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