mirror of https://github.com/waku-org/research.git
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
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import matplotlib.pyplot as plt
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import scienceplots
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import numpy as np
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import pandas as pd
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from analyze import load
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latencies = pd.DataFrame({
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"2kb": load("raw/paper_latency_2kb_v2.txt", "arrival_diff="),
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"25kb": load("raw/paper_latency_25kb_v2.txt", "arrival_diff="),
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"100kb": load("raw/paper_latency_100kb_v2.txt", "arrival_diff="),
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"500kb": load("raw/paper_latency_500kb_v2.txt", "arrival_diff=")})
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num_bins = 50
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#fig, ax = plt.subplots(2, 2)
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with plt.style.context(['science', 'ieee']):
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fig, ax = plt.subplots(2, 2)
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possitions = [
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("2kb", ax[0][0]),
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("25kb", ax[0][1]),
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("100kb", ax[1][0]),
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("500kb", ax[1][1])
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]
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for (size, pos) in possitions:
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latencies.hist(size, bins=num_bins, ax=pos)
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pos.grid(False)
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text = r'$ \mu=$' + '{:.0f};'.format(latencies[size].mean(axis=0)) + r' $ p_{95}=$' + '{:.0f};'.format(
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np.percentile(latencies[size], 95)) + ' max={:.0f}'.format(latencies[size].max())
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pos.set_title(f"msgsize={size}; " + text, fontsize=6)
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ax[0][0].set(ylabel='Amount samples')
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ax[1][0].set(xlabel='Latency (ms)', ylabel='Amount samples')
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ax[1][1].set(xlabel='Latency (ms)')
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fig.set_size_inches(4, 3)
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fig.savefig('paper_distribution.svg', dpi=600)
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