How to select elements in numpy array with given starting point indices

Question

For example, I have a matrix like this:

In [2]: a = np.arange(12).reshape(3, 4)

In [3]: a
Out[3]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])

and a starting point index array:

In [4]: idx = np.array([1, 2, 0])

In [5]: idx
Out[5]: array([1, 2, 0])

Are there any vectorized ways to do such things:

for i in range(3):
    # The following are some usecases
    a[i, idx[i]:] = 0
    a[i, idx[i]-1:] = 0
    a[i, :idx[i]] = 0
    a[i, idx[i]:idx[i]+2] = 0

Edit: expected output:

array([[ 0,  x,  x,  x],
       [ 4,  5,  x,  x],
       [ x,  x,  x,  x]])

x is placeholder indicating what I'd like to select.

Answer 1

An expected, exact, output is not provided. So, I think the followings may help you in general.

>>> a = np.arange(12).reshape(3, 4)
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
>>> row = np.array([0, 1, 2])
>>> col = np.array([1, 2, 0])
>>> a[row, col]
array([1, 6, 8])

You can set the row and col s of a to an value:

>>> a[row, col] = 0
>>> a
array([[ 0,  0,  2,  3],
       [ 4,  5,  0,  7],
       [ 0,  9, 10, 11]])

Answer 2

This aproach works for rectangular matrices too. Create a boolean mask trough broadcasting:

a = np.arange(12).reshape(3, 4)
idx = np.array([1, 2, 0])
mask=np.arange(a.shape[1]) >= idx[:,None]
mask
#array([[False,  True,  True,  True],
#       [False, False,  True,  True],
#       [ True,  True,  True,  True]], dtype=bool)

Make your placeholder -1 , for example, and set the values of a where mask is true equal to that placeholder:

x = -1
a[mask] = x
a
#array([[ 0, -1, -1, -1],
#       [ 4,  5, -1, -1],
#      [-1, -1, -1, -1]])