Find closest values in an array of x and y coordinated compared to a given set of coordinates

Hello all,

I've got two vectors of coordinates

x = linspace(400000,500000,100) and

y = linspace(100000,200000,100)

*********

I've got the given coordinates of a point

x_coord= 406000 and y_coord = 170000 and I'd like to find the position/index of the BOTH vectors x and y that are CLOSER to the given coordinate point.

********

I need an index that would fulfill BOTH the nearest values of x and y and at the end I'd get only one index, not two different indices for vectors x and y.

I know that if I had just one vector, I could use the commands:

[c_x index_x] = min(abs(x_coord-x));

[c_y index_y] = min(abs(y_coord-y));

But I don't need that now.

**********

Any thoughts on that?

Answer 1

[Christina]

Actually I found the solution:

I created a table with the x and y coordinates:

The small code is:

*********

table[x y];

[d,p] = min((table(:,1)-x_coord).^2 + (table(:,2)-y_coord).^2);

**************

and p gives the index in 'table' matrix that meets the condition of getting the minimum distance between the point (x_coord,y_coord) and both x and y vectors

Answer 2

[dpb]

See

doc pdist2

[Christina]

Hello

I tried the 'pdist2' command, but when I typed

[D,I] = pdist2(abs(x-x_coord),abs(y-y_coord),distance,'Smallest',k) ;

I get the error that there are not enough input arguments.

Do you know what would be the solution to that?

[dpb]

Rows in {X,Y} to pdist2 are observations so

[dmin,imin]=pdist2([x y],[x0 y0],'euclidean','smallest',1);

is the result the same as your other solution. Not sure which is quicker...