CODEWITHSUNDEEP
pythonarraysreshape
ferrelwill
ferrelwill

Reputation: 821

ValueError: cannot reshape array of size 7267 into shape (302,24,1)

I am reshaping a 1D array into 3D using the following. It works fine but it throws an error when x is 7267. I understand that it is not possible to slice an odd number as an int without losing some values. Would appreciate any solution to this.

code

x = 7248
y= 24

A = np.arange(x)
A.reshape(int(x/y),y,1).transpose()

output

array([[[   0,   24,   48, ..., 7176, 7200, 7224],
        [   1,   25,   49, ..., 7177, 7201, 7225],
        [   2,   26,   50, ..., 7178, 7202, 7226],
        ...,
        [  21,   45,   69, ..., 7197, 7221, 7245],
        [  22,   46,   70, ..., 7198, 7222, 7246],
        [  23,   47,   71, ..., 7199, 7223, 7247]]])

Upvotes: 1

Views: 2109

Answers (1)

L.Grozinger
L.Grozinger

Reputation: 2398

The key is, of course, that in order to reshape A in this way, it must be that len(A) % y == 0. How you do this depends on how you would like to handle the extra values.

If you are fine to discard some values in order to shape the array, then you can simply truncate A so that len(A) % y == 0.

E.g.

x = 7267
y = 24

A = np.arange(x - x % y)
A.reshape(x // y, y, 1).transpose()

You may also truncate the array using slices.

E.g.

x = 7267
y = 24

A = np.arange(x)

A[:x - x % y].reshape(x // y, y, 1).transpose()

In the case where all the data must be retained, you can pad A with zeros (or some other value), so that len(A) % y == 0.

E.g.

x = 7267
y = 24

A = np.arange(x)
A = np.pad(A, (0, y - x % y), 'constant')
A = A.reshape(A.shape[0] // y, y, 1).transpose()

Upvotes: 1

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