diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/linalg/linalg.py | 4 | ||||
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 72 |
2 files changed, 40 insertions, 36 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 49d645e80..ff9877549 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -1896,12 +1896,12 @@ def _multi_svd_norm(x, row_axis, col_axis, op): z = y.reshape((-1,) + y.shape[-2:]) else: z = y - if x.ndim == 2: + if x.ndim == 2: result = op(svd(z, compute_uv=0)) else: result = array([op(svd(m, compute_uv=0)) for m in z]) result.shape = y.shape[:-2] - return result + return result def norm(x, ord=None, axis=None): diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 7ee7b8317..881311c94 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -515,8 +515,10 @@ class TestEigh(HermitianTestCase, HermitianGeneralizedTestCase, TestCase): class _TestNorm(TestCase): + dt = None dec = None + def test_empty(self): assert_equal(norm([]), 0.0) assert_equal(norm(array([], dtype=self.dt)), 0.0) @@ -528,17 +530,22 @@ class _TestNorm(TestCase): c = [-1, 2, -3, 4] def _test(v): - np.testing.assert_almost_equal(norm(v), 30**0.5, decimal=self.dec) - np.testing.assert_almost_equal(norm(v,inf), 4.0, decimal=self.dec) - np.testing.assert_almost_equal(norm(v,-inf), 1.0, decimal=self.dec) - np.testing.assert_almost_equal(norm(v,1), 10.0, decimal=self.dec) - np.testing.assert_almost_equal(norm(v,-1), 12.0/25, - decimal=self.dec) - np.testing.assert_almost_equal(norm(v,2), 30**0.5, - decimal=self.dec) - np.testing.assert_almost_equal(norm(v,-2), ((205./144)**-0.5), - decimal=self.dec) - np.testing.assert_almost_equal(norm(v,0), 4, decimal=self.dec) + np.testing.assert_almost_equal(norm(v), 30**0.5, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, inf), 4.0, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, -inf), 1.0, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, 1), 10.0, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, -1), 12.0/25, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, 2), 30**0.5, + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, -2), ((205./144)**-0.5), + decimal=self.dec) + np.testing.assert_almost_equal(norm(v, 0), 4, + decimal=self.dec) for v in (a, b, c,): _test(v) @@ -550,13 +557,13 @@ class _TestNorm(TestCase): def test_matrix(self): A = matrix([[1, 3], [5, 7]], dtype=self.dt) assert_almost_equal(norm(A), 84**0.5) - assert_almost_equal(norm(A,'fro'), 84**0.5) - assert_almost_equal(norm(A,inf), 12.0) - assert_almost_equal(norm(A,-inf), 4.0) - assert_almost_equal(norm(A,1), 10.0) - assert_almost_equal(norm(A,-1), 6.0) - assert_almost_equal(norm(A,2), 9.1231056256176615) - assert_almost_equal(norm(A,-2), 0.87689437438234041) + assert_almost_equal(norm(A, 'fro'), 84**0.5) + assert_almost_equal(norm(A, inf), 12.0) + assert_almost_equal(norm(A, -inf), 4.0) + assert_almost_equal(norm(A, 1), 10.0) + assert_almost_equal(norm(A, -1), 6.0) + assert_almost_equal(norm(A, 2), 9.1231056256176615) + assert_almost_equal(norm(A, -2), 0.87689437438234041) self.assertRaises(ValueError, norm, A, 'nofro') self.assertRaises(ValueError, norm, A, -3) @@ -574,36 +581,33 @@ class _TestNorm(TestCase): assert_almost_equal(norm(A, ord=order, axis=1), expected1) # Matrix norms. - B = np.arange(1, 25, dtype=self.dt).reshape(2,3,4) + B = np.arange(1, 25, dtype=self.dt).reshape(2, 3, 4) for order in [None, -2, 2, -1, 1, np.Inf, -np.Inf, 'fro']: - assert_almost_equal(norm(A, ord=order), norm(A, ord=order, axis=(0,1))) + assert_almost_equal(norm(A, ord=order), norm(A, ord=order, + axis=(0, 1))) - n = norm(B, ord=order, axis=(1,2)) + n = norm(B, ord=order, axis=(1, 2)) expected = [norm(B[k], ord=order) for k in range(B.shape[0])] - print("shape is %r, axis=(1,2)" % (B.shape,)) assert_almost_equal(n, expected) - n = norm(B, ord=order, axis=(2,1)) + n = norm(B, ord=order, axis=(2, 1)) expected = [norm(B[k].T, ord=order) for k in range(B.shape[0])] - print("shape is %r, axis=(2,1)" % (B.shape,)) assert_almost_equal(n, expected) - n = norm(B, ord=order, axis=(0,2)) + n = norm(B, ord=order, axis=(0, 2)) expected = [norm(B[:,k,:], ord=order) for k in range(B.shape[1])] - print("shape is %r, axis=(0,2)" % (B.shape,)) assert_almost_equal(n, expected) - n = norm(B, ord=order, axis=(0,1)) + n = norm(B, ord=order, axis=(0, 1)) expected = [norm(B[:,:,k], ord=order) for k in range(B.shape[2])] - print("shape is %r, axis=(0,1)" % (B.shape,)) assert_almost_equal(n, expected) def test_bad_args(self): # Check that bad arguments raise the appropriate exceptions. A = array([[1, 2, 3], [4, 5, 6]], dtype=self.dt) - B = np.arange(1, 25, dtype=self.dt).reshape(2,3,4) + B = np.arange(1, 25, dtype=self.dt).reshape(2, 3, 4) # Using `axis=<integer>` or passing in a 1-D array implies vector # norms are being computed, so also using `ord='fro'` raises a @@ -615,18 +619,18 @@ class _TestNorm(TestCase): # number other than 1, 2, -1 or -2 when computing matrix norms. for order in [0, 3]: self.assertRaises(ValueError, norm, A, order, None) - self.assertRaises(ValueError, norm, A, order, (0,1)) - self.assertRaises(ValueError, norm, B, order, (1,2)) + self.assertRaises(ValueError, norm, A, order, (0, 1)) + self.assertRaises(ValueError, norm, B, order, (1, 2)) # Invalid axis self.assertRaises(ValueError, norm, B, None, 3) - self.assertRaises(ValueError, norm, B, None, (2,3)) - self.assertRaises(ValueError, norm, B, None, (0,1,2)) + self.assertRaises(ValueError, norm, B, None, (2, 3)) + self.assertRaises(ValueError, norm, B, None, (0, 1, 2)) class TestNormDouble(_TestNorm): dt = np.double - dec= 12 + dec = 12 class TestNormSingle(_TestNorm): |