiles.strip()]
if options.noPlotFiles=="":
self.noPlotFiles=[]
else:
self.noPlotFiles = map(lambda x:x.strip(), options.noPlotFiles.split(",")) if "," in options.noPlotFiles else [options.noPlotFiles.strip()]
self.bound = []
if options.bound=="":
self.bound=[]
else:
# print(options.bound)
bounds_tmp = map(lambda x:x.strip(), options.bound.split("]")) if "]" in options.bound else [options.bound.strip()]
for bt in bounds_tmp:
bt = bt.replace("[", "")
bt_arr = map(lambda x:x.strip(), bt.split(","))
bound_item=[]
for b in bt_arr:
if b.strip()!= "":
bound_item.append(b)
if len(bound_item)==3:
bound_item[0]=float(bound_item[0])
bound_item[1]=float(bound_item[1])
self.bound.append(bound_item)
self.output = options.output
return (self.foldername, list(self.plotFiles), list(self.noPlotFiles), self.output,options.upperLimit,options.lowerLimit, self.bound)
def generate_BW(self, iperf):
"""Do the actual formatting."""
idx=[]
value=[]
duration = iperf.get('start').get('test_start').get('duration')
for i in iperf.get('intervals'):
for ii in i.get('streams'):
if (round(float(ii.get('start')), 0)) <= duration:
idx.append(round(float(ii.get('start')), 0))
value.append(round(float(ii.get('bits_per_second')) / (1024*1024), 3))
return pd.Series(value, index=idx)
def get_plotFiles(self,foldername, plotFiles, noPlotFiles):
# print(foldername, plotFiles, noPlotFiles)
if len(plotFiles)==0:
for root, dirs, files in os.walk(foldername, topdown=False):
for filename in files:
plotFiles.append(filename)
else:
for root, dirs, files in os.walk(foldername, topdown=False):
i=0;
while i < len(plotFiles):
if plotFiles[i] not in files:
del plotFiles[i]
else:
i = i+1;
for f in noPlotFiles:
if f in plotFiles: plotFiles.remove(f)
return plotFiles
def get_dataset(self, plotFiles):
datasetIndex=[]
raw_arrays=[]
for name in plotFiles:
if "json" in name:
datasetIndex.append(name.replace(".json",""))
else:
datasetIndex.append(name)
file_path = foldername+os.path.sep+str(name)
with open(file_path, 'r') as fh:
data = fh.read()
try:
iperf = json.loads(data)
except Exception as ex: # pylint: disable=broad-except
print('Could not parse JSON from file (ex): {0}'.format(str(ex)))
raw_arrays.append(self.generate_BW(iperf))
dataset=pd.concat(raw_arrays, axis=1)
dataset.columns=datasetIndex
dataset.index.names=['start']
# dataset.apply(lambda x: x.fillna(x.mean(),inplace=True),axis=0)
dataset = dataset.fillna(method='ffill')
return dataset
# if __name__ == '__main__':
# s = Parser()
# (foldername, plotFiles, noPlotFiles, output, upperLimit, lowerLimit,bound) = s.parseOptions(sys.argv[1:])
# print (foldername, plotFiles, noPlotFiles, output, upperLimit, lowerLimit,bound)
if __name__ == '__main__':
"""Execute the read and formatting."""
s = Parser()
(foldername, plotFiles, noPlotFiles, output, upperLimit, lowerLimit, bound) = s.parseOptions(sys.argv[1:])
print('foldername {}\nplotFiles {}\nnoPlotFiles {}\noutput {}\nupperLimit {}\nlowerLimit {}\nbound {}\n'.format(foldername,str(plotFiles), str(noPlotFiles), output, upperLimit, lowerLimit,str(bound)))
plotFiles=s.get_plotFiles(foldername, plotFiles, noPlotFiles)
# print (plotFiles)
if len(plotFiles) > 0:
dataset = s.get_dataset(plotFiles)
plotter = Plotter(upperLimit, lowerLimit, bound)
#plot overall box
dataset.to_csv(os.path.join(output, "iperf.csv"))
dataset.describe().to_csv(os.path.join(output, "iperf_stats.csv"))
desc="x_labels: Seconds\ny_lebel: Mbps\nclients: "+str(len(dataset.columns))
title= "iperf throughput Mbps per seconds"
# if len(bound) > 0:
png_file = os.path.join(output, "iperf.png")
plotter.plotBox(dataset, png_file, desc, title)
#plot individual
if upperLimit>=0 and lowerLimit >=0:
s=0
e=0
shift=5
output_single = png_file
while e < len(dataset.columns):
e = e + shift
if e >=len(dataset.columns):
e = len(dataset.columns)
plotDf = dataset[dataset.columns[s:e]]
output_single = png_file.replace(".png", "_line_"+str(s)+".png")
plotter.plotLine(plotDf, output_single,desc, title, shift)
output_single = png_file
s = e
#plot all lines, sort by mean value/column
if len(bound) >=0:
dataset = dataset.reindex_axis(dataset.mean().sort_values().index, axis=1)
# last_row_name = dataset.index[-1]
# dataset = dataset.T.sort(columns=last_row_name, ascending=False).T
# dataset.to_csv(output + "_sort_by_mean.csv")
plotter.plotLinePretty(dataset, png_file, desc, title)