I have a large matrix that represents.. say a Rubik's cube.
>>cube
>>[[-1, -1, -1, 1, 2, 3, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 4, 5, 6, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 7, 8, 9, -1, -1, -1, -1, -1, -1],
[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 8, 1, 8],
[ 4, 5, 6, 0, 7, 7, 6, 9, 6, 8, 1, 0],
[ 7, 8, 9, 6, 9, 7, 6, 6, 9, 0, 1, 7],
[-1, -1, -1, 1, 1, 0, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 8, 8, 1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 8, 0, 1, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 7, 1, 0, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 0, 1, 8, -1, -1, -1, -1, -1, -1],
[-1, -1, -1, 8, 1, 8, -1, -1, -1, -1, -1, -1]])
I have sliced it into parts that represent the faces.
top_f = cube[0:3,3:6]
botm_f = cube[6:9,3:6]
back_f = cube[3:6,9:12]
front_f = cube[3:6,3:6]
left_f = cube[3:6,0:3]
right_f = cube[3:6,6:9]
I want to now assign a modified matrix to the left face.
left_f = numpyp.rot90(left_f, k=3)
But this does not change the values in the parent matrix cube
.
I understand this is because the newly generated matrix is being assigned to the variable left_f
and so the reference to the sub-slice cube[3:6,0:3]
is lost.
I could just resort to replacing it directly.
cube[3:6,0:3] = numpyp.rot90(left_f, k=3)
But that wouldn't be very readable. How do I assign a new matrix to a named slice of another matrix in a pythonic way?
You can assign your slices to a variable:
left_face = slice(3, 6), slice(0, 3)
cube[left_face] = np.rot90(cube[left_face], k=3)
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