Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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59 lines
1.8 KiB
59 lines
1.8 KiB
4 years ago
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import numpy as np
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import numpy.matlib
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from numpy.testing import assert_array_equal, assert_
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def test_empty():
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x = numpy.matlib.empty((2,))
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assert_(isinstance(x, np.matrix))
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assert_(x.shape, (1, 2))
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def test_ones():
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assert_array_equal(numpy.matlib.ones((2, 3)),
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np.matrix([[ 1., 1., 1.],
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[ 1., 1., 1.]]))
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assert_array_equal(numpy.matlib.ones(2), np.matrix([[ 1., 1.]]))
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def test_zeros():
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assert_array_equal(numpy.matlib.zeros((2, 3)),
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np.matrix([[ 0., 0., 0.],
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[ 0., 0., 0.]]))
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assert_array_equal(numpy.matlib.zeros(2), np.matrix([[ 0., 0.]]))
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def test_identity():
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x = numpy.matlib.identity(2, dtype=int)
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assert_array_equal(x, np.matrix([[1, 0], [0, 1]]))
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def test_eye():
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xc = numpy.matlib.eye(3, k=1, dtype=int)
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assert_array_equal(xc, np.matrix([[ 0, 1, 0],
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[ 0, 0, 1],
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[ 0, 0, 0]]))
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assert xc.flags.c_contiguous
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assert not xc.flags.f_contiguous
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xf = numpy.matlib.eye(3, 4, dtype=int, order='F')
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assert_array_equal(xf, np.matrix([[ 1, 0, 0, 0],
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[ 0, 1, 0, 0],
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[ 0, 0, 1, 0]]))
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assert not xf.flags.c_contiguous
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assert xf.flags.f_contiguous
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def test_rand():
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x = numpy.matlib.rand(3)
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# check matrix type, array would have shape (3,)
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assert_(x.ndim == 2)
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def test_randn():
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x = np.matlib.randn(3)
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# check matrix type, array would have shape (3,)
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assert_(x.ndim == 2)
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def test_repmat():
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a1 = np.arange(4)
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x = numpy.matlib.repmat(a1, 2, 2)
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y = np.array([[0, 1, 2, 3, 0, 1, 2, 3],
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[0, 1, 2, 3, 0, 1, 2, 3]])
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assert_array_equal(x, y)
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