I tried to show effect of uncertain parameters on bi-variate function with color map and aslo highlight changes to max and min,I am not sure the function I wrote is right!!!

1 vue (au cours des 30 derniers jours)
for i=1:length(x)
x=lhsdesign(10,1,"iterations",2);
for j=1:length(y)
y=lhsnorm(50,10,10,"on");
Z=[x,y];
Z(i,j)=2.*x(i).^3+y(j).^3-3.*x(i).^2-12.*x(i)-3.*y(j);
end
end
options = optimset('Display','iter','PlotFcns',@optimplotfval);
x0=[x(1),y(1)]
[xmin,fval]=fminsearch(@(xy)Z(xy(1),xy(2)),x0,options); %min
[xmax ,fval]=fminsearch(@(xy) -1 *Z(xy(1),xy(2)),x0,options); %max
[X,Y]=meshgrid(x,y);
surf(X,Y,Z(i,j),'EdgeColor',"interp","FaceAlpha",0.5);
hold on
plot(xmin(1),xmin(2), f(xmin(1),xmin(2)),'MarkerSize',6);
hold on
plot(xmax(1),xmax(2), f(xmax(1),xmax(2)),'MarkerSize',6);
hold off
xlabel("optimum valeus for x")
ylabel("optimum valeus for y")
colormap(parula(6));%default colormap with 6 colors
colorbar
can anyone help me for correcting this function?
  11 commentaires
sogol bandekian
sogol bandekian le 23 Mai 2022
but they are not optimization solvers like fminsearch.are not they?
Torsten
Torsten le 23 Mai 2022
No. It's a search for a minimum or maximum of a functrion on a discrete set of (x/y) values. The function is evaluated on a (fine enough) grid and the point where this evaluation is minimal (or maximal) is taken as the minimum (or maximum) of the function. It's an alternative to fminsearch and other optimizers if the region where minimum (or maximum) is is approximately known and if the function is badly behaved (not differentiable etc).

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Walter Roberson
Walter Roberson le 22 Mai 2022
y=lhsnorm(50,10,10,"on");
[xmin,fval]=fminsearch(@(x)Z(x,y),x0,options) %min
The y referred to there is being "captured" from the workspace variable y which is the lhsnorm that you defined earlier.
With y being non-scalar, your multinomial Z function is going to return multiple values for each input x value, but for fminsearch you need to return a vector.
Perhaps what you need is
[xmin,fval]=fminsearch(@(xy)Z(xy(1),xy(2)),x0,options) %min
  9 commentaires
Walter Roberson
Walter Roberson le 24 Mai 2022
x = 0:0.2:1;
y = 0:0.2:1;
[X,Y] = meshgrid(x,y);
Z = 2.*X.^3+Y.^3-3.*X.^2-12.*X-3.*Y;
Z = Z + (-0.1+0.2*rand(size(Z)));
fun = @(x)interp2(X,Y,Z,x(1),x(2), 'spline');
fun2 = @(x)-fun(x);
options = optimset('Display','iter','PlotFcns',@optimplotfval);
x0=[x(1),y(1)]
lb = [min(x), min(y)];
ub = [max(x), max(y)];
[xmin,fvalmin] = fmincon(fun, x0, [], [], [], [], lb, ub, [], options); %min
[xmax,fvalmax]= fmincon(fun2, x0, [], [], [], [], lb, ub, [], options); %max
fvalmax = -fvalmax;
surf(X, Y, Z, 'edgecolor', 'none')
hold on
plot3(xmin(1), xmin(2), fvalmin, 'rv')
plot3(xmax(1), xmax(2), fvalmax, 'r^')
hold off

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