Issue
I have an nd array, for example this:
x = np.array([[1,2,3],[4,5,6]])
I would like to double the size of the last dimension, and insert zeroes between the elements to fill the space. The result should look like this:
[[1,0,2,0,3,0],[4,0,5,0,6,0]]
I tried to solve it using expand_dims
and pad
. But the pad
function inserts zeroes not just after each value in the last dimension. The shape of it's result is (3, 4, 2)
, but it should be (2,3,2)
y = np.expand_dims(x,-1)
z = np.pad(y, (0,1), 'constant', constant_values=0)
res = np.reshape(z,[-1,2*3]
Result of my code:
array([[1, 0, 2, 0, 3, 0],
[0, 0, 4, 0, 5, 0],
[6, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0]])
How is it possible with pad
to insert zeroes in the last dimension after each element? Or is there any better way to solve the problem?
Solution
Simply initialize output array and assign with slicing
-
m,n = x.shape
out = np.zeros((m,2*n),dtype=x.dtype)
out[:,::2] = x
Alternatively with stacking -
np.dstack((x,np.zeros_like(x))).reshape(x.shape[0],-1)
Answered By - Divakar
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