I have a problem with printing a column in a numpy 3D Matrix. Here is a simplified version of the problem:
import numpy as np
Matrix = np.zeros(((10,9,3))) # Creates a 10 x 9 x 3 3D matrix
Matrix[2][2][6] = 578
# I want to print Matrix[2][x][6] for x in range(9)
# the purpose of this is that I want to get all the Values in Matrix[2][x][6]
Much appreciated if you guys can help me out. Thanks in advance.
Slicing would work:
a = np.zeros((10, 9, 3))
a[6, 2, 2] = 578
for x in a[6, :, 2]:
print(x)
Output:
0.0
0.0
578.0
0.0
0.0
0.0
0.0
0.0
0.0
Not sure if Numpy supports this, but you can do it with normal lists this way:
If you have three lists a = [1,2,3], b = [4,5,6], and c = [7,8,9], you can get the second dimension [2,5,8] for example by doing
list(zip(a,b,c))[1]
EDIT:
Turns out this is pretty simple in Numpy. According to this thread you can just do:
Matrix[:,1]
No sure if this is what you want. Here is demo:
In [1]: x = np.random.randint(0, 20, size=(4, 5, 3))
In [2]: x
Out[2]:
array([[[ 5, 13, 9],
[ 8, 16, 5],
[15, 17, 1],
[ 6, 14, 5],
[11, 13, 9]],
[[ 5, 8, 0],
[ 8, 15, 5],
[ 9, 2, 13],
[18, 4, 14],
[ 8, 3, 13]],
[[ 3, 7, 4],
[15, 11, 6],
[ 7, 8, 14],
[12, 8, 18],
[ 4, 2, 8]],
[[10, 1, 16],
[ 5, 2, 1],
[11, 12, 13],
[11, 9, 1],
[14, 5, 1]]])
In [4]: x[:, 2, :]
Out[4]:
array([[15, 17, 1],
[ 9, 2, 13],
[ 7, 8, 14],
[11, 12, 13]])
Matrix[2][2][6] = 578gives anIndexErrorbecause your last dimension is not big enough for the index6. This would workMatrix[6][2][2] = 578