how does cdfplot works?

can someone tell me how cdfplot works....? i know the matlab help about this function but i dont understand it...the answer in my code is upside down but it should be like this picture...

clc;
clear;
C=[250;200;150;150;100];
q=[0.15;0.15;0.1;0.1;0];
y=[660;660;770;880];
f=[10;15;20;25;30;50];
Aeq=ones(1,6);
LB=zeros(6,1);
prob=[0.25;0.25;0.25;0.25];
%% Monte Carlo
iteration=3000;% Number of iterations
deterministic_index=zeros(iteration,1);
margin=zeros(iteration,1);
for t=1:iteration
    %generation program
    for i=1:length(C)
        if rand<=q(i) 
            outage_capacity(i)=C(i);
            UB1(i)=0;
        else
            UB1(i)=C(i);
            outage_capacity(i)=0;
        end
    end
    %% Load random samples
    sum_prob(1)=prob(1);
    for i=2:length(prob)
        sum_prob(i)=sum_prob(i-1)+prob(i);
    end
    flag=find(rand<=sum_prob);
    load=y(min(flag));
    %% Margin random variable
    margin(t) = sum(C) - sum(outage_capacity) - load;
    if margin(t)<0 
        deterministic_index(t)=1;
    end
    beq=load;
    UB=[UB1,beq] ;
    [X,faval,exitflag]=linprog(f,[],[],Aeq,beq,LB,UB);
    X1(:,t)=X;
    
end
C1 = X1(1,:);
C2 = X1(2,:);
C3 = X1(3,:);
C4 = X1(4,:);
C5 = X1(5,:);
Plsh = X1(6,:);
% Plsh=Plsh(end:-1:1);

ExpectationC1 = mean(C1); 
ExpectationC2 = mean(C2); 
ExpectationC3 = mean(C3);
ExpectationC4 = mean(C4); 
ExpectationC5 = mean(C5); 
ExpectationPlsh = mean(Plsh);
standard_deviationC1 = std(C1); 
standard_deviationC2 = std(C2); 
standard_deviationC3 = std(C3); 
standard_deviationC4 = std(C4); 
standard_deviationC5 = std(C5); 
standard_deviationPlsh = std(Plsh);
LOLP = mean(deterministic_index);
LOLE = 8760*LOLP;
EENS = mean(mean(margin .* deterministic_index));
disp(['LOLP=',num2str(LOLP)]);
disp(['LOLE=',num2str(LOLE)]);
disp(['EENS=',num2str(EENS)]);
disp(['ExpectationC1=',num2str(ExpectationC1)]);
disp(['ExpectationC2=',num2str(ExpectationC2)]);
disp(['ExpectationC3=',num2str(ExpectationC3)]);
disp(['ExpectationC4=',num2str(ExpectationC4)]);
disp(['ExpectationC5=',num2str(ExpectationC5)]);
disp(['ExpectationPlsh=',num2str(ExpectationPlsh)]);
disp(['standard_deviationC1=',num2str(standard_deviationC1)]);
disp(['standard_deviationC2=',num2str(standard_deviationC2)]);
disp(['standard_deviationC3=',num2str(standard_deviationC3)]);
disp(['standard_deviationC4=',num2str(standard_deviationC4)]);
disp(['standard_deviationC5=',num2str(standard_deviationC5)]);
disp(['standard_deviationPlsh=',num2str(standard_deviationPlsh)]);
disp(['Exitflag=',num2str(exitflag)]);

%% Probability Density Function
figure(1);
subplot(3,2,1); hist(C1); title('Probability Density Function(Unit1)');
subplot(3,2,2); hist(C2); title('Probability Density Function(Unit2)');
subplot(3,2,3); hist(C3); title('Probability Density Function(Unit3)');
subplot(3,2,4); hist(C4); title('Probability Density Function(Unit4)');
subplot(3,2,5); hist(C5); title('Probability Density Function(Unit5)');


figure(2);
hist(Plsh); title('Probability Density Function(Plsh)');

%%Cumulative distribution function
figure(3);
subplot(5,1,1); cdfplot(C1); title('Cumulative distribution function(Unit1)');
subplot(5,1,2); cdfplot(C2); title('Cumulative distribution function(Unit2)');
subplot(5,1,3); cdfplot(C3); title('Cumulative distribution function(Unit3)');
subplot(5,1,4); cdfplot(C4); title('Cumulative distribution function(Unit4)');
subplot(5,1,5); cdfplot(C5); title('Cumulative distribution function(Unit5)');
figure(4);

cdfplot(Plsh);

[Torsten]

I understand cdfplot, but I don't understand your picture. Funny, isn't it ?

[arian hoseini]

u see my cdfplot(Plsh) starts from zero and goes to top that is 1 but i need it to start from 1 to 0 like stairs but going than instead of going up...i hope u get what i mean

[Torsten]

Then plot 1-cdfplot (if this is what you want).

[arian hoseini]

u mean 1-cdfplot(Plsh)??????????

[Torsten]

I'm not sure, though, if this is what you want.

You should explain in detail how you want to transform the original CDF curve.

Maybe the following code will do what you want:

x = rand(1000,1);
h = cdfplot(x);
h.XData(1:end-1) = h.XData(end-1)-h.XData(1:end-1);
h.YData = fliplr(h.YData);

[arian hoseini]

thank u so much.

[Torsten]

As you see from my answer, you get access to the x and y plot data by

h = cdfplot(x)
x = h.XData
y = h.YData

Now you can rearrange the data according to your needs.

I mention this because I'm still not sure whether the suggested rearrangement is correct in your case. You will have to check it carefully.

Answer 1

[the cyclist]

What you are plotting is known as a "survival" curve, and I think it is possible that you want to use the ecdf function instead of cdfplot. That function allows you to specify that you are using a survival function.

[arian hoseini]

tried it not working...

[the cyclist]

Here is the equivalent to what @Torsten posted as an example:

x = rand(1000,1);

ecdf(x,'Function','survivor');