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soft-an04/ReversalModel/make_plots.py

71 lines
1.8 KiB
Python
Executable file

#!/usr/bin/env python3
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib
import os
DIR: str = os.path.dirname(__file__)
matplotlib.use('pgf')
matplotlib.rcParams.update({
'pgf.texsystem': 'pdflatex',
'font.family': 'serif',
'text.usetex': True,
'pgf.rcfonts': False,
})
df = pd.read_csv(DIR + '/time.csv')
df['cpu'] = df['user'] + df['sys']
del df['real']
del df['user']
del df['sys']
df_cpu = df.loc[~df.cpu.isnull(), :]
del df_cpu['ltl']
df_cpu = df_cpu.melt(id_vars=['cpu'])
df_cpu['value'] = df_cpu['value'].astype(str)
df_timeout = df.loc[:, :].copy()
df_timeout['timeout'] = 0
df_timeout.loc[df_timeout['cpu'].isnull(), 'timeout'] = 1
del df_timeout['cpu']
def timeout_by(name: str) -> pd.DataFrame:
df_return = df_timeout.loc[:, [name, 'timeout']] \
.groupby(name) \
.mean() \
.reset_index()
df_return['timeout'] = df_return['timeout'] * 100
df_return[name] = df_return[name].astype(str)
return df_return
def plot_by(df_cpu: pd.DataFrame, name: str, color: any):
# Initialize the matplotlib figure
f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))
sns.stripplot(ax=ax1, color=color, data=df_cpu.loc[df_cpu.variable == name],
x='cpu', y='value')
sns.barplot(ax=ax2, color=color, data=timeout_by(name), y=name, x='timeout',
width=0.75)
ax1.set(ylabel='Value of ' + name.upper(), xlim=[0, 300],
xlabel='CPU time (seconds)')
ax2.set(ylabel='Value of ' + name.upper(), xlim=[0, 100],
xlabel='Timeouts (%)')
sns.despine(left=True, bottom=True)
plt.savefig(DIR + '/../plots/' + name + '.pgf')
def main():
plot_by(df_cpu, 'n', 'teal')
plot_by(df_cpu, 'length', 'red')
plot_by(df_cpu, 'r', 'orange')
if __name__ == '__main__':
main()