diff options
Diffstat (limited to 'numpy/linalg/linalg.py')
| -rw-r--r-- | numpy/linalg/linalg.py | 65 |
1 files changed, 48 insertions, 17 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index e70227e5a..30180f24a 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -319,6 +319,8 @@ def solve(a, b): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -476,6 +478,8 @@ def inv(a): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -553,6 +557,8 @@ def cholesky(a): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -849,6 +855,8 @@ def eigvals(a): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -937,6 +945,8 @@ def eigvalsh(a, UPLO='L'): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -1010,13 +1020,18 @@ def eig(a): See Also -------- + eigvals : eigenvalues of a non-symmetric array. + + eigh : eigenvalues and eigenvectors of a symmetric or Hermitian + (conjugate symmetric) array. + eigvalsh : eigenvalues of a symmetric or Hermitian (conjugate symmetric) array. - eigvals : eigenvalues of a non-symmetric array. - Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -1123,7 +1138,7 @@ def eigh(a, UPLO='L'): Parameters ---------- - A : (..., M, M) array + a : (..., M, M) array Hermitian/Symmetric matrices whose eigenvalues and eigenvectors are to be computed. UPLO : {'L', 'U'}, optional @@ -1152,6 +1167,8 @@ def eigh(a, UPLO='L'): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -1259,6 +1276,8 @@ def svd(a, full_matrices=1, compute_uv=1): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -1628,13 +1647,15 @@ def slogdet(a): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. + .. versionadded:: 1.6.0. The determinant is computed via LU factorization using the LAPACK routine z/dgetrf. - .. versionadded:: 1.6.0. Examples -------- @@ -1697,6 +1718,8 @@ def det(a): Notes ----- + + .. versionadded:: 1.8.0 Broadcasting rules apply, see the `numpy.linalg` documentation for details. @@ -2059,18 +2082,22 @@ def norm(x, ord=None, axis=None, keepdims=False): """ x = asarray(x) - # Check the default case first and handle it immediately. - if ord is None and axis is None: + # Immediately handle some default, simple, fast, and common cases. + if axis is None: ndim = x.ndim - x = x.ravel(order='K') - if isComplexType(x.dtype.type): - sqnorm = dot(x.real, x.real) + dot(x.imag, x.imag) - else: - sqnorm = dot(x, x) - ret = sqrt(sqnorm) - if keepdims: - ret = ret.reshape(ndim*[1]) - return ret + if ((ord is None) or + (ord in ('f', 'fro') and ndim == 2) or + (ord == 2 and ndim == 1)): + + x = x.ravel(order='K') + if isComplexType(x.dtype.type): + sqnorm = dot(x.real, x.real) + dot(x.imag, x.imag) + else: + sqnorm = dot(x, x) + ret = sqrt(sqnorm) + if keepdims: + ret = ret.reshape(ndim*[1]) + return ret # Normalize the `axis` argument to a tuple. nd = x.ndim @@ -2119,10 +2146,14 @@ def norm(x, ord=None, axis=None, keepdims=False): return add.reduce(absx, axis=axis, keepdims=keepdims) ** (1.0 / ord) elif len(axis) == 2: row_axis, col_axis = axis - if not (-nd <= row_axis < nd and -nd <= col_axis < nd): + if row_axis < 0: + row_axis += nd + if col_axis < 0: + col_axis += nd + if not (0 <= row_axis < nd and 0 <= col_axis < nd): raise ValueError('Invalid axis %r for an array with shape %r' % (axis, x.shape)) - if row_axis % nd == col_axis % nd: + if row_axis == col_axis: raise ValueError('Duplicate axes given.') if ord == 2: ret = _multi_svd_norm(x, row_axis, col_axis, amax) |