[pymvpa] Custom distance metrics for SOM

[Sheen, David A.]

Hi,

I'm trying to use a custom distance metric for the self-organizing map 
in PyMVPA, and I'm having some difficulty. The documentation says that I 
can define the SOM as follows:

som = SimpleSOMMapper(size, niter, 
learning_rate=something,distance_metric=d)

where d is a function such that distance_between_x_and_y = d(x,y), and 
presumably x and y are vectors and d returns a scalar.

However, the SOM package appears to pass a matrix to distance_metric, 
and it's unclear what the expected inputs and outputs from 
distance_metric are supposed to be in this case.

For instance the following code:

def jeffries(x,y):
     entropy_xy = sp.stats.entropy(x,y)
     entropy_yx = sp.stats.entropy(y,x)
     jeffries_entropy = (entropy_xy+entropy_yx)/2.0
     return jeffries_entropy
som = SimpleSOMMapper(size, niter, 
learning_rate=something,distance_metric=jeffries)

produces this error:

PyMVPA/mvpa2/mappers/som.pyc in _train(self, samples)
     159                     np.hstack((
     160                         # upper left
--> 161                         k[self._dqdshape[0]:0:-1, 
self._dqdshape[1]:0:-1],
     162                         # upper right
     163                         k[self._dqdshape[0]:0:-1, 
:self._dqdshape[3]])),

IndexError: too many indices for array

Does anyone have any experience with this issue?

Dave