diff options
Diffstat (limited to 'numpy/linalg/linalg.py')
| -rw-r--r-- | numpy/linalg/linalg.py | 20 |
1 files changed, 10 insertions, 10 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 |