Find nearest value X in ndarray in numpy, Python

Question

I have got a ndarray shaped into 2D matrix of values between 0 and 255. Let's name it img. Moreover, I have got value x between 0 and 255, for example 120. I want to create matrix dist_img which calculates distance to nearest value x or lower. So I would like to have something like this:

x = 120
img = [[100, 120, 130],
       [110, 140, 160],
       [130, 150, 170]]
some_function(img, x)

And get something like this

dist_img = [[0, 0, 1],
            [0, 1, 2],
            [1, 2, 3]]

If I can be peaky, I would love to have distance in taxicab geometry, but Euclidean geometry will work. Sorry for poor English, but I hope everything is understandable.

I am not sure if I understand the question, but I generate perlin noise with "noise" library, then I normalize it from [-1,1] to [0,255]. After that I say: "Everything under 120 is water". I want to find distance to nearest water — MS103
– MS103, Commented Mar 3, 2020 at 11:11
I mean how did you end up with each of the elements in dist_img? Why is dist_img[0,0] 0 and so on? — Divakar
– Divakar, Commented Mar 3, 2020 at 11:18
Oh, so if img[0,0] is lower of equal to x, then it is 0. If not, for each field I need to walk in matrix to get to nearest value <=x I add 1. I hope, it is more clear now — MS103
– MS103, Commented Mar 3, 2020 at 11:23

javidcf · Accepted Answer · 2020-03-03 11:19:36Z

2

Make a mask of the values that match the condition and then use scipy.ndimage.morphology.distance_transform_cdt to make the distance map:

import numpy as np
from scipy.ndimage.morphology import distance_transform_cdt

x = 120
img = np.array([[100, 120, 130],
                [110, 140, 160],
                [130, 150, 170]])
m = img <= x
d = distance_transform_cdt(~m, 'taxicab')
print(d)
# [[0 0 1]
#  [0 1 2]
#  [1 2 3]]

answered Mar 3, 2020 at 11:19

javidcf

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1 Comment

MS103 Over a year ago

That's it! Thank you!

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