MATLAB REPMAT FREE

This is faster, but will probably hit a memory wall later on, too:

You can try to alleviate this by using a single for loop and inside the loop a single repmat. % Slow, especially if hitting memory paging You can also do this using two repmats in a one-liner, but this gets slow if you hit a memory wall: You can achieve the all pairs distance computation between V and U in the most naive way using two for loops (like you would probably do it in C++):Д(i,j) = sqrt(sum((V(i,:)-U(j,:)).^2,2)) That is, if I have a set of points V and another set of points U, IвЂ™d like to build D, a #V by #U matrix of distance, where D(i,j) gives me the distance from point V(i) to point U(i).ДЇor the sake of timings, construct some V and U values using: Often I like to get list of distances between all pairs of points in two sets. Tags: alpha, bsxfun, checkerboard, image, matlab, repmat, xor Im HereвЂ™s an even gnarlier anonymous function which takes an image im and an alpha map A and produces an image of the composite over the checkboard:Д¬hecker = xor((mod(repmat(0:size(im,2)-1,size(im,1),1),82)>7),(mod(repmat((0:size(im,1)-1)вЂ™,1,size(im,2)),8*2)>7)),)) + you can quickly display your checkboard background images with: imshow(checker(im,A)) Then you could composite the star over ch: imshow([. So suppose you had an alpha-map A to extract the star from this colorful image im. Should the program prove % defective, you assume the cost of all necessary servicing, repair % or correction.HereвЂ™s a gnarly one-liner to produce a checkerboard image ch with the same dimensions as you image im in matlab: ch = repmat(1-0.2*xor((mod(repmat(0:size(im,2)-1,size(im,1),1),8*2)>7),(mod(repmat((0:size(im,1)-1)',1,size(im,2)),8*2)>7)),) The entire risk as to the quality and % performance of the program is with you.

Except when otherwise stated in writing the copyright holder % and/or other parties provide the program 'as is' without warranty % of any kind, either expressed or implied, including, but not % limited to, the implied warranties of merchantability and fitness % for a particular purpose.

MATLAB REPMAT FREE

Rohn, A Handbook of Results on Interval Linear Problems, % posted at % % WARRANTY % % Because the program is licensed free of charge, there is % no warranty for the program, to the extent permitted by applicable % law. % Copyright 2007-2008 Jiri Rohn % % Based on the algorithm 'hull' described in % J. sec.' % This is a useful feature, considering the NP-hardness of % the problem however, it slows down the actual computation. % % =verintervalhull(A,b,1) % is the same as before, but in course of the computation % it also produces screen output of the form % 'Expected remaining time. % C.D, C.Xlower, and C.Xupper are empty if x is empty. % % =verintervalhull(A,b) produces additional information in the % structure C: % C.xun is an unverified interval hull, issued in case a verified % one could not be computed, % C.Asun is a thin unverified singular matrix, issued in case a verified % one could not be computed, % C.flag describes verbally the output it has one of the forms % 'verified interval hull computed ' % 'interval matrix verified singular ' % 'interval hull computed, result not verified ' % 'interval matrix singular, result not verified', % C.orth is the number of orthants inspected by the algorithm, % C.iter is the total number of iterations of the core algorithm, % C.D is a (possibly huge) matrix with rows of the form, where % z is a plus/minus-one vector, and % infsup(xl,xu) is a verified (possibly not optimal) % enclosure of the intersection of the solution set % with the z-orthant % if some plus/minus vector z is not present, then it is % verified that the intersection of the solution set with % the z-orthant is empty, % C.Xlower is a matrix such that for each i the lower bound x.inf(i) was % attained as the lower bound of the solution of the system % (mid(A)-diag(y)*rad(A)*diag(z))*x=mid(b)+diag(y)*rad(b), % where is the ith row of C.Xlower, % C.Xupper is a matrix such that for each i the upper bound x.sup(i) was % attained as the upper bound of the solution of the system % (mid(A)-diag(y)*rad(A)*diag(z))*x=mid(b)+diag(y)*rad(b), % where is the ith row of C.Xupper. If no verified result % is achieved, then both x and As consist of NaN's. % % =verintervalhull(A,b) gives either a verified interval hull x, % or a very tight ('almost thin') interval matrix As which is a part of % A and is verified to contain a singular matrix. % % x=verintervalhull(A,b) computes a verified interval hull x of the % solution set of a system of interval linear equations A*x=b, A square, % or yields a vector of NaN's. It requires to have INTLAB installed under % MATLAB to function properly. % VERINTERVALHULL Verified interval hull of the solution set of a system of interval linear equations.

Matlab repmat