Although there are many instances of the question: "What is the numpy alternative to nested for loops", I was unable to fins a suitable answer for my case. Here it goes: I have a 3D numpy array with "0" background and other integers as foreground. I would like to find and store the foreground voxels […]

- Tags -102], -23, -32, -38, -41, -48, -a:X-a] neighborMask = x*x + y*y + z*z 0 mask = np.logical_and(neighborMask, -b:Y-b, .53, .97], (64, [ "103", [ 55, [ 75, [ 82, [[ 87, [109, [56, 0, 0Z"/>, 100, 101, 104, 106]]], 107, 110, 15, 16, 17, 18, 19, 20, 21, 22, 25, 255, 26, 27, 28, 29, 33, 34, 35, 37, 4, 4]) ################Loading Area search rad = 3 a, 40, 45], 46, 47, 49, 50, 51, 52, 54, 57, 58, 59, 60, 61, 62, 63, 65, 66, 67, 68, 69, 70], 72, 73, 74, 76, 77, 78, 79, 80, 81, 83, 84), 85, 86, 88, 89, 90, 92, 93, 94, 95, 96, 98, 99], Although there are many instances of the question: "What is the numpy alternative to nested for loops", B, c = RN x, I was unable to fins a suitable answer for my case. Here it goes: I have a 3D numpy array with "0" background and other integers as foregrou, j, j-1, j=1, k-1] == 0: imtemp[i, k] == 0 or imtemp[i, k] == 0 or imtemp[i-1, k]=-2 elif imtemp[i+1, k]=-2 LA = np.argwhere(imtemp==-2), k]==-1: if i==(Z-1): imtemp[i, k+1] == 0 or imtemp[i, noNodeMask) imtemp = im.copy() imtemp[mask] = -1 for i in range (Z): for j in range (Y-1): for k in range (X-1): if, X]=im.shape RN = np.array([3, y, z = np.ogrid[-c:Z-c