diff options
Diffstat (limited to 'numpy/linalg/tests/test_linalg.py')
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 52 |
1 files changed, 26 insertions, 26 deletions
diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 0a6566bde..d1e032bbb 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -465,7 +465,7 @@ class TestSolve(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype) assert_equal(linalg.solve(x, x).dtype, dtype) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): class ArraySubclass(np.ndarray): @@ -532,7 +532,7 @@ class TestInv(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype) assert_equal(linalg.inv(x).dtype, dtype) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): # Check that all kinds of 0-sized arrays work @@ -565,7 +565,7 @@ class TestEigvals(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): x = np.array([[1, 0.5], [-1, 1]], dtype=dtype) assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype)) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): # Check that all kinds of 0-sized arrays work @@ -608,7 +608,7 @@ class TestEig(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): assert_equal(v.dtype, get_complex_dtype(dtype)) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): # Check that all kinds of 0-sized arrays work @@ -658,7 +658,7 @@ class TestSVD(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): assert_equal(s.dtype, get_real_dtype(dtype)) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): # These raise errors currently @@ -765,7 +765,7 @@ class TestDet(LinalgSquareTestCase, LinalgGeneralizedSquareTestCase): assert_equal(s.dtype, get_real_dtype(dtype)) assert_equal(ph.dtype, dtype) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_0_size(self): a = np.zeros((0, 0), dtype=np.complex64) @@ -861,7 +861,7 @@ class TestMatrixPower(object): assert_equal(mz, identity(M.shape[0])) assert_equal(mz.dtype, M.dtype) for M in [self.Arb22, self.arbfloat, self.large]: - yield tz, M + tz(M) def testip_one(self): def tz(M): @@ -869,7 +869,7 @@ class TestMatrixPower(object): assert_equal(mz, M) assert_equal(mz.dtype, M.dtype) for M in [self.Arb22, self.arbfloat, self.large]: - yield tz, M + tz(M) def testip_two(self): def tz(M): @@ -877,14 +877,14 @@ class TestMatrixPower(object): assert_equal(mz, dot(M, M)) assert_equal(mz.dtype, M.dtype) for M in [self.Arb22, self.arbfloat, self.large]: - yield tz, M + tz(M) def testip_invert(self): def tz(M): mz = matrix_power(M, -1) assert_almost_equal(identity(M.shape[0]), dot(mz, M)) for M in [self.R90, self.Arb22, self.arbfloat, self.large]: - yield tz, M + tz(M) def test_invert_noninvertible(self): import numpy.linalg @@ -918,7 +918,7 @@ class TestEigvalsh(HermitianTestCase, HermitianGeneralizedTestCase): w = np.linalg.eigvalsh(x) assert_equal(w.dtype, get_real_dtype(dtype)) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_invalid(self): x = np.array([[1, 0.5], [0.5, 1]], dtype=np.float32) @@ -995,7 +995,7 @@ class TestEigh(HermitianTestCase, HermitianGeneralizedTestCase): assert_equal(w.dtype, get_real_dtype(dtype)) assert_equal(v.dtype, dtype) for dtype in [single, double, csingle, cdouble]: - yield check, dtype + check(dtype) def test_invalid(self): x = np.array([[1, 0.5], [0.5, 1]], dtype=np.float32) @@ -1365,36 +1365,36 @@ class TestMatrixRank(object): def test_matrix_rank(self): # Full rank matrix - yield assert_equal, 4, matrix_rank(np.eye(4)) + assert_equal(4, matrix_rank(np.eye(4))) # rank deficient matrix I = np.eye(4) I[-1, -1] = 0. - yield assert_equal, matrix_rank(I), 3 + assert_equal(matrix_rank(I), 3) # All zeros - zero rank - yield assert_equal, matrix_rank(np.zeros((4, 4))), 0 + assert_equal(matrix_rank(np.zeros((4, 4))), 0) # 1 dimension - rank 1 unless all 0 - yield assert_equal, matrix_rank([1, 0, 0, 0]), 1 - yield assert_equal, matrix_rank(np.zeros((4,))), 0 + assert_equal(matrix_rank([1, 0, 0, 0]), 1) + assert_equal(matrix_rank(np.zeros((4,))), 0) # accepts array-like - yield assert_equal, matrix_rank([1]), 1 + assert_equal(matrix_rank([1]), 1) # greater than 2 dimensions treated as stacked matrices ms = np.array([I, np.eye(4), np.zeros((4,4))]) - yield assert_equal, matrix_rank(ms), np.array([3, 4, 0]) + assert_equal(matrix_rank(ms), np.array([3, 4, 0])) # works on scalar - yield assert_equal, matrix_rank(1), 1 + assert_equal(matrix_rank(1), 1) def test_symmetric_rank(self): - yield assert_equal, 4, matrix_rank(np.eye(4), hermitian=True) - yield assert_equal, 1, matrix_rank(np.ones((4, 4)), hermitian=True) - yield assert_equal, 0, matrix_rank(np.zeros((4, 4)), hermitian=True) + assert_equal(4, matrix_rank(np.eye(4), hermitian=True)) + assert_equal(1, matrix_rank(np.ones((4, 4)), hermitian=True)) + assert_equal(0, matrix_rank(np.zeros((4, 4)), hermitian=True)) # rank deficient matrix I = np.eye(4) I[-1, -1] = 0. - yield assert_equal, 3, matrix_rank(I, hermitian=True) + assert_equal(3, matrix_rank(I, hermitian=True)) # manually supplied tolerance I[-1, -1] = 1e-8 - yield assert_equal, 4, matrix_rank(I, hermitian=True, tol=0.99e-8) - yield assert_equal, 3, matrix_rank(I, hermitian=True, tol=1.01e-8) + assert_equal(4, matrix_rank(I, hermitian=True, tol=0.99e-8)) + assert_equal(3, matrix_rank(I, hermitian=True, tol=1.01e-8)) def test_reduced_rank(): |