Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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60 lines
1.9 KiB
60 lines
1.9 KiB
4 years ago
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import numpy as np
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from numpy.testing import assert_allclose, assert_equal
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import pytest
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import scipy.special as sc
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class TestInverseErrorFunction:
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def test_compliment(self):
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# Test erfcinv(1 - x) == erfinv(x)
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x = np.linspace(-1, 1, 101)
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assert_allclose(sc.erfcinv(1 - x), sc.erfinv(x), rtol=0, atol=1e-15)
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def test_literal_values(self):
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# calculated via https://keisan.casio.com/exec/system/1180573448
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# for y = 0, 0.1, ... , 0.9
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actual = sc.erfinv(np.linspace(0, 0.9, 10))
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expected = [
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0,
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0.08885599049425768701574,
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0.1791434546212916764928,
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0.27246271472675435562,
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0.3708071585935579290583,
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0.4769362762044698733814,
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0.5951160814499948500193,
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0.7328690779592168522188,
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0.9061938024368232200712,
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1.163087153676674086726,
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]
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assert_allclose(actual, expected, rtol=0, atol=1e-15)
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@pytest.mark.parametrize(
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'f, x, y',
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[
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(sc.erfinv, -1, -np.inf),
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(sc.erfinv, 0, 0),
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(sc.erfinv, 1, np.inf),
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(sc.erfinv, -100, np.nan),
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(sc.erfinv, 100, np.nan),
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(sc.erfcinv, 0, np.inf),
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(sc.erfcinv, 1, -0.0),
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(sc.erfcinv, 2, -np.inf),
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(sc.erfcinv, -100, np.nan),
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(sc.erfcinv, 100, np.nan),
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],
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ids=[
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'erfinv at lower bound',
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'erfinv at midpoint',
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'erfinv at upper bound',
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'erfinv below lower bound',
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'erfinv above upper bound',
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'erfcinv at lower bound',
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'erfcinv at midpoint',
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'erfcinv at upper bound',
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'erfcinv below lower bound',
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'erfcinv above upper bound',
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]
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)
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def test_domain_bounds(self, f, x, y):
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assert_equal(f(x), y)
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