How can I find distances to the chosen point from all the other points ( Euclidean distance ) ?

4 views (last 30 days)
Hi all, Let's assume that I have a huge matrix and say that I pick a point from that matrix. Is there a way of calculating euclidean distance from all the other points of that matrix and store them separately in the matrix of the same dimension where the number in each entry of a matrix is a number that represents the Euclidean distance to the pre-chosen point ?? Thank you

Accepted Answer

Image Analyst
Image Analyst on 27 Jun 2017
Assuming you mean in spatial space (which ignores the actual matrix values and just looks at their location), and not in intensity or value space (which compares differences in intensity or value of the matrix to some other intensity or value), then you can do:
% Setup
rows = 4; % For example
columns = 5;
% x and y can be column and row indexes, respectively, but they don't have to be.
x = 1; % For example
y = 1;
% Now compute the distances from every element to (x, y).
[XGrid, YGrid] = meshgrid(1:columns, 1:rows)
distances = sqrt((x - XGrid) .^ 2 + (y - YGrid) .^ 2)
  7 Comments
Image Analyst
Image Analyst on 28 Jun 2017
It looks like that's what Jan's code does. You can have his X be any number of rows and columns. And Point would be X(someRowIndex, someColumnIndex).
Damian Wierzbicki
Damian Wierzbicki on 28 Jun 2017
B = zeros (rows , columns );
for c = 1:columns
for r = 1:rows
if ref_matrix ( r , c ) == 0
B = 0;
elseif ref_matrix ( r , c ) ~= 0
B = ( r , c ) = distances ( r , c );
end
end
end
% found a mistake, this a working version.

Sign in to comment.

More Answers (1)

Jan
Jan on 26 Jun 2017
Edited: Jan on 26 Jun 2017
Hm, yes. Why not?
X = rand(1000, 3);
Pick = 17;
Point = X(Pick, :);
Dist = sqrt(sum((X - Point) .^ 2, 2)); % >= R2016b
% Dist = sqrt(sum(bsxfun(@minus, X, Point) .^ 2, 2)); % < R2016b
If this is time critical: FEX: DNorm2

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!