Function ndpointer

site-packages/numpy/ctypeslib.py:231–346

Array-checking restype/argtypes. An ndpointer instance is used to describe an ndarray in restypes and argtypes specifications. This approach is more flexible than using, for example, ``POINTER(c_double)``, since several restrictions can be specified, which are verified upon ca

(dtype=None, ndim=None, shape=None, flags=None)

#  use with ctypes argtypes mechanism
_pointer_type_cache = {}
def ndpointer(dtype=None, ndim=None, shape=None, flags=None):
    """
    Array-checking restype/argtypes.

    An ndpointer instance is used to describe an ndarray in restypes
    and argtypes specifications.  This approach is more flexible than
    using, for example, ``POINTER(c_double)``, since several restrictions
    can be specified, which are verified upon calling the ctypes function.
    These include data type, number of dimensions, shape and flags.  If a
    given array does not satisfy the specified restrictions,
    a ``TypeError`` is raised.

    Parameters
    ----------
    dtype : data-type, optional
        Array data-type.
    ndim : int, optional
        Number of array dimensions.
    shape : tuple of ints, optional
        Array shape.
    flags : str or tuple of str
        Array flags; may be one or more of:

          - C_CONTIGUOUS / C / CONTIGUOUS
          - F_CONTIGUOUS / F / FORTRAN
          - OWNDATA / O
          - WRITEABLE / W
          - ALIGNED / A
          - WRITEBACKIFCOPY / X
          - UPDATEIFCOPY / U

    Returns
    -------
    klass : ndpointer type object
        A type object, which is an ``_ndtpr`` instance containing
        dtype, ndim, shape and flags information.

    Raises
    ------
    TypeError
        If a given array does not satisfy the specified restrictions.

    Examples
    --------
    >>> clib.somefunc.argtypes = [np.ctypeslib.ndpointer(dtype=np.float64,
    ...                                                  ndim=1,
    ...                                                  flags='C_CONTIGUOUS')]
    ... #doctest: +SKIP
    >>> clib.somefunc(np.array([1, 2, 3], dtype=np.float64))
    ... #doctest: +SKIP

    """

    # normalize dtype to an Optional[dtype]
    if dtype is not None:
        dtype = _dtype(dtype)

    # normalize flags to an Optional[int]