diff options
Diffstat (limited to 'numpy/linalg/linalg.py')
| -rw-r--r-- | numpy/linalg/linalg.py | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 6002c63b9..84e450b12 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -192,15 +192,15 @@ def _fastCopyAndTranspose(type, *arrays): def _assertRank2(*arrays): for a in arrays: - if len(a.shape) != 2: + if a.ndim != 2: raise LinAlgError('%d-dimensional array given. Array must be ' - 'two-dimensional' % len(a.shape)) + 'two-dimensional' % a.ndim) def _assertRankAtLeast2(*arrays): for a in arrays: - if len(a.shape) < 2: + if a.ndim < 2: raise LinAlgError('%d-dimensional array given. Array must be ' - 'at least two-dimensional' % len(a.shape)) + 'at least two-dimensional' % a.ndim) def _assertSquareness(*arrays): for a in arrays: @@ -231,7 +231,7 @@ def tensorsolve(a, b, axes=None): It is assumed that all indices of `x` are summed over in the product, together with the rightmost indices of `a`, as is done in, for example, - ``tensordot(a, x, axes=len(b.shape))``. + ``tensordot(a, x, axes=b.ndim)``. Parameters ---------- @@ -1917,7 +1917,7 @@ def lstsq(a, b, rcond=-1): import math a, _ = _makearray(a) b, wrap = _makearray(b) - is_1d = len(b.shape) == 1 + is_1d = b.ndim == 1 if is_1d: b = b[:, newaxis] _assertRank2(a, b) |