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| import numpy as np
| import numpy.matlib
| from numpy.testing import assert_array_equal, assert_
|
| def test_empty():
| x = numpy.matlib.empty((2,))
| assert_(isinstance(x, np.matrix))
| assert_(x.shape, (1, 2))
|
| def test_ones():
| assert_array_equal(numpy.matlib.ones((2, 3)),
| np.matrix([[ 1., 1., 1.],
| [ 1., 1., 1.]]))
|
| assert_array_equal(numpy.matlib.ones(2), np.matrix([[ 1., 1.]]))
|
| def test_zeros():
| assert_array_equal(numpy.matlib.zeros((2, 3)),
| np.matrix([[ 0., 0., 0.],
| [ 0., 0., 0.]]))
|
| assert_array_equal(numpy.matlib.zeros(2), np.matrix([[ 0., 0.]]))
|
| def test_identity():
| x = numpy.matlib.identity(2, dtype=int)
| assert_array_equal(x, np.matrix([[1, 0], [0, 1]]))
|
| def test_eye():
| xc = numpy.matlib.eye(3, k=1, dtype=int)
| assert_array_equal(xc, np.matrix([[ 0, 1, 0],
| [ 0, 0, 1],
| [ 0, 0, 0]]))
| assert xc.flags.c_contiguous
| assert not xc.flags.f_contiguous
|
| xf = numpy.matlib.eye(3, 4, dtype=int, order='F')
| assert_array_equal(xf, np.matrix([[ 1, 0, 0, 0],
| [ 0, 1, 0, 0],
| [ 0, 0, 1, 0]]))
| assert not xf.flags.c_contiguous
| assert xf.flags.f_contiguous
|
| def test_rand():
| x = numpy.matlib.rand(3)
| # check matrix type, array would have shape (3,)
| assert_(x.ndim == 2)
|
| def test_randn():
| x = np.matlib.randn(3)
| # check matrix type, array would have shape (3,)
| assert_(x.ndim == 2)
|
| def test_repmat():
| a1 = np.arange(4)
| x = numpy.matlib.repmat(a1, 2, 2)
| y = np.array([[0, 1, 2, 3, 0, 1, 2, 3],
| [0, 1, 2, 3, 0, 1, 2, 3]])
| assert_array_equal(x, y)
|
|