Plot based on bins with binary data

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I have two arrays, say array stimDuration - which contains the duration a subject has seen a stimulation - and array answers, which is binary (containing 1 or 0's) to indicate if subject could correctly identify the stimulus or not. The data could look something like that:
stimDuration = [1, 2, 3, 2, 4, 6, 8, 1, 11, 12, 9] answers = [0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0]
I want now to have n bins for the stimDuration (for instance 2 bins, one going from 1 to 6, the other from 7 to 12) as the x axis. The y axis would be the percentage of the correct answers for each bin. For instance for the bin from 1 to 6, we have a total of 7 answers, 5 of which are correct (hence the y value would be 5/7). Is there a straightforward way of doing that? Thanks
MiauMiau on 24 Nov 2016
yes and equal size would be ok, as I calculate a percentage, and will have enough trials such that it won't matter if one of the bins contains a bit more data samples..

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Accepted Answer

Alexandra Harkai
Alexandra Harkai on 24 Nov 2016
This would do the trick if you bin them from 0 to max(stimDuration):
n = 2; % number of bins
bar(splitapply(@(x) sum(x)/size(x,2), answers, ceil(stimDuration/(max(stimDuration)/n))));
If you have R2016b you could do:
bar(splitapply(@(x) sum(x)/size(x,2), answers, discretize(stimDuration, n)));
Alexandra Harkai
Alexandra Harkai on 25 Nov 2016
Yes. It gives 2 bins as far as I can see. If you look into the documentation for discretize and linspace, you can see what they do and how you can modify the command depending on what you need.

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