2021-02-07 20:19:08 +00:00
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"""
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In this script, we generate a strategy sigma that is optimal for a distribution
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of read fractions. We plot this strategy's capacity as a function of read
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fraction and compare it to other strategies optimized for specific points in
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this distribution. This plot was used in our paper
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(https://mwhittaker.github.io/publications/quoracle.pdf).
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"""
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2021-02-05 04:53:42 +00:00
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# See https://stackoverflow.com/a/19521297/3187068
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import matplotlib
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matplotlib.use('pdf')
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font = {'size': 8}
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matplotlib.rc('font', **font)
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2021-02-05 04:59:10 +00:00
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from quoracle import *
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import argparse
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2021-02-05 04:53:42 +00:00
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import itertools
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import matplotlib
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import matplotlib.pyplot as plt
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2021-02-07 20:19:08 +00:00
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def main(output_filename: str) -> None:
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a = Node('a', write_capacity=100, read_capacity=200)
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b = Node('b', write_capacity=100, read_capacity=200)
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c = Node('c', write_capacity=50, read_capacity=100)
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d = Node('d', write_capacity=50, read_capacity=100)
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dist = {
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0.00: 10 / 18,
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0.25: 4 / 18,
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0.50: 2 / 18,
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0.75: 1 / 18,
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1.00: 1 / 18,
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}
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qs = QuorumSystem(reads=a*c + b*d)
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2021-02-07 20:07:55 +00:00
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xs = [0.01 * i for i in range(101)]
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markers = itertools.cycle(['o', 'v', '^', 'p', '*'])
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fig, ax = plt.subplots(figsize=(3.25, 2.5))
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for fr in dist.keys():
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sigma = qs.strategy(read_fraction=fr)
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ys = [sigma.capacity(read_fraction=x) for x in xs]
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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)
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sigma = qs.strategy(read_fraction=dist)
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ys = [sigma.capacity(read_fraction=x) for x in xs]
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ax.plot(xs, ys, label='$\sigma$', linewidth=1.5,
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marker=next(markers), markevery=25, markersize=4)
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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')
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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)
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print(f'Wrote figure to "{output_filename}".')
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--output',
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type=str,
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default='workload_distribution.pdf',
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help='Output filename')
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args = parser.parse_args()
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main(args.output)
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