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authorMelissa Weber Mendonça <melissawm@gmail.com>2020-01-24 10:42:51 -0300
committerGitHub <noreply@github.com>2020-01-24 10:42:51 -0300
commitf5a644d4d3c9276e0e428ab8897640b3d9ef996c (patch)
treebcb2553705c982165ee9d16a0d0ba58d9ab8a6af /doc/source
parentc53bd9b4eb0577e7e560cb5c20b4267ab77ffac5 (diff)
downloadnumpy-f5a644d4d3c9276e0e428ab8897640b3d9ef996c.tar.gz
Update doc/source/user/tutorial-svd.rst
Co-Authored-By: Anne Bonner <35413198+bonn0062@users.noreply.github.com>
Diffstat (limited to 'doc/source')
-rw-r--r--doc/source/user/tutorial-svd.rst2
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/source/user/tutorial-svd.rst b/doc/source/user/tutorial-svd.rst
index f77064617..306213c39 100644
--- a/doc/source/user/tutorial-svd.rst
+++ b/doc/source/user/tutorial-svd.rst
@@ -316,7 +316,7 @@ In our case,
>>> img_array.shape
(768, 1024, 3)
-so we need to permutate the axis on this array to make get a shape like
+so we need to permutate the axis on this array to get a shape like
``(3, 768, 1024)``. Fortunately, the `numpy.transpose` function can do that for
us: