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author | Katharine Hyatt <khyatt@flatironinstitute.org> | 2019-03-18 09:23:13 -0400 |
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committer | Katharine Hyatt <khyatt@flatironinstitute.org> | 2019-03-18 09:23:13 -0400 |
commit | 1872427bb86ab192d2e93311e9a38a409e1d6efa (patch) | |
tree | f1891c9da8f0a2d88eb9002f55af2e7cd89cf4e4 /numpy | |
parent | c67c73aced04c1ba9d93a3ce69fde6a076d6af39 (diff) | |
download | numpy-1872427bb86ab192d2e93311e9a38a409e1d6efa.tar.gz |
Double to single for linking, = -> ==
Diffstat (limited to 'numpy')
-rw-r--r-- | numpy/linalg/linalg.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 67b86e9fd..29da77655 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -1279,7 +1279,7 @@ def eig(a): [0. -0.70710678j, 0. +0.70710678j]]) Complex-valued matrix with real e-values (but complex-valued e-vectors); - note that ``a.conj().T = a``, i.e., `a` is Hermitian. + note that ``a.conj().T == a``, i.e., `a` is Hermitian. >>> a = np.array([[1, 1j], [-1j, 1]]) >>> w, v = LA.eig(a) @@ -2288,7 +2288,7 @@ def lstsq(a, b, rcond="warn"): def _multi_svd_norm(x, row_axis, col_axis, op): """Compute a function of the singular values of the 2-D matrices in `x`. - This is a private utility function used by ``numpy.linalg.norm()``. + This is a private utility function used by `numpy.linalg.norm()`. Parameters ---------- @@ -2296,7 +2296,7 @@ def _multi_svd_norm(x, row_axis, col_axis, op): row_axis, col_axis : int The axes of `x` that hold the 2-D matrices. op : callable - This should be either numpy.amin or ``numpy.amax`` or ``numpy.sum``. + This should be either numpy.amin or `numpy.amax` or `numpy.sum`. Returns ------- |