How to change array shapes in in numpy?

Question

If I create an array X = np.random.rand(D, 1) it has shape (3,1):

[[ 0.31215124]
 [ 0.84270715]
 [ 0.41846041]]

If I create my own array A = np.array([0,1,2]) then it has shape (1,3) and looks like

[0 1 2]

How can I force the shape (3, 1) on my array A?

Answer 1

You can assign a shape tuple directly to numpy.ndarray.shape.

A.shape = (3,1)

Answer 2

A=np.array([0,1,2])
A.shape=(3,1)

or

A=np.array([0,1,2]).reshape((3,1))  #reshape takes the tuple shape as input

Answer 3

The numpy module has a reshape function and the ndarray has a reshape method, either of these should work to create an array with the shape you want:

import numpy as np
A = np.reshape([1, 2, 3, 4], (4, 1))
# Now change the shape to (2, 2)
A = A.reshape(2, 2)

Numpy will check that the size of the array does not change, ie prod(old_shape) == prod(new_shape). Because of this relation, you're allowed to replace one of the values in shape with -1 and numpy will figure it out for you:

A = A.reshape([1, 2, 3, 4], (-1, 1))

Answer 4

You can set the shape directy i.e.

A.shape = (3L, 1L)

or you can use the resize function:

A.resize((3L, 1L))

or during creation with reshape

A = np.array([0,1,2]).reshape((3L, 1L))