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.

Your code returns a as all zeros. Are you looking for something like this? — Brenlla
– Brenlla, Commented Jul 20, 2018 at 11:25
@Brenlla My requirement is similar to what you provided, but that only applies to square matrix. — dianlujitao
– dianlujitao, Commented Jul 21, 2018 at 3:40

Brenlla · Accepted Answer · 2018-07-21 08:00:21Z

0

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]])

answered Jul 21, 2018 at 8:00

Brenlla

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1 Comment

dianlujitao Over a year ago

Thanks, works as expected, didn't realize arange should be on dim 1

Ersel Er · Accepted Answer · 2018-07-20 11:45:23Z

0

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 cols of a to an value:

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

answered Jul 20, 2018 at 11:45

Ersel Er

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