How can I calculate the distance between a set of points and a single point within a matrix?

Hi,

I need to calculate the euclidean distance between a set of points on a matrix, and one other point in the same matrix. I and J are 9x1 vectors, where I represents the "x" and J represents "y" coordinates of a set of 9 points. "rows" and "columns" are the x and y coordinates of a single point. I have the following code:

for g=1:length(I)
   for f=2

       I(g)=x2

       J(f)=y2

       distance_between_points = sqrt((x2 - rows)^2 + (y2 - columns)^2);

    end    
end

I obtain a single value from this, where I should be getting a distance value between each point represented by I,J,and the point represent by (rows, columns). I've tried pdist2 and I get ~30 values which makes a little less sense. Is there a way to do this?

Answer 1

[Image Analyst]

If x and y are the vectors of all the coordinates, and xp and xp are the coordinates of the single point, then you can find all the distances between (xp, yp) and all the other points doing this:

distances = sqrt((x-xp).^2 + (y-yp).^2);

No for loop(s) needed.

By the way, don't confuse x with rows and y with columns like you did in your code. x is columns, not rows. y is rows, not columns. Arrays are indexed m(y, x) and NOT as m(x,y)!

[Stephanie Diaz]

got it, thanks!

[fatemeh zare]

:)

Answer 2

[Walter Roberson]

Without a loop:

distance_between_points = sqrt((I - columns).^2 + (J - rows).^2)

Notice that columns is an x coordinate, not a y coordinate

[Stephanie Diaz]

thank you!