Index: /issm/trunk-jpl/src/c/modules/InputUpdateFromDakotax/InputUpdateFromDakotax.cpp =================================================================== --- /issm/trunk-jpl/src/c/modules/InputUpdateFromDakotax/InputUpdateFromDakotax.cpp (revision 24987) +++ /issm/trunk-jpl/src/c/modules/InputUpdateFromDakotax/InputUpdateFromDakotax.cpp (revision 24988) @@ -13,5 +13,4 @@ int i,j,k,l; - int dummy; int numberofvertices; @@ -19,7 +18,11 @@ int nrows; int ncols; - int npart; - double *qmu_vpart = NULL; - double *qmu_epart = NULL; + IssmDouble **variable_partitions = NULL; + IssmDouble * variable_partition = NULL; + int variable_partitions_num; + int *partitions_m = NULL; + int *partitions_n = NULL; + int npart; + int dummy; //should match numvariables double *distributed_values = NULL; @@ -29,7 +32,6 @@ /*retrieve parameters: */ - femmodel->parameters->FindParam(&npart,QmuNumberofpartitionsEnum); - femmodel->parameters->FindParam(&qmu_vpart,NULL,QmuVpartitionEnum); - femmodel->parameters->FindParam(&qmu_epart,NULL,QmuEpartitionEnum); + femmodel->parameters->FindParam(&variable_partitions,&variable_partitions_num,&partitions_m,&partitions_n,QmuVariablePartitionsEnum); + numberofvertices=femmodel->vertices->NumberOfVertices(); numberofelements=femmodel->elements->NumberOfElements(); @@ -44,4 +46,9 @@ /*From descriptor, figure out if the variable is scaled, indexed, nodal, or just a simple variable: */ if (strncmp(descriptor,"scaled_",7)==0){ + + /*recover partition vector: */ + variable_partition=variable_partitions[i]; + //_printf_("variable_partition_M: " << variable_partition_M << " variable_partition_N " << variable_partition_N << "\n"); + npart=partitions_m[i]; /*Variable is scaled. Determine root name of variable (ex: scaled_DragCoefficient_1 -> DragCoefficient). Allocate distributed_values and fill the @@ -57,11 +64,11 @@ } + /*Now, pick up the parameter corresponding to root: */ femmodel->parameters->FindParamInDataset(¶meter,&nrows,&ncols,QmuVariableDescriptorsEnum,StringToEnumx(root)); - - /*We've got the parameter, we need to update it using qmu_vpart or qmu_epart (depending on whether - * it is element or vertex distributed), and the distributed_values. - In addition, the parameter can be either a static or transient (nrows+1) vector. */ + /*We've got the parameter, we need to update it using the partition vector, and the distributed_values. + In addition, the parameter can be either a static or transient (nrows+1) vector. Finally, the partition vectors can include + -1 (meaning, don't update). */ //_printf_("nrows: " << nrows << " numberofvertices: " << numberofvertices << " numberofelements: " << numberofelements << "\n"); @@ -69,6 +76,9 @@ if (nrows==numberofvertices || nrows==(numberofvertices+1)){ for(k=0;k(parameter); @@ -126,5 +139,11 @@ /*Free ressources:*/ - xDelete(qmu_vpart); - xDelete(qmu_epart); + for(i=0;i(matrix); + } + xDelete(partitions_m); + xDelete(partitions_n); + xDelete(variable_partitions); + } Index: /issm/trunk-jpl/src/c/modules/ModelProcessorx/Dakota/CreateParametersDakota.cpp =================================================================== --- /issm/trunk-jpl/src/c/modules/ModelProcessorx/Dakota/CreateParametersDakota.cpp (revision 24987) +++ /issm/trunk-jpl/src/c/modules/ModelProcessorx/Dakota/CreateParametersDakota.cpp (revision 24988) @@ -13,7 +13,4 @@ /*variable declarations*/ int i; - double *vpart = NULL; - double *epart = NULL; - int npart; char **responsedescriptors = NULL; int numresponsedescriptors; @@ -35,4 +32,10 @@ int numberofresponses; int nrows,ncols; + + //variable partitions: + IssmDouble **array = NULL; + int *mdims_array = NULL; + int *ndims_array = NULL; + int num_partitions; /*recover parameters: */ @@ -70,9 +73,9 @@ /*Load partitioning vectors (both vertex and element based: */ parameters->AddObject(iomodel->CopyConstantObject("md.qmu.numberofpartitions",QmuNumberofpartitionsEnum)); - iomodel->FetchData(&vpart,&npart,NULL,"md.qmu.vpartition"); if(!vpart) _error_("md.qmu.vpartition is empty"); - parameters->AddObject(new DoubleVecParam(QmuVpartitionEnum,vpart,npart)); - iomodel->FetchData(&epart,&npart,NULL,"md.qmu.epartition"); if(!epart) _error_("md.qmu.epartition is empty"); - parameters->AddObject(new DoubleVecParam(QmuEpartitionEnum,epart,npart)); + /*Load partitioning vectors specific to variables:*/ + iomodel->FetchData(&array,&mdims_array,&ndims_array,&num_partitions,"md.qmu.variablepartitions"); + parameters->AddObject(new DoubleMatArrayParam(QmuVariablePartitionsEnum,array,num_partitions,mdims_array,ndims_array)); + /*Deal with data needed because of qmu variables*/ @@ -114,9 +117,16 @@ } xDelete(variabledescriptors); - xDelete(vpart); - xDelete(epart); xDelete(qmuinname); xDelete(qmuerrname); xDelete(qmuoutname); + + for(i=0;i(matrix); + } + xDelete(mdims_array); + xDelete(ndims_array); + xDelete(array); + } Index: /issm/trunk-jpl/src/m/classes/qmu.m =================================================================== --- /issm/trunk-jpl/src/m/classes/qmu.m (revision 24987) +++ /issm/trunk-jpl/src/m/classes/qmu.m (revision 24988) @@ -18,4 +18,5 @@ numberofresponses = 0; variabledescriptors = {}; + variablepartitions = {}; responsedescriptors = {}; mass_flux_profile_directory = NaN; @@ -57,6 +58,4 @@ methods function self = extrude(self,md) % {{{ - self.vpartition=project3d(md,'vector',self.vpartition','type','node'); - self.epartition=project3d(md,'vector',self.epartition','type','element'); end % }}} function self = qmu(varargin) % {{{ @@ -97,29 +96,4 @@ end end - if ~isempty(md.qmu.vpartition) & ~any(isnan(md.qmu.vpartition)), - if size(md.qmu.vpartition,1)~=md.mesh.numberofvertices - md = checkmessage(md,['user supplied vertex partition for qmu analysis should have size md.mesh.numberofvertices x 1']); - end - if min(md.qmu.vpartition)~=0, - md = checkmessage(md,['vertex partition vector not indexed from 0 on']); - end - if max(md.qmu.vpartition)>=md.qmu.numberofpartitions, - md = checkmessage(md,['for qmu analysis, vertex partitioning vector cannot go over npart, number of partition areas']); - end - end - if ~isempty(md.qmu.epartition) & ~any(isnan(md.qmu.epartition)), - if size(md.qmu.epartition,1)~=md.mesh.numberofelements, - md = checkmessage(md,['user supplied element partition for qmu analysis should have size md.mesh.numberofelements x 1']); - end - if min(md.qmu.epartition)~=0, - md = checkmessage(md,['element partition vector not indexed from 0 on']); - end - if max(md.qmu.epartition)>=md.qmu.numberofpartitions, - md = checkmessage(md,['for qmu analysis, element partitioning vector cannot go over npart, number of partition areas']); - end - end - if isempty(md.qmu.vpartition) | any(isnan(md.qmu.vpartition)) | isempty(md.qmu.epartition) | any(isnan(md.qmu.epartition)), - md = checkmessage(md,['for qmu analysis, both an element and partitioning vectors need to be supplied with no nan values! One can be defaulted to all zeros.']); - end %go through variables and check for consistency: @@ -198,7 +172,5 @@ end end - fielddisplay(self,'vpartition','user provided mesh partitioning (vertex based)'); - fielddisplay(self,'epartition','user provided mesh partitioning (element based)'); - fielddisplay(self,'numberofpartitions','number of partitions for semi-discrete qmu') + fielddisplay(self,'variablepartitions',''); fielddisplay(self,'variabledescriptors',''); fielddisplay(self,'responsedescriptors',''); @@ -223,4 +195,5 @@ WriteData(fid,prefix,'object',self,'fieldname','numberofresponses','format','Integer'); WriteData(fid,prefix,'object',self,'fieldname','variabledescriptors','format','StringArray'); + WriteData(fid,prefix,'object',self,'fieldname','variablepartitions','format','MatArray'); WriteData(fid,prefix,'object',self,'fieldname','responsedescriptors','format','StringArray'); if ~isempty(self.mass_flux_segments), Index: /issm/trunk-jpl/src/m/qmu/preqmu.m =================================================================== --- /issm/trunk-jpl/src/m/qmu/preqmu.m (revision 24987) +++ /issm/trunk-jpl/src/m/qmu/preqmu.m (revision 24988) @@ -87,7 +87,22 @@ end +%build a MatArray of variable partitions: +variable_fieldnames=fieldnames(md.qmu.variables(ivar)); +variablepartitions={}; +for i=1:length(variable_fieldnames), + field_name=variable_fieldnames{i}; + fieldvariable=md.qmu.variables(ivar).(field_name); + if fieldvariable.isscaled(); + variablepartitions{end+1}=fieldvariable.partition; + else + variablepartitions{end+1}=[]; + end +end + + %register the fields that will be needed by the Qmu model. md.qmu.numberofresponses=numresponses; md.qmu.variabledescriptors=variabledescriptors; +md.qmu.variablepartitions=variablepartitions; md.qmu.responsedescriptors=responsedescriptors; Index: /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.m =================================================================== --- /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.m (revision 24987) +++ /issm/trunk-jpl/src/m/qmu/setupdesign/QmuSetupVariables.m (revision 24988) @@ -9,13 +9,19 @@ %ok, key off according to type of descriptor: if strncmp(descriptor,'scaled_',7), - %we have a scaled variable, expand it over the partition. + %we have a scaled variable, expand it over the partition. First recover the partition: + partition=variables.partition; + %figure out number of partitions: + npart=qmupart2npart(partition) if isa(variables,'uniform_uncertain'), - if (length(variables.lower)>md.qmu.numberofpartitions || length(variables.upper)>md.qmu.numberofpartitions) - error('QmuSetupDesign error message: stddev should be either a scalar or a ''npart'' length vector'); + nlower=length(variables.lower); nupper=length(variables.upper); + if (nlower ~= npart || nupper ~=npart), + error('QmuSetupVariables error message: upper and lower fields should be same size as the number of partitions'); end elseif isa(variables,'normal_uncertain'), - if length(variables.stddev)>md.qmu.numberofpartitions, - error('QmuSetupDesign error message: stddev should be either a scalar or a ''npart'' length vector'); + nstddev=length(variables.stddev); + nmean=length(variables.mean); + if (nstddev ~= npart || nmean ~=npart), + error('QmuSetupVariables error message: stddev and mean fields should be same size as the number of partitions'); end end @@ -23,22 +29,13 @@ %ok, dealing with semi-discrete distributed variable. Distribute according to how many %partitions we want - for j=1:md.qmu.numberofpartitions + for j=1:npart, dvar(end+1) =variables; dvar(end ).descriptor=sprintf('%s_%d',variables.descriptor,j); if isa(variables,'uniform_uncertain'), - if length(variables.lower)>1, - dvar(end ).lower=variables.lower(j); - end - if length(variables.upper)>1, - dvar(end ).upper=variables.upper(j); - end + dvar(end ).lower=variables.lower(j); + dvar(end ).upper=variables.upper(j); elseif isa(variables,'normal_uncertain'), - if length(variables.stddev)>1, - dvar(end ).stddev=variables.stddev(j); - end - if length(variables.mean)>1, - dvar(end ).mean=variables.mean(j); - end - + dvar(end ).stddev=variables.stddev(j); + dvar(end ).mean=variables.mean(j); end end