Convert to Histogram figure

I have the probiblity distrbuion function (see the attached figure) i want to convert this figure to the histogram distbuion

i plot the PDF based on this code

for i=1:length(y_pred)
    if y_pred(i) <= failure_threshold
        mu =( i + Future_Cycle)*100;
        mu=2300
        break
    end
end
sigma =100
xz    = linspace(mu-200 , x1(end-2), 100);
yz    = 0.1*gaussian(xz, mu, sigma) + min(y_pred);
 plot(xz, yz, 'r-')

Answer 1

[Voss]

You might try something like this:

% first, re-creating something like your xz and yz:
pd = makedist('Normal',2300,100);
xz = linspace(2100,2900,100);
yz = 25*pdf(pd,xz)+0.7675;
plot(xz,yz,'r-','LineWidth',2);
grid on

% now, translate each of those yz values into a histogram count for the
% corresponding xz value:
max_count = 1000;
xz_counts = round(max_count*(yz-min(yz))/(max(yz)-min(yz)));
% replicating each xz value a certain number of times depending on yz:
xz_new = arrayfun(@(x,n)repmat(x,1,n),xz,xz_counts,'UniformOutput',false);
xz_new = [xz_new{:}];
% plot a histogram of the new replicated xz values, using the original xz
% values as the bin edges
figure()
histogram(xz_new,xz);
xlim(xz([1 end]));