How to length the last dimension of a numpy array and fill it up with another array?-CodePudding

I have a numpy array of shape (5, 4, 3) and another numpy array of shape (4,) and what I want to do is expand the last dimension of the first array (5, 4, 3) -> (5, 4, 4) and then broadcast the other array with shape (4,) such that it fills up the new array cells respectively.

Example:

np.ones((5,4,3))
array([[[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]],

       [[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]],

       [[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]],

       [[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]],

       [[1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.],
        [1., 1., 1.]]])

becomes

array([[[1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.]],

       [[1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.]],

       [[1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.]],

       [[1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.]],

       [[1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.],
        [1., 1., 1., 0.]]])

And then I have another array

array([2., 3., 4., 5.])

which I somehow broadcast with the first one to fill the zeros:

array([[[1., 1., 1., 2.],
        [1., 1., 1., 3.],
        [1., 1., 1., 4.],
        [1., 1., 1., 5.]],

       [[1., 1., 1., 2.],
        [1., 1., 1., 3.],
        [1., 1., 1., 4.],
        [1., 1., 1., 5.]],

       [[1., 1., 1., 2.],
        [1., 1., 1., 3.],
        [1., 1., 1., 4.],
        [1., 1., 1., 5.]],

       [[1., 1., 1., 2.],
        [1., 1., 1., 3.],
        [1., 1., 1., 4.],
        [1., 1., 1., 5.]],

       [[1., 1., 1., 2.],
        [1., 1., 1., 3.],
        [1., 1., 1., 4.],
        [1., 1., 1., 5.]]])

How can I accomplish this?

CodePudding user response：

You can use numpy.append :

A=np.ones((5,4,3))
AA=np.zeros((5,4,1))
B=np.array([2., 3., 4., 5.])
C=np.append(A,AA, axis=2)
for i in range(np.shape(C)[0]):
    for j in range(np.shape(C)[1]):
            C[i,j,-1]=B[j]
print(C)

> 
[[[1. 1. 1. 2.]
  [1. 1. 1. 3.]
  [1. 1. 1. 4.]
  [1. 1. 1. 5.]]

 [[1. 1. 1. 2.]
  [1. 1. 1. 3.]
  [1. 1. 1. 4.]
  [1. 1. 1. 5.]]

 [[1. 1. 1. 2.]
  [1. 1. 1. 3.]
  [1. 1. 1. 4.]
  [1. 1. 1. 5.]]

 [[1. 1. 1. 2.]
  [1. 1. 1. 3.]
  [1. 1. 1. 4.]
  [1. 1. 1. 5.]]

 [[1. 1. 1. 2.]
  [1. 1. 1. 3.]
  [1. 1. 1. 4.]
  [1. 1. 1. 5.]]]

CodePudding user response：

You can use numpy.c_ and numpy.tile:

A = np.ones((5,4,3), dtype='int')
B = np.array([2, 3, 4, 5])

np.c_[A, np.tile(B[:,None], (A.shape[0], 1, 1))]

output:

array([[[1, 1, 1, 2],
        [1, 1, 1, 3],
        [1, 1, 1, 4],
        [1, 1, 1, 5]],

       [[1, 1, 1, 2],
        [1, 1, 1, 3],
        [1, 1, 1, 4],
        [1, 1, 1, 5]],

       [[1, 1, 1, 2],
        [1, 1, 1, 3],
        [1, 1, 1, 4],
        [1, 1, 1, 5]],

       [[1, 1, 1, 2],
        [1, 1, 1, 3],
        [1, 1, 1, 4],
        [1, 1, 1, 5]],

       [[1, 1, 1, 2],
        [1, 1, 1, 3],
        [1, 1, 1, 4],
        [1, 1, 1, 5]]])

How it works:

# reshape B to add one dimension
>>> B[:, None]
array([[2],
       [3],
       [4],
       [5]])

# tile to match A's first dimension
>>> np.tile(B[:,None], (A.shape[0], 1, 1))
array([[[2],
        [3],
        [4],
        [5]],

       [[2],
        [3],
        [4],
        [5]],

       [[2],
        [3],
        [4],
        [5]],

       [[2],
        [3],
        [4],
        [5]],

       [[2],
        [3],
        [4],
        [5]]])