Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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107 lines
2.9 KiB
107 lines
2.9 KiB
4 years ago
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"""Tests for polyutils module.
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"""
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import numpy as np
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import numpy.polynomial.polyutils as pu
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from numpy.testing import (
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assert_almost_equal, assert_raises, assert_equal, assert_,
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)
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class TestMisc:
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def test_trimseq(self):
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for i in range(5):
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tgt = [1]
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res = pu.trimseq([1] + [0]*5)
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assert_equal(res, tgt)
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def test_as_series(self):
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# check exceptions
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assert_raises(ValueError, pu.as_series, [[]])
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assert_raises(ValueError, pu.as_series, [[[1, 2]]])
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assert_raises(ValueError, pu.as_series, [[1], ['a']])
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# check common types
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types = ['i', 'd', 'O']
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for i in range(len(types)):
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for j in range(i):
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ci = np.ones(1, types[i])
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cj = np.ones(1, types[j])
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[resi, resj] = pu.as_series([ci, cj])
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assert_(resi.dtype.char == resj.dtype.char)
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assert_(resj.dtype.char == types[i])
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def test_trimcoef(self):
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coef = [2, -1, 1, 0]
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# Test exceptions
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assert_raises(ValueError, pu.trimcoef, coef, -1)
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# Test results
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assert_equal(pu.trimcoef(coef), coef[:-1])
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assert_equal(pu.trimcoef(coef, 1), coef[:-3])
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assert_equal(pu.trimcoef(coef, 2), [0])
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class TestDomain:
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def test_getdomain(self):
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# test for real values
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x = [1, 10, 3, -1]
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tgt = [-1, 10]
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res = pu.getdomain(x)
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assert_almost_equal(res, tgt)
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# test for complex values
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x = [1 + 1j, 1 - 1j, 0, 2]
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tgt = [-1j, 2 + 1j]
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res = pu.getdomain(x)
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assert_almost_equal(res, tgt)
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def test_mapdomain(self):
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# test for real values
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dom1 = [0, 4]
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dom2 = [1, 3]
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tgt = dom2
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res = pu.mapdomain(dom1, dom1, dom2)
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assert_almost_equal(res, tgt)
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# test for complex values
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dom1 = [0 - 1j, 2 + 1j]
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dom2 = [-2, 2]
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tgt = dom2
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x = dom1
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res = pu.mapdomain(x, dom1, dom2)
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assert_almost_equal(res, tgt)
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# test for multidimensional arrays
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dom1 = [0, 4]
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dom2 = [1, 3]
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tgt = np.array([dom2, dom2])
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x = np.array([dom1, dom1])
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res = pu.mapdomain(x, dom1, dom2)
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assert_almost_equal(res, tgt)
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# test that subtypes are preserved.
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class MyNDArray(np.ndarray):
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pass
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dom1 = [0, 4]
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dom2 = [1, 3]
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x = np.array([dom1, dom1]).view(MyNDArray)
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res = pu.mapdomain(x, dom1, dom2)
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assert_(isinstance(res, MyNDArray))
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def test_mapparms(self):
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# test for real values
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dom1 = [0, 4]
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dom2 = [1, 3]
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tgt = [1, .5]
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res = pu. mapparms(dom1, dom2)
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assert_almost_equal(res, tgt)
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# test for complex values
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dom1 = [0 - 1j, 2 + 1j]
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dom2 = [-2, 2]
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tgt = [-1 + 1j, 1 - 1j]
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res = pu.mapparms(dom1, dom2)
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assert_almost_equal(res, tgt)
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