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added: allow specifying a function for beta

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t holds the adaptive step number. this allows for
flexible specification of how much to refine at each step.
This commit is contained in:
Arne Morten Kvarving 2020-07-15 10:23:03 +02:00
parent 4faf645010
commit 5a671fa594
2 changed files with 32 additions and 15 deletions
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43
src/SIM/AdaptiveSetup.C
View File

@ -16,6 +16,7 @@
#include "SIMenums.h"
#include "ASMbase.h"
#include "ASMunstruct.h"
#include "Functions.h"
#include "IntegrandBase.h"
#include "Utilities.h"
#include "IFEM.h"
@ -33,6 +34,7 @@ AdaptiveSetup::AdaptiveSetup (SIMoutput& sim, bool sa) : model(sim), alone(sa)
// Default grid adaptation parameters
linIndep = false;
beta = 10.0;
betaFunc = nullptr;
errTol = 1.0;
rCond = 1.0;
condLimit = 1.0e12;
@ -52,6 +54,12 @@ AdaptiveSetup::AdaptiveSetup (SIMoutput& sim, bool sa) : model(sim), alone(sa)
}
AdaptiveSetup::~AdaptiveSetup()
{
delete betaFunc;
}
bool AdaptiveSetup::parse (const TiXmlElement* elem)
{
if (strcasecmp(elem->Value(),"adaptive"))
@ -114,7 +122,13 @@ bool AdaptiveSetup::parse (const TiXmlElement* elem)
} else if ((value = utl::getValue(child,"use_sub_norm")))
adNorm = atoi(value);
else if ((value = utl::getValue(child,"beta"))) {
beta = atof(value);
std::string functype;
utl::getAttribute(child,"functype",functype);
if (functype == "expression") {
IFEM::cout << "\tRefinement function: ";
betaFunc = utl::parseTimeFunc(value,functype,1.0);
} else
beta = atof(value);
std::string type;
utl::getAttribute(child,"type",type,true);
if (type.compare("threshold") == 0 || type.compare("threashold") == 0)
@ -133,7 +147,8 @@ bool AdaptiveSetup::parse (const TiXmlElement* elem)
threshold = SYMMETRIZED;
utl::getAttribute(child,"eps",symmEps);
}
IFEM::cout <<"\tRefinement percentage: "<< beta <<" type="<< threshold;
IFEM::cout <<"\tRefinement percentage: "<< (betaFunc ? (*betaFunc)(1) : beta)
<<" type="<< threshold;
if (threshold == SYMMETRIZED)
IFEM::cout <<" (eps = "<< symmEps <<")";
IFEM::cout << std::endl;
@ -283,7 +298,7 @@ int AdaptiveSetup::calcRefinement (LR::RefineData& prm, int iStep,
}
prm.options.reserve(8);
prm.options.push_back(beta);
prm.options.push_back(betaFunc ? (*betaFunc)(iStep-1) : beta);
prm.options.push_back(knot_mult);
prm.options.push_back(scheme);
prm.options.push_back(linIndep);
@ -301,7 +316,7 @@ int AdaptiveSetup::calcRefinement (LR::RefineData& prm, int iStep,
return -2;
}
IFEM::cout <<"\nRefining by increasing solution space by "<< beta
IFEM::cout <<"\nRefining by increasing solution space by "<< prm.options[0]
<<" percent."<< std::endl;
prm.errors.resize(thePatch->getNoRefineElms());
dynamic_cast<ASMunstruct*>(thePatch)->remapErrors(prm.errors,refIn,true);
@ -370,19 +385,19 @@ int AdaptiveSetup::calcRefinement (LR::RefineData& prm, int iStep,
double limit, sumErr = 0.0, curErr = 0.0;
switch (threshold) {
case MAXIMUM: // beta percent of max error (less than 100%)
limit = error.front().first * beta*0.01;
limit = error.front().first * prm.options[0]*0.01;
break;
case AVERAGE: // beta percent of avg error (typical 100%)
for (const DblIdx& e : error) sumErr += e.first;
limit = (sumErr/error.size()) * beta*0.01;
limit = (sumErr/error.size()) * prm.options[0]*0.01;
break;
case MINIMUM: // beta percent of min error (more than 100%)
limit = error.back().first * beta*0.01;
limit = error.back().first * prm.options[0]*0.01;
break;
case DORFEL:
limit = error.back().first;
for (const DblIdx& e : error) sumErr += e.first;
sumErr *= beta*0.01;
sumErr *= prm.options[0]*0.01;
for (const DblIdx& e : error)
if (curErr < sumErr)
curErr += e.first;
@ -397,7 +412,7 @@ int AdaptiveSetup::calcRefinement (LR::RefineData& prm, int iStep,
}
if (threshold == NONE || threshold == SYMMETRIZED)
refineSize = ceil(error.size()*beta/100.0);
refineSize = ceil(error.size()*prm.options[0]/100.0);
else
refineSize = std::upper_bound(error.begin(), error.end(), DblIdx(limit,0),
std::greater_equal<DblIdx>()) - error.begin();
@ -433,22 +448,22 @@ int AdaptiveSetup::calcRefinement (LR::RefineData& prm, int iStep,
switch (threshold) {
case NONE:
IFEM::cout << beta <<"% of all "<< str;
IFEM::cout << prm.options[0] <<"% of all "<< str;
break;
case SYMMETRIZED:
IFEM::cout << 100.0*refineSize/error.size() <<"% of all "<< str;
break;
case MAXIMUM:
IFEM::cout << beta <<"% of max error ("<< limit <<")";
IFEM::cout << prm.options[0] <<"% of max error ("<< limit <<")";
break;
case AVERAGE:
IFEM::cout << beta <<"% of average error ("<< limit <<")";
IFEM::cout << prm.options[0] <<"% of average error ("<< limit <<")";
break;
case MINIMUM:
IFEM::cout << beta <<"% of min error ("<< limit <<")";
IFEM::cout << prm.options[0] <<"% of min error ("<< limit <<")";
break;
case DORFEL:
IFEM::cout << beta <<"% of total error ("<< limit <<")";
IFEM::cout << prm.options[0] <<"% of total error ("<< limit <<")";
break;
default:
break;

4
src/SIM/AdaptiveSetup.h
View File

@ -16,6 +16,7 @@
#include "MatVec.h"
class ScalarFunc;
class SIMoutput;
class TiXmlElement;
namespace LR { struct RefineData; }
@ -39,7 +40,7 @@ public:
//! \param[in] sa If \e true, this is a stand-alone driver
explicit AdaptiveSetup(SIMoutput& sim, bool sa = true);
//! \brief Empty destructor.
virtual ~AdaptiveSetup() {}
virtual ~AdaptiveSetup();
//! \brief Sets the norm group/index of the norm to base mesh adaptation on.
void setAdaptationNorm(size_t g, size_t i = 0) { adaptor = g; adNorm = i; }
@ -96,6 +97,7 @@ private:
bool alone; //!< If \e false, this class is wrapped by SIMSolver
bool linIndep; //!< Test mesh for linear independence after refinement
double beta; //!< Refinement percentage in each step
ScalarFunc* betaFunc;//!< Beta as a function
double errTol; //!< Global error stop tolerance
double condLimit; //!< Upper limit on condition number
int maxStep; //!< Maximum number of adaptive refinements