140 lines
5.1 KiB
Python
140 lines
5.1 KiB
Python
#!/usr/bin/env python3
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import glob
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from datetime import datetime
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import matplotlib.pyplot as plt
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def load_data(path):
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all_data = {}
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for file in glob.glob(path):
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with open(file, 'r') as f:
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lines = list(map(lambda l: l.strip(), f))
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ts = file.split('_')[-1][:-4]
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bucket = datetime.fromtimestamp(float(ts))
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data = {}
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data['avg_out'] = float(lines[1].split(': ')[1])
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data['min_out'] = float(lines[2].split(': ')[1].split(', ')[3][0:-1])
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data['max_out'] = float(lines[3].split(': ')[1].split(', ')[3][0:-1])
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data['known_out'] = float(lines[4].split(': ')[1].split(' ')[-1])
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pr_sr_line = lines[11].split(' & ')
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data['known_pr'] = float(pr_sr_line[2])
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data['avg_pr'] = float(pr_sr_line[1])
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data['known_sr'] = float(pr_sr_line[4].split(' ')[0])
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data['avg_sr'] = float(pr_sr_line[3])
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# pr_percentiles = filter(lambda l: l.startswith('PR4('), lines)
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# sr_percentiles = filter(lambda l: l.startswith('SR4('), lines)
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percentiles_to_plot = [50, 60, 70, 80, 90, 95]
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for rank in ['PR', 'SR']:
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percentiles = list(filter(lambda l: l.startswith(rank), lines))
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for to_plot in percentiles_to_plot:
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line = list(filter(lambda l: l.endswith(f': {to_plot}'), percentiles))[0]
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percentile = line.split(': ')[2]
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data[f'{rank.lower()}_perc_{to_plot}'] = float(percentile)
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all_data[bucket] = data
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return all_data
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def main():
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# for edges in [0, 20, 30, 40, 50, 60, 70, 80, 90, 100, 130, 150, 200]:
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for edges in [3, 5, 10]:
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print(f'plotting for {edges} edges')
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all_data = load_data(f'./churn_rank/{edges}_*')
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x = []
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avg_out = []
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min_out = []
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max_out = []
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known_out = []
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known_pr = []
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known_sr = []
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avg_pr = []
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avg_sr = []
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pr_perc_50 = []
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pr_perc_60 = []
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pr_perc_70 = []
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pr_perc_80 = []
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pr_perc_90 = []
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pr_perc_95 = []
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sr_perc_50 = []
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sr_perc_60 = []
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sr_perc_70 = []
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sr_perc_80 = []
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sr_perc_90 = []
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sr_perc_95 = []
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for bucket, data in sorted(all_data.items(), key=lambda kv: kv[0]):
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x.append(bucket)
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avg_out.append(data['avg_out'])
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min_out.append(data['min_out'])
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max_out.append(data['max_out'])
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known_out.append(data['known_out'])
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known_pr.append(data['known_pr'])
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known_sr.append(data['known_sr'])
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avg_sr.append(data['avg_sr'])
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avg_pr.append(data['avg_pr'])
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pr_perc_50.append(data['pr_perc_50'])
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pr_perc_60.append(data['pr_perc_60'])
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pr_perc_70.append(data['pr_perc_70'])
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pr_perc_80.append(data['pr_perc_80'])
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pr_perc_90.append(data['pr_perc_90'])
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pr_perc_95.append(data['pr_perc_95'])
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sr_perc_50.append(data['sr_perc_50'])
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sr_perc_60.append(data['sr_perc_60'])
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sr_perc_70.append(data['sr_perc_70'])
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sr_perc_80.append(data['sr_perc_80'])
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sr_perc_90.append(data['sr_perc_90'])
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sr_perc_95.append(data['sr_perc_95'])
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# plt.plot(x, avg_out, label='avg_out')
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# plt.plot(x, max_out, label='max_out')
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# plt.plot(x, min_out, label='min_out')
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# plt.plot(x, known_out, label='known_out')
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# plt.plot(x, known_pr, label='known_pr')
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fig, ax = plt.subplots()
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ax.plot(x, known_sr, label='known_sr')
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# plt.plot(x, pr_perc_50, label='pr_perc_50')
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# plt.plot(x, pr_perc_80, label='pr_perc_80')
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# plt.plot(x, pr_perc_90, label='pr_perc_90')
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# plt.plot(x, pr_perc_95, label='pr_perc_95')
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ax.plot(x, sr_perc_50, label='sr_perc_50')
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ax.plot(x, sr_perc_60, label='sr_perc_60')
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ax.plot(x, sr_perc_70, label='sr_perc_70')
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ax.plot(x, sr_perc_80, label='sr_perc_80')
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ax.plot(x, sr_perc_90, label='sr_perc_90')
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ax.plot(x, sr_perc_95, label='sr_perc_95')
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ax.plot(x, avg_sr, label='avg_sr')
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ax.set_title(f'SensorRank after adding {edges} edges')
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fig.autofmt_xdate()
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fig.legend()
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plt.savefig(f'./{edges}_sr_percentiles.png')
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print('created sr plot')
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# plt.show()
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fig, ax = plt.subplots()
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ax.plot(x, known_pr, label='known_pr')
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ax.plot(x, pr_perc_50, label='pr_perc_50')
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ax.plot(x, pr_perc_60, label='pr_perc_60')
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ax.plot(x, pr_perc_70, label='pr_perc_70')
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ax.plot(x, pr_perc_80, label='pr_perc_80')
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ax.plot(x, pr_perc_90, label='pr_perc_90')
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ax.plot(x, pr_perc_95, label='pr_perc_95')
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ax.plot(x, avg_pr, label='avg_pr')
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ax.set_title(f'PageRank after adding {edges} edges')
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fig.autofmt_xdate()
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fig.legend()
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plt.savefig(f'./{edges}_pr_percentiles.png')
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print('created pr plot')
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# plt.show()
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if __name__ == '__main__':
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main()
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