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+Array API
+=========
+
+.. sectionauthor:: Travis E. Oliphant
+
+|    The test of a first-rate intelligence is the ability to hold two
+|    opposed ideas in the mind at the same time, and still retain the
+|    ability to function. 
+|    --- *F. Scott Fitzgerald* 
+
+|    For a successful technology, reality must take precedence over public
+|    relations, for Nature cannot be fooled. 
+|    --- *Richard P. Feynman* 
+
+.. index::
+   pair: ndarray; C-API
+   pair: C-API; array
+
+
+Array structure and data access
+-------------------------------
+
+These macros all access the :ctype:`PyArrayObject` structure members. The input
+argument, obj, can be any :ctype:`PyObject *` that is directly interpretable
+as a :ctype:`PyArrayObject *` (any instance of the :cdata:`PyArray_Type` and its
+sub-types).
+
+.. cfunction:: void *PyArray_DATA(PyObject *obj)
+
+.. cfunction:: char *PyArray_BYTES(PyObject *obj)
+
+    These two macros are similar and obtain the pointer to the
+    data-buffer for the array. The first macro can (and should be)
+    assigned to a particular pointer where the second is for generic
+    processing. If you have not guaranteed a contiguous and/or aligned
+    array then be sure you understand how to access the data in the
+    array to avoid memory and/or alignment problems.
+
+.. cfunction:: npy_intp *PyArray_DIMS(PyObject *arr)
+
+.. cfunction:: npy_intp *PyArray_STRIDES(PyObject* arr)
+
+.. cfunction:: npy_intp PyArray_DIM(PyObject* arr, int n)
+
+    Return the shape in the *n* :math:`^{\textrm{th}}` dimension.
+
+.. cfunction:: npy_intp PyArray_STRIDE(PyObject* arr, int n)
+
+    Return the stride in the *n* :math:`^{\textrm{th}}` dimension.
+
+.. cfunction:: PyObject *PyArray_BASE(PyObject* arr)
+
+.. cfunction:: PyArray_Descr *PyArray_DESCR(PyObject* arr)
+
+.. cfunction:: int PyArray_FLAGS(PyObject* arr)
+
+.. cfunction:: int PyArray_ITEMSIZE(PyObject* arr)
+
+    Return the itemsize for the elements of this array.
+
+.. cfunction:: int PyArray_TYPE(PyObject* arr)
+
+    Return the (builtin) typenumber for the elements of this array.
+
+.. cfunction:: PyObject *PyArray_GETITEM(PyObject* arr, void* itemptr)
+
+    Get a Python object from the ndarray, *arr*, at the location
+    pointed to by itemptr. Return ``NULL`` on failure.
+
+.. cfunction:: int PyArray_SETITEM(PyObject* arr, void* itemptr, PyObject* obj)
+
+    Convert obj and place it in the ndarray, *arr*, at the place
+    pointed to by itemptr. Return -1 if an error occurs or 0 on
+    success.
+
+.. cfunction:: npy_intp PyArray_SIZE(PyObject* arr)
+
+    Returns the total size (in number of elements) of the array.
+
+.. cfunction:: npy_intp PyArray_Size(PyObject* obj)
+
+    Returns 0 if *obj* is not a sub-class of bigndarray. Otherwise,
+    returns the total number of elements in the array. Safer version
+    of :cfunc:`PyArray_SIZE` (*obj*).
+
+.. cfunction:: npy_intp PyArray_NBYTES(PyObject* arr)
+
+    Returns the total number of bytes consumed by the array.
+
+
+Data access
+^^^^^^^^^^^
+
+These functions and macros provide easy access to elements of the
+ndarray from C. These work for all arrays. You may need to take care
+when accessing the data in the array, however, if it is not in machine
+byte-order, misaligned, or not writeable. In other words, be sure to
+respect the state of the flags unless you know what you are doing, or
+have previously guaranteed an array that is writeable, aligned, and in
+machine byte-order using :cfunc:`PyArray_FromAny`. If you wish to handle all
+types of arrays, the copyswap function for each type is useful for
+handling misbehaved arrays. Some platforms (e.g. Solaris) do not like
+misaligned data and will crash if you de-reference a misaligned
+pointer. Other platforms (e.g. x86 Linux) will just work more slowly
+with misaligned data.
+
+.. cfunction:: void* PyArray_GetPtr(PyArrayObject* aobj, npy_intp* ind)
+
+    Return a pointer to the data of the ndarray, *aobj*, at the
+    N-dimensional index given by the c-array, *ind*, (which must be
+    at least *aobj* ->nd in size). You may want to typecast the
+    returned pointer to the data type of the ndarray.
+
+.. cfunction:: void* PyArray_GETPTR1(PyObject* obj, <npy_intp> i)
+
+.. cfunction:: void* PyArray_GETPTR2(PyObject* obj, <npy_intp> i, <npy_intp> j)
+
+.. cfunction:: void* PyArray_GETPTR3(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k)
+
+.. cfunction:: void* PyArray_GETPTR4(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k, <npy_intp> l)
+
+    Quick, inline access to the element at the given coordinates in
+    the ndarray, *obj*, which must have respectively 1, 2, 3, or 4
+    dimensions (this is not checked). The corresponding *i*, *j*,
+    *k*, and *l* coordinates can be any integer but will be
+    interpreted as ``npy_intp``. You may want to typecast the
+    returned pointer to the data type of the ndarray.
+
+
+Creating arrays
+---------------
+
+
+From scratch
+^^^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_NewFromDescr(PyTypeObject* subtype, PyArray_Descr* descr, int nd, npy_intp* dims, npy_intp* strides, void* data, int flags, PyObject* obj)
+
+    This is the main array creation function. Most new arrays are
+    created with this flexible function. The returned object is an
+    object of Python-type *subtype*, which must be a subtype of
+    :cdata:`PyArray_Type`. The array has *nd* dimensions, described by
+    *dims*. The data-type descriptor of the new array is *descr*. If
+    *subtype* is not :cdata:`&PyArray_Type` (*e.g.* a Python subclass of
+    the ndarray), then *obj* is the object to pass to the
+    :obj:`__array_finalize__` method of the subclass. If *data* is
+    ``NULL``, then new memory will be allocated and *flags* can be
+    non-zero to indicate a Fortran-style contiguous array. If *data*
+    is not ``NULL``, then it is assumed to point to the memory to be
+    used for the array and the *flags* argument is used as the new
+    flags for the array (except the state of :cdata:`NPY_OWNDATA` and
+    :cdata:`UPDATEIFCOPY` flags of the new array will be reset). In
+    addition, if *data* is non-NULL, then *strides* can also be
+    provided. If *strides* is ``NULL``, then the array strides are
+    computed as C-style contiguous (default) or Fortran-style
+    contiguous (*flags* is nonzero for *data* = ``NULL`` or *flags* &
+    :cdata:`NPY_F_CONTIGUOUS` is nonzero non-NULL *data*). Any provided
+    *dims* and *strides* are copied into newly allocated dimension and
+    strides arrays for the new array object.
+
+.. cfunction:: PyObject* PyArray_New(PyTypeObject* subtype, int nd, npy_intp* dims, int type_num, npy_intp* strides, void* data, int itemsize, int flags, PyObject* obj)
+
+    This is similar to :cfunc:`PyArray_DescrNew` (...) except you
+    specify the data-type descriptor with *type_num* and *itemsize*,
+    where *type_num* corresponds to a builtin (or user-defined)
+    type. If the type always has the same number of bytes, then
+    itemsize is ignored. Otherwise, itemsize specifies the particular
+    size of this array.
+
+
+
+.. warning::
+
+    If data is passed to :cfunc:`PyArray_NewFromDescr` or :cfunc:`PyArray_New`,
+    this memory must not be deallocated until the new array is
+    deleted.  If this data came from another Python object, this can
+    be accomplished using :cfunc:`Py_INCREF` on that object and setting the
+    base member of the new array to point to that object. If strides
+    are passed in they must be consistent with the dimensions, the
+    itemsize, and the data of the array.
+
+.. cfunction:: PyObject* PyArray_SimpleNew(int nd, npy_intp* dims, int typenum)
+
+    Create a new unitialized array of type, *typenum*, whose size in
+    each of *nd* dimensions is given by the integer array, *dims*.
+    This function cannot be used to create a flexible-type array (no
+    itemsize given).
+
+.. cfunction:: PyObject* PyArray_SimpleNewFromData(int nd, npy_intp* dims, int typenum, void* data)
+
+    Create an array wrapper around *data* pointed to by the given
+    pointer. The array flags will have a default that the data area is
+    well-behaved and C-style contiguous. The shape of the array is
+    given by the *dims* c-array of length *nd*. The data-type of the
+    array is indicated by *typenum*.
+
+.. cfunction:: PyObject* PyArray_SimpleNewFromDescr(int nd, npy_intp* dims, PyArray_Descr* descr)
+
+    Create a new array with the provided data-type descriptor, *descr*
+    , of the shape deteremined by *nd* and *dims*.
+
+.. cfunction:: PyArray_FILLWBYTE(PyObject* obj, int val)
+
+    Fill the array pointed to by *obj* ---which must be a (subclass
+    of) bigndarray---with the contents of *val* (evaluated as a byte).
+
+.. cfunction:: PyObject* PyArray_Zeros(int nd, npy_intp* dims, PyArray_Descr* dtype, int fortran)
+
+    Construct a new *nd* -dimensional array with shape given by *dims*
+    and data type given by *dtype*. If *fortran* is non-zero, then a
+    Fortran-order array is created, otherwise a C-order array is
+    created. Fill the memory with zeros (or the 0 object if *dtype*
+    corresponds to :ctype:`PyArray_OBJECT` ).
+
+.. cfunction:: PyObject* PyArray_ZEROS(int nd, npy_intp* dims, int type_num, int fortran)
+
+    Macro form of :cfunc:`PyArray_Zeros` which takes a type-number instead
+    of a data-type object.
+
+.. cfunction:: PyObject* PyArray_Empty(int nd, npy_intp* dims, PyArray_Descr* dtype, int fortran)
+
+    Construct a new *nd* -dimensional array with shape given by *dims*
+    and data type given by *dtype*. If *fortran* is non-zero, then a
+    Fortran-order array is created, otherwise a C-order array is
+    created. The array is uninitialized unless the data type
+    corresponds to :ctype:`PyArray_OBJECT` in which case the array is
+    filled with :cdata:`Py_None`.
+
+.. cfunction:: PyObject* PyArray_EMPTY(int nd, npy_intp* dims, int typenum, int fortran)
+
+    Macro form of :cfunc:`PyArray_Empty` which takes a type-number,
+    *typenum*, instead of a data-type object.
+
+.. cfunction:: PyObject* PyArray_Arange(double start, double stop, double step, int typenum)
+
+    Construct a new 1-dimensional array of data-type, *typenum*, that
+    ranges from *start* to *stop* (exclusive) in increments of *step*
+    . Equivalent to **arange** (*start*, *stop*, *step*, dtype).
+
+.. cfunction:: PyObject* PyArray_ArangeObj(PyObject* start, PyObject* stop, PyObject* step, PyArray_Descr* descr)
+
+    Construct a new 1-dimensional array of data-type determined by
+    ``descr``, that ranges from ``start`` to ``stop`` (exclusive) in
+    increments of ``step``. Equivalent to arange( ``start``,
+    ``stop``, ``step``, ``typenum`` ).
+
+
+From other objects
+^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_FromAny(PyObject* op, PyArray_Descr* dtype, int min_depth, int max_depth, int requirements, PyObject* context)
+
+    This is the main function used to obtain an array from any nested
+    sequence, or object that exposes the array interface, ``op``. The
+    parameters allow specification of the required *type*, the
+    minimum (*min_depth*) and maximum (*max_depth*) number of
+    dimensions acceptable, and other *requirements* for the array. The
+    *dtype* argument needs to be a :ctype:`PyArray_Descr` structure
+    indicating the desired data-type (including required
+    byteorder). The *dtype* argument may be NULL, indicating that any
+    data-type (and byteorder) is acceptable. If you want to use
+    ``NULL`` for the *dtype* and ensure the array is notswapped then
+    use :cfunc:`PyArray_CheckFromAny`. A value of 0 for either of the
+    depth parameters causes the parameter to be ignored. Any of the
+    following array flags can be added (*e.g.* using \|) to get the
+    *requirements* argument. If your code can handle general (*e.g.*
+    strided, byte-swapped, or unaligned arrays) then *requirements*
+    may be 0. Also, if *op* is not already an array (or does not
+    expose the array interface), then a new array will be created (and
+    filled from *op* using the sequence protocol). The new array will
+    have :cdata:`NPY_DEFAULT` as its flags member. The *context* argument
+    is passed to the :obj:`__array__` method of *op* and is only used if
+    the array is constructed that way.
+
+    .. cvar:: NPY_C_CONTIGUOUS
+
+        Make sure the returned array is C-style contiguous
+    
+    .. cvar:: NPY_F_CONTIGUOUS
+
+        Make sure the returned array is Fortran-style contiguous.
+    
+    .. cvar:: NPY_ALIGNED
+
+        Make sure the returned array is aligned on proper boundaries for its
+        data type. An aligned array has the data pointer and every strides
+        factor as a multiple of the alignment factor for the data-type-
+        descriptor.
+    
+    .. cvar:: NPY_WRITEABLE
+
+        Make sure the returned array can be written to.
+    
+    .. cvar:: NPY_ENSURECOPY
+
+        Make sure a copy is made of *op*. If this flag is not
+        present, data is not copied if it can be avoided.
+    
+    .. cvar:: NPY_ENSUREARRAY
+
+        Make sure the result is a base-class ndarray or bigndarray. By
+        default, if *op* is an instance of a subclass of the
+        bigndarray, an instance of that same subclass is returned. If
+        this flag is set, an ndarray object will be returned instead.
+    
+    .. cvar:: NPY_FORCECAST
+
+        Force a cast to the output type even if it cannot be done
+        safely.  Without this flag, a data cast will occur only if it
+        can be done safely, otherwise an error is reaised.
+    
+    .. cvar:: NPY_UPDATEIFCOPY
+
+        If *op* is already an array, but does not satisfy the
+        requirements, then a copy is made (which will satisfy the
+        requirements). If this flag is present and a copy (of an
+        object that is already an array) must be made, then the
+        corresponding :cdata:`NPY_UPDATEIFCOPY` flag is set in the returned
+        copy and *op* is made to be read-only. When the returned copy
+        is deleted (presumably after your calculations are complete),
+        its contents will be copied back into *op* and the *op* array
+        will be made writeable again. If *op* is not writeable to
+        begin with, then an error is raised. If *op* is not already an
+        array, then this flag has no effect.
+    
+    .. cvar:: NPY_BEHAVED
+
+        :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE`
+    
+    .. cvar:: NPY_CARRAY
+
+        :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_BEHAVED`
+    
+    .. cvar:: NPY_CARRAY_RO
+
+        :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_FARRAY
+
+        :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_BEHAVED`
+    
+    .. cvar:: NPY_FARRAY_RO
+
+        :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_DEFAULT
+
+        :cdata:`NPY_CARRAY`
+    
+    .. cvar:: NPY_IN_ARRAY
+
+        :cdata:`NPY_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_IN_FARRAY
+
+        :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_INOUT_ARRAY
+
+        :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \|
+        :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_INOUT_FARRAY
+
+        :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \|
+        :cdata:`NPY_ALIGNED`
+    
+    .. cvar:: NPY_OUT_ARRAY
+
+        :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \|
+        :cdata:`NPY_ALIGNED` \| :cdata:`NPY_UPDATEIFCOPY`
+    
+    .. cvar:: NPY_OUT_FARRAY
+
+        :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \|
+        :cdata:`NPY_ALIGNED` \| :cdata:`UPDATEIFCOPY`
+    
+    
+.. cfunction:: PyObject* PyArray_CheckFromAny(PyObject* op, PyArray_Descr* dtype, int min_depth, int max_depth, int requirements, PyObject* context)
+
+    Nearly identical to :cfunc:`PyArray_FromAny` (...) except
+    *requirements* can contain :cdata:`NPY_NOTSWAPPED` (over-riding the
+    specification in *dtype*) and :cdata:`NPY_ELEMENTSTRIDES` which
+    indicates that the array should be aligned in the sense that the
+    strides are multiples of the element size.
+
+.. cvar:: NPY_NOTSWAPPED
+
+    Make sure the returned array has a data-type descriptor that is in
+    machine byte-order, over-riding any specification in the *dtype*
+    argument. Normally, the byte-order requirement is determined by
+    the *dtype* argument. If this flag is set and the dtype argument
+    does not indicate a machine byte-order descriptor (or is NULL and
+    the object is already an array with a data-type descriptor that is
+    not in machine byte- order), then a new data-type descriptor is
+    created and used with its byte-order field set to native.
+
+.. cvar:: NPY_BEHAVED_NS
+
+    :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` \| :cdata:`NPY_NOTSWAPPED`
+
+.. cvar:: NPY_ELEMENTSTRIDES
+
+    Make sure the returned array has strides that are multiples of the
+    element size.
+
+.. cfunction:: PyObject* PyArray_FromArray(PyArrayObject* op, PyArray_Descr* newtype, int requirements)
+
+    Special case of :cfunc:`PyArray_FromAny` for when *op* is already an
+    array but it needs to be of a specific *newtype* (including
+    byte-order) or has certain *requirements*.
+
+.. cfunction:: PyObject* PyArray_FromStructInterface(PyObject* op)
+
+    Returns an ndarray object from a Python object that exposes the
+    :obj:`__array_struct__`` method and follows the array interface
+    protocol. If the object does not contain this method then a
+    borrowed reference to :cdata:`Py_NotImplemented` is returned.
+
+.. cfunction:: PyObject* PyArray_FromInterface(PyObject* op)
+
+    Returns an ndarray object from a Python object that exposes the
+    :obj:`__array_shape__` and :obj:`__array_typestr__`
+    methods following
+    the array interface protocol. If the object does not contain one
+    of these method then a borrowed reference to :cdata:`Py_NotImplemented`
+    is returned.
+
+.. cfunction:: PyObject* PyArray_FromArrayAttr(PyObject* op, PyArray_Descr* dtype, PyObject* context)
+
+    Return an ndarray object from a Python object that exposes the
+    :obj:`__array__` method. The :obj:`__array__` method can take 0, 1, or 2
+    arguments ([dtype, context]) where *context* is used to pass
+    information about where the :obj:`__array__` method is being called
+    from (currently only used in ufuncs).
+
+.. cfunction:: PyObject* PyArray_ContiguousFromAny(PyObject* op, int typenum, int min_depth, int max_depth)
+
+    This function returns a (C-style) contiguous and behaved function
+    array from any nested sequence or array interface exporting
+    object, *op*, of (non-flexible) type given by the enumerated
+    *typenum*, of minimum depth *min_depth*, and of maximum depth
+    *max_depth*. Equivalent to a call to :cfunc:`PyArray_FromAny` with
+    requirements set to :cdata:`NPY_DEFAULT` and the type_num member of the
+    type argument set to *typenum*.
+
+.. cfunction:: PyObject *PyArray_FromObject(PyObject *op, int typenum, int min_depth, int max_depth)
+
+    Return an aligned and in native-byteorder array from any nested
+    sequence or array-interface exporting object, op, of a type given by
+    the enumerated typenum. The minimum number of dimensions the array can
+    have is given by min_depth while the maximum is max_depth. This is
+    equivalent to a call to :cfunc:`PyArray_FromAny` with requirements set to
+    BEHAVED.
+
+.. cfunction:: PyObject* PyArray_EnsureArray(PyObject* op)
+
+    This function **steals a reference** to ``op`` and makes sure that
+    ``op`` is a base-class ndarray. It special cases array scalars,
+    but otherwise calls :cfunc:`PyArray_FromAny` ( ``op``, NULL, 0, 0,
+    :cdata:`NPY_ENSUREARRAY`).
+
+.. cfunction:: PyObject* PyArray_FromString(char* string, npy_intp slen, PyArray_Descr* dtype, npy_intp num, char* sep)
+
+    Construct a one-dimensional ndarray of a single type from a binary
+    or (ASCII) text ``string`` of length ``slen``. The data-type of
+    the array to-be-created is given by ``dtype``. If num is -1, then
+    **copy** the entire string and return an appropriately sized
+    array, otherwise, ``num`` is the number of items to **copy** from
+    the string. If ``sep`` is NULL (or ""), then interpret the string
+    as bytes of binary data, otherwise convert the sub-strings
+    separated by ``sep`` to items of data-type ``dtype``. Some
+    data-types may not be readable in text mode and an error will be
+    raised if that occurs. All errors return NULL.
+
+.. cfunction:: PyObject* PyArray_FromFile(FILE* fp, PyArray_Descr* dtype, npy_intp num, char* sep)
+
+    Construct a one-dimensional ndarray of a single type from a binary
+    or text file. The open file pointer is ``fp``, the data-type of
+    the array to be created is given by ``dtype``. This must match
+    the data in the file. If ``num`` is -1, then read until the end of
+    the file and return an appropriately sized array, otherwise,
+    ``num`` is the number of items to read. If ``sep`` is NULL (or
+    ""), then read from the file in binary mode, otherwise read from
+    the file in text mode with ``sep`` providing the item
+    separator. Some array types cannot be read in text mode in which
+    case an error is raised.
+
+.. cfunction:: PyObject* PyArray_FromBuffer(PyObject* buf, PyArray_Descr* dtype, npy_intp count, npy_intp offset)
+
+    Construct a one-dimensional ndarray of a single type from an
+    object, ``buf``, that exports the (single-segment) buffer protocol
+    (or has an attribute __buffer\__ that returns an object that
+    exports the buffer protocol). A writeable buffer will be tried
+    first followed by a read- only buffer. The :cdata:`NPY_WRITEABLE`
+    flag of the returned array will reflect which one was
+    successful. The data is assumed to start at ``offset`` bytes from
+    the start of the memory location for the object. The type of the
+    data in the buffer will be interpreted depending on the data- type
+    descriptor, ``dtype.`` If ``count`` is negative then it will be
+    determined from the size of the buffer and the requested itemsize,
+    otherwise, ``count`` represents how many elements should be
+    converted from the buffer.
+
+.. cfunction:: int PyArray_CopyInto(PyArrayObject* dest, PyArrayObject* src)
+
+    Copy from the source array, ``src``, into the destination array,
+    ``dest``, performing a data-type conversion if necessary. If an
+    error occurs return -1 (otherwise 0). The shape of ``src`` must be
+    broadcastable to the shape of ``dest``. The data areas of dest
+    and src must not overlap.
+
+.. cfunction:: int PyArray_MoveInto(PyArrayObject* dest, PyArrayObject* src)
+
+    Move data from the source array, ``src``, into the destination
+    array, ``dest``, performing a data-type conversion if
+    necessary. If an error occurs return -1 (otherwise 0). The shape
+    of ``src`` must be broadcastable to the shape of ``dest``. The
+    data areas of dest and src may overlap.
+
+.. cfunction:: PyArrayObject* PyArray_GETCONTIGUOUS(PyObject* op)
+
+    If ``op`` is already (C-style) contiguous and well-behaved then
+    just return a reference, otherwise return a (contiguous and
+    well-behaved) copy of the array. The parameter op must be a
+    (sub-class of an) ndarray and no checking for that is done.
+
+.. cfunction:: PyObject* PyArray_FROM_O(PyObject* obj)
+
+    Convert ``obj`` to an ndarray. The argument can be any nested
+    sequence or object that exports the array interface. This is a
+    macro form of :cfunc:`PyArray_FromAny` using ``NULL``, 0, 0, 0 for the
+    other arguments. Your code must be able to handle any data-type
+    descriptor and any combination of data-flags to use this macro.
+
+.. cfunction:: PyObject* PyArray_FROM_OF(PyObject* obj, int requirements)
+
+    Similar to :cfunc:`PyArray_FROM_O` except it can take an argument
+    of *requirements* indicating properties the resulting array must
+    have. Available requirements that can be enforced are
+    :cdata:`NPY_CONTIGUOUS`, :cdata:`NPY_F_CONTIGUOUS`,
+    :cdata:`NPY_ALIGNED`, :cdata:`NPY_WRITEABLE`,
+    :cdata:`NPY_NOTSWAPPED`, :cdata:`NPY_ENSURECOPY`,
+    :cdata:`NPY_UPDATEIFCOPY`, :cdata:`NPY_FORCECAST`, and
+    :cdata:`NPY_ENSUREARRAY`. Standard combinations of flags can also
+    be used:
+
+.. cfunction:: PyObject* PyArray_FROM_OT(PyObject* obj, int typenum)
+
+    Similar to :cfunc:`PyArray_FROM_O` except it can take an argument of
+    *typenum* specifying the type-number the returned array.
+
+.. cfunction:: PyObject* PyArray_FROM_OTF(PyObject* obj, int typenum, int requirements)
+
+    Combination of :cfunc:`PyArray_FROM_OF` and :cfunc:`PyArray_FROM_OT`
+    allowing both a *typenum* and a *flags* argument to be provided..
+
+.. cfunction:: PyObject* PyArray_FROMANY(PyObject* obj, int typenum, int min, int max, int requirements)
+
+    Similar to :cfunc:`PyArray_FromAny` except the data-type is
+    specified using a typenumber. :cfunc:`PyArray_DescrFromType`
+    (*typenum*) is passed directly to :cfunc:`PyArray_FromAny`. This
+    macro also adds :cdata:`NPY_DEFAULT` to requirements if
+    :cdata:`NPY_ENSURECOPY` is passed in as requirements.
+
+.. cfunction:: PyObject *PyArray_CheckAxis(PyObject* obj, int* axis, int requirements)
+
+    Encapsulate the functionality of functions and methods that take
+    the axis= keyword and work properly with None as the axis
+    argument. The input array is ``obj``, while ``*axis`` is a
+    converted integer (so that >=MAXDIMS is the None value), and
+    ``requirements`` gives the needed properties of ``obj``. The
+    output is a converted version of the input so that requirements
+    are met and if needed a flattening has occurred. On output
+    negative values of ``*axis`` are converted and the new value is
+    checked to ensure consistency with the shape of ``obj``.
+
+
+Dealing with types
+------------------
+
+
+General check of Python Type
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyArray_Check(op)
+
+    Evaluates true if *op* is a Python object whose type is a sub-type
+    of :cdata:`PyArray_Type`.
+
+.. cfunction:: PyArray_CheckExact(op)
+
+    Evaluates true if *op* is a Python object with type
+    :cdata:`PyArray_Type`.
+
+.. cfunction:: PyArray_HasArrayInterface(op, out)
+
+    If ``op`` implements any part of the array interface, then ``out``
+    will contain a new reference to the newly created ndarray using
+    the interface or ``out`` will contain ``NULL`` if an error during
+    conversion occurs. Otherwise, out will contain a borrowed
+    reference to :cdata:`Py_NotImplemented` and no error condition is set.
+
+.. cfunction:: PyArray_HasArrayInterfaceType(op, type, context, out)
+
+    If ``op`` implements any part of the array interface, then ``out``
+    will contain a new reference to the newly created ndarray using
+    the interface or ``out`` will contain ``NULL`` if an error during
+    conversion occurs. Otherwise, out will contain a borrowed
+    reference to Py_NotImplemented and no error condition is set.
+    This version allows setting of the type and context in the part of
+    the array interface that looks for the :obj:`__array__` attribute.
+
+.. cfunction:: PyArray_IsZeroDim(op)
+
+    Evaluates true if *op* is an instance of (a subclass of)
+    :cdata:`PyArray_Type` and has 0 dimensions.
+
+.. cfunction:: PyArray_IsScalar(op, cls)
+
+    Evaluates true if *op* is an instance of :cdata:`Py{cls}ArrType_Type`.
+
+.. cfunction:: PyArray_CheckScalar(op)
+
+    Evaluates true if *op* is either an array scalar (an instance of a
+    sub-type of :cdata:`PyGenericArr_Type` ), or an instance of (a
+    sub-class of) :cdata:`PyArray_Type` whose dimensionality is 0.
+
+.. cfunction:: PyArray_IsPythonScalar(op)
+
+    Evaluates true if *op* is a builtin Python "scalar" object (int,
+    float, complex, str, unicode, long, bool).
+
+.. cfunction:: PyArray_IsAnyScalar(op)
+
+    Evaluates true if *op* is either a Python scalar or an array
+    scalar (an instance of a sub- type of :cdata:`PyGenericArr_Type` ).
+
+
+Data-type checking
+^^^^^^^^^^^^^^^^^^
+
+For the typenum macros, the argument is an integer representing an
+enumerated array data type. For the array type checking macros the
+argument must be a :ctype:`PyObject *` that can be directly interpreted as a
+:ctype:`PyArrayObject *`.
+
+.. cfunction:: PyTypeNum_ISUNSIGNED(num)
+
+.. cfunction:: PyDataType_ISUNSIGNED(descr)
+
+.. cfunction:: PyArray_ISUNSIGNED(obj)
+
+    Type represents an unsigned integer.
+
+.. cfunction:: PyTypeNum_ISSIGNED(num)
+
+.. cfunction:: PyDataType_ISSIGNED(descr)
+
+.. cfunction:: PyArray_ISSIGNED(obj)
+
+    Type represents a signed integer.
+
+.. cfunction:: PyTypeNum_ISINTEGER(num)
+
+.. cfunction:: PyDataType_ISINTEGER(descr)
+
+.. cfunction:: PyArray_ISINTEGER(obj)
+
+    Type represents any integer.
+
+.. cfunction:: PyTypeNum_ISFLOAT(num)
+
+.. cfunction:: PyDataType_ISFLOAT(descr)
+
+.. cfunction:: PyArray_ISFLOAT(obj)
+
+    Type represents any floating point number.
+
+.. cfunction:: PyTypeNum_ISCOMPLEX(num)
+
+.. cfunction:: PyDataType_ISCOMPLEX(descr)
+
+.. cfunction:: PyArray_ISCOMPLEX(obj)
+
+    Type represents any complex floating point number.
+
+.. cfunction:: PyTypeNum_ISNUMBER(num)
+
+.. cfunction:: PyDataType_ISNUMBER(descr)
+
+.. cfunction:: PyArray_ISNUMBER(obj)
+
+    Type represents any integer, floating point, or complex floating point
+    number.
+
+.. cfunction:: PyTypeNum_ISSTRING(num)
+
+.. cfunction:: PyDataType_ISSTRING(descr)
+
+.. cfunction:: PyArray_ISSTRING(obj)
+
+    Type represents a string data type.
+
+.. cfunction:: PyTypeNum_ISPYTHON(num)
+
+.. cfunction:: PyDataType_ISPYTHON(descr)
+
+.. cfunction:: PyArray_ISPYTHON(obj)
+
+    Type represents an enumerated type corresponding to one of the
+    standard Python scalar (bool, int, float, or complex).
+
+.. cfunction:: PyTypeNum_ISFLEXIBLE(num)
+
+.. cfunction:: PyDataType_ISFLEXIBLE(descr)
+
+.. cfunction:: PyArray_ISFLEXIBLE(obj)
+
+    Type represents one of the flexible array types ( :cdata:`NPY_STRING`,
+    :cdata:`NPY_UNICODE`, or :cdata:`NPY_VOID` ).
+
+.. cfunction:: PyTypeNum_ISUSERDEF(num)
+
+.. cfunction:: PyDataType_ISUSERDEF(descr)
+
+.. cfunction:: PyArray_ISUSERDEF(obj)
+
+    Type represents a user-defined type.
+
+.. cfunction:: PyTypeNum_ISEXTENDED(num)
+
+.. cfunction:: PyDataType_ISEXTENDED(descr)
+
+.. cfunction:: PyArray_ISEXTENDED(obj)
+
+    Type is either flexible or user-defined.
+
+.. cfunction:: PyTypeNum_ISOBJECT(num)
+
+.. cfunction:: PyDataType_ISOBJECT(descr)
+
+.. cfunction:: PyArray_ISOBJECT(obj)
+
+    Type represents object data type.
+
+.. cfunction:: PyTypeNum_ISBOOL(num)
+
+.. cfunction:: PyDataType_ISBOOL(descr)
+
+.. cfunction:: PyArray_ISBOOL(obj)
+
+    Type represents Boolean data type.
+
+.. cfunction:: PyDataType_HASFIELDS(descr)
+
+.. cfunction:: PyArray_HASFIELDS(obj)
+
+    Type has fields associated with it.
+
+.. cfunction:: PyArray_ISNOTSWAPPED(m)
+
+    Evaluates true if the data area of the ndarray *m* is in machine
+    byte-order according to the array's data-type descriptor.
+
+.. cfunction:: PyArray_ISBYTESWAPPED(m)
+
+    Evaluates true if the data area of the ndarray *m* is **not** in
+    machine byte-order according to the array's data-type descriptor.
+
+.. cfunction:: Bool PyArray_EquivTypes(PyArray_Descr* type1, PyArray_Descr* type2)
+
+    Return :cdata:`NPY_TRUE` if *type1* and *type2* actually represent
+    equivalent types for this platform (the fortran member of each
+    type is ignored). For example, on 32-bit platforms,
+    :cdata:`NPY_LONG` and :cdata:`NPY_INT` are equivalent. Otherwise
+    return :cdata:`NPY_FALSE`.
+
+.. cfunction:: Bool PyArray_EquivArrTypes(PyArrayObject* a1, PyArrayObject * a2)
+
+    Return :cdata:`NPY_TRUE` if *a1* and *a2* are arrays with equivalent
+    types for this platform.
+
+.. cfunction:: Bool PyArray_EquivTypenums(int typenum1, int typenum2)
+
+    Special case of :cfunc:`PyArray_EquivTypes` (...) that does not accept
+    flexible data types but may be easier to call.
+
+.. cfunction:: int PyArray_EquivByteorders({byteorder} b1, {byteorder} b2)
+
+    True if byteorder characters ( :cdata:`NPY_LITTLE`,
+    :cdata:`NPY_BIG`, :cdata:`NPY_NATIVE`, :cdata:`NPY_IGNORE` ) are
+    either equal or equivalent as to their specification of a native
+    byte order. Thus, on a little-endian machine :cdata:`NPY_LITTLE`
+    and :cdata:`NPY_NATIVE` are equivalent where they are not
+    equivalent on a big-endian machine.
+
+
+Converting data types
+^^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_Cast(PyArrayObject* arr, int typenum)
+
+    Mainly for backwards compatibility to the Numeric C-API and for
+    simple casts to non-flexible types. Return a new array object with
+    the elements of *arr* cast to the data-type *typenum* which must
+    be one of the enumerated types and not a flexible type.
+
+.. cfunction:: PyObject* PyArray_CastToType(PyArrayObject* arr, PyArray_Descr* type, int fortran)
+
+    Return a new array of the *type* specified, casting the elements
+    of *arr* as appropriate. The fortran argument specifies the
+    ordering of the output array.
+
+.. cfunction:: int PyArray_CastTo(PyArrayObject* out, PyArrayObject* in)
+
+    Cast the elements of the array *in* into the array *out*. The
+    output array should be writeable, have an integer-multiple of the
+    number of elements in the input array (more than one copy can be
+    placed in out), and have a data type that is one of the builtin
+    types.  Returns 0 on success and -1 if an error occurs.
+
+.. cfunction:: PyArray_VectorUnaryFunc* PyArray_GetCastFunc(PyArray_Descr* from, int totype)
+
+    Return the low-level casting function to cast from the given
+    descriptor to the builtin type number. If no casting function
+    exists return ``NULL`` and set an error. Using this function
+    instead of direct access to *from* ->f->cast will allow support of
+    any user-defined casting functions added to a descriptors casting
+    dictionary.
+
+.. cfunction:: int PyArray_CanCastSafely(int fromtype, int totype)
+
+    Returns non-zero if an array of data type *fromtype* can be cast
+    to an array of data type *totype* without losing information. An
+    exception is that 64-bit integers are allowed to be cast to 64-bit
+    floating point values even though this can lose precision on large
+    integers so as not to proliferate the use of long doubles without
+    explict requests. Flexible array types are not checked according
+    to their lengths with this function.
+
+.. cfunction:: int PyArray_CanCastTo(PyArray_Descr* fromtype, PyArray_Descr* totype)
+
+    Returns non-zero if an array of data type *fromtype* (which can
+    include flexible types) can be cast safely to an array of data
+    type *totype* (which can include flexible types). This is
+    basically a wrapper around :cfunc:`PyArray_CanCastSafely` with
+    additional support for size checking if *fromtype* and *totype*
+    are :cdata:`NPY_STRING` or :cdata:`NPY_UNICODE`.
+
+.. cfunction:: int PyArray_ObjectType(PyObject* op, int mintype)
+
+    This function is useful for determining a common type that two or
+    more arrays can be converted to. It only works for non-flexible
+    array types as no itemsize information is passed. The *mintype*
+    argument represents the minimum type acceptable, and *op*
+    represents the object that will be converted to an array. The
+    return value is the enumerated typenumber that represents the
+    data-type that *op* should have.
+
+.. cfunction:: void PyArray_ArrayType(PyObject* op, PyArray_Descr* mintype, PyArray_Descr* outtype)
+
+    This function works similarly to :cfunc:`PyArray_ObjectType` (...)
+    except it handles flexible arrays. The *mintype* argument can have
+    an itemsize member and the *outtype* argument will have an
+    itemsize member at least as big but perhaps bigger depending on
+    the object *op*.
+
+.. cfunction:: PyArrayObject** PyArray_ConvertToCommonType(PyObject* op, int* n)
+
+    Convert a sequence of Python objects contained in *op* to an array
+    of ndarrays each having the same data type. The type is selected
+    based on the typenumber (larger type number is chosen over a
+    smaller one) ignoring objects that are only scalars. The length of
+    the sequence is returned in *n*, and an *n* -length array of
+    :ctype:`PyArrayObject` pointers is the return value (or ``NULL`` if an
+    error occurs). The returned array must be freed by the caller of
+    this routine (using :cfunc:`PyDataMem_FREE` ) and all the array objects
+    in it ``DECREF`` 'd or a memory-leak will occur. The example
+    template-code below shows a typically usage:
+    
+    .. code-block:: c
+
+        mps = PyArray_ConvertToCommonType(obj, &n);
+        if (mps==NULL) return NULL;
+        {code}
+        <before return>
+        for (i=0; i<n; i++) Py_DECREF(mps[i]);
+        PyDataMem_FREE(mps);
+        {return}
+
+.. cfunction:: char* PyArray_Zero(PyArrayObject* arr)
+
+    A pointer to newly created memory of size *arr* ->itemsize that
+    holds the representation of 0 for that type. The returned pointer,
+    *ret*, **must be freed** using :cfunc:`PyDataMem_FREE` (ret) when it is
+    not needed anymore.
+
+.. cfunction:: char* PyArray_One(PyArrayObject* arr)
+
+    A pointer to newly created memory of size *arr* ->itemsize that
+    holds the representation of 1 for that type. The returned pointer,
+    *ret*, **must be freed** using :cfunc:`PyDataMem_FREE` (ret) when it
+    is not needed anymore.
+
+.. cfunction:: int PyArray_ValidType(int typenum)
+
+    Returns :cdata:`NPY_TRUE` if *typenum* represents a valid type-number
+    (builtin or user-defined or character code). Otherwise, this
+    function returns :cdata:`NPY_FALSE`.
+
+
+New data types
+^^^^^^^^^^^^^^
+
+.. cfunction:: void PyArray_InitArrFuncs(PyArray_ArrFuncs* f)
+
+    Initialize all function pointers and members to ``NULL``.
+
+.. cfunction:: int PyArray_RegisterDataType(PyArray_Descr* dtype)
+
+    Register a data-type as a new user-defined data type for
+    arrays. The type must have most of its entries filled in. This is
+    not always checked and errors can produce segfaults. In
+    particular, the typeobj member of the ``dtype`` structure must be
+    filled with a Python type that has a fixed-size element-size that
+    corresponds to the elsize member of *dtype*. Also the ``f``
+    member must have the required functions: nonzero, copyswap,
+    copyswapn, getitem, setitem, and cast (some of the cast functions
+    may be ``NULL`` if no support is desired). To avoid confusion, you
+    should choose a unique character typecode but this is not enforced
+    and not relied on internally.
+
+    A user-defined type number is returned that uniquely identifies
+    the type. A pointer to the new structure can then be obtained from
+    :cfunc:`PyArray_DescrFromType` using the returned type number. A -1 is
+    returned if an error occurs.  If this *dtype* has already been
+    registered (checked only by the address of the pointer), then
+    return the previously-assigned type-number.
+
+.. cfunction:: int PyArray_RegisterCastFunc(PyArray_Descr* descr, int totype, PyArray_VectorUnaryFunc* castfunc)
+
+    Register a low-level casting function, *castfunc*, to convert
+    from the data-type, *descr*, to the given data-type number,
+    *totype*. Any old casting function is over-written. A ``0`` is
+    returned on success or a ``-1`` on failure.
+
+.. cfunction:: int PyArray_RegisterCanCast(PyArray_Descr* descr, int totype, PyArray_SCALARKIND scalar)
+
+    Register the data-type number, *totype*, as castable from
+    data-type object, *descr*, of the given *scalar* kind. Use
+    *scalar* = :cdata:`NPY_NOSCALAR` to register that an array of data-type
+    *descr* can be cast safely to a data-type whose type_number is
+    *totype*.
+
+
+Special functions for PyArray_OBJECT
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: int PyArray_INCREF(PyArrayObject* op)
+
+    Used for an array, *op*, that contains any Python objects. It
+    increments the reference count of every object in the array
+    according to the data-type of *op*. A -1 is returned if an error
+    occurs, otherwise 0 is returned.
+
+.. cfunction:: void PyArray_Item_INCREF(char* ptr, PyArray_Descr* dtype)
+
+    A function to INCREF all the objects at the location *ptr*
+    according to the data-type *dtype*. If *ptr* is the start of a
+    record with an object at any offset, then this will (recursively)
+    increment the reference count of all object-like items in the
+    record.
+
+.. cfunction:: int PyArray_XDECREF(PyArrayObject* op)
+
+    Used for an array, *op*, that contains any Python objects. It
+    decrements the reference count of every object in the array
+    according to the data-type of *op*. Normal return value is 0. A
+    -1 is returned if an error occurs.
+
+.. cfunction:: void PyArray_Item_XDECREF(char* ptr, PyArray_Descr* dtype)
+
+    A function to XDECREF all the object-like items at the loacation
+    *ptr* as recorded in the data-type, *dtype*. This works
+    recursively so that if ``dtype`` itself has fields with data-types
+    that contain object-like items, all the object-like fields will be
+    XDECREF ``'d``.
+
+.. cfunction:: void PyArray_FillObjectArray(PyArrayObject* arr, PyObject* obj)
+
+    Fill a newly created array with a single value obj at all
+    locations in the structure with object data-types. No checking is
+    performed but *arr* must be of data-type :ctype:`PyArray_OBJECT` and be
+    single-segment and uninitialized (no previous objects in
+    position). Use :cfunc:`PyArray_DECREF` (*arr*) if you need to
+    decrement all the items in the object array prior to calling this
+    function.
+
+
+Array flags
+-----------
+
+
+Basic Array Flags
+^^^^^^^^^^^^^^^^^
+
+An ndarray can have a data segment that is not a simple contiguous
+chunk of well-behaved memory you can manipulate. It may not be aligned
+with word boundaries (very important on some platforms). It might have
+its data in a different byte-order than the machine recognizes. It
+might not be writeable. It might be in Fortan-contiguous order. The
+array flags are used to indicate what can be said about data
+associated with an array.
+
+.. cvar:: NPY_C_CONTIGUOUS
+
+    The data area is in C-style contiguous order (last index varies the
+    fastest).
+
+.. cvar:: NPY_F_CONTIGUOUS
+
+    The data area is in Fortran-style contiguous order (first index varies
+    the fastest).
+
+.. cvar:: NPY_OWNDATA
+
+    The data area is owned by this array.
+
+.. cvar:: NPY_ALIGNED
+
+    The data area is aligned appropriately (for all strides).
+
+.. cvar:: NPY_WRITEABLE
+
+    The data area can be written to.
+
+    Notice that the above 3 flags are are defined so that a new, well-
+    behaved array has these flags defined as true.
+
+.. cvar:: NPY_UPDATEIFCOPY
+
+    The data area represents a (well-behaved) copy whose information
+    should be transferred back to the original when this array is deleted.
+
+
+Combinations of array flags
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. cvar:: NPY_BEHAVED
+
+    :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE`
+
+.. cvar:: NPY_CARRAY
+
+    :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_BEHAVED`
+
+.. cvar:: NPY_CARRAY_RO
+
+    :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+
+.. cvar:: NPY_FARRAY
+
+    :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_BEHAVED`
+
+.. cvar:: NPY_FARRAY_RO
+
+    :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+
+.. cvar:: NPY_DEFAULT
+
+    :cdata:`NPY_CARRAY`
+
+.. cvar:: NPY_UPDATE_ALL
+
+    :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED`
+
+
+Flag-like constants
+^^^^^^^^^^^^^^^^^^^
+
+These constants are used in :cfunc:`PyArray_FromAny` (and its macro forms) to
+specify desired properties of the new array. 
+
+.. cvar:: NPY_FORCECAST
+
+    Cast to the desired type, even if it can't be done without losing
+    information.
+
+.. cvar:: NPY_ENSURECOPY
+
+    Make sure the resulting array is a copy of the original.
+
+.. cvar:: NPY_ENSUREARRAY
+
+    Make sure the resulting object is an actual ndarray (or bigndarray),
+    and not a sub-class.
+
+.. cvar:: NPY_NOTSWAPPED
+
+    Only used in :cfunc:`PyArray_CheckFromAny` to over-ride the byteorder
+    of the data-type object passed in.
+
+.. cvar:: NPY_BEHAVED_NS
+
+    :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` \| :cdata:`NPY_NOTSWAPPED`
+
+
+Flag checking
+^^^^^^^^^^^^^
+
+For all of these macros *arr* must be an instance of a (subclass of)
+:cdata:`PyArray_Type`, but no checking is done.
+
+.. cfunction:: PyArray_CHKFLAGS(arr, flags)
+
+    The first parameter, arr, must be an ndarray or subclass. The
+    parameter, *flags*, should be an integer consisting of bitwise
+    combinations of the possible flags an array can have:
+    :cdata:`NPY_C_CONTIGUOUS`, :cdata:`NPY_F_CONTIGUOUS`,
+    :cdata:`NPY_OWNDATA`, :cdata:`NPY_ALIGNED`,
+    :cdata:`NPY_WRITEABLE`, :cdata:`NPY_UPDATEIFCOPY`.
+
+.. cfunction:: PyArray_ISCONTIGUOUS(arr)
+
+    Evaluates true if *arr* is C-style contiguous.
+
+.. cfunction:: PyArray_ISFORTRAN(arr)
+
+    Evaluates true if *arr* is Fortran-style contiguous.
+
+.. cfunction:: PyArray_ISWRITEABLE(arr)
+
+    Evaluates true if the data area of *arr* can be written to
+
+.. cfunction:: PyArray_ISALIGNED(arr)
+
+    Evaluates true if the data area of *arr* is properly aligned on
+    the machine.
+
+.. cfunction:: PyArray_ISBEHAVED(arr)
+
+    Evalutes true if the data area of *arr* is aligned and writeable
+    and in machine byte-order according to its descriptor.
+
+.. cfunction:: PyArray_ISBEHAVED_RO(arr)
+
+    Evaluates true if the data area of *arr* is aligned and in machine
+    byte-order.
+
+.. cfunction:: PyArray_ISCARRAY(arr)
+
+    Evaluates true if the data area of *arr* is C-style contiguous,
+    and :cfunc:`PyArray_ISBEHAVED` (*arr*) is true.
+
+.. cfunction:: PyArray_ISFARRAY(arr)
+
+    Evaluates true if the data area of *arr* is Fortran-style
+    contiguous and :cfunc:`PyArray_ISBEHAVED` (*arr*) is true.
+
+.. cfunction:: PyArray_ISCARRAY_RO(arr)
+
+    Evaluates true if the data area of *arr* is C-style contiguous,
+    aligned, and in machine byte-order.
+
+.. cfunction:: PyArray_ISFARRAY_RO(arr)
+
+    Evaluates true if the data area of *arr* is Fortran-style
+    contiguous, aligned, and in machine byte-order **.**
+
+.. cfunction:: PyArray_ISONESEGMENT(arr)
+
+    Evaluates true if the data area of *arr* consists of a single
+    (C-style or Fortran-style) contiguous segment.
+
+.. cfunction:: void PyArray_UpdateFlags(PyArrayObject* arr, int flagmask)
+
+    The :cdata:`NPY_C_CONTIGUOUS`, :cdata:`NPY_ALIGNED`, and
+    :cdata:`NPY_F_CONTIGUOUS` array flags can be "calculated" from the
+    array object itself. This routine updates one or more of these
+    flags of *arr* as specified in *flagmask* by performing the
+    required calculation.
+
+
+.. warning::
+
+    It is important to keep the flags updated (using
+    :cfunc:`PyArray_UpdateFlags` can help) whenever a manipulation with an
+    array is performed that might cause them to change. Later
+    calculations in NumPy that rely on the state of these flags do not
+    repeat the calculation to update them.
+
+
+Array method alternative API
+----------------------------
+
+
+Conversion
+^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_GetField(PyArrayObject* self, PyArray_Descr* dtype, int offset)
+
+    Equivalent to :meth:`ndarray.getfield` (*self*, *dtype*, *offset*). Return
+    a new array of the given *dtype* using the data in the current
+    array at a specified *offset* in bytes. The *offset* plus the
+    itemsize of the new array type must be less than *self*
+    ->descr->elsize or an error is raised. The same shape and strides
+    as the original array are used. Therefore, this function has the
+    effect of returning a field from a record array. But, it can also
+    be used to select specific bytes or groups of bytes from any array
+    type.
+
+.. cfunction:: int PyArray_SetField(PyArrayObject* self, PyArray_Descr* dtype, int offset, PyObject* val)
+
+    Equivalent to :meth:`ndarray.setfield` (*self*, *val*, *dtype*, *offset*
+    ). Set the field starting at *offset* in bytes and of the given
+    *dtype* to *val*. The *offset* plus *dtype* ->elsize must be less
+    than *self* ->descr->elsize or an error is raised. Otherwise, the
+    *val* argument is converted to an array and copied into the field
+    pointed to. If necessary, the elements of *val* are repeated to
+    fill the destination array, But, the number of elements in the
+    destination must be an integer multiple of the number of elements
+    in *val*.
+
+.. cfunction:: PyObject* PyArray_Byteswap(PyArrayObject* self, Bool inplace)
+
+    Equivalent to :meth:`ndarray.byteswap` (*self*, *inplace*). Return an array
+    whose data area is byteswapped. If *inplace* is non-zero, then do
+    the byteswap inplace and return a reference to self. Otherwise,
+    create a byteswapped copy and leave self unchanged.
+
+.. cfunction:: PyObject* PyArray_NewCopy(PyArrayObject* old, NPY_ORDER order)
+
+    Equivalent to :meth:`ndarray.copy` (*self*, *fortran*). Make a copy of the
+    *old* array. The returned array is always aligned and writeable
+    with data interpreted the same as the old array. If *order* is
+    :cdata:`NPY_CORDER`, then a C-style contiguous array is returned. If
+    *order* is :cdata:`NPY_FORTRANORDER`, then a Fortran-style contiguous
+    array is returned. If *order is* :cdata:`NPY_ANYORDER`, then the array
+    returned is Fortran-style contiguous only if the old one is;
+    otherwise, it is C-style contiguous.
+
+.. cfunction:: PyObject* PyArray_ToList(PyArrayObject* self)
+
+    Equivalent to :meth:`ndarray.tolist` (*self*). Return a nested Python list
+    from *self*.
+
+.. cfunction:: PyObject* PyArray_ToString(PyArrayObject* self, NPY_ORDER order)
+
+    Equivalent to :meth:`ndarray.tostring` (*self*, *order*). Return the bytes
+    of this array in a Python string.
+
+.. cfunction:: PyObject* PyArray_ToFile(PyArrayObject* self, FILE* fp, char* sep, char* format)
+
+    Write the contents of *self* to the file pointer *fp* in C-style
+    contiguous fashion. Write the data as binary bytes if *sep* is the
+    string ""or ``NULL``. Otherwise, write the contents of *self* as
+    text using the *sep* string as the item separator. Each item will
+    be printed to the file.  If the *format* string is not ``NULL`` or
+    "", then it is a Python print statement format string showing how
+    the items are to be written.
+
+.. cfunction:: int PyArray_Dump(PyObject* self, PyObject* file, int protocol)
+
+    Pickle the object in *self* to the given *file* (either a string
+    or a Python file object). If *file* is a Python string it is
+    considered to be the name of a file which is then opened in binary
+    mode. The given *protocol* is used (if *protocol* is negative, or
+    the highest available is used). This is a simple wrapper around
+    cPickle.dump(*self*, *file*, *protocol*).
+
+.. cfunction:: PyObject* PyArray_Dumps(PyObject* self, int protocol)
+
+    Pickle the object in *self* to a Python string and return it. Use
+    the Pickle *protocol* provided (or the highest available if
+    *protocol* is negative).
+
+.. cfunction:: int PyArray_FillWithScalar(PyArrayObject* arr, PyObject* obj)
+
+    Fill the array, *arr*, with the given scalar object, *obj*. The
+    object is first converted to the data type of *arr*, and then
+    copied into every location. A -1 is returned if an error occurs,
+    otherwise 0 is returned.
+
+.. cfunction:: PyObject* PyArray_View(PyArrayObject* self, PyArray_Descr* dtype)
+
+    Equivalent to :meth:`ndarray.view` (*self*, *dtype*). Return a new view of
+    the array *self* as possibly a different data-type, *dtype*. If
+    *dtype* is ``NULL``, then the returned array will have the same
+    data type as *self*. The new data-type must be consistent with
+    the size of *self*. Either the itemsizes must be identical, or
+    *self* must be single-segment and the total number of bytes must
+    be the same.  In the latter case the dimensions of the returned
+    array will be altered in the last (or first for Fortran-style
+    contiguous arrays) dimension. The data area of the returned array
+    and self is exactly the same.
+
+
+Shape Manipulation
+^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_Newshape(PyArrayObject* self, PyArray_Dims* newshape)
+
+    Result will be a new array (pointing to the same memory location
+    as *self* if possible), but having a shape given by *newshape*
+    . If the new shape is not compatible with the strides of *self*,
+    then a copy of the array with the new specified shape will be
+    returned.
+
+.. cfunction:: PyObject* PyArray_Reshape(PyArrayObject* self, PyObject* shape)
+
+    Equivalent to :meth:`ndarray.reshape` (*self*, *shape*) where *shape* is a
+    sequence. Converts *shape* to a :ctype:`PyArray_Dims` structure and
+    calls :cfunc:`PyArray_Newshape` internally.
+
+.. cfunction:: PyObject* PyArray_Squeeze(PyArrayObject* self)
+
+    Equivalent to :meth:`ndarray.squeeze` (*self*). Return a new view of *self*
+    with all of the dimensions of length 1 removed from the shape.
+
+.. warning::
+
+    matrix objects are always 2-dimensional. Therefore,
+    :cfunc:`PyArray_Squeeze` has no effect on arrays of matrix sub-class.
+
+.. cfunction:: PyObject* PyArray_SwapAxes(PyArrayObject* self, int a1, int a2)
+
+    Equivalent to :meth:`ndarray.swapaxes` (*self*, *a1*, *a2*). The returned
+    array is a new view of the data in *self* with the given axes,
+    *a1* and *a2*, swapped.
+
+.. cfunction:: PyObject* PyArray_Resize(PyArrayObject* self, PyArray_Dims* newshape, int refcheck, NPY_ORDER fortran)
+
+    Equivalent to :meth:`ndarray.resize` (*self*, *newshape*, refcheck
+    ``=`` *refcheck*, order= fortran ). This function only works on
+    single-segment arrays. It changes the shape of *self* inplace and
+    will reallocate the memory for *self* if *newshape* has a
+    different total number of elements then the old shape. If
+    reallocation is necessary, then *self* must own its data, have
+    *self* - ``>base==NULL``, have *self* - ``>weakrefs==NULL``, and
+    (unless refcheck is 0) not be referenced by any other array. A
+    reference to the new array is returned. The fortran argument can
+    be :cdata:`NPY_ANYORDER`, :cdata:`NPY_CORDER`, or
+    :cdata:`NPY_FORTRANORDER`. This argument is used if the number of
+    dimension is (or is being resized to be) greater than 2. It
+    currently has no effect. Eventually it could be used to determine
+    how the resize operation should view the data when constructing a
+    differently-dimensioned array.
+
+.. cfunction:: PyObject* PyArray_Transpose(PyArrayObject* self, PyArray_Dims* permute)
+
+    Equivalent to :meth:`ndarray.transpose` (*self*, *permute*). Permute the
+    axes of the ndarray object *self* according to the data structure
+    *permute* and return the result. If *permute* is ``NULL``, then
+    the resulting array has its axes reversed. For example if *self*
+    has shape :math:`10\times20\times30`, and *permute* ``.ptr`` is
+    (0,2,1) the shape of the result is :math:`10\times30\times20.` If
+    *permute* is ``NULL``, the shape of the result is
+    :math:`30\times20\times10.`
+
+.. cfunction:: PyObject* PyArray_Flatten(PyArrayObject* self, NPY_ORDER order)
+
+    Equivalent to :meth:`ndarray.flatten` (*self*, *order*). Return a 1-d copy
+    of the array. If *order* is :cdata:`NPY_FORTRANORDER` the elements are
+    scanned out in Fortran order (first-dimension varies the
+    fastest). If *order* is :cdata:`NPY_CORDER`, the elements of ``self``
+    are scanned in C-order (last dimension varies the fastest). If
+    *order* :cdata:`NPY_ANYORDER`, then the result of
+    :cfunc:`PyArray_ISFORTRAN` (*self*) is used to determine which order
+    to flatten.
+
+.. cfunction:: PyObject* PyArray_Ravel(PyArrayObject* self, NPY_ORDER order)
+
+    Equivalent to *self*.ravel(*order*). Same basic functionality
+    as :cfunc:`PyArray_Flatten` (*self*, *order*) except if *order* is 0
+    and *self* is C-style contiguous, the shape is altered but no copy
+    is performed.
+
+
+Item selection and manipulation
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyObject* PyArray_TakeFrom(PyArrayObject* self, PyObject* indices, int axis, PyArrayObject* ret, NPY_CLIPMODE clipmode)
+
+    Equivalent to :meth:`ndarray.take` (*self*, *indices*, *axis*, *ret*,
+    *clipmode*) except *axis* =None in Python is obtained by setting
+    *axis* = :cdata:`NPY_MAXDIMS` in C. Extract the items from self
+    indicated by the integer-valued *indices* along the given *axis.*
+    The clipmode argument can be :cdata:`NPY_RAISE`, :cdata:`NPY_WRAP`, or
+    :cdata:`NPY_CLIP` to indicate what to do with out-of-bound indices. The
+    *ret* argument can specify an output array rather than having one
+    created internally.
+
+.. cfunction:: PyObject* PyArray_PutTo(PyArrayObject* self, PyObject* values, PyObject* indices, NPY_CLIPMODE clipmode)
+
+    Equivalent to *self*.put(*values*, *indices*, *clipmode*
+    ). Put *values* into *self* at the corresponding (flattened)
+    *indices*. If *values* is too small it will be repeated as
+    necessary.
+
+.. cfunction:: PyObject* PyArray_PutMask(PyArrayObject* self, PyObject* values, PyObject* mask)
+
+    Place the *values* in *self* wherever corresponding positions
+    (using a flattened context) in *mask* are true. The *mask* and
+    *self* arrays must have the same total number of elements. If
+    *values* is too small, it will be repeated as necessary.
+
+.. cfunction:: PyObject* PyArray_Repeat(PyArrayObject* self, PyObject* op, int axis)
+
+    Equivalent to :meth:`ndarray.repeat` (*self*, *op*, *axis*). Copy the
+    elements of *self*, *op* times along the given *axis*. Either
+    *op* is a scalar integer or a sequence of length *self*
+    ->dimensions[ *axis* ] indicating how many times to repeat each
+    item along the axis.
+
+.. cfunction:: PyObject* PyArray_Choose(PyArrayObject* self, PyObject* op, PyArrayObject* ret, NPY_CLIPMODE clipmode)
+
+    Equivalent to :meth:`ndarray.choose` (*self*, *op*, *ret*, *clipmode*).
+    Create a new array by selecting elements from the sequence of
+    arrays in *op* based on the integer values in *self*. The arrays
+    must all be broadcastable to the same shape and the entries in
+    *self* should be between 0 and len(*op*). The output is placed
+    in *ret* unless it is ``NULL`` in which case a new output is
+    created. The *clipmode* argument determines behavior for when
+    entries in *self* are not between 0 and len(*op*).
+
+    .. cvar:: NPY_RAISE
+    
+        raise a ValueError;
+    
+    .. cvar:: NPY_WRAP
+    
+        wrap values < 0 by adding len(*op*) and values >=len(*op*)
+        by subtracting len(*op*) until they are in range;
+    
+    .. cvar:: NPY_CLIP
+    
+        all values are clipped to the region [0, len(*op*) ).
+    
+    
+.. cfunction:: PyObject* PyArray_Sort(PyArrayObject* self, int axis)
+
+    Equivalent to :meth:`ndarray.sort` (*self*, *axis*). Return an array with
+    the items of *self* sorted along *axis*.
+
+.. cfunction:: PyObject* PyArray_ArgSort(PyArrayObject* self, int axis)
+
+    Equivalent to :meth:`ndarray.argsort` (*self*, *axis*). Return an array of
+    indices such that selection of these indices along the given
+    ``axis`` would return a sorted version of *self*. If *self*
+    ->descr is a data-type with fields defined, then
+    self->descr->names is used to determine the sort order. A
+    comparison where the first field is equal will use the second
+    field and so on. To alter the sort order of a record array, create
+    a new data-type with a different order of names and construct a
+    view of the array with that new data-type.
+
+.. cfunction:: PyObject* PyArray_LexSort(PyObject* sort_keys, int axis)
+
+    Given a sequence of arrays (*sort_keys*) of the same shape,
+    return an array of indices (similar to :cfunc:`PyArray_ArgSort` (...))
+    that would sort the arrays lexicographically. A lexicographic sort
+    specifies that when two keys are found to be equal, the order is
+    based on comparison of subsequent keys. A merge sort (which leaves
+    equal entries unmoved) is required to be defined for the
+    types. The sort is accomplished by sorting the indices first using
+    the first *sort_key* and then using the second *sort_key* and so
+    forth. This is equivalent to the lexsort(*sort_keys*, *axis*)
+    Python command. Because of the way the merge-sort works, be sure
+    to understand the order the *sort_keys* must be in (reversed from
+    the order you would use when comparing two elements).
+
+    If these arrays are all collected in a record array, then
+    :cfunc:`PyArray_Sort` (...) can also be used to sort the array
+    directly.
+
+.. cfunction:: PyObject* PyArray_SearchSorted(PyArrayObject* self, PyObject* values)
+
+    Equivalent to :meth:`ndarray.searchsorted` (*self*, *values*). Assuming
+    *self* is a 1-d array in ascending order representing bin
+    boundaries then the output is an array the same shape as *values*
+    of bin numbers, giving the bin into which each item in *values*
+    would be placed. No checking is done on whether or not self is in
+    ascending order.
+
+.. cfunction:: PyObject* PyArray_Diagonal(PyArrayObject* self, int offset, int axis1, int axis2)
+
+    Equivalent to :meth:`ndarray.diagonal` (*self*, *offset*, *axis1*, *axis2*
+    ). Return the *offset* diagonals of the 2-d arrays defined by
+    *axis1* and *axis2*.
+
+.. cfunction:: PyObject* PyArray_Nonzero(PyArrayObject* self)
+
+    Equivalent to :meth:`ndarray.nonzero` (*self*). Returns a tuple of index
+    arrays that select elements of *self* that are nonzero. If (nd=
+    :cfunc:`PyArray_NDIM` ( ``self`` ))==1, then a single index array is
+    returned. The index arrays have data type :cdata:`NPY_INTP`. If a
+    tuple is returned (nd :math:`\neq` 1), then its length is nd.
+
+.. cfunction:: PyObject* PyArray_Compress(PyArrayObject* self, PyObject* condition, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.compress` (*self*, *condition*, *axis*
+    ). Return the elements along *axis* corresponding to elements of
+    *condition* that are true.
+
+
+Calculation
+^^^^^^^^^^^
+
+.. tip::
+
+    Pass in :cdata:`NPY_MAXDIMS` for axis in order to achieve the same
+    effect that is obtained by passing in *axis* = :const:`None` in Python
+    (treating the array as a 1-d array).
+
+.. cfunction:: PyObject* PyArray_ArgMax(PyArrayObject* self, int axis)
+
+    Equivalent to :meth:`ndarray.argmax` (*self*, *axis*). Return the index of
+    the largest element of *self* along *axis*.
+
+.. cfunction:: PyObject* PyArray_ArgMin(PyArrayObject* self, int axis)
+
+    Equivalent to :meth:`ndarray.argmin` (*self*, *axis*). Return the index of
+    the smallest element of *self* along *axis*.
+
+.. cfunction:: PyObject* PyArray_Max(PyArrayObject* self, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.max` (*self*, *axis*). Return the largest
+    element of *self* along the given *axis*.
+
+.. cfunction:: PyObject* PyArray_Min(PyArrayObject* self, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.min` (*self*, *axis*). Return the smallest
+    element of *self* along the given *axis*.
+
+.. cfunction:: PyObject* PyArray_Ptp(PyArrayObject* self, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.ptp` (*self*, *axis*). Return the difference
+    between the largest element of *self* along *axis* and the
+    smallest element of *self* along *axis*.
+
+
+
+.. note::
+
+    The rtype argument specifies the data-type the reduction should
+    take place over. This is important if the data-type of the array
+    is not "large" enough to handle the output. By default, all
+    integer data-types are made at least as large as :cdata:`NPY_LONG`
+    for the "add" and "multiply" ufuncs (which form the basis for
+    mean, sum, cumsum, prod, and cumprod functions).
+
+.. cfunction:: PyObject* PyArray_Mean(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.mean` (*self*, *axis*, *rtype*). Returns the
+    mean of the elements along the given *axis*, using the enumerated
+    type *rtype* as the data type to sum in. Default sum behavior is
+    obtained using :cdata:`PyArray_NOTYPE` for *rtype*.
+
+.. cfunction:: PyObject* PyArray_Trace(PyArrayObject* self, int offset, int axis1, int axis2, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.trace` (*self*, *offset*, *axis1*, *axis2*,
+    *rtype*). Return the sum (using *rtype* as the data type of
+    summation) over the *offset* diagonal elements of the 2-d arrays
+    defined by *axis1* and *axis2* variables. A positive offset
+    chooses diagonals above the main diagonal. A negative offset
+    selects diagonals below the main diagonal.
+
+.. cfunction:: PyObject* PyArray_Clip(PyArrayObject* self, PyObject* min, PyObject* max)
+
+    Equivalent to :meth:`ndarray.clip` (*self*, *min*, *max*). Clip an array,
+    *self*, so that values larger than *max* are fixed to *max* and
+    values less than *min* are fixed to *min*.
+
+.. cfunction:: PyObject* PyArray_Conjugate(PyArrayObject* self)
+
+    Equivalent to :meth:`ndarray.conjugate` (*self*).
+    Return the complex conjugate of *self*. If *self* is not of
+    complex data type, then return *self* with an reference.
+
+.. cfunction:: PyObject* PyArray_Round(PyArrayObject* self, int decimals, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.round` (*self*, *decimals*, *out*). Returns
+    the array with elements rounded to the nearest decimal place. The
+    decimal place is defined as the :math:`10^{-\textrm{decimals}}`
+    digit so that negative *decimals* cause rounding to the nearest 10's, 100's, etc. If out is ``NULL``, then the output array is created, otherwise the output is placed in *out* which must be the correct size and type.
+
+.. cfunction:: PyObject* PyArray_Std(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.std` (*self*, *axis*, *rtype*). Return the
+    standard deviation using data along *axis* converted to data type
+    *rtype*.
+
+.. cfunction:: PyObject* PyArray_Sum(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.sum` (*self*, *axis*, *rtype*). Return 1-d
+    vector sums of elements in *self* along *axis*. Perform the sum
+    after converting data to data type *rtype*.
+
+.. cfunction:: PyObject* PyArray_CumSum(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.cumsum` (*self*, *axis*, *rtype*). Return
+    cumulative 1-d sums of elements in *self* along *axis*. Perform
+    the sum after converting data to data type *rtype*.
+
+.. cfunction:: PyObject* PyArray_Prod(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.prod` (*self*, *axis*, *rtype*). Return 1-d
+    products of elements in *self* along *axis*. Perform the product
+    after converting data to data type *rtype*.
+
+.. cfunction:: PyObject* PyArray_CumProd(PyArrayObject* self, int axis, int rtype, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.cumprod` (*self*, *axis*, *rtype*). Return
+    1-d cumulative products of elements in ``self`` along ``axis``.
+    Perform the product after converting data to data type ``rtype``.
+
+.. cfunction:: PyObject* PyArray_All(PyArrayObject* self, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.all` (*self*, *axis*). Return an array with
+    True elements for every 1-d sub-array of ``self`` defined by
+    ``axis`` in which all the elements are True.
+
+.. cfunction:: PyObject* PyArray_Any(PyArrayObject* self, int axis, PyArrayObject* out)
+
+    Equivalent to :meth:`ndarray.any` (*self*, *axis*). Return an array with
+    True elements for every 1-d sub-array of *self* defined by *axis*
+    in which any of the elements are True.
+
+Functions
+---------
+
+
+Array Functions
+^^^^^^^^^^^^^^^
+
+.. cfunction:: int PyArray_AsCArray(PyObject** op, void* ptr, npy_intp* dims, int nd, int typenum, int itemsize)
+
+    Sometimes it is useful to access a multidimensional array as a
+    C-style multi-dimensional array so that algorithms can be
+    implemented using C's a[i][j][k] syntax. This routine returns a
+    pointer, *ptr*, that simulates this kind of C-style array, for
+    1-, 2-, and 3-d ndarrays.
+
+    :param op:
+                
+        The address to any Python object. This Python object will be replaced
+        with an equivalent well-behaved, C-style contiguous, ndarray of the
+        given data type specifice by the last two arguments. Be sure that
+        stealing a reference in this way to the input object is justified.
+    
+    :param ptr:
+                
+        The address to a (ctype* for 1-d, ctype** for 2-d or ctype*** for 3-d)
+        variable where ctype is the equivalent C-type for the data type. On
+        return, *ptr* will be addressable as a 1-d, 2-d, or 3-d array.
+    
+    :param dims:
+                
+        An output array that contains the shape of the array object. This
+        array gives boundaries on any looping that will take place.
+    
+    :param nd:
+                
+        The dimensionality of the array (1, 2, or 3).
+    
+    :param typenum:
+                
+        The expected data type of the array.
+    
+    :param itemsize:
+                
+        This argument is only needed when *typenum* represents a
+        flexible array. Otherwise it should be 0.
+
+.. note::
+
+    The simulation of a C-style array is not complete for 2-d and 3-d
+    arrays. For example, the simulated arrays of pointers cannot be passed
+    to subroutines expecting specific, statically-defined 2-d and 3-d
+    arrays. To pass to functions requiring those kind of inputs, you must
+    statically define the required array and copy data. 
+
+.. cfunction:: int PyArray_Free(PyObject* op, void* ptr)
+
+    Must be called with the same objects and memory locations returned
+    from :cfunc:`PyArray_AsCArray` (...). This function cleans up memory
+    that otherwise would get leaked.
+
+.. cfunction:: PyObject* PyArray_Concatenate(PyObject* obj, int axis)
+
+    Join the sequence of objects in *obj* together along *axis* into a
+    single array. If the dimensions or types are not compatible an
+    error is raised.
+
+.. cfunction:: PyObject* PyArray_InnerProduct(PyObject* obj1, PyObject* obj2)
+
+    Compute a product-sum over the last dimensions of *obj1* and
+    *obj2*. Neither array is conjugated.
+
+.. cfunction:: PyObject* PyArray_MatrixProduct(PyObject* obj1, PyObject* obj)
+
+    Compute a product-sum over the last dimension of *obj1* and the
+    second-to-last dimension of *obj2*. For 2-d arrays this is a
+    matrix-product. Neither array is conjugated.
+
+.. cfunction:: PyObject* PyArray_CopyAndTranspose(PyObject \* op)
+
+    A specialized copy and transpose function that works only for 2-d
+    arrays. The returned array is a transposed copy of *op*.
+
+.. cfunction:: PyObject* PyArray_Correlate(PyObject* op1, PyObject* op2, int mode)
+
+    Compute the 1-d correlation of the 1-d arrays *op1* and *op2*
+    . The correlation is computed at each output point by multiplying
+    *op1* by a shifted version of *op2* and summing the result. As a
+    result of the shift, needed values outside of the defined range of
+    *op1* and *op2* are interpreted as zero. The mode determines how
+    many shifts to return: 0 - return only shifts that did not need to
+    assume zero- values; 1 - return an object that is the same size as
+    *op1*, 2 - return all possible shifts (any overlap at all is
+    accepted).
+
+.. cfunction:: PyObject* PyArray_Where(PyObject* condition, PyObject* x, PyObject* y)
+
+    If both ``x`` and ``y`` are ``NULL``, then return
+    :cfunc:`PyArray_Nonzero` (*condition*). Otherwise, both *x* and *y*
+    must be given and the object returned is shaped like *condition*
+    and has elements of *x* and *y* where *condition* is respectively
+    True or False.
+
+
+Other functions
+^^^^^^^^^^^^^^^
+
+.. cfunction:: Bool PyArray_CheckStrides(int elsize, int nd, npy_intp numbytes, npy_intp* dims, npy_intp* newstrides)
+
+    Determine if *newstrides* is a strides array consistent with the
+    memory of an *nd* -dimensional array with shape ``dims`` and
+    element-size, *elsize*. The *newstrides* array is checked to see
+    if jumping by the provided number of bytes in each direction will
+    ever mean jumping more than *numbytes* which is the assumed size
+    of the available memory segment. If *numbytes* is 0, then an
+    equivalent *numbytes* is computed assuming *nd*, *dims*, and
+    *elsize* refer to a single-segment array. Return :cdata:`NPY_TRUE` if
+    *newstrides* is acceptable, otherwise return :cdata:`NPY_FALSE`.
+
+.. cfunction:: npy_intp PyArray_MultiplyList(npy_intp* seq, int n)
+
+.. cfunction:: int PyArray_MultiplyIntList(int* seq, int n)
+
+    Both of these routines multiply an *n* -length array, *seq*, of
+    integers and return the result. No overflow checking is performed.
+
+.. cfunction:: int PyArray_CompareLists(npy_intp* l1, npy_intp* l2, int n)
+
+    Given two *n* -length arrays of integers, *l1*, and *l2*, return
+    1 if the lists are identical; otherwise, return 0.
+
+
+Array Iterators
+---------------
+
+An array iterator is a simple way to access the elements of an
+N-dimensional array quickly and efficiently. Section `2
+<#sec-array-iterator>`__ provides more description and examples of
+this useful approach to looping over an array.
+
+.. cfunction:: PyObject* PyArray_IterNew(PyObject* arr)
+
+    Return an array iterator object from the array, *arr*. This is
+    equivalent to *arr*. **flat**. The array iterator object makes
+    it easy to loop over an N-dimensional non-contiguous array in
+    C-style contiguous fashion.
+
+.. cfunction:: PyObject* PyArray_IterAllButAxis(PyObject* arr, int \*axis)
+
+    Return an array iterator that will iterate over all axes but the
+    one provided in *\*axis*. The returned iterator cannot be used
+    with :cfunc:`PyArray_ITER_GOTO1D`. This iterator could be used to
+    write something similar to what ufuncs do wherein the loop over
+    the largest axis is done by a separate sub-routine. If *\*axis* is
+    negative then *\*axis* will be set to the axis having the smallest
+    stride and that axis will be used.
+
+.. cfunction:: PyObject *PyArray_BroadcastToShape(PyObject* arr, npy_intp *dimensions, int nd)
+
+    Return an array iterator that is broadcast to iterate as an array
+    of the shape provided by *dimensions* and *nd*.
+
+.. cfunction:: int PyArrayIter_Check(PyObject* op)
+
+    Evaluates true if *op* is an array iterator (or instance of a
+    subclass of the array iterator type).
+
+.. cfunction:: void PyArray_ITER_RESET(PyObject* iterator)
+
+    Reset an *iterator* to the beginning of the array.
+
+.. cfunction:: void PyArray_ITER_NEXT(PyObject* iterator)
+
+    Incremement the index and the dataptr members of the *iterator* to
+    point to the next element of the array. If the array is not
+    (C-style) contiguous, also increment the N-dimensional coordinates
+    array.
+
+.. cfunction:: void *PyArray_ITER_DATA(PyObject* iterator)
+
+    A pointer to the current element of the array.
+
+.. cfunction:: void PyArray_ITER_GOTO(PyObject* iterator, npy_intp* destination)
+
+    Set the *iterator* index, dataptr, and coordinates members to the
+    location in the array indicated by the N-dimensional c-array,
+    *destination*, which must have size at least *iterator*
+    ->nd_m1+1.
+
+.. cfunction:: PyArray_ITER_GOTO1D(PyObject* iterator, npy_intp index)
+
+    Set the *iterator* index and dataptr to the location in the array
+    indicated by the integer *index* which points to an element in the
+    C-styled flattened array.
+
+.. cfunction:: int PyArray_ITER_NOTDONE(PyObject* iterator)
+
+    Evaluates TRUE as long as the iterator has not looped through all of
+    the elements, otherwise it evaluates FALSE.
+
+
+Broadcasting (multi-iterators)
+------------------------------
+
+.. cfunction:: PyObject* PyArray_MultiIterNew(int num, ...)
+
+    A simplified interface to broadcasting. This function takes the
+    number of arrays to broadcast and then *num* extra ( :ctype:`PyObject *`
+    ) arguments. These arguments are converted to arrays and iterators
+    are created. :cfunc:`PyArray_Broadcast` is then called on the resulting
+    multi-iterator object. The resulting, broadcasted mult-iterator
+    object is then returned. A broadcasted operation can then be
+    performed using a single loop and using :cfunc:`PyArray_MultiIter_NEXT`
+    (..)
+
+.. cfunction:: void PyArray_MultiIter_RESET(PyObject* multi)
+
+    Reset all the iterators to the beginning in a multi-iterator
+    object, *multi*.
+
+.. cfunction:: void PyArray_MultiIter_NEXT(PyObject* multi)
+
+    Advance each iterator in a multi-iterator object, *multi*, to its
+    next (broadcasted) element.
+
+.. cfunction:: void *PyArray_MultiIter_DATA(PyObject* multi, int i)
+
+    Return the data-pointer of the *i* :math:`^{\textrm{th}}` iterator
+    in a multi-iterator object.
+
+.. cfunction:: void PyArray_MultiIter_NEXTi(PyObject* multi, int i)
+
+    Advance the pointer of only the *i* :math:`^{\textrm{th}}` iterator.
+
+.. cfunction:: void PyArray_MultiIter_GOTO(PyObject* multi, npy_intp* destination)
+
+    Advance each iterator in a multi-iterator object, *multi*, to the
+    given :math:`N` -dimensional *destination* where :math:`N` is the
+    number of dimensions in the broadcasted array.
+
+.. cfunction:: void PyArray_MultiIter_GOTO1D(PyObject* multi, npy_intp index)
+
+    Advance each iterator in a multi-iterator object, *multi*, to the
+    corresponding location of the *index* into the flattened
+    broadcasted array.
+
+.. cfunction:: int PyArray_MultiIter_NOTDONE(PyObject* multi)
+
+    Evaluates TRUE as long as the multi-iterator has not looped
+    through all of the elements (of the broadcasted result), otherwise
+    it evaluates FALSE.
+
+.. cfunction:: int PyArray_Broadcast(PyArrayMultiIterObject* mit)
+
+    This function encapsulates the broadcasting rules. The *mit*
+    container should already contain iterators for all the arrays that
+    need to be broadcast. On return, these iterators will be adjusted
+    so that iteration over each simultaneously will accomplish the
+    broadcasting. A negative number is returned if an error occurs.
+
+.. cfunction:: int PyArray_RemoveSmallest(PyArrayMultiIterObject* mit)
+
+    This function takes a multi-iterator object that has been
+    previously "broadcasted," finds the dimension with the smallest
+    "sum of strides" in the broadcasted result and adapts all the
+    iterators so as not to iterate over that dimension (by effectively
+    making them of length-1 in that dimension). The corresponding
+    dimension is returned unless *mit* ->nd is 0, then -1 is
+    returned. This function is useful for constructing ufunc-like
+    routines that broadcast their inputs correctly and then call a
+    strided 1-d version of the routine as the inner-loop.  This 1-d
+    version is usually optimized for speed and for this reason the
+    loop should be performed over the axis that won't require large
+    stride jumps.
+
+
+Array Scalars
+-------------
+
+.. cfunction:: PyObject* PyArray_Return(PyArrayObject* arr)
+
+    This function checks to see if *arr* is a 0-dimensional array and,
+    if so, returns the appropriate array scalar. It should be used
+    whenever 0-dimensional arrays could be returned to Python.
+
+.. cfunction:: PyObject* PyArray_Scalar(void* data, PyArray_Descr* dtype, PyObject* itemsize)
+
+    Return an array scalar object of the given enumerated *typenum*
+    and *itemsize* by **copying** from memory pointed to by *data*
+    . If *swap* is nonzero then this function will byteswap the data
+    if appropriate to the data-type because array scalars are always
+    in correct machine-byte order.
+
+.. cfunction:: PyObject* PyArray_ToScalar(void* data, PyArrayObject* arr)
+
+    Return an array scalar object of the type and itemsize indicated
+    by the array object *arr* copied from the memory pointed to by
+    *data* and swapping if the data in *arr* is not in machine
+    byte-order.
+
+.. cfunction:: PyObject* PyArray_FromScalar(PyObject* scalar, PyArray_Descr* outcode)
+
+    Return a 0-dimensional array of type determined by *outcode* from
+    *scalar* which should be an array-scalar object. If *outcode* is
+    NULL, then the type is determined from *scalar*.
+
+.. cfunction:: void PyArray_ScalarAsCtype(PyObject* scalar, void* ctypeptr)
+
+    Return in *ctypeptr* a pointer to the actual value in an array
+    scalar. There is no error checking so *scalar* must be an
+    array-scalar object, and ctypeptr must have enough space to hold
+    the correct type. For flexible-sized types, a pointer to the data
+    is copied into the memory of *ctypeptr*, for all other types, the
+    actual data is copied into the address pointed to by *ctypeptr*.
+
+.. cfunction:: void PyArray_CastScalarToCtype(PyObject* scalar, void* ctypeptr, PyArray_Descr* outcode)
+
+    Return the data (cast to the data type indicated by *outcode*)
+    from the array-scalar, *scalar*, into the memory pointed to by
+    *ctypeptr* (which must be large enough to handle the incoming
+    memory).
+
+.. cfunction:: PyObject* PyArray_TypeObjectFromType(int type)
+
+    Returns a scalar type-object from a type-number, *type*
+    . Equivalent to :cfunc:`PyArray_DescrFromType` (*type*)->typeobj
+    except for reference counting and error-checking. Returns a new
+    reference to the typeobject on success or ``NULL`` on failure.
+
+.. cfunction:: NPY_SCALARKIND PyArray_ScalarKind(int typenum, PyArrayObject** arr)
+
+    Return the kind of scalar represented by *typenum* and the array
+    in *\*arr* (if *arr* is not ``NULL`` ). The array is assumed to be
+    rank-0 and only used if *typenum* represents a signed integer. If
+    *arr* is not ``NULL`` and the first element is negative then
+    :cdata:`NPY_INTNEG_SCALAR` is returned, otherwise
+    :cdata:`NPY_INTPOS_SCALAR` is returned. The possible return values
+    are :cdata:`NPY_{kind}_SCALAR` where ``{kind}`` can be **INTPOS**,
+    **INTNEG**, **FLOAT**, **COMPLEX**, **BOOL**, or **OBJECT**.
+    :cdata:`NPY_NOSCALAR` is also an enumerated value
+    :ctype:`NPY_SCALARKIND` variables can take on.
+
+.. cfunction:: int PyArray_CanCoerceScalar(char thistype, char neededtype, NPY_SCALARKIND scalar)
+
+    Implements the rules for scalar coercion. Scalars are only
+    silently coerced from thistype to neededtype if this function
+    returns nonzero.  If scalar is :cdata:`NPY_NOSCALAR`, then this
+    function is equivalent to :cfunc:`PyArray_CanCastSafely`. The rule is
+    that scalars of the same KIND can be coerced into arrays of the
+    same KIND. This rule means that high-precision scalars will never
+    cause low-precision arrays of the same KIND to be upcast.
+
+
+Data-type descriptors
+---------------------
+
+
+
+.. warning::
+
+    Data-type objects must be reference counted so be aware of the
+    action on the data-type reference of different C-API calls. The
+    standard rule is that when a data-type object is returned it is a
+    new reference.  Functions that take :ctype:`PyArray_Descr *` objects and
+    return arrays steal references to the data-type their inputs
+    unless otherwise noted. Therefore, you must own a reference to any
+    data-type object used as input to such a function.
+
+.. cfunction:: int PyArrayDescr_Check(PyObject* obj)
+
+    Evaluates as true if *obj* is a data-type object ( :ctype:`PyArray_Descr *` ).
+
+.. cfunction:: PyArray_Descr* PyArray_DescrNew(PyArray_Descr* obj)
+
+    Return a new data-type object copied from *obj* (the fields
+    reference is just updated so that the new object points to the
+    same fields dictionary if any).
+
+.. cfunction:: PyArray_Descr* PyArray_DescrNewFromType(int typenum)
+
+    Create a new data-type object from the built-in (or
+    user-registered) data-type indicated by *typenum*. All builtin
+    types should not have any of their fields changed. This creates a
+    new copy of the :ctype:`PyArray_Descr` structure so that you can fill
+    it in as appropriate. This function is especially needed for
+    flexible data-types which need to have a new elsize member in
+    order to be meaningful in array construction.
+
+.. cfunction:: PyArray_Descr* PyArray_DescrNewByteorder(PyArray_Descr* obj, char newendian)
+
+    Create a new data-type object with the byteorder set according to
+    *newendian*. All referenced data-type objects (in subdescr and
+    fields members of the data-type object) are also changed
+    (recursively). If a byteorder of :cdata:`NPY_IGNORE` is encountered it
+    is left alone. If newendian is :cdata:`NPY_SWAP`, then all byte-orders
+    are swapped. Other valid newendian values are :cdata:`NPY_NATIVE`,
+    :cdata:`NPY_LITTLE`, and :cdata:`NPY_BIG` which all cause the returned
+    data-typed descriptor (and all it's
+    referenced data-type descriptors) to have the corresponding byte-
+    order.
+
+.. cfunction:: PyArray_Descr* PyArray_DescrFromObject(PyObject* op, PyArray_Descr* mintype)
+
+    Determine an appropriate data-type object from the object *op*
+    (which should be a "nested" sequence object) and the minimum
+    data-type descriptor mintype (which can be ``NULL`` ). Similar in
+    behavior to array(*op*).dtype. Don't confuse this function with
+    :cfunc:`PyArray_DescrConverter`. This function essentially looks at
+    all the objects in the (nested) sequence and determines the
+    data-type from the elements it finds.
+
+.. cfunction:: PyArray_Descr* PyArray_DescrFromScalar(PyObject* scalar)
+
+    Return a data-type object from an array-scalar object. No checking
+    is done to be sure that *scalar* is an array scalar. If no
+    suitable data-type can be determined, then a data-type of
+    :cdata:`NPY_OBJECT` is returned by default.
+
+.. cfunction:: PyArray_Descr* PyArray_DescrFromType(int typenum)
+
+    Returns a data-type object corresponding to *typenum*. The
+    *typenum* can be one of the enumerated types, a character code for
+    one of the enumerated types, or a user-defined type.
+
+.. cfunction:: int PyArray_DescrConverter(PyObject* obj, PyArray_Descr** dtype)
+
+    Convert any compatible Python object, *obj*, to a data-type object
+    in *dtype*. A large number of Python objects can be converted to
+    data-type objects. See :ref:`arrays.dtypes` for a complete
+    description. This version of the converter converts None objects
+    to a :cdata:`NPY_DEFAULT_TYPE` data-type object. This function can
+    be used with the "O&" character code in :cfunc:`PyArg_ParseTuple`
+    processing.
+
+.. cfunction:: int PyArray_DescrConverter2(PyObject* obj, PyArray_Descr** dtype)
+
+    Convert any compatible Python object, *obj*, to a data-type
+    object in *dtype*. This version of the converter converts None
+    objects so that the returned data-type is ``NULL``. This function
+    can also be used with the "O&" character in PyArg_ParseTuple
+    processing.
+
+.. cfunction:: int Pyarray_DescrAlignConverter(PyObject* obj, PyArray_Descr** dtype)
+
+    Like :cfunc:`PyArray_DescrConverter` except it aligns C-struct-like
+    objects on word-boundaries as the compiler would.
+
+.. cfunction:: int Pyarray_DescrAlignConverter2(PyObject* obj, PyArray_Descr** dtype)
+
+    Like :cfunc:`PyArray_DescrConverter2` except it aligns C-struct-like
+    objects on word-boundaries as the compiler would.
+
+.. cfunction:: PyObject *PyArray_FieldNames(PyObject* dict)
+
+    Take the fields dictionary, *dict*, such as the one attached to a
+    data-type object and construct an ordered-list of field names such
+    as is stored in the names field of the :ctype:`PyArray_Descr` object.
+
+
+Conversion Utilities
+--------------------
+
+
+For use with :cfunc:`PyArg_ParseTuple`
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+All of these functions can be used in :cfunc:`PyArg_ParseTuple` (...) with
+the "O&" format specifier to automatically convert any Python object
+to the required C-object. All of these functions return
+:cdata:`NPY_SUCCEED` if successful and :cdata:`NPY_FAIL` if not. The first
+argument to all of these function is a Python object. The second
+argument is the **address** of the C-type to convert the Python object
+to.
+
+
+.. warning::
+
+    Be sure to understand what steps you should take to manage the
+    memory when using these conversion functions. These functions can
+    require freeing memory, and/or altering the reference counts of
+    specific objects based on your use.
+
+.. cfunction:: int PyArray_Converter(PyObject* obj, PyObject** address)
+
+    Convert any Python object to a :ctype:`PyArrayObject`. If
+    :cfunc:`PyArray_Check` (*obj*) is TRUE then its reference count is
+    incremented and a reference placed in *address*. If *obj* is not
+    an array, then convert it to an array using :cfunc:`PyArray_FromAny`
+    . No matter what is returned, you must DECREF the object returned
+    by this routine in *address* when you are done with it.
+
+.. cfunction:: int PyArray_OutputConverter(PyObject* obj, PyArrayObject** address)
+
+    This is a default converter for output arrays given to
+    functions. If *obj* is :cdata:`Py_None` or ``NULL``, then *\*address*
+    will be ``NULL`` but the call will succeed. If :cfunc:`PyArray_Check` (
+    *obj*) is TRUE then it is returned in *\*address* without
+    incrementing its reference count.
+
+.. cfunction:: int PyArray_IntpConverter(PyObject* obj, PyArray_Dims* seq)
+
+    Convert any Python sequence, *obj*, smaller than :cdata:`NPY_MAXDIMS`
+    to a C-array of :ctype:`npy_intp`. The Python object could also be a
+    single number. The *seq* variable is a pointer to a structure with
+    members ptr and len. On successful return, *seq* ->ptr contains a
+    pointer to memory that must be freed to avoid a memory leak. The
+    restriction on memory size allows this converter to be
+    conveniently used for sequences intended to be interpreted as
+    array shapes.
+
+.. cfunction:: int PyArray_BufferConverter(PyObject* obj, PyArray_Chunk* buf)
+
+    Convert any Python object, *obj*, with a (single-segment) buffer
+    interface to a variable with members that detail the object's use
+    of its chunk of memory. The *buf* variable is a pointer to a
+    structure with base, ptr, len, and flags members. The
+    :ctype:`PyArray_Chunk` structure is binary compatibile with the
+    Python's buffer object (through its len member on 32-bit platforms
+    and its ptr member on 64-bit platforms or in Python 2.5). On
+    return, the base member is set to *obj* (or its base if *obj* is
+    already a buffer object pointing to another object). If you need
+    to hold on to the memory be sure to INCREF the base member. The
+    chunk of memory is pointed to by *buf* ->ptr member and has length
+    *buf* ->len. The flags member of *buf* is :cdata:`NPY_BEHAVED_RO` with
+    the :cdata:`NPY_WRITEABLE` flag set if *obj* has a writeable buffer
+    interface.
+
+.. cfunction:: int PyArray_AxisConverter(PyObject \* obj, int* axis)
+
+    Convert a Python object, *obj*, representing an axis argument to
+    the proper value for passing to the functions that take an integer
+    axis. Specifically, if *obj* is None, *axis* is set to
+    :cdata:`NPY_MAXDIMS` which is interpreted correctly by the C-API
+    functions that take axis arguments.
+
+.. cfunction:: int PyArray_BoolConverter(PyObject* obj, Bool* value)
+
+    Convert any Python object, *obj*, to :cdata:`NPY_TRUE` or
+    :cdata:`NPY_FALSE`, and place the result in *value*.
+
+.. cfunction:: int PyArray_ByteorderConverter(PyObject* obj, char* endian)
+
+    Convert Python strings into the corresponding byte-order
+    character:
+    '>', '<', 's', '=', or '\|'.
+
+.. cfunction:: int PyArray_SortkindConverter(PyObject* obj, NPY_SORTKIND* sort)
+
+    Convert Python strings into one of :cdata:`NPY_QUICKSORT` (starts
+    with 'q' or 'Q') , :cdata:`NPY_HEAPSORT` (starts with 'h' or 'H'),
+    or :cdata:`NPY_MERGESORT` (starts with 'm' or 'M').
+
+.. cfunction:: int PyArray_SearchsideConverter(PyObject* obj, NPY_SEARCHSIDE* side)
+
+    Convert Python strings into one of :cdata:`NPY_SEARCHLEFT` (starts with 'l'
+    or 'L'), or :cdata:`NPY_SEARCHRIGHT` (starts with 'r' or 'R').
+
+Other conversions
+^^^^^^^^^^^^^^^^^
+
+.. cfunction:: int PyArray_PyIntAsInt(PyObject* op)
+
+    Convert all kinds of Python objects (including arrays and array
+    scalars) to a standard integer. On error, -1 is returned and an
+    exception set. You may find useful the macro:
+
+    .. code-block:: c
+
+        #define error_converting(x) (((x) == -1) && PyErr_Occurred()
+
+.. cfunction:: npy_intp PyArray_PyIntAsIntp(PyObject* op)
+
+    Convert all kinds of Python objects (including arrays and array
+    scalars) to a (platform-pointer-sized) integer. On error, -1 is
+    returned and an exception set.
+
+.. cfunction:: int PyArray_IntpFromSequence(PyObject* seq, npy_intp* vals, int maxvals)
+
+    Convert any Python sequence (or single Python number) passed in as
+    *seq* to (up to) *maxvals* pointer-sized integers and place them
+    in the *vals* array. The sequence can be smaller then *maxvals* as
+    the number of converted objects is returned.
+
+.. cfunction:: int PyArray_TypestrConvert(int itemsize, int gentype)
+
+    Convert typestring characters (with *itemsize*) to basic
+    enumerated data types. The typestring character corresponding to
+    signed and unsigned integers, floating point numbers, and
+    complex-floating point numbers are recognized and converted. Other
+    values of gentype are returned. This function can be used to
+    convert, for example, the string'f4' to :cdata:`NPY_FLOAT32`.
+
+
+Miscellaneous
+-------------
+
+
+Importing the API
+^^^^^^^^^^^^^^^^^
+
+In order to make use of the C-API from another extension module, the
+``import_array`` () command must be used. If the extension module is
+self-contained in a single .c file, then that is all that needs to be
+done. If, however, the extension module involves multiple files where
+the C-API is needed then some additional steps must be taken.
+
+.. cfunction:: void import_array(void)
+
+    This function must be called in the initialization section of a
+    module that will make use of the C-API. It imports the module
+    where the function-pointer table is stored and points the correct
+    variable to it.
+
+.. cmacro:: PY_ARRAY_UNIQUE_SYMBOL
+    
+.. cmacro:: NO_IMPORT_ARRAY
+
+    Using these #defines you can use the C-API in multiple files for a
+    single extension module. In each file you must define
+    :cmacro:`PY_ARRAY_UNIQUE_SYMBOL` to some name that will hold the
+    C-API (*e.g.* myextension_ARRAY_API). This must be done **before**
+    including the numpy/arrayobject.h file. In the module
+    intialization routine you call ``import_array`` (). In addition,
+    in the files that do not have the module initialization
+    sub_routine define :cmacro:`NO_IMPORT_ARRAY` prior to including
+    numpy/arrayobject.h.
+
+    Suppose I have two files coolmodule.c and coolhelper.c which need
+    to be compiled and linked into a single extension module. Suppose
+    coolmodule.c contains the required initcool module initialization
+    function (with the import_array() function called). Then,
+    coolmodule.c would have at the top:
+    
+    .. code-block:: c
+    
+        #define PY_ARRAY_UNIQUE_SYMBOL cool_ARRAY_API
+        #include numpy/arrayobject.h
+    
+    On the other hand, coolhelper.c would contain at the top:
+    
+    .. code-block:: c
+    
+        #define PY_ARRAY_UNIQUE_SYMBOL cool_ARRAY_API
+        #define NO_IMPORT_ARRAY
+        #include numpy/arrayobject.h
+
+.. cfunction:: unsigned int PyArray_GetNDArrayCVersion(void)
+
+    This just returns the value :cdata:`NPY_VERSION`. Because it is in the
+    C-API, however, comparing the output of this function from the
+    value defined in the current header gives a way to test if the
+    C-API has changed thus requiring a re-compilation of extension
+    modules that use the C-API.
+
+
+Internal Flexibility
+^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: int PyArray_SetNumericOps(PyObject* dict)
+
+    NumPy stores an internal table of Python callable objects that are
+    used to implement arithmetic operations for arrays as well as
+    certain array calculation methods. This function allows the user
+    to replace any or all of these Python objects with their own
+    versions. The keys of the dictionary, *dict*, are the named
+    functions to replace and the paired value is the Python callable
+    object to use. Care should be taken that the function used to
+    replace an internal array operation does not itself call back to
+    that internal array operation (unless you have designed the
+    function to handle that), or an unchecked infinite recursion can
+    result (possibly causing program crash). The key names that
+    represent operations that can be replaced are:
+
+        **add**, **subtract**, **multiply**, **divide**,
+        **remainder**, **power**, **square**, **reciprocal**,
+        **ones_like**, **sqrt**, **negative**, **absolute**,
+        **invert**, **left_shift**, **right_shift**,
+        **bitwise_and**, **bitwise_xor**, **bitwise_or**,
+        **less**, **less_equal**, **equal**, **not_equal**,
+        **greater**, **greater_equal**, **floor_divide**,
+        **true_divide**, **logical_or**, **logical_and**,
+        **floor**, **ceil**, **maximum**, **minimum**, **rint**.
+    
+    
+    These functions are included here because they are used at least once
+    in the array object's methods. The function returns -1 (without
+    setting a Python Error) if one of the objects being assigned is not
+    callable.
+
+.. cfunction:: PyObject* PyArray_GetNumericOps(void)
+
+    Return a Python dictionary containing the callable Python objects
+    stored in the the internal arithmetic operation table. The keys of
+    this dictionary are given in the explanation for :cfunc:`PyArray_SetNumericOps`.
+
+.. cfunction:: void PyArray_SetStringFunction(PyObject* op, int repr)
+
+    This function allows you to alter the tp_str and tp_repr methods
+    of the array object to any Python function. Thus you can alter
+    what happens for all arrays when str(arr) or repr(arr) is called
+    from Python. The function to be called is passed in as *op*. If
+    *repr* is non-zero, then this function will be called in response
+    to repr(arr), otherwise the function will be called in response to
+    str(arr). No check on whether or not *op* is callable is
+    performed. The callable passed in to *op* should expect an array
+    argument and should return a string to be printed.
+
+
+Memory management
+^^^^^^^^^^^^^^^^^
+
+.. cfunction:: char* PyDataMem_NEW(size_t nbytes)
+
+.. cfunction:: PyDataMem_FREE(char* ptr)
+
+.. cfunction:: char* PyDataMem_RENEW(void * ptr, size_t newbytes)
+
+    Macros to allocate, free, and reallocate memory. These macros are used
+    internally to create arrays.
+
+.. cfunction:: npy_intp*  PyDimMem_NEW(nd)
+
+.. cfunction:: PyDimMem_FREE(npy_intp* ptr)
+
+.. cfunction:: npy_intp* PyDimMem_RENEW(npy_intp* ptr, npy_intp newnd)
+
+    Macros to allocate, free, and reallocate dimension and strides memory.
+
+.. cfunction:: PyArray_malloc(nbytes)
+
+.. cfunction:: PyArray_free(ptr)
+
+.. cfunction:: PyArray_realloc(ptr, nbytes)
+
+    These macros use different memory allocators, depending on the
+    constant :cdata:`NPY_USE_PYMEM`. The system malloc is used when
+    :cdata:`NPY_USE_PYMEM` is 0, if :cdata:`NPY_USE_PYMEM` is 1, then
+    the Python memory allocator is used.
+
+
+Threading support
+^^^^^^^^^^^^^^^^^
+
+These macros are only meaningful if :cdata:`NPY_ALLOW_THREADS`
+evaluates True during compilation of the extension module. Otherwise,
+these macros are equivalent to whitespace. Python uses a single Global
+Interpreter Lock (GIL) for each Python process so that only a single
+thread may excecute at a time (even on multi-cpu machines). When
+calling out to a compiled function that may take time to compute (and
+does not have side-effects for other threads like updated global
+variables), the GIL should be released so that other Python threads
+can run while the time-consuming calculations are performed. This can
+be accomplished using two groups of macros. Typically, if one macro in
+a group is used in a code block, all of them must be used in the same
+code block. Currently, :cdata:`NPY_ALLOW_THREADS` is defined to the
+python-defined :cdata:`WITH_THREADS` constant unless the environment
+variable :cdata:`NPY_NOSMP` is set in which case
+:cdata:`NPY_ALLOW_THREADS` is defined to be 0.
+
+Group 1
+"""""""
+
+    This group is used to call code that may take some time but does not
+    use any Python C-API calls. Thus, the GIL should be released during
+    its calculation.
+
+    .. cmacro:: NPY_BEGIN_ALLOW_THREADS
+    
+        Equivalent to :cmacro:`Py_BEGIN_ALLOW_THREADS` except it uses
+        :cdata:`NPY_ALLOW_THREADS` to determine if the macro if
+        replaced with white-space or not.
+    
+    .. cmacro:: NPY_END_ALLOW_THREADS
+    
+        Equivalent to :cmacro:`Py_END_ALLOW_THREADS` except it uses
+        :cdata:`NPY_ALLOW_THREADS` to determine if the macro if
+        replaced with white-space or not.
+    
+    .. cmacro:: NPY_BEGIN_THREADS_DEF
+    
+        Place in the variable declaration area. This macro sets up the
+        variable needed for storing the Python state.
+    
+    .. cmacro:: NPY_BEGIN_THREADS
+    
+        Place right before code that does not need the Python
+        interpreter (no Python C-API calls). This macro saves the
+        Python state and releases the GIL.
+    
+    .. cmacro:: NPY_END_THREADS
+    
+        Place right after code that does not need the Python
+        interpreter. This macro acquires the GIL and restores the
+        Python state from the saved variable.
+    
+    .. cfunction:: NPY_BEGIN_THREADS_DESCR(PyArray_Descr *dtype) 
+    
+        Useful to release the GIL only if *dtype* does not contain
+        arbitrary Python objects which may need the Python interpreter
+        during execution of the loop. Equivalent to
+    
+    .. cfunction:: NPY_END_THREADS_DESCR(PyArray_Descr *dtype)
+
+        Useful to regain the GIL in situations where it was released
+        using the BEGIN form of this macro.
+    
+Group 2
+"""""""
+
+    This group is used to re-acquire the Python GIL after it has been
+    released. For example, suppose the GIL has been released (using the
+    previous calls), and then some path in the code (perhaps in a
+    different subroutine) requires use of the Python C-API, then these
+    macros are useful to acquire the GIL. These macros accomplish
+    essentially a reverse of the previous three (acquire the LOCK saving
+    what state it had) and then re-release it with the saved state.
+
+    .. cmacro:: NPY_ALLOW_C_API_DEF
+    
+        Place in the variable declaration area to set up the necessary
+        variable.
+    
+    .. cmacro:: NPY_ALLOW_C_API
+    
+        Place before code that needs to call the Python C-API (when it is
+        known that the GIL has already been released).
+    
+    .. cmacro:: NPY_DISABLE_C_API
+    
+        Place after code that needs to call the Python C-API (to re-release
+        the GIL).
+
+.. tip::
+
+    Never use semicolons after the threading support macros. 
+
+
+Priority
+^^^^^^^^
+
+.. cvar:: NPY_PRIOIRTY
+
+    Default priority for arrays.
+
+.. cvar:: NPY_SUBTYPE_PRIORITY
+
+    Default subtype priority.
+
+.. cvar:: NPY_SCALAR_PRIORITY
+
+    Default scalar priority (very small)
+
+.. cfunction:: double PyArray_GetPriority(PyObject* obj, double def)
+
+    Return the :obj:`__array_priority__` attribute (converted to a
+    double) of *obj* or *def* if no attribute of that name
+    exists. Fast returns that avoid the attribute lookup are provided
+    for objects of type :cdata:`PyArray_Type`.
+
+
+Default buffers
+^^^^^^^^^^^^^^^
+
+.. cvar:: NPY_BUFSIZE
+
+    Default size of the user-settable internal buffers.
+
+.. cvar:: NPY_MIN_BUFSIZE
+
+    Smallest size of user-settable internal buffers.
+
+.. cvar:: NPY_MAX_BUFSIZE
+
+    Largest size allowed for the user-settable buffers.
+
+
+Other constants
+^^^^^^^^^^^^^^^
+
+.. cvar:: NPY_NUM_FLOATTYPE
+
+    The number of floating-point types
+
+.. cvar:: NPY_MAXDIMS
+
+    The maximum number of dimensions allowed in arrays.
+
+.. cvar:: NPY_VERSION
+
+    The current version of the ndarray object (check to see if this
+    variable is defined to guarantee the numpy/arrayobject.h header is
+    being used).
+
+.. cvar:: NPY_FALSE
+
+    Defined as 0 for use with Bool.
+
+.. cvar:: NPY_TRUE
+
+    Defined as 1 for use with Bool.
+
+.. cvar:: NPY_FAIL
+
+    The return value of failed converter functions which are called using
+    the "O&" syntax in :cfunc:`PyArg_ParseTuple`-like functions.
+
+.. cvar:: NPY_SUCCEED
+
+    The return value of successful converter functions which are called
+    using the "O&" syntax in :cfunc:`PyArg_ParseTuple`-like functions.
+
+
+Miscellaneous Macros
+^^^^^^^^^^^^^^^^^^^^
+
+.. cfunction:: PyArray_SAMESHAPE(a1, a2)
+
+    Evaluates as True if arrays *a1* and *a2* have the same shape.
+
+.. cfunction:: PyArray_MAX(a,b)
+
+    Returns the maximum of *a* and *b*. If (*a*) or (*b*) are
+    expressions they are evaluated twice.
+
+.. cfunction:: PyArray_MIN(a,b)
+
+    Returns the minimum of *a* and *b*. If (*a*) or (*b*) are
+    expressions they are evaluated twice.
+
+.. cfunction:: PyArray_CLT(a,b)
+
+.. cfunction:: PyArray_CGT(a,b)
+
+.. cfunction:: PyArray_CLE(a,b)
+
+.. cfunction:: PyArray_CGE(a,b)
+
+.. cfunction:: PyArray_CEQ(a,b)
+
+.. cfunction:: PyArray_CNE(a,b)
+
+    Implements the complex comparisons between two complex numbers
+    (structures with a real and imag member) using NumPy's definition
+    of the ordering which is lexicographic: comparing the real parts
+    first and then the complex parts if the real parts are equal.
+
+.. cfunction:: PyArray_REFCOUNT(PyObject* op)
+
+    Returns the reference count of any Python object.
+
+.. cfunction:: PyArray_XDECREF_ERR(PyObject \*obj)
+
+    DECREF's an array object which may have the :cdata:`NPY_UPDATEIFCOPY`
+    flag set without causing the contents to be copied back into the
+    original array. Resets the :cdata:`NPY_WRITEABLE` flag on the base
+    object. This is useful for recovering from an error condition when
+    :cdata:`NPY_UPDATEIFCOPY` is used.
+
+
+Enumerated Types
+^^^^^^^^^^^^^^^^
+
+.. ctype:: NPY_SORTKIND
+
+    A special variable-type which can take on the values :cdata:`NPY_{KIND}`
+    where ``{KIND}`` is
+
+        **QUICKSORT**, **HEAPSORT**, **MERGESORT** 
+    
+    .. cvar:: NPY_NSORTS
+    
+       Defined to be the number of sorts.
+
+.. ctype:: NPY_SCALARKIND
+
+    A special variable type indicating the number of "kinds" of
+    scalars distinguished in determining scalar-coercion rules. This
+    variable can take on the values :cdata:`NPY_{KIND}` where ``{KIND}`` can be
+
+        **NOSCALAR**, **BOOL_SCALAR**, **INTPOS_SCALAR**,
+        **INTNEG_SCALAR**, **FLOAT_SCALAR**, **COMPLEX_SCALAR**,
+        **OBJECT_SCALAR** 
+    
+    
+    .. cvar:: NPY_NSCALARKINDS
+    
+       Defined to be the number of scalar kinds
+       (not including :cdata:`NPY_NOSCALAR`).
+
+.. ctype:: NPY_ORDER
+
+    A variable type indicating the order that an array should be
+    interpreted in. The value of a variable of this type can be
+    :cdata:`NPY_{ORDER}` where ``{ORDER}`` is
+
+        **ANYORDER**, **CORDER**, **FORTRANORDER** 
+
+.. ctype:: NPY_CLIPMODE
+
+    A variable type indicating the kind of clipping that should be
+    applied in certain functions. The value of a variable of this type
+    can be :cdata:`NPY_{MODE}` where ``{MODE}`` is
+
+        **CLIP**, **WRAP**, **RAISE** 
+    
+.. index::
+   pair: ndarray; C-API