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James Goppert
14 lines
391 B
Python
14 lines
391 B
Python
#!/bin/bash
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from __future__ import print_function
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import pylab as pl
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import scipy.optimize
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from scipy.stats import chi2
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for fa_rate in 1.0/pl.array([1e1, 1e2, 1e4, 1e6, 1e9]):
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print(fa_rate)
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for df in range(1,7):
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f_eq = lambda x: ((1- fa_rate) - chi2.cdf(x, df))**2
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res = scipy.optimize.minimize(f_eq, df)
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assert res['success']
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print('\t', res.x[0])
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