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authorMatti Picus <matti.picus@gmail.com>2020-04-08 09:08:05 +0300
committerGitHub <noreply@github.com>2020-04-08 09:08:05 +0300
commite78d0764d414952716ec75e3c44a74359643cffc (patch)
tree509f5045fe14a8f160b5dd0c74f7f3ce4521056a
parent0ce156413feb21a4f2a8eae3b1cd954d04240edd (diff)
parentf8c598a104c91d094d654cf7b98391d795f7835d (diff)
downloadnumpy-e78d0764d414952716ec75e3c44a74359643cffc.tar.gz
Merge pull request #15931 from anirudh2290/nep_doc_correction
DOC: Correct private function name to PyArray_AdaptFlexibleDType
-rw-r--r--doc/neps/nep-0040-legacy-datatype-impl.rst2
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/neps/nep-0040-legacy-datatype-impl.rst b/doc/neps/nep-0040-legacy-datatype-impl.rst
index 86bd488fe..a768fa08c 100644
--- a/doc/neps/nep-0040-legacy-datatype-impl.rst
+++ b/doc/neps/nep-0040-legacy-datatype-impl.rst
@@ -65,7 +65,7 @@ values are unaffected by it, and it is always possible to cast them to the
native, canonical representation without any loss of information.
The concept of flexibility can be generalized to parametric datatypes.
-For example the private ``AdaptFlexibleDType`` function also accepts the
+For example the private ``PyArray_AdaptFlexibleDType`` function also accepts the
naive datetime dtype as input to find the correct time unit.
The datetime dtype is thus parametric not in the size of its storage,
but instead in what the stored value represents.