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How can I normalize a histogram (dividing by the maximum number of observations in a bin, so that the histogram maximum = 1).

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Hello everyone,
I need to normalize a histogram, so that the histogram maximum is equal to 1. I want to divide by the maximum No. of values in each bin.
I tried to normalize using cumcount but it doesn't give me the graph I want although it gives me the limit of histogram between 0, and 1.
I need to plot a graph like this
any suggestions??

Accepted Answer

Image Analyst
Image Analyst on 27 Jun 2021
Just divide by the max
counts = histcounts(data);
counts = counts / max(counts);
Seems so obvious - am I missing something?
Ebtesam Farid
Ebtesam Farid on 27 Jun 2021
sorry again. first, my measurements are estimated precipitation from one of GNSS stations , and I am trying to plot the histogram for the precipitable water vapor variable to look to its shape to see if it's lognormally distributed or not, and the paper that I attached a graph from it, did what you said, plotted the histogram of varaible (black curve) then lognormally fitted it (red curve).
when I tried your codes,
counts = histcounts(data);
counts = counts / max(counts);
h = hist(data, counts);
it give me the values on x that's between 0 and 1, maybe I mistaken in something.
sorry for replying late

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More Answers (1)

Image Analyst
Image Analyst on 27 Jun 2021
I think you need to use kstest(), kstest2(), or lillietest() to determine if your samples are normally distributed. Of course take the log of them first if you want to see if the log of your values are normally distributed.

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