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authorCharles Harris <charlesr.harris@gmail.com>2020-04-25 15:04:36 -0600
committerGitHub <noreply@github.com>2020-04-25 15:04:36 -0600
commit017f717934274e481f1304d3c2f52bfaa193e7f2 (patch)
tree352dadf469f0e8f8483f3586e9caa74415d41000 /doc/neps
parent619422b493eaf88c42373af1725ac0aa2297fa91 (diff)
parent31910e196e13d1042cae3e6c334c38318cf8dfaa (diff)
downloadnumpy-017f717934274e481f1304d3c2f52bfaa193e7f2.tar.gz
Merge pull request #16053 from anirudh2290/nep_40_doc_change_2
DOC: Small typo fixes to NEP 40.
Diffstat (limited to 'doc/neps')
-rw-r--r--doc/neps/nep-0040-legacy-datatype-impl.rst6
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/neps/nep-0040-legacy-datatype-impl.rst b/doc/neps/nep-0040-legacy-datatype-impl.rst
index 799c6c026..c9a4fd7c8 100644
--- a/doc/neps/nep-0040-legacy-datatype-impl.rst
+++ b/doc/neps/nep-0040-legacy-datatype-impl.rst
@@ -180,8 +180,8 @@ These issues do not need to solved right away:
scalars behave much like NumPy arrays, a feature that general Python objects
do not have.
* Seamless integration probably requires that ``np.array(scalar)`` finds the
- correct DType automatically since some operations (such as indexing) are
- return the scalar instead of a 0D array.
+ correct DType automatically since some operations (such as indexing) return
+ the scalar instead of a 0D array.
This is problematic if multiple users independently decide to implement
for example a DType for ``decimal.Decimal``.
@@ -207,7 +207,7 @@ Many datatype-specific functions are defined within a C structure called
:c:type:`PyArray_ArrFuncs`, which is part of each ``dtype`` instance and
has a similarity to Python's ``PyNumberMethods``.
For user-defined datatypes this structure is exposed to the user, making
-ABI-compatible changes changes impossible.
+ABI-compatible changes impossible.
This structure holds important information such as how to copy or cast,
and provides space for pointers to functions, such as comparing elements,
converting to bool, or sorting.