quoracle/examples/plot_workload_distribution.py

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"""
In this script, we generate a strategy sigma that is optimal for a distribution
of read fractions. We plot this strategy's capacity as a function of read
fraction and compare it to other strategies optimized for specific points in
this distribution. This plot was used in our paper
(https://mwhittaker.github.io/publications/quoracle.pdf).
"""
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# See https://stackoverflow.com/a/19521297/3187068
import matplotlib
matplotlib.use('pdf')
font = {'size': 8}
matplotlib.rc('font', **font)
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from quoracle import *
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import argparse
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import itertools
import matplotlib
import matplotlib.pyplot as plt
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def main(output_filename: str) -> None:
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a = Node('a', write_capacity=100, read_capacity=200)
b = Node('b', write_capacity=100, read_capacity=200)
c = Node('c', write_capacity=50, read_capacity=100)
d = Node('d', write_capacity=50, read_capacity=100)
dist = {
0.00: 10 / 18,
0.25: 4 / 18,
0.50: 2 / 18,
0.75: 1 / 18,
1.00: 1 / 18,
}
qs = QuorumSystem(reads=a*c + b*d)
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xs = [0.01 * i for i in range(101)]
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markers = itertools.cycle(['o', 'v', '^', 'p', '*'])
fig, ax = plt.subplots(figsize=(3.25, 2.5))
for fr in dist.keys():
sigma = qs.strategy(read_fraction=fr)
ys = [sigma.capacity(read_fraction=x) for x in xs]
ax.plot(xs, ys, '--', label=str(f'$\\sigma_{{{fr}}}$'), linewidth=1,
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marker=next(markers), markevery=25, markersize=4, alpha=0.75)
sigma = qs.strategy(read_fraction=dist)
ys = [sigma.capacity(read_fraction=x) for x in xs]
ax.plot(xs, ys, label='$\\sigma$', linewidth=1.5,
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marker=next(markers), markevery=25, markersize=4)
ax.legend(ncol=3, loc='lower center', bbox_to_anchor=(0.5, 1.0))
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ax.set_ylabel('Capacity (commands per second)')
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ax.set_xlabel('Read Fraction')
ax.set_xticks([0, 0.25, 0.5, 0.75, 1])
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ax.grid()
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fig.tight_layout()
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fig.savefig(output_filename)
print(f'Wrote figure to "{output_filename}".')
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
parser.add_argument('--output',
type=str,
default='workload_distribution.pdf',
help='Output filename')
args = parser.parse_args()
main(args.output)