I want to do divide an 8*8 array in to 4 segments(each segment of 4*4 array) as shown below in step2. Then again divide each segment in to other small 4 subsegemnts(each subsegment of 2*2 array) and then find the mean of each subsegment and then find the stabbndard deviation of each segment using the 4 means of the 4 subsegments in it. So that finally I only have an array (2*2 array) ie with 1 standard deviation for 1 segment.
import numpy as np from skimage.util.shape import view_as_blocks arr=np.array([[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8]]) img= view_as_blocks(arr, block_shape=(4,4))
upto this I have tried but I was unable to go further in my requirement as I am completely new to python and numpy. Kindly, help me in achieve my requirement.
#step1-Array array([[1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8]]) #step2-segments array([[[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]], [[5, 6, 7, 8], [5, 6, 7, 8], [5, 6, 7, 8], [5, 6, 7, 8]]], [[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]], [[5, 6, 7, 8], [5, 6, 7, 8], [5, 6, 7, 8], [5, 6, 7, 8]]]]) **more steps to go to get final output**
Expected Output
([[1.0, 1.0], [1.0, 1.0]])
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Answer
It can be done using a function view_as_blocks
of skimage.util.shape
.