I'm trying to subclass numpy.complex64 in order to make use of the way numpy stores the data, (contiguous, alternating real and imaginary part) but use my own __add__, __sub__, ... routines.

My problem is that when I make a numpy.ndarray, setting dtype=mysubclass, I get a numpy.ndarray with dtype='numpy.complex64' in stead, which results in numpy not using my own functions for additions, subtractions and so on.

Example:

import numpy as np
class mysubclass(np.complex64):passa = mysubclass(1+1j)
A = np.empty(2, dtype=mysubclass)print type(a)
print repr(A)

Output:

<class '__main__.mysubclass'>
array([ -2.07782988e-20 +4.58546896e-41j,  -2.07782988e-20 +4.58546896e-41j], dtype=complex64)'

Does anyone know how to do this?

Thanks in advance - Soren

The NumPy type system is only designed to be extended from C, via the PyArray_RegisterDataType function. It may be possible to access this functionality from Python using ctypes but I wouldn't recommend it; better to write an extension in C or Cython, or subclass ndarray as @seberg describes.

There's a simple example dtype in the NumPy source tree: newdtype_example/floatint.c. If you're into Pyrex, reference.pyx in the pytables source may be worth a look.