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authorKatharine Hyatt <khyatt@flatironinstitute.org>2019-03-18 09:23:13 -0400
committerKatharine Hyatt <khyatt@flatironinstitute.org>2019-03-18 09:23:13 -0400
commit1872427bb86ab192d2e93311e9a38a409e1d6efa (patch)
treef1891c9da8f0a2d88eb9002f55af2e7cd89cf4e4 /numpy
parentc67c73aced04c1ba9d93a3ce69fde6a076d6af39 (diff)
downloadnumpy-1872427bb86ab192d2e93311e9a38a409e1d6efa.tar.gz
Double to single for linking, = -> ==
Diffstat (limited to 'numpy')
-rw-r--r--numpy/linalg/linalg.py6
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
-------