distance.m

A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors.

Description

A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors.

The output is the same as MathWorks' (Neural Network Toolbox) 'dist' funtion (ie, d = dist(A',B), where A is a (DxM) matrix and B a (DxN) matrix, returns the same as my d = distance(A,B) ), but this function executes much faster.

• Acknowledgements: This submission has inspired the following:; Efficient K-Nearest Neighbor Search using JIT, IPDM: Inter-Point Distance Matrix
• MATLAB release: MATLAB 5.2 (R10)

[Jan de Vries]

Fantastic!

[Peter G]

useful...good

[ti saigon]

 

[imad ali]

need the file

[Emily Van Ark]

great, fast little function. Exactly what I was looking for!

[uday desai]

 

[Hsuan-Tien Lin]

great code

[Anton Cervantes]

 

[Babak Taati]

good!

[Catherine Sweeney-Reed]

Great! Thanks!

[Enrique Guevara]

Is a very fast code. Is faster than any other code for any vectors biger that 8 points.

[Markus Buehren]

Simple but nice. Performance can still be improved by about 60% by avoiding calls to repmat:

d = abs(aa( ones(size(bb,2),1), :)' + bb( ones(size(aa,2),1), :) - 2*a'*b);

Markus

[Markus Buehren]

Sorry, I forgot the sqrt:

d = sqrt(abs(aa( ones(size(bb,2),1), :)' + bb( ones(size(aa,2),1), :) - 2*a'*b));

[Xi-Lin Li]

very good code

Thanks

[A. S.]

Very useful, especially Markus' version.

[M. Shoaib Sehgal]

for vectors it simple to compute using:

distance = norm(A-B)

[Panyam Narahari Sastry]

Good

[Philipp Berens]

Quick and clean.

What might be nice: Optional only one argument.

[Oliver Woodford]

Could be faster still by using bsxfun:
d = sqrt(abs(bsxfun(@plus, aa', bb) - 2*a'*b));