[FIXED] numpy, "cleaning" an index and value array

Issue

I have an index array, and an associated value array.

delta = np.array([0,3,4,1,1,4,4,5,7,10], dtype = int)
theta = np.random.normal(size = (12, 5))

I want to "clean" the index array such indices with no presence are dropped, and higher indices are moved down to take their place. In this case, the result will be:

delta == np.array([0,2,3,1,1,3,3,4,5,6], dtype = int)
theta == theta[np.array([0,1,3,4,5,7,10, 2,6,8,9,11], dtype = int)]

and the associated entries are moved up in the theta array such that their indices match the new indices in the delta vector. How do I go about this?

Solution

Let's ask unique for all of the optional values.

In [799]: np.unique(x,return_index=True,return_inverse=True, return_counts=True)
Out[799]: 
(array([ 0,  1,  3,  4,  5,  7, 10]),
 array([0, 3, 1, 2, 7, 8, 9]),
 array([0, 2, 3, 1, 1, 3, 3, 4, 5, 6]),
 array([1, 2, 1, 3, 1, 1, 1]))

Looks like the 'inverse' is what you want.

Review np.unique docs for more details.

Answered By - hpaulj