I have an array that is size (214, 144). I need it to be (214,144,1) is there a way to do this easily in Python? Basically the dimensions are supposed to be (Days, Times, Stations). Since I only have 1 station's data that dimension would be a 1. However if I could also make the code flexible enough work for say 2 stations that would be great (e.g. changing the dimension size from (428,288) to (214,144,2)) that would be great!
2 Answers
You could use reshape:
>>> a = numpy.array([[1,2,3,4,5,6],[7,8,9,10,11,12]])
>>> a.shape
(2, 6)
>>> a.reshape((2, 6, 1))
array([[[ 1],
[ 2],
[ 3],
[ 4],
[ 5],
[ 6]],
[[ 7],
[ 8],
[ 9],
[10],
[11],
[12]]])
>>> _.shape
(2, 6, 1)
Besides changing the shape from (x, y) to (x, y, 1), you could use (x, y/n, n) as well, but you may want to specify the column order depending on the input:
>>> a.reshape((2, 3, 2))
array([[[ 1, 2],
[ 3, 4],
[ 5, 6]],
[[ 7, 8],
[ 9, 10],
[11, 12]]])
>>> a.reshape((2, 3, 2), order='F')
array([[[ 1, 4],
[ 2, 5],
[ 3, 6]],
[[ 7, 10],
[ 8, 11],
[ 9, 12]]])
Comments
1) To add a dimension to an array a of arbitrary dimensionality:
b = numpy.reshape (a, list (numpy.shape (a)) + [1])
Explanation:
You get the shape of a, turn it into a list, concatenate 1 to that list, and use that list as the new shape in a reshape operation.
2) To specify subdivisions of the dimensions, and have the size of the last dimension calculated automatically, use -1 for the size of the last dimension. e.g.:
b = numpy.reshape(a, [numpy.size(a,0)/2, numpy.size(a,1)/2, -1])
The shape of b in this case will be [214,144,4].
(obviously you could combine the two approaches if necessary):
b = numpy.reshape (a, numpy.append (numpy.array (numpy.shape (a))/2, -1))
answered Sep 10, 2016 at 17:18
Tasos Papastylianou
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1 Comment
hpaulj
np.expand_dims(a, -1) does this kind of reshape, adding a new axis at the end with the -1 parameter. No new functionality, but the newish np.stack uses it to concatenate arrays on any new axis.
(428, 288)to(214, 144, 2)doesn't make sense: you're halving the total number of elements there. Did you want something like(428, 144, 2)instead?