Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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37 lines
1.2 KiB
37 lines
1.2 KiB
4 years ago
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import numpy as np
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import scipy.special as sc
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from scipy.special._testutils import FuncData
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def test_sici_consistency():
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# Make sure the implementation of sici for real arguments agrees
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# with the implementation of sici for complex arguments.
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# On the negative real axis Cephes drops the imaginary part in ci
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def sici(x):
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si, ci = sc.sici(x + 0j)
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return si.real, ci.real
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x = np.r_[-np.logspace(8, -30, 200), 0, np.logspace(-30, 8, 200)]
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si, ci = sc.sici(x)
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dataset = np.column_stack((x, si, ci))
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FuncData(sici, dataset, 0, (1, 2), rtol=1e-12).check()
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def test_shichi_consistency():
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# Make sure the implementation of shichi for real arguments agrees
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# with the implementation of shichi for complex arguments.
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# On the negative real axis Cephes drops the imaginary part in chi
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def shichi(x):
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shi, chi = sc.shichi(x + 0j)
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return shi.real, chi.real
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# Overflow happens quickly, so limit range
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x = np.r_[-np.logspace(np.log10(700), -30, 200), 0,
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np.logspace(-30, np.log10(700), 200)]
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shi, chi = sc.shichi(x)
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dataset = np.column_stack((x, shi, chi))
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FuncData(shichi, dataset, 0, (1, 2), rtol=1e-14).check()
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