从现有的2d数组中构造numpy的3d数组

Question

During preparing data for NumPy calculate. I am curious about way to construct:

myarray.shape => (2,18,18)

from:

d1.shape => (18,18)
d2.shape => (18,18)

I try to use NumPy command:

hstack([[d1],[d2]])

but it looks not work!

Answer 1

Just doing d3 = array([d1,d2]) seems to work for me:

>>> from numpy import array
>>> # ... create d1 and d2 ...
>>> d1.shape
(18,18)
>>> d2.shape
(18,18)
>>> d3 = array([d1, d2])
>>> d3.shape
(2, 18, 18)

Answer 2

hstack and vstack do no change the number of dimensions of the arrays: they merely put them "side by side". Thus, combining 2-dimensional arrays creates a new 2-dimensional array (not a 3D one!).

You can do what Daniel suggested (directly use numpy.array([d1, d2]) ).

You can alternatively convert your arrays to 3D arrays before stacking them, by adding a new dimension to each array:

d3 = numpy.vstack([ d1[newaxis,...], d2[newaxis,...] ])  # shape = (2, 18, 18)

In fact, d1[newaxis,...].shape == (1, 18, 18) , and you can stack both 3D arrays directly and get the new 3D array ( d3 ) that you wanted.

Answer 3

arr3=np.dstack([arr1, arr2])

arr1，arr2是2d数组shape (256,256) ， shape (256,256) ： shape(256,256,2)