Conjugate transpose operator ".H" in numpy

You can subclass the ndarray object like:

from numpy import ndarray

class myarray(ndarray):    
    @property
    def H(self):
        return self.conj().T

such that:

a = np.random.rand(3, 3).view(myarray)
a.H

will give you the desired behavior.

Edit:

As suggested by @slek120, you can force to transpose only the last 2 axes with:

self.swapaxes(-2, -1).conj()

instead of self.conj().T.

In general, the difficulty in this problem is that Numpy is a C-extension, which cannot be monkey patched...or can it? The forbiddenfruit module allows one to do this, although it feels a little like playing with knives.

So here is what I've done:

1. Install the very simple forbiddenfruit package

2. Determine the user customization directory:

   import site
   print site.getusersitepackages()
   

3. In that directory, edit usercustomize.py to include the following:

   from forbiddenfruit import curse
   from numpy import ndarray
   from numpy.linalg import inv
   curse(ndarray,'H',property(fget=lambda A: A.conj().T))
   curse(ndarray,'I',property(fget=lambda A: inv(A)))
   

4. Test it:

   python -c python -c "import numpy as np; A = np.array([[1,1j]]);  print A; print A.H"
   

   Results in:

   [[ 1.+0.j  0.+1.j]]
   [[ 1.-0.j]
    [ 0.-1.j]]