Numpy array assignment by boolean indices array-CodePudding

I have a very large array, but I'll use a smaller one to explain.

Given source array X

X = [ [1,1,1,1],
      [2,2,2,2],
      [3,3,3,3]]

A target array with the same size Y

Y = [ [-1,-1,-1,-1],
      [-2,-2,-2,-2],
      [-3,-3,-3,-3]]

And an assigment array IDX:

IDX = [ [1,0,0,0],
        [0,0,1,0],
        [0,1,0,1]]

I want to assign Y to X by IDX - Only assign where IDX==1 In this case, something like:

X[IDX] = Y[IDX]

will result in:

X = [ [-1,1,1,1],
      [2,2,-2,2],
      [3,-3,3,-3]]

How can this be done efficiently (not a for-loop) in numpy/pandas? Thx

CodePudding user response：

If IDX is a NumPy array of Boolean type, and X and Y are NumPy arrays then your intuition works:

X = np.array(X)
Y = np.array(Y)
IDX = np.array(IDX).astype(bool)

X[IDX] = Y[IDX]

This changes X in place.

If you don't want to do all this type casting, or don't want to overwrite X, then np.where() does what you want in one go:

np.where(IDX==1, Y, X)