Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
In numpy I have a 2d array of 1s and 0s. I need to calculate a new array (same dimensions) where each element contains the distance to the nearest 1 from the corresponding point in the mask array.
e.g.
a=np.array(
[[1,1,0],
[1,0,0],
[1,0,0]])
I need b to look like this:
array([[0,0,1],
[0,1,1.41],
[0,1,2]])
PS. I’ll be doing this over very large arrays, so the more efficient the better!
Thanks!
You’re looking for the equivalent of MATLAB’s
bwdist; check out this SO question for more details. The short answer is to usescipy.ndimage.morphology.distance_transform_edt.