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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) | |