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Diffstat (limited to 'doc/source/reference/arrays.classes.rst')
| -rw-r--r-- | doc/source/reference/arrays.classes.rst | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst index 865838699..671c95bbf 100644 --- a/doc/source/reference/arrays.classes.rst +++ b/doc/source/reference/arrays.classes.rst @@ -13,7 +13,7 @@ difficult decision, and can be simply a matter of choice. NumPy has several tools for simplifying how your new object interacts with other array objects, and so the choice may not be significant in the end. One way to simplify the question is by asking yourself if the -object you are interested can be replaced as a single array or does it +object you are interested in can be replaced as a single array or does it really require two or more arrays at its core. Note that :func:`asarray` always returns the base-class ndarray. If @@ -24,7 +24,7 @@ principal a subclass could redefine any aspect of the array and therefore, under strict guidelines, :func:`asanyarray` would rarely be useful. However, most subclasses of the arrayobject will not redefine certain aspects of the array object such as the buffer -interface, or the attributes of the array. One of important example, +interface, or the attributes of the array. One important example, however, of why your subroutine may not be able to handle an arbitrary subclass of an array is that matrices redefine the "*" operator to be matrix-multiplication, rather than element-by-element multiplication. @@ -77,7 +77,7 @@ Matrix objects :class:`matrix` objects inherit from the ndarray and therefore, they have the same attributes and methods of ndarrays. There are six -important differences of matrix objects, however that may lead to +important differences of matrix objects, however, that may lead to unexpected results when you use matrices but expect them to act like arrays: |