mirror of https://github.com/waku-org/research.git
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
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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"2 KB": load("raw/paper_latency_2kb_v2.txt", "arrival_diff="),
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"25 KB": load("raw/paper_latency_25kb_v2.txt", "arrival_diff="),
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"100 KB": load("raw/paper_latency_100kb_v2.txt", "arrival_diff="),
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"500 KB": load("raw/paper_latency_500kb_v2.txt", "arrival_diff=")})
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num_bins = 50
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# Best (1 hop) and worst (4 hops) latencies in ms
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# See Table 2 from paper
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multi_host_simulations = {
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# msg_size: min/max
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"2 KB": [280, 498],
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"25 KB": [349, 931],
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"100 KB": [350, 1781],
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"500 KB": [539, 3141],
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}
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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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("2 KB", ax[0][0]),
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("25 KB", ax[0][1]),
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("100 KB", ax[1][0]),
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("500 KB", ax[1][1])
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]
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for (size, pos) in possitions:
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# Plot single host results
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latencies.hist(size, bins=num_bins, ax=pos, density=True, label="Single-host")
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# Plot multi host results
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pos.axvline(x=multi_host_simulations[size][0], color='red', linestyle='--', label="Multi-host")
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pos.axvline(x=multi_host_simulations[size][1], color='red', linestyle='--')
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pos.grid(False)
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title = ('Message Size = {size}'.format(size=size))
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pos.set_title(title, fontsize=8)
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if size == "25kb":
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pos.legend(fontsize="5", loc="upper left")
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else:
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pos.legend(fontsize="5", loc="best")
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ax[0][0].set(ylabel='Message share')
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ax[1][0].set(xlabel='Latency (ms)', ylabel='Message share')
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ax[1][1].set(xlabel='Latency (ms)')
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plt.tight_layout(pad=0, w_pad=0, h_pad=0.7)
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fig.set_size_inches(4, 3)
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fig.savefig('paper_distribution.svg', dpi=600) |