Adjusting Y-Values in Histograms

Hello,

This might sound like a simple question, but how do I change the y-values of the histograms in the figure below (bottom panels)? Both the left and right histograms have bins with only 2 or 3 y-values, meaning they are binned. How can I adjust this?

The code is simply:

histogram(-xuncL(:,2), 'BinWidth', BWidth, 'Normalization', 'Probability', 'Facecolor', 'c')

Thank you!

[Umar]

Hi Alberto,

By using 'histcounts' to compute bin counts and then customizing the counts before plotting the histogram, you can precisely control the y-values for each bin in your histogram visualization. For more information on histcounts function, please refer to https://www.mathworks.com/help/matlab/ref/histcounts.html

I will further illustrate it with example below.

% Calculate bin counts

[counts, edges] = histcounts(-xuncL(:,2), 'BinWidth', BWidth);

% Adjust y-values as needed

counts(counts == 2) = {desired_value}; % Replace 'desired_value' with the value you want counts(counts == 3) = {another_value}; % Replace 'another_value' with the value you prefer

% Plot histogram with custom y-values

bar(edges(1:end-1), counts, 'hist');

Hope this will help resolve your problem.

[alberto tonizzo]

Thank you!

[Umar]

No problem Alberto, glad to help out. If you have any further questions, please let us know.

Answer 1

[the cyclist]

Your question is not perfectly clear to me. If you don't want the values binned, I think you more likely want to use the bar function rather than the histogram function to plot them. By construction, histograms are for binning!

Plot bars with x positions where the data are, y values of one.

N = 5;
x = rand(N,1); % <-- Made up data
y = ones(N,1);

bar(x,y)

[Umar]

Hi @cyclist,

I do appreciate your contribution and helping out to resolve this problem.

Answer 2

[DGM]

The reason that the bar heights have discrete values is simply that the height represents an underlying integer count, and you have relatively few things to count compared to the number of bins (along x) that you have. Consequently, you have only a few counts in each bin. Based on your images, I'm estimating that there are only about 42 items being counted in total.

A = randi([1 100],50,1);
histogram(A, 'BinWidth', 1, 'Normalization', 'Probability', 'Facecolor', 'c')

At least that's my suspicion.