Can't reshape numpy array

Question

I have a function that is supposed to take a 1D array of integers and shapes it into a 2D array of 1x3 arrays. It then is supposed to take each 1x3 array and shift it into a 3x1 array. The result is supposed to be a 2D array of 3x1 arrays. Here is my function

def RGBtoLMS(rgbValues, rgbLength): #Method to convert from RGB to LMS
    print rgbValues
    lmsValues = rgbValues.reshape(-1, 3)
    print lmsValues
    for i in xrange(len(lmsValues)):
        lmsValues[i] = lmsValues[i].reshape(3, 1)

    return lmsValues

The issue rises when I try to change the 1x3 arrays to 3x1 arrays. I get the following output assuming rgbValues = [14, 25, 19, 24, 25, 28, 58, 87, 43]

[14 25 19 ..., 58 87 43]
[[14 25 19]
 [24, 25, 28]
 [58 87 43]]

ValueError [on line lmsValues[i] = lmsValues[i].reshape(3, 1)]: could not broadcast input array from shape (3,1) into shape (3)

How can I avoid this error?

Answer 1

As mentioned in the comments, you are really always just modifying one array with different shapes. It doesn't really make sense in numpy to say that you have a 2d array of 1 x 3 arrays. What that really is is actually a n x 3 array.

We start with a 1d array of length 3*n (I've added three numbers to your example to make the difference between a 3 x n and n x 3 array clear):

>>> import numpy as np

>>> rgbValues = np.array([14, 25, 19, 24, 25, 28, 58, 87, 43, 1, 2, 3])
>>> rgbValues.shape
(12,)

And reshape it to be n x 3:

>>> lmsValues = rgbValues.reshape(-1, 3)
>>> lmsValues
array([[14, 25, 19],
       [24, 25, 28],
       [58, 87, 43],
       [ 1,  2,  3]])
>>> lmsValues.shape
(4, 3)

If you want each element to be shaped 3 x 1, maybe you just want to transpose the array. This switches rows and columns, so the shape is 3 x n

>>> lmsValues.T
array([[14, 24, 58,  1],
       [25, 25, 87,  2],
       [19, 28, 43,  3]])

>>> lmsValues.T.shape
(3, 4)

>>> lmsValues.T[0]
array([14, 24, 58,  1])

>>> lmsValues.T[0].shape
(4,)

If you truly want each element in lmsValues to be a 1 x 3 array, you can do that, but then it has to be a 3d array with shape n x 1 x 3:

>>> lmsValues = rgbValues.reshape(-1, 1, 3)
>>> lmsValues
array([[[14, 25, 19]],

       [[24, 25, 28]],

       [[58, 87, 43]],

       [[ 1,  2,  3]]])

>>> lmsValues.shape
(4, 1, 3)

>>> lmsValues[0]
array([[14, 25, 19]])

>>> lmsValues[0].shape
(1, 3)