added 2D GP example

MatlabGP/+BO/EImin.m

@@ -1,4 +1,4 @@
-function [alpha, dalpha] = EI(Z,x)
+function [alpha, dalpha] = EImin(Z,x)
 
 ys = min(Z.Y);
 

MatlabGP/+BO/argmax.m

@@ -3,7 +3,7 @@
 lb = Z.lb_x;
 ub = Z.ub_x;
 
-x0 = lb + (ub-lb).*rand(length(lb));
+x0 = lb + (ub-lb).*rand(1,length(lb));
 
 [x,R] = VSGD(@(x) FF(Z,x),x0,'lr',0.03,'lb',lb,'ub',ub,'gamma',0.01,'iters',100,'tol',1*10^(-5));
 

MatlabGP/+BO/argmin.m

@@ -6,11 +6,11 @@
 for i = 1
     x0 = lb + (ub-lb).*rand(1,length(lb));
 
-    opts = optimoptions('fmincon','SpecifyObjectiveGradient',true,'Display','none');
+    %opts = optimoptions('fmincon','SpecifyObjectiveGradient',true,'Display','none');
 
-    [x{i},R(i)] = fmincon(@(x) FF(Z,x),x0,[],[],[],[],lb,ub,[],opts);
+    %[x{i},R(i)] = fmincon(@(x) FF(Z,x),x0,[],[],[],[],lb,ub,[],opts);
 
-    %[x{i},R(i),xv{i},fv{i}] = VSGD(@(x) FF(Z,x),x0,'lr',0.05,'lb',lb,'ub',ub,'gamma',1*10^(-2),'iters',100,'tol',1*10^(-6));
+    [x{i},R(i),xv{i},fv{i}] = VSGD(@(x) FF(Z,x),x0,'lr',0.05,'lb',lb,'ub',ub,'gamma',1*10^(-2),'iters',100,'tol',1*10^(-6));
 end
 
 [~,ii] = min(R);

MatlabGP/+BO/opt.m

@@ -1,12 +1,12 @@
 function [x,R,Q,Z] = opt(f,FF,lb,ub)
 
-x0 = lb + (ub - lb).*lhsdesign(20,length(lb));
+x0 = lb + (ub - lb).*lhsdesign(3,length(lb));
 y0 = f(x0);
 
 a = means.linear(ones(1,length(lb)))*means.linear(ones(1,length(lb))) + means.linear(ones(1,length(lb))) + means.const(1);
 
-b = kernels.RQ(1,1,0.2*ones(1,length(lb)));
-b.signn = 0.0001;
+b = kernels.Matern52(1,0.2*ones(1,length(lb)));
+b.signn = 0;
 
 Z = GP(a,b);
 Z = Z.condition(x0,y0,lb,ub);
@@ -25,14 +25,14 @@
     x0 = [x0;x];
     y0 = [y0;y];
 
-    %Z = Z.condition(x0,y0,lb,ub);
-    Z = Z.resolve(x,y);
+    Z = Z.condition(x0,y0,lb,ub);
+    %Z = Z.resolve(x,y);
     Z.lb_x = lb;
     Z.ub_x = ub;
 
-    % if i<10
-    %     Z = Z.train();
-    % end
+    if i==15
+        Z = Z.train();
+    end
 
     [Q(i)] = min(Z.Y);
 

MatlabGP/GP.m

@@ -71,7 +71,7 @@
                 dksf = obj.kernel.grad(xs,xx);
                 dm = obj.mean.grad(xs);
 
-                dy = dm + (dksf*obj.alpha)';
+                dy = dm + (dksf'*obj.alpha)';
             end
 
         end
@@ -88,7 +88,7 @@
 
             if nargout>1
                 dksf = obj.kernel.grad(xs,xx);
-                dsig = -1*(-2*(ksf*obj.Kinv*dksf'));
+                dsig = -1*(-2*(ksf*obj.Kinv*dksf));
             end
 
         end
@@ -206,6 +206,7 @@
                 if regress
                     dnLL(end+1) = -1*sum(sum(2*sqrt(obj.kernel.signn)*(obj.alpha*obj.alpha' - obj.Kinv)));
                 end
+
             end
 
         end
@@ -268,11 +269,14 @@
             % 
             % theta = sum(xxt.*LL')/sum(LL);
 
-            for i = 1:5
+            for i = 1:2
                 tx0 = tlb + (tub - tlb).*rand(1,length(tlb));
+
+                opts = optimoptions('fmincon','SpecifyObjectiveGradient',true,'Display','none');
 
+                [theta{i},val(i)] = fmincon(func,tx0,[],[],[],[],tlb,tub,[],opts);
                 %[theta{i},val(i)] = bads(func,tx0,tlb,tub);
-                [theta{i},val(i)] = VSGD(func,tx0,'lr',0.02,'lb',tlb,'ub',tub,'gamma',0.0001,'iters',400,'tol',1*10^(-4));
+                %[theta{i},val(i)] = VSGD(func,tx0,'lr',0.02,'lb',tlb,'ub',tub,'gamma',0.0001,'iters',400,'tol',1*10^(-4));
 
             end
 

MatlabGP/docs/testNN.m

@@ -3,18 +3,18 @@
 close all
 clc
 
-xx = [0;lhsdesign(8,1);1];
+xx = [0;lhsdesign(10,1);1];
 yy = forr(xx,0);
 
 xmesh = linspace(0,1,100)';
 ymesh = forr(xmesh,0);
 
-layers{1} = NN.FF(1,20);
-layers{2} = NN.FF(20,10);
+layers{1} = NN.FF(1,5);
+layers{2} = NN.FF(5,10);
 layers{3} = NN.FF(10,3);
 
-acts{1} = NN.SWISH(1);
-acts{2} = NN.LIN();
+acts{1} = NN.SNAKE(1);
+acts{2} = NN.SWISH(1);
 
 lss = NN.MSE();
 

MatlabGP/warpGP.m

@@ -58,7 +58,5 @@
 
         end
 
-
-
     end
 end