diff options
Diffstat (limited to 'numpy/linalg')
| -rw-r--r-- | numpy/linalg/linalg.py | 7 | ||||
| -rw-r--r-- | numpy/linalg/tests/test_linalg.py | 2 |
2 files changed, 7 insertions, 2 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 287b38d9b..0b7aa132e 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -1674,7 +1674,7 @@ def norm(x, ord=None): Notes ----- - For values of ``ord < 0``, the result is, strictly speaking, not a + For values of ``ord <= 0``, the result is, strictly speaking, not a mathematical 'norm', but it may still be useful for various numerical purposes. @@ -1687,6 +1687,7 @@ def norm(x, ord=None): 'fro' Frobenius norm -- inf max(sum(abs(x), axis=1)) max(abs(x)) -inf min(sum(abs(x), axis=1)) min(abs(x)) + 0 -- sum(x != 0) 1 max(sum(abs(x), axis=0)) as below -1 min(sum(abs(x), axis=0)) as below 2 2-norm (largest sing. value) as below @@ -1754,15 +1755,17 @@ def norm(x, ord=None): """ x = asarray(x) - nd = len(x.shape) if ord is None: # check the default case first and handle it immediately return sqrt(add.reduce((x.conj() * x).ravel().real)) + nd = x.ndim if nd == 1: if ord == Inf: return abs(x).max() elif ord == -Inf: return abs(x).min() + elif ord == 0: + return (x != 0).sum() # Zero norm elif ord == 1: return abs(x).sum() # special case for speedup elif ord == 2: diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 849f30a50..01e96d6a2 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -282,6 +282,7 @@ class _TestNorm(TestCase): 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) @@ -304,6 +305,7 @@ class _TestNorm(TestCase): self.assertRaises(ValueError, norm, A, 'nofro') self.assertRaises(ValueError, norm, A, -3) + self.assertRaises(ValueError, norm, A, 0) class TestNormDouble(_TestNorm): dt = np.double |