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37 lines
1.1 KiB
37 lines
1.1 KiB
2 years ago
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from __future__ import print_function
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from cnmodel.util import ExpFitting
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import numpy as np
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def test_fit1():
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fit = ExpFitting(nexp=1)
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x = np.linspace(0.0, 50, 500)
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p = [-50.0, 4.0, 5.0]
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y = p[0] + p[1] * np.exp(-x / p[2])
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res = fit.fit(x, y, fit.fitpars)
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pr = [float(res[k].value) for k in res.keys()]
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print("\noriginal: ", p)
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print("fit res: ", pr)
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for i, v in enumerate(p):
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assert np.allclose(v, pr[i])
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def test_fit2():
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fit = ExpFitting(nexp=2)
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x = np.linspace(0.0, 50, 500)
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p = [
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-50.0,
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4.0,
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5.0,
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1.0,
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4.5,
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] # last term is ratio of the two time constants (t2 = delta*t1)
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y = p[0] + p[1] * np.exp(-x / p[2]) + p[3] * np.exp(-x / (p[2] * p[4]))
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res = fit.fit(x, y, fit.fitpars)
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pr = [float(res[k].value) for k in res.keys()]
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print("\noriginal: ", p)
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print("fit res: ", pr)
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# we can only do this approximately for 2 exp fits
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for i, v in enumerate(p): # test each one individually
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assert np.allclose(pr[i] / v, 1.0, atol=1e-4, rtol=1e-2)
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