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| author | Adam J. Stewart <ajstewart426@gmail.com> | 2019-01-30 12:26:52 -0600 |
|---|---|---|
| committer | Adam J. Stewart <ajstewart426@gmail.com> | 2019-01-30 12:26:52 -0600 |
| commit | 66710151a7130bc01de920a1a08431524c0ca513 (patch) | |
| tree | 3fdda1fcd92d59ca67ba6557ee038034cbdf8f91 /numpy/linalg/linalg.py | |
| parent | da417627f6ffef5820d8c95140497ebde15c7e95 (diff) | |
| download | numpy-66710151a7130bc01de920a1a08431524c0ca513.tar.gz | |
DOC: fix math formatting of np.linalg.lstsq docs
Replace double pipe with actual norm symbol.
Also remove unnecessary space after hanging hyphen.
Diffstat (limited to 'numpy/linalg/linalg.py')
| -rw-r--r-- | numpy/linalg/linalg.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 189c64a39..47b1c4050 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -1010,7 +1010,7 @@ def eigvals(a): See Also -------- eig : eigenvalues and right eigenvectors of general arrays - eigvalsh : eigenvalues of real symmetric or complex Hermitian + eigvalsh : eigenvalues of real symmetric or complex Hermitian (conjugate symmetric) arrays. eigh : eigenvalues and eigenvectors of real symmetric or complex Hermitian (conjugate symmetric) arrays. @@ -1214,7 +1214,7 @@ def eig(a): -------- eigvals : eigenvalues of a non-symmetric array. - eigh : eigenvalues and eigenvectors of a real symmetric or complex + eigh : eigenvalues and eigenvectors of a real symmetric or complex Hermitian (conjugate symmetric) array. eigvalsh : eigenvalues of a real symmetric or complex Hermitian @@ -2133,9 +2133,9 @@ def lstsq(a, b, rcond="warn"): """ Return the least-squares solution to a linear matrix equation. - Solves the equation `a x = b` by computing a vector `x` that - minimizes the Euclidean 2-norm `|| b - a x ||^2`. The equation may - be under-, well-, or over- determined (i.e., the number of + Solves the equation :math:`a x = b` by computing a vector `x` that + minimizes the Euclidean 2-norm :math:`\| b - a x \|_2`. The equation may + be under-, well-, or over-determined (i.e., the number of linearly independent rows of `a` can be less than, equal to, or greater than its number of linearly independent columns). If `a` is square and of full rank, then `x` (but for round-off error) is |