Multiple Multiple Buffering

Question

I'm having trouble editing values ​​in a numpy array

import numpy as np foo = np.ones(10,10,2) foo[row_criteria, col_criteria, 0] += 5 foo[row_criteria,:,0][:,col_criteria] += 5 

row_criteria and col_criteria are logical arrays (1D). In the first case, I get

"form mismatch: objects cannot be transferred to one form" error

In the second case, + = 5 is not applied at all. When i do

 foo[row_criteria,:,0][:,col_criteria] + 5 

I get a modified return value, but changing the value in place does not work ...

Can someone explain how to fix this? Thanks!

Answer 1

Do you want to:

 foo[np.ix_(row_criteria, col_criteria, [0])] += 5 

To understand how this works, take this example:

 import numpy as np A = np.arange(25).reshape([5, 5]) print A[[0, 2, 4], [0, 2, 4]] # [0, 12, 24] # The above example gives the the elements A[0, 0], A[2, 2], A[4, 4] # But what if I want the "outer product?" ie for [[0, 2, 4], [1, 3]] i want # A[0, 1], A[0, 3], A[2, 1], A[2, 3], A[4, 1], A[4, 3] print A[np.ix_([0, 2, 4], [1, 3])] # [[ 1 3] # [11 13] # [21 23]] 

The same thing works with boolean indexing. In addition, np.ix_ does nothing really amazing, it just changes its arguments so that they can be broadcast against each other:

 i, j = np.ix_([0, 2, 4], [1, 3]) print i.shape # (3, 1) print j.shape # (1, 2)