Changeset 2211

Timestamp:

09/11/09 11:58:27 (16 years ago)

Author:

Mathieu Morlighem

Message:

Added eps_cm control method convergence criterion

Location:

issm/trunk/src

Files:

• c/ModelProcessorx/Control/CreateParametersControl.cpp (modified) (1 diff)
• c/ModelProcessorx/IoModel.cpp (modified) (2 diffs)
• c/ModelProcessorx/IoModel.h (modified) (1 diff)
• c/parallel/control_core.cpp (modified) (4 diffs)
• m/classes/@model/model.m (modified) (1 diff)
• m/classes/@model/setdefaultparameters.m (modified) (1 diff)
• m/classes/public/display/displaycontrol.m (modified) (1 diff)
• m/classes/public/ismodelselfconsistent.m (modified) (1 diff)
• m/classes/public/marshall.m (modified) (1 diff)
• m/solutions/cielo/control_core.m (modified) (2 diffs)

issm/trunk/src/c/ModelProcessorx/Control/CreateParametersControl.cpp

@@ -80 +80 @@
                 param= new Param(count,"tolx",DOUBLE);
                 param->SetDouble(iomodel->tolx);
+                parameters->AddObject(param);
+
+                /*eps_cm: */
+                count++;
+                param= new Param(count,"eps_cm",DOUBLE);
+                param->SetDouble(iomodel->eps_cm);
                 parameters->AddObject(param);
 

issm/trunk/src/c/ModelProcessorx/IoModel.cpp

@@ -113 +113 @@
         iomodel->artificial_diffusivity=0;
         iomodel->nsteps=0;
+        iomodel->eps_cm=0;
         iomodel->tolx=0;
         iomodel->maxiter=NULL;
@@ -327 +328 @@
         IoModelFetchData((void**)&iomodel->artificial_diffusivity,NULL,NULL,iomodel_handle,"artificial_diffusivity","Integer",NULL);
         IoModelFetchData((void**)&iomodel->nsteps,NULL,NULL,iomodel_handle,"nsteps","Integer",NULL);
+        IoModelFetchData((void**)&iomodel->eps_cm,NULL,NULL,iomodel_handle,"eps_cm","Scalar",NULL);
         IoModelFetchData((void**)&iomodel->tolx,NULL,NULL,iomodel_handle,"tolx","Scalar",NULL);
         IoModelFetchData((void**)&iomodel->mincontrolconstraint,NULL,NULL,iomodel_handle,"mincontrolconstraint","Scalar",NULL);

issm/trunk/src/c/ModelProcessorx/IoModel.h

@@ -111 +111 @@
         int     artificial_diffusivity;
         int     nsteps;
+        double  eps_cm;
         double  tolx;
         double* maxiter;

issm/trunk/src/c/parallel/control_core.cpp

@@ -30 +30 @@
         double* maxiter=NULL;
         double* cmjump=NULL;
+        double  eps_cm;
         double  tolx;
         double* param_g=NULL;
@@ -48 +49 @@
         int sub_analysis_type;
         int debug=0;
+        int convergence=0;
         int numberofnodes;
 
@@ -61 +63 @@
         model->FindParam(&maxiter,"maxiter");
         model->FindParam(&cmjump,"cmjump");
+        model->FindParam(&eps_cm,"eps_cm");
         model->FindParam(&tolx,"tolx");
         model->FindParam(&mincontrolconstraint,"mincontrolconstraint");
@@ -124 +127 @@
                 xfree((void**)&grad_g_double);
 
+                /*Has convergence been reached?*/
+                if (!isnan(eps_cm)){
+                        i=n-2;
+                        //go through the previous misfits(starting from n-2)
+                        while(i>=0){
+                                if (fit[i]==fit[n]){
+                                        //convergence test only if we have the same misfits
+                                        if ((J[i]-J[n])/J[n] <= eps_cm){
+                                                //convergence if convergence criteria fullfilled
+                                                convergence=1;
+                                                _printf_("%s%g%s%g\n","      Convergence criterion: dJ/J = ",(J[i]-J[n])/J[n],"<",eps_cm);
+                                        }
+                                        else{
+                                                _printf_("%s%g%s%g\n","      Convergence criterion: dJ/J = ",(J[i]-J[n])/J[n],">",eps_cm);
+                                        }
+                                        break;
+                                }
+                                i=i-1;
+                        }
+                }
+                //stop if convergence has been reached
+                if(convergence) break;
+
                 //some temporary saving
                 /*if (((n+1)%5)==0){

issm/trunk/src/m/classes/@model/model.m

@@ -178 +178 @@
         md.nsteps=0;
         md.maxiter=[];
+        md.eps_cm=0;
         md.tolx=0;
         md.optscal=[];

issm/trunk/src/m/classes/@model/setdefaultparameters.m

@@ -190 +190 @@
 
 %cmjump
-md.cmjump=.7*ones(md.nsteps,1); %30 % decrement.
+md.cmjump=.7*ones(md.nsteps,1); %30 per cent decrement.
+
+%eps_cm is a criteria to stop the control methods.
+%if J[n]-J[n-1]/J[n] < criteria, the control run stops
+%NaN if not applied
+md.eps_cm=0.01; %1 percent
 
 %minimum velocity to avoid the misfit to be singular

issm/trunk/src/m/classes/public/display/displaycontrol.m

@@ -13 +13 @@
         fielddisplay(md,'control_type','parameter where inverse control is carried out; ex: ''drag'', or ''B'')');
         fielddisplay(md,'nsteps','number of optimization searches');
+        fielddisplay(md,'eps_cm','misfit convergence criterion. Default is 1%, NaN if not applied');
         fielddisplay(md,'optscal','scaling factor on gradient direction during optimization, for each optimization step');
         fielddisplay(md,'fit','''absolute: 0'', ''relative: 1'', or ''logarithmic: 2''. default is ''absolute: 0'', for each optimization steps');

issm/trunk/src/m/classes/public/ismodelselfconsistent.m

@@ -351 +351 @@
 
         %LENGTH CONTROL FIELDS
-        if (length(md.maxiter)~=md.nsteps | length(md.optscal)~=md.nsteps | length(md.fit)~=md.nsteps)
-                disp('maxiter, optscal and fit must have the length specified by nsteps')
+        if (length(md.maxiter)~=md.nsteps | length(md.optscal)~=md.nsteps | length(md.fit)~=md.nsteps | length(md.cmjump)~=md.nsteps)
+                disp('maxiter, optscal, fit and cmjump must have the length specified by nsteps')
                 bool=0;return;
         end

issm/trunk/src/m/classes/public/marshall.m

@@ -109 +109 @@
 WriteData(fid,md.artificial_diffusivity,'Integer','artificial_diffusivity');
 WriteData(fid,md.nsteps,'Integer','nsteps');
+WriteData(fid,md.eps_cm,'Scalar','eps_cm');
 WriteData(fid,md.tolx,'Scalar','tolx');
 WriteData(fid,md.maxiter,'Mat','maxiter');

issm/trunk/src/m/solutions/cielo/control_core.m

@@ -16 +16 @@
 dim=model.parameters.dim;
 isstokes=model.parameters.isstokes;
+
+%recover other parameters
+eps_cm=model.parameters.eps_cm;
+fit=model.parameters.fit;
 
 %initialize control parameters
@@ -71 +75 @@
         param_g=ControlConstrain(param_g,model.parameters);
 
-        %visualize direction.
-        if model.parameters.plot,
-                plot_newdistribution;
+        disp(['      value of misfit J after optimization #' num2str(n) ':' num2str(c(n).J)]);
+
+        %Has convergence been reached?
+        convergence=0;
+        if ~isnan(eps_cm),
+                i=n-2;
+                %go through the previous misfits(starting from n-2)
+                while (i>=1),
+                        if (fit(i)==fit(n)),
+                                %convergence test only if we have the same misfits
+                                if ((c(i).J-c(n).J)/c(n).J <= eps_cm),
+                                        %convergence if convergence criteria fullfilled
+                                        convergence=1;
+                                        displaystring(debug,'\n%s%g%s%g\n','      Convergence criterion: dJ/J = ',(c(i).J-c(n).J)/c(n).J,'<',eps_cm);
+                                else
+                                        displaystring(debug,'\n%s%g%s%g\n','      Convergence criterion: dJ/J = ',(c(i).J-c(n).J)/c(n).J,'>',eps_cm);
+                                end
+                                break;
+                        end
+                        i=i-1;                                                                                                                                         
+                end
         end
+        %stop if convergence has been reached                                                                                                               
+        if (convergence), break; end
 
-        disp(['      value of misfit J after optimization #' num2str(n) ':' num2str(c(n).J)]);
 end