[Numpy-discussion] numpy ndarray questions

[Sturla Molden]

On 1/27/2009 1:26 AM, Jochen wrote:

> a = fftw3.AlignedArray(1024,complex)
> 
> a = a+1

= used this way is not assignment, it is name binding.

It is easy to use function's like fftw_malloc with NumPy:


import ctypes
import numpy

fftw_malloc = ctypes.cdll.fftw.fftw_malloc
fftw_malloc.argtypes = [ctypes.c_ulong,]
fftw_malloc.restype = ctypes.c_ulong

def aligned_array(N, dtype):
     d = dtype()
     address = fftw_malloc(N * d.nbytes) # restype = ctypes.c_ulong
     if (address = 0): raise MemoryError, 'fftw_malloc returned NULL'
     class Dummy(object): pass
     d = Dummy()
     d.__array_interface__ = {
         'data' = (address, False),
         'typestr' : dtype.str,
         'descr' : dtype.descr,
         'shape' : shape,
         'strides' : strides,
         'version' : 3
     }
     return numpy.asarray(d)


If you have to check for a particular alignment before calling fftw, 
that is trivial as well:


def is_aligned(array, boundary):
     address = array.__array_interface__['data'][0]
     return not(address % boundary)




> there a way that I get a different object type?  Or even better is there
> a way to prevent operations like a=a+1 or make them automatically
> in-place operations?

a = a + 1 # rebinds the name 'a' to another array

a[:] = a + 1 # fills a with the result of a + 1


This has to do with Python syntax, not NumPy per se. You cannot overload 
the behaviour of Python's name binding operator (=).


Sturla Molden