I want to generate a twodimensional array in Python and I would like to iterate through each element and take an average. An element i should be averaged using the 8 surrounding array elements (including element i).
I generated the twodimensional array with a frame of zeros using Forming a frame of zeros around a matrix in python.
A = np.array([[1,2,3],[4,5,6],[7,8,9]])
x,y = A.shape
n = 1
B = np.zeros((x+2*n,y+2*n),dtype=int)
B[n:x+n, n:y+n] = A
print(B)
What is the easiest way to take the average?
What you want is a 2D convolution, use scipy.signal.convolve2d with numpy.ones to get the sum:
from scipy.signal import convolve2d
out = convolve2d(B, np.ones((3, 3), dtype='int'), mode='same')
Output:
array([[ 1, 3, 6, 5, 3],
[ 5, 12, 21, 16, 9],
[12, 27, 45, 33, 18],
[11, 24, 39, 28, 15],
[ 7, 15, 24, 17, 9]])
If you want the small matrix, no need to pad with zeros:
convolve2d(A, np.ones((3, 3), dtype='int'), mode='same')
# array([[12, 21, 16],
# [27, 45, 33],
# [24, 39, 28]])
For the average, repeat the same operation with an array od ones and divide:
kernel = np.ones((3, 3), dtype='int')
out = (convolve2d(A, kernel, mode='same')
/convolve2d(np.ones_like(A), kernel, mode='same')
)
output:
array([[3. , 3.5, 4. ],
[4.5, 5. , 5.5],
[6. , 6.5, 7. ]])