From 773e3cad9a71cb9a7849d8e251fb8a99ab35d06b Mon Sep 17 00:00:00 2001 From: Pierre de Buyl Date: Mon, 5 Sep 2016 22:24:34 +0200 Subject: change all non-code instances of Numpy to NumPy Instances remain for NumpyVersion and Numpy.rec.fromarrays that are references to code. Release notes were left unchanged. see issue #7986 --- doc/source/reference/arrays.scalars.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'doc/source/reference/arrays.scalars.rst') diff --git a/doc/source/reference/arrays.scalars.rst b/doc/source/reference/arrays.scalars.rst index f8fad0095..4acaf1b3b 100644 --- a/doc/source/reference/arrays.scalars.rst +++ b/doc/source/reference/arrays.scalars.rst @@ -94,7 +94,7 @@ Python Boolean scalar. :class:`int` built-in under Python 3, because type :class:`int` is no longer a fixed-width integer type. -.. tip:: The default data type in Numpy is :class:`float_`. +.. tip:: The default data type in NumPy is :class:`float_`. In the tables below, ``platform?`` means that the type may not be available on all platforms. Compatibility with different C or Python @@ -288,4 +288,4 @@ the built-in scalar types): One way is to simply subclass the a degree, but internally certain behaviors are fixed by the data type of the array. To fully customize the data type of an array you need to define a new data-type, and register it with NumPy. Such new types can only -be defined in C, using the :ref:`Numpy C-API `. +be defined in C, using the :ref:`NumPy C-API `. -- cgit v1.2.1