mirror of
https://github.com/polhenarejos/pico-rng.git
synced 2026-04-09 17:25:51 +02:00
57 lines
1.7 KiB
Python
57 lines
1.7 KiB
Python
#!/usr/bin/env python3
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import numpy as np
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import matplotlib.pyplot as plt
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import argparse
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from scipy import stats
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parser = argparse.ArgumentParser(description="Raspberry Pi Pico Random Number Generator Test Analyzer")
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parser.add_argument("file", help="File that contains a random sample of bytes.", metavar="FILENAME")
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args = parser.parse_args()
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def read_in_chunks(file_object, chunk_size=1024):
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"""Lazy function (generator) to read a file piece by piece.
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Default chunk size: 1k."""
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while True:
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data = file_object.read(chunk_size)
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if not data:
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break
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yield data
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with open(args.file, 'rb') as f:
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myhist = np.zeros(256, dtype='float64')
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chisqs = []
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chisps = []
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acumd = 0
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acumn = 0
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for data in read_in_chunks(f, 10000):
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n, jnk = np.histogram(list(data), list(range(257)))
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myhist += n
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chisq, chisp = stats.chisquare(n)
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chisqs.append(chisq)
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chisps.append(chisp*100)
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acumd += sum(data)
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acumn += len(data)
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# plt.subplot(1, 2, 1)
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plt.bar(range(256), myhist/np.sum(myhist), width=1)
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plt.ylabel('Probability')
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plt.title(f'Distribution of randomness [$\mu$={acumd/acumn:.4f}]')
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plt.grid(True)
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plt.show()
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plt.subplot(1, 2, 1)
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n, bins, _ = plt.hist(chisqs, 401, density=True)
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plt.ylabel('Probability')
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plt.title(f'Distribution of chi-square [$\mu$={np.mean(chisqs):.4f}, Mdn={np.median(chisqs):.4f}]')
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plt.grid(True)
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plt.subplot(1, 2, 2)
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n, bins, _ = plt.hist(chisps, list(range(101)), density=False)
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plt.ylabel('Probability')
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plt.title(f'Distribution of percentage excess [$\mu$={np.mean(chisps):.4f}, Mdn={np.median(chisps):.4f}]')
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plt.grid(True)
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plt.show()
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