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| author | Jarrod Millman <millman@berkeley.edu> | 2008-04-20 11:49:35 +0000 |
|---|---|---|
| committer | Jarrod Millman <millman@berkeley.edu> | 2008-04-20 11:49:35 +0000 |
| commit | 8c663313de36e860bbfea0909de181d330bfdfc7 (patch) | |
| tree | a7b5f3585d2b8a2d8307bfb03dd0e449fa732860 /numpy/linalg | |
| parent | cb7de97f089b67eaacf37ddbebcfb91c292c0ef4 (diff) | |
| download | numpy-8c663313de36e860bbfea0909de181d330bfdfc7.tar.gz | |
ran reindent in preparation for the 1.1 release
Diffstat (limited to 'numpy/linalg')
| -rw-r--r-- | numpy/linalg/linalg.py | 20 | ||||
| -rw-r--r-- | numpy/linalg/tests/test_regression.py | 8 |
2 files changed, 14 insertions, 14 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 1706ff4a9..f56005292 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -972,8 +972,8 @@ def svd(a, full_matrices=1, compute_uv=1): def cond(x,p=None): """Compute the condition number of a matrix. - The condition number of x is the norm of x times the norm - of the inverse of x. The norm can be the usual L2 + The condition number of x is the norm of x times the norm + of the inverse of x. The norm can be the usual L2 (root-of-sum-of-squares) norm or a number of other matrix norms. Parameters @@ -983,16 +983,16 @@ def cond(x,p=None): p : {None, 1, -1, 2, -2, inf, -inf, 'fro'} Order of the norm: - p norm for matrices + p norm for matrices ===== ============================ None 2-norm, computed directly using the SVD - 'fro' Frobenius norm - inf max(sum(abs(x), axis=1)) - -inf min(sum(abs(x), axis=1)) - 1 max(sum(abs(x), axis=0)) - -1 min(sum(abs(x), axis=0)) - 2 2-norm (largest sing. value) - -2 smallest singular value + 'fro' Frobenius norm + inf max(sum(abs(x), axis=1)) + -inf min(sum(abs(x), axis=1)) + 1 max(sum(abs(x), axis=0)) + -1 min(sum(abs(x), axis=0)) + 2 2-norm (largest sing. value) + -2 smallest singular value ===== ============================ Returns diff --git a/numpy/linalg/tests/test_regression.py b/numpy/linalg/tests/test_regression.py index f712adb54..1335643bb 100644 --- a/numpy/linalg/tests/test_regression.py +++ b/numpy/linalg/tests/test_regression.py @@ -12,9 +12,9 @@ rlevel = 1 class TestRegression(NumpyTestCase): def test_eig_build(self, level = rlevel): """Ticket #652""" - rva = [1.03221168e+02 +0.j, + rva = [1.03221168e+02 +0.j, -1.91843603e+01 +0.j, - -6.04004526e-01+15.84422474j, + -6.04004526e-01+15.84422474j, -6.04004526e-01-15.84422474j, -1.13692929e+01 +0.j, -6.57612485e-01+10.41755503j, @@ -24,7 +24,7 @@ class TestRegression(NumpyTestCase): 7.80732773e+00 +0.j , -7.65390898e-01 +0.j, 1.51971555e-15 +0.j , - -1.51308713e-15 +0.j] + -1.51308713e-15 +0.j] a = arange(13*13, dtype = float64) a.shape = (13,13) a = a%17 @@ -38,7 +38,7 @@ class TestRegression(NumpyTestCase): cov = array([[ 77.70273908, 3.51489954, 15.64602427], [3.51489954, 88.97013878, -1.07431931], [15.64602427, -1.07431931, 98.18223512]]) - + vals, vecs = linalg.eigh(cov) assert_array_almost_equal(vals, rvals) |