Create a numpy array from a ctypes array or a ctypes POINTER. The numpy array shares the memory with the ctypes object.
The size parameter must be given if converting from a ctypes POINTER. The size parameter is ignored if converting from a ctypes array
Create and return a ctypes object from a numpy array. Actually anything that exposes the __array_interface__ is accepted.
ctypes_load_library is deprecated, use load_library instead!
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 
 ndim : int, optional 
 shape : tuple of ints, optional 
 flags : str or tuple of str 
  | 
|---|---|
| Returns : | klass : ndpointer type object 
  | 
| Raises : | TypeError : 
  | 
Examples
>>> clib.somefunc.argtypes = [np.ctypeslib.ndpointer(dtype=np.float64,
...                                                  ndim=1,
...                                                  flags='C_CONTIGUOUS')]
... 
>>> clib.somefunc(np.array([1, 2, 3], dtype=np.float64))
...