Plot based on bins with binary data
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MiauMiau
am 24 Nov. 2016
Kommentiert: Alexandra Harkai
am 25 Nov. 2016
Hello
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
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Alexandra Harkai
am 24 Nov. 2016
If you have n bins, how would they be distributed exactly? It seems you want them to be of equal size ranging from the smallest to the largest stimDuration values, but it may not be what you ultimately want.
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Alexandra Harkai
am 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)));
10 Kommentare
Alexandra Harkai
am 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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