===========
NumPy C-API
===========
::

  unsigned int
  PyArray_GetNDArrayCVersion(void )


Included at the very first so not auto-grabbed and thus not labeled.

::

  int
  PyArray_SetNumericOps(PyObject *dict)

Set internal structure with number functions that all arrays will use

::

  PyObject *
  PyArray_GetNumericOps(void )

Get dictionary showing number functions that all arrays will use

::

  int
  PyArray_INCREF(PyArrayObject *mp)

For object arrays, increment all internal references.

::

  int
  PyArray_XDECREF(PyArrayObject *mp)

Decrement all internal references for object arrays.
(or arrays with object fields)

::

  void
  PyArray_SetStringFunction(PyObject *op, int repr)

Set the array print function to be a Python function.

::

  PyArray_Descr *
  PyArray_DescrFromType(int type)

Get the PyArray_Descr structure for a type.

::

  PyObject *
  PyArray_TypeObjectFromType(int type)

Get a typeobject from a type-number -- can return NULL.

New reference

::

  char *
  PyArray_Zero(PyArrayObject *arr)

Get pointer to zero of correct type for array.

::

  char *
  PyArray_One(PyArrayObject *arr)

Get pointer to one of correct type for array

::

  PyObject *
  PyArray_CastToType(PyArrayObject *arr, PyArray_Descr *dtype, int
                     is_f_order)

For backward compatibility

Cast an array using typecode structure.
steals reference to dtype --- cannot be NULL

This function always makes a copy of arr, even if the dtype
doesn't change.

::

  int
  PyArray_CastTo(PyArrayObject *out, PyArrayObject *mp)

Cast to an already created array.

::

  int
  PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp)

Cast to an already created array.  Arrays don't have to be "broadcastable"
Only requirement is they have the same number of elements.

::

  int
  PyArray_CanCastSafely(int fromtype, int totype)

Check the type coercion rules.

::

  npy_bool
  PyArray_CanCastTo(PyArray_Descr *from, PyArray_Descr *to)

leaves reference count alone --- cannot be NULL

PyArray_CanCastTypeTo is equivalent to this, but adds a 'casting'
parameter.

::

  int
  PyArray_ObjectType(PyObject *op, int minimum_type)

Return the typecode of the array a Python object would be converted to

Returns the type number the result should have, or NPY_NOTYPE on error.

::

  PyArray_Descr *
  PyArray_DescrFromObject(PyObject *op, PyArray_Descr *mintype)

new reference -- accepts NULL for mintype

::

  PyArrayObject **
  PyArray_ConvertToCommonType(PyObject *op, int *retn)


This function is only used in one place within NumPy and should
generally be avoided. It is provided mainly for backward compatibility.

The user of the function has to free the returned array.

::

  PyArray_Descr *
  PyArray_DescrFromScalar(PyObject *sc)

Return descr object from array scalar.

New reference

::

  PyArray_Descr *
  PyArray_DescrFromTypeObject(PyObject *type)


::

  npy_intp
  PyArray_Size(PyObject *op)

Compute the size of an array (in number of items)

::

  PyObject *
  PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base)

Get scalar-equivalent to a region of memory described by a descriptor.

::

  PyObject *
  PyArray_FromScalar(PyObject *scalar, PyArray_Descr *outcode)

Get 0-dim array from scalar

0-dim array from array-scalar object
always contains a copy of the data
unless outcode is NULL, it is of void type and the referrer does
not own it either.

steals reference to outcode

::

  void
  PyArray_ScalarAsCtype(PyObject *scalar, void *ctypeptr)

Convert to c-type

no error checking is performed -- ctypeptr must be same type as scalar
in case of flexible type, the data is not copied
into ctypeptr which is expected to be a pointer to pointer

::

  int
  PyArray_CastScalarToCtype(PyObject *scalar, void
                            *ctypeptr, PyArray_Descr *outcode)

Cast Scalar to c-type

The output buffer must be large-enough to receive the value
Even for flexible types which is different from ScalarAsCtype
where only a reference for flexible types is returned

This may not work right on narrow builds for NumPy unicode scalars.

::

  int
  PyArray_CastScalarDirect(PyObject *scalar, PyArray_Descr
                           *indescr, void *ctypeptr, int outtype)

Cast Scalar to c-type

::

  PyObject *
  PyArray_ScalarFromObject(PyObject *object)

Get an Array Scalar From a Python Object

Returns NULL if unsuccessful but error is only set if another error occurred.
Currently only Numeric-like object supported.

::

  PyArray_VectorUnaryFunc *
  PyArray_GetCastFunc(PyArray_Descr *descr, int type_num)

Get a cast function to cast from the input descriptor to the
output type_number (must be a registered data-type).
Returns NULL if un-successful.

::

  PyObject *
  PyArray_FromDims(int NPY_UNUSED(nd) , int *NPY_UNUSED(d) , int
                   NPY_UNUSED(type) )

Deprecated, use PyArray_SimpleNew instead.

::

  PyObject *
  PyArray_FromDimsAndDataAndDescr(int NPY_UNUSED(nd) , int
                                  *NPY_UNUSED(d) , PyArray_Descr
                                  *descr, char *NPY_UNUSED(data) )

Deprecated, use PyArray_NewFromDescr instead.

::

  PyObject *
  PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int
                  min_depth, int max_depth, int flags, PyObject
                  *context)

Does not check for NPY_ARRAY_ENSURECOPY and NPY_ARRAY_NOTSWAPPED in flags
Steals a reference to newtype --- which can be NULL

::

  PyObject *
  PyArray_EnsureArray(PyObject *op)

This is a quick wrapper around
PyArray_FromAny(op, NULL, 0, 0, NPY_ARRAY_ENSUREARRAY, NULL)
that special cases Arrays and PyArray_Scalars up front
It *steals a reference* to the object
It also guarantees that the result is PyArray_Type
Because it decrefs op if any conversion needs to take place
so it can be used like PyArray_EnsureArray(some_function(...))

::

  PyObject *
  PyArray_EnsureAnyArray(PyObject *op)


::

  PyObject *
  PyArray_FromFile(FILE *fp, PyArray_Descr *dtype, npy_intp num, char
                   *sep)


Given a ``FILE *`` pointer ``fp``, and a ``PyArray_Descr``, return an
array corresponding to the data encoded in that file.

The reference to `dtype` is stolen (it is possible that the passed in
dtype is not held on to).

The number of elements to read is given as ``num``; if it is < 0, then
then as many as possible are read.

If ``sep`` is NULL or empty, then binary data is assumed, else
text data, with ``sep`` as the separator between elements. Whitespace in
the separator matches any length of whitespace in the text, and a match
for whitespace around the separator is added.

For memory-mapped files, use the buffer interface. No more data than
necessary is read by this routine.

::

  PyObject *
  PyArray_FromString(char *data, npy_intp slen, PyArray_Descr
                     *dtype, npy_intp num, char *sep)


Given a pointer to a string ``data``, a string length ``slen``, and
a ``PyArray_Descr``, return an array corresponding to the data
encoded in that string.

If the dtype is NULL, the default array type is used (double).
If non-null, the reference is stolen.

If ``slen`` is < 0, then the end of string is used for text data.
It is an error for ``slen`` to be < 0 for binary data (since embedded NULLs
would be the norm).

The number of elements to read is given as ``num``; if it is < 0, then
then as many as possible are read.

If ``sep`` is NULL or empty, then binary data is assumed, else
text data, with ``sep`` as the separator between elements. Whitespace in
the separator matches any length of whitespace in the text, and a match
for whitespace around the separator is added.

::

  PyObject *