Closest value of huge data, Avoiding excessive iterations

Hi all,

I have the location of red dots (1000 points) and black dots (4000 points). The red dots have values associated with them.

What I want is for each black dot, find the one closest red dot and get that associated value. So the result would be a matrix of 4000x4, where 4000 is the number of black dots:

Result=[
1 x y AssociatedRedDotValue1
2 x y AssociatedRedDotValue2
3 x y AssociatedRedDotValue3
.
.
.
4000 x y AssociatedRedDotValue4000
]

If I use nested for loop, that would be 4000000 iterations, and will crash my computer. Is there much efficient way to do this?

Thanks in advance.

Answer 1

[KSSV]

Read about knnsearch. This will give you the required number of nearest points for a given point out of the data. This is very fast and effective.