Changeset 11446

Timestamp:

02/14/12 16:28:54 (13 years ago)

Author:

Mathieu Morlighem

Message:

Added incomplete_adjoint field

File:

• issm/trunk-jpl/src/m/classes/inversion.m (modified) (5 diffs)

issm/trunk-jpl/src/m/classes/inversion.m ¶

@@ -8 +8 @@
                 iscontrol                   = 0
                 tao                         = 0
+                incomplete_adjoint          = 0
                 control_parameters          = NaN
                 nsteps                      = 0
@@ -43 +44 @@
                 function obj = setdefaultparameters(obj) % {{{
 
-                         %parameter to be inferred by control methods (only
-                         %drag and B are supported yet)
-                         obj.control_parameters={'FrictionCoefficient'};
+                        %default is incomplete adjoint for now
+                        obj.incomplete_adjoint=1;
 
-                         %number of steps in the control methods
-                         obj.nsteps=20;
+                        %parameter to be inferred by control methods (only
+                        %drag and B are supported yet)
+                        obj.control_parameters={'FrictionCoefficient'};
 
-                         %maximum number of iteration in the optimization algorithm for
-                         %each step
-                         obj.maxiter_per_step=20*ones(obj.nsteps,1);
+                        %number of steps in the control methods
+                        obj.nsteps=20;
 
-                         %the inversed parameter is updated as follows:
-                         %new_par=old_par + gradient_scaling(n)*C*gradient with C in [0 1];
-                         %usually the gradient_scaling must be of the order of magnitude of the 
-                         %inversed parameter (10^8 for B, 50 for drag) and can be decreased
-                         %after the first iterations
-                         obj.gradient_scaling=50*ones(obj.nsteps,1);
+                        %maximum number of iteration in the optimization algorithm for
+                        %each step
+                        obj.maxiter_per_step=20*ones(obj.nsteps,1);
 
-                         %several responses can be used:
-                         obj.cost_functions=101*ones(obj.nsteps,1);
+                        %the inversed parameter is updated as follows:
+                        %new_par=old_par + gradient_scaling(n)*C*gradient with C in [0 1];
+                        %usually the gradient_scaling must be of the order of magnitude of the 
+                        %inversed parameter (10^8 for B, 50 for drag) and can be decreased
+                        %after the first iterations
+                        obj.gradient_scaling=50*ones(obj.nsteps,1);
 
-                         %step_threshold is used to speed up control method. When
-                         %misfit(1)/misfit(0) < obj.step_threshold, we go directly to
-                         %the next step
-                         obj.step_threshold=.7*ones(obj.nsteps,1); %30 per cent decrement.
+                        %several responses can be used:
+                        obj.cost_functions=101*ones(obj.nsteps,1);
 
-                         %stop control solution at the gradient computation and return it? 
-                         obj.gradient_only=0;
+                        %step_threshold is used to speed up control method. When
+                        %misfit(1)/misfit(0) < obj.step_threshold, we go directly to
+                        %the next step
+                        obj.step_threshold=.7*ones(obj.nsteps,1); %30 per cent decrement.
 
-                         %cost_function_threshold 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
-                         obj.cost_function_threshold=NaN; %not activated
+                        %stop control solution at the gradient computation and return it? 
+                        obj.gradient_only=0;
+
+                        %cost_function_threshold 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
+                        obj.cost_function_threshold=NaN; %not activated
 
                 end % }}}
@@ -87 +91 @@
 
                         checkfield(md,'inversion.iscontrol','values',[0 1]);
+                        checkfield(md,'inversion.tao','values',[0 1]);
+                        checkfield(md,'inversion.incomplete_adjoint','values',[0 1]);
                         checkfield(md,'inversion.control_parameters','cell',1,'values',{'BalancethicknessThickeningRate' 'FrictionCoefficient' 'MaterialsRheologyBbar' 'Vx' 'Vy'});
                         checkfield(md,'inversion.nsteps','numel',1,'>=',1);
@@ -107 +113 @@
                 function disp(obj) % {{{
                         fielddisplay(obj,'iscontrol','is inversion activated?');
+                        fielddisplay(obj,'incomplete_adjoint','do we assume linear viscosity?');
                         fielddisplay(obj,'control_parameters','parameter where inverse control is carried out; ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}');
                         fielddisplay(obj,'nsteps','number of optimization searches');
@@ -137 +144 @@
                         WriteData(fid,'object',obj,'fieldname','iscontrol','format','Boolean');
                         WriteData(fid,'object',obj,'fieldname','tao','format','Boolean');
+                        WriteData(fid,'object',obj,'fieldname','incomplete_adjoint','format','Boolean');
                         if ~obj.iscontrol, return; end
                         WriteData(fid,'object',obj,'fieldname','nsteps','format','Integer');