What is your favourite MATLAB/Octave programming trick? [closed]

Answer 1

Asking 'why' (useful for jarring me out of a Matlab runtime-fail debugging trance at 3am...)

Answer 2

Using persistent (static) variables when running an online algorithm. It may speed up the code in areas like Bayesian machine learning where the model is trained iteratively for the new samples. For example, for computing the independent loglikelihoods, I compute the loglikelihood initially from scratch and update it by summing this previously computed loglikelihood and the additional loglikelihood.

Instead of giving a more specialized machine learning problem, let me give a general online averaging code which I took from here:

function av = runningAverage(x)
% The number of values entered so far - declared persistent.
persistent n;
% The sum of values entered so far - declared persistent.
persistent sumOfX;
if x == 'reset' % Initialise the persistent variables.
    n = 0;
    sumOfX = 0;
    av = 0;
else % A data value has been added.
    n = n + 1;
    sumOfX = sumOfX + x;
    av = sumOfX / n; % Update the running average.
end

Then, the calls will give the following results

runningAverage('reset')
ans = 0
>> runningAverage(5)
ans = 5
>> runningAverage(10)
ans = 7.5000
>> runningAverage(3)
ans = 6
>> runningAverage('reset')
ans = 0
>> runningAverage(8)
ans = 8

Answer 3

The colon operator for the manipulation of arrays.

@ScottieT812, mentions one: flattening an array, but there's all the other variants of selecting bits of an array:

x=rand(10,10);
flattened=x(:);
Acolumn=x(:,10);
Arow=x(10,:);

y=rand(100);
firstSix=y(1:6);
lastSix=y(end-5:end);
alternate=y(1:2:end);

Answer 4

Oh, and reverse an array

v = 1:10;
v_reverse = v(length(v):-1:1);

Answer 5

Vectorization:

function iNeedle = findClosest(hay,needle)
%FINDCLOSEST find the indicies of the closest elements in an array.
% Given two vectors [A,B], findClosest will find the indicies of the values
% in vector A closest to the values in vector B.
[hay iOrgHay] = sort(hay(:)');  %#ok must have row vector

% Use histogram to find indices of elements in hay closest to elements in
% needle. The bins are centered on values in hay, with the edges on the
% midpoint between elements.
[iNeedle iNeedle] = histc(needle,[-inf hay+[diff(hay)/2 inf]]); %#ok

% Reversing the sorting.
iNeedle = iOrgHay(iNeedle);

Answer 6

Matlab's bsxfun, arrayfun, cellfun, and structfun are quite interesting and often save a loop.

M = rand(1000, 1000);
v = rand(1000,    1);
c = bsxfun(@plus, M, v);

This code, for instance, adds column-vector v to each column of matrix M.

Though, in performance critical parts of your application you should benchmark these functions versus the trivial for-loop because often loops are still faster.