[FIXED] advanced indexing using numpy

Issue

I'm trying to use advanced indexing but I cannot get it to work with this simple array

arr = np.array([[[ 1, 10, 100,1000],[ 2, 20, 200,2000]],[[ 3, 30, 300,3000],[ 4,40,400,4000]],[[5, 50, 500,5000],[6, 60,600,6000]]])

d1=np.array([0])
d2=np.array([0,1])
d3=np.array([0,1,2])  

arr[d1,d2,d3]

IndexError: shape mismatch: indexing arrays could not be broadcast together with shapes (1,) (2,) (3,)

and

arr[d1[:,np.newaxis],d2[np.newaxis,:],d3]

IndexError: shape mismatch: indexing arrays could not be broadcast together with shapes (1,1) (1,2) (3,) 

Expected output:

array([[[  1,  10, 100],
        [  2,  20, 200]]])

Solution

You can use np.ix_ to combine several one-dimensional index arrays of different lengths to index a multidimensional array. For example:

arr[np.ix_(d1,d2,d3)]

To add more context, np.ix_ returns a tuple of ndimensional arrays. The same can be achieved "by hand" by adding np.newaxis for appropriate dimensions:

xs, ys, zs = np.ix_(d1,d2,d3)

# xs.shape == (1, 1, 1) == (len(d1), 1,       1      )
# ys.shape == (1, 2, 1) == (1,       len(d2), 1      )
# zs.shape == (1, 1, 3) == (1,       1,       len(d3))

result_ix = arr[xs, ys, zs]

# using newaxis:

result_newaxis = arr[
  d1[:,          np.newaxis, np.newaxis],
  d2[np.newaxis, :,          np.newaxis],
  d3[np.newaxis, np.newaxis, :],
]

assert (result_ix == result_newaxis).all()

Answered By - hilberts_drinking_problem