diff options
Diffstat (limited to 'doc/source/reference')
| -rw-r--r-- | doc/source/reference/arrays.ndarray.rst | 8 | ||||
| -rw-r--r-- | doc/source/reference/c-api/array.rst | 4 | ||||
| -rw-r--r-- | doc/source/reference/c-api/types-and-structures.rst | 9 | ||||
| -rw-r--r-- | doc/source/reference/internals.code-explanations.rst | 7 | ||||
| -rw-r--r-- | doc/source/reference/maskedarray.generic.rst | 18 | ||||
| -rw-r--r-- | doc/source/reference/random/c-api.rst | 2 | ||||
| -rw-r--r-- | doc/source/reference/routines.array-manipulation.rst | 1 | ||||
| -rw-r--r-- | doc/source/reference/ufuncs.rst | 4 |
8 files changed, 28 insertions, 25 deletions
diff --git a/doc/source/reference/arrays.ndarray.rst b/doc/source/reference/arrays.ndarray.rst index 689240c7d..405ae8f6a 100644 --- a/doc/source/reference/arrays.ndarray.rst +++ b/doc/source/reference/arrays.ndarray.rst @@ -469,7 +469,7 @@ Comparison operators: ndarray.__eq__ ndarray.__ne__ -Truth value of an array (:func:`bool()`): +Truth value of an array (:class:`bool() <bool>`): .. autosummary:: :toctree: generated/ @@ -604,9 +604,9 @@ Container customization: (see :ref:`Indexing <arrays.indexing>`) ndarray.__setitem__ ndarray.__contains__ -Conversion; the operations :func:`int()`, :func:`float()` and -:func:`complex()`. -. They work only on arrays that have one element in them +Conversion; the operations :class:`int() <int>`, +:class:`float() <float>` and :class:`complex() <complex>`. +They work only on arrays that have one element in them and return the appropriate scalar. .. autosummary:: diff --git a/doc/source/reference/c-api/array.rst b/doc/source/reference/c-api/array.rst index 68547fd45..ae39f980f 100644 --- a/doc/source/reference/c-api/array.rst +++ b/doc/source/reference/c-api/array.rst @@ -1335,7 +1335,7 @@ Special functions for NPY_OBJECT locations in the structure with object data-types. No checking is performed but *arr* must be of data-type :c:type:`NPY_OBJECT` and be single-segment and uninitialized (no previous objects in - position). Use :c:func:`PyArray_DECREF` (*arr*) if you need to + position). Use :c:func:`PyArray_XDECREF` (*arr*) if you need to decrement all the items in the object array prior to calling this function. @@ -1354,7 +1354,7 @@ Special functions for NPY_OBJECT strides, ordering, etc.) Sets the :c:data:`NPY_ARRAY_WRITEBACKIFCOPY` flag and ``arr->base``, and set ``base`` to READONLY. Call :c:func:`PyArray_ResolveWritebackIfCopy` before calling - `Py_DECREF`` in order copy any changes back to ``base`` and + `Py_DECREF` in order copy any changes back to ``base`` and reset the READONLY flag. Returns 0 for success, -1 for failure. diff --git a/doc/source/reference/c-api/types-and-structures.rst b/doc/source/reference/c-api/types-and-structures.rst index fb5753c02..c45ebb692 100644 --- a/doc/source/reference/c-api/types-and-structures.rst +++ b/doc/source/reference/c-api/types-and-structures.rst @@ -69,6 +69,7 @@ PyArray_Type and PyArrayObject typeobject. .. c:type:: PyArrayObject + NPY_AO The :c:type:`PyArrayObject` C-structure contains all of the required information for an array. All instances of an ndarray (and its @@ -77,7 +78,7 @@ PyArray_Type and PyArrayObject provided macros. If you need a shorter name, then you can make use of :c:type:`NPY_AO` (deprecated) which is defined to be equivalent to :c:type:`PyArrayObject`. Direct access to the struct fields are - deprecated. Use the `PyArray_*(arr)` form instead. + deprecated. Use the ``PyArray_*(arr)`` form instead. .. code-block:: c @@ -813,7 +814,7 @@ PyUFunc_Type and PyUFuncObject .. c:member:: int identity Either :c:data:`PyUFunc_One`, :c:data:`PyUFunc_Zero`, - :c:data:`PyUFunc_None` or :c:data:`PyUFunc_AllOnes` to indicate + or :c:data:`PyUFunc_None` to indicate the identity for this operation. It is only used for a reduce-like call on an empty array. @@ -1216,8 +1217,8 @@ are ``Py{TYPE}ArrType_Type`` where ``{TYPE}`` can be **Object**. These type names are part of the C-API and can therefore be created in -extension C-code. There is also a :c:data:`PyIntpArrType_Type` and a -:c:data:`PyUIntpArrType_Type` that are simple substitutes for one of the +extension C-code. There is also a ``PyIntpArrType_Type`` and a +``PyUIntpArrType_Type`` that are simple substitutes for one of the integer types that can hold a pointer on the platform. The structure of these scalar objects is not exposed to C-code. The function :c:func:`PyArray_ScalarAsCtype` (..) can be used to extract the C-type diff --git a/doc/source/reference/internals.code-explanations.rst b/doc/source/reference/internals.code-explanations.rst index 65553e07e..e8e428f2e 100644 --- a/doc/source/reference/internals.code-explanations.rst +++ b/doc/source/reference/internals.code-explanations.rst @@ -147,7 +147,8 @@ an iterator for each of the arrays being broadcast. The :c:func:`PyArray_Broadcast` function takes the iterators that have already been defined and uses them to determine the broadcast shape in each dimension (to create the iterators at the same time that broadcasting -occurs then use the :c:func:`PyMultiIter_New` function). Then, the iterators are +occurs then use the :c:func:`PyArray_MultiIterNew` function). +Then, the iterators are adjusted so that each iterator thinks it is iterating over an array with the broadcast size. This is done by adjusting the iterators number of dimensions, and the shape in each dimension. This works @@ -162,7 +163,7 @@ for the extended dimensions. It is done in exactly the same way in NumPy. The big difference is that now the array of strides is kept track of in a :c:type:`PyArrayIterObject`, the iterators involved in a broadcast result are kept track of in a :c:type:`PyArrayMultiIterObject`, -and the :c:func:`PyArray_BroadCast` call implements the broad-casting rules. +and the :c:func:`PyArray_Broadcast` call implements the broad-casting rules. Array Scalars @@ -368,7 +369,7 @@ The output arguments (if any) are then processed and any missing return arrays are constructed. If any provided output array doesn't have the correct type (or is mis-aligned) and is smaller than the buffer size, then a new output array is constructed with the special -:c:data:`WRITEBACKIFCOPY` flag set. At the end of the function, +:c:data:`NPY_ARRAY_WRITEBACKIFCOPY` flag set. At the end of the function, :c:func:`PyArray_ResolveWritebackIfCopy` is called so that its contents will be copied back into the output array. Iterators for the output arguments are then processed. diff --git a/doc/source/reference/maskedarray.generic.rst b/doc/source/reference/maskedarray.generic.rst index 41c3ee564..d3849c50d 100644 --- a/doc/source/reference/maskedarray.generic.rst +++ b/doc/source/reference/maskedarray.generic.rst @@ -177,8 +177,8 @@ attribute. We must keep in mind that a ``True`` entry in the mask indicates an *invalid* data. Another possibility is to use the :func:`getmask` and :func:`getmaskarray` -functions. :func:`getmask(x)` outputs the mask of ``x`` if ``x`` is a masked -array, and the special value :data:`nomask` otherwise. :func:`getmaskarray(x)` +functions. ``getmask(x)`` outputs the mask of ``x`` if ``x`` is a masked +array, and the special value :data:`nomask` otherwise. ``getmaskarray(x)`` outputs the mask of ``x`` if ``x`` is a masked array. If ``x`` has no invalid entry or is not a masked array, the function outputs a boolean array of ``False`` with as many elements as ``x``. @@ -296,11 +296,11 @@ new valid values to them:: .. note:: Unmasking an entry by direct assignment will silently fail if the masked - array has a *hard* mask, as shown by the :attr:`hardmask` attribute. This - feature was introduced to prevent overwriting the mask. To force the - unmasking of an entry where the array has a hard mask, the mask must first - to be softened using the :meth:`soften_mask` method before the allocation. - It can be re-hardened with :meth:`harden_mask`:: + array has a *hard* mask, as shown by the :attr:`~MaskedArray.hardmask` + attribute. This feature was introduced to prevent overwriting the mask. + To force the unmasking of an entry where the array has a hard mask, + the mask must first to be softened using the :meth:`soften_mask` method + before the allocation. It can be re-hardened with :meth:`harden_mask`:: >>> x = ma.array([1, 2, 3], mask=[0, 0, 1], hard_mask=True) >>> x @@ -406,8 +406,8 @@ Operations on masked arrays Arithmetic and comparison operations are supported by masked arrays. As much as possible, invalid entries of a masked array are not processed, -meaning that the corresponding :attr:`data` entries *should* be the same -before and after the operation. +meaning that the corresponding :attr:`~MaskedArray.data` entries +*should* be the same before and after the operation. .. warning:: We need to stress that this behavior may not be systematic, that masked diff --git a/doc/source/reference/random/c-api.rst b/doc/source/reference/random/c-api.rst index 63b0fdc2b..bd119abe3 100644 --- a/doc/source/reference/random/c-api.rst +++ b/doc/source/reference/random/c-api.rst @@ -181,6 +181,6 @@ Generate a single integer Generate random uint64 numbers in closed interval [off, off + rng]. -.. c:function:: npy_uint64 random_bounded_uint64(bitgen_t *bitgen_state, npy_uint64 off, npy_uint64 rng, npy_uint64 mask, bint use_masked) +.. c:function:: npy_uint64 random_bounded_uint64(bitgen_t *bitgen_state, npy_uint64 off, npy_uint64 rng, npy_uint64 mask, int use_masked) diff --git a/doc/source/reference/routines.array-manipulation.rst b/doc/source/reference/routines.array-manipulation.rst index 8d13a1800..1c96495d9 100644 --- a/doc/source/reference/routines.array-manipulation.rst +++ b/doc/source/reference/routines.array-manipulation.rst @@ -74,6 +74,7 @@ Joining arrays hstack dstack column_stack + row_stack Splitting arrays ================ diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst index c729f8d37..06fbe28dd 100644 --- a/doc/source/reference/ufuncs.rst +++ b/doc/source/reference/ufuncs.rst @@ -1,5 +1,7 @@ .. sectionauthor:: adapted from "Guide to NumPy" by Travis E. Oliphant +.. currentmodule:: numpy + .. _ufuncs: ************************************ @@ -8,8 +10,6 @@ Universal functions (:class:`ufunc`) .. note: XXX: section might need to be made more reference-guideish... -.. currentmodule:: numpy - .. index: ufunc, universal function, arithmetic, operation A universal function (or :term:`ufunc` for short) is a function that |