bool HesperisIO::AddTransform(const MDagPath & path, HesperisFile * file, const std::string & beheadName)
{
MFnDagNode fdg(path);
if(fdg.parentCount() < 1) return false;
MGlobal::displayInfo(MString("hes io add transform ")+path.fullPathName());
MObject oparent = fdg.parent(0);
MFnDagNode fp(oparent);
MDagPath pp;
fp.getPath(pp);
AddTransform(pp, file, beheadName);
std::string nodeName = path.fullPathName().asChar();
if(beheadName.size() > 1) SHelper::behead(nodeName, beheadName);
// todo extract tm
file->addTransform(nodeName, new BaseTransform);
return true;
}
bool HesperisIO::AddTransform(const MDagPath & path, HesperisFile * file )
{
const std::string nodeName = H5PathNameTo(path);
if(nodeName.size() < 2 ) return false;
MFnDagNode fdg(path);
if(fdg.parentCount() < 1) return false;
// AHelper::Info<MString>("hes io add transform ", path.fullPathName());
MObject oparent = fdg.parent(0);
MFnDagNode fp(oparent);
MDagPath pp;
fp.getPath(pp);
AddTransform(pp, file);
// todo extract tm
file->addTransform( nodeName, new BaseTransform );
return true;
}
// Validate gradients with finite differences.
void GPCMOptimization::validateGradients(
GPCMOptimizable *model // Model to validate gradients for.
)
{
// Compute gradient.
clearGradients();
double center = model->recompute(true);
double centerc = 0.0;
packGradients(x,g);
// std::cout << x << std::endl;
// Optionally compute the constraint gradient.
VectorXd cg(g.rows());
if (model->hasConstraint())
{
clearGradients();
centerc = model->recomputeConstraint(true);
packGradients(x,cg);
}
// Take samples to evaluate finite differences.
VectorXd pt = x;
VectorXd fdg(params);
VectorXd fdgc(params);
for (int i = 0; i < params; i++)
{
// Evaluate upper and lower values.
pt.noalias() = x + VectorXd::Unit(params,i)*FD_EPSILON;
unpackVariables(pt);
double valp = model->recompute(false);
double valpc = model->recomputeConstraint(false);
pt.noalias() = x - VectorXd::Unit(params,i)*FD_EPSILON;
unpackVariables(pt);
double valm = model->recompute(false);
double valmc = model->recomputeConstraint(false);
fdg(i) = 0.5*(valp-valm)/FD_EPSILON;
fdgc(i) = 0.5*(valpc-valmc)/FD_EPSILON;
DBPRINTLN("Computed finite difference for dimension " << i << " of " << params << ": " << fdg(i));
}
// std::cout << x << std::endl;
// Reset variables.
unpackVariables(x);
// Construct gradient names.
std::vector<std::string> varname(x.rows());
for (std::vector<GPCMOptVariable>::iterator itr = variables.begin();
itr != variables.end(); itr++)
{
for (int i = itr->getIndex(); i < itr->getIndex()+itr->getParamCount(); i++)
{
varname[i] = itr->getName();
if (itr->getParamCount() > 1)
varname[i] += std::string(" ") +
boost::lexical_cast<std::string>(i-itr->getIndex());
}
}
// Print gradients.
int idx;
DBPRINTLN("True gradient / finite-difference gradient:");
for (int i = 0; i < params; i++)
{
if (model->hasConstraint())
{
DBPRINTLN(std::setw(10) << g(i) << " " <<
std::setw(10) << fdg(i) <<
std::setw(10) << cg(i) << " " <<
std::setw(10) << fdgc(i) <<
std::setw(10) << "(" << x(i) << ")" << " " << varname[i]);
}
else
{
DBPRINTLN(std::setw(10) << g(i) << " " <<
std::setw(10) << fdg(i) <<
std::setw(10) << "(" << x(i) << ")" << " " << varname[i]);
}
}
// Check objective gradient.
double maxDiff = (g-fdg).array().abs().matrix().maxCoeff(&idx);
if (maxDiff >= 0.1)
DBWARNING("Gradients appear significantly different!");
DBPRINTLN("Max difference: " << maxDiff);
DBPRINTLN("Max difference at index " << idx << ":" << std::endl << std::setw(10) << g(idx)
<< " " << std::setw(10) << fdg(idx) << " " << varname[idx]);
if (model->hasConstraint())
{
// Check constraint gradient.
maxDiff = (cg-fdgc).array().abs().matrix().maxCoeff(&idx);
if (maxDiff >= 0.1)
DBWARNING("Constraint gradients appear significantly different!");
DBPRINTLN("Max constraint difference: " << maxDiff);
DBPRINTLN("Max constraint difference at index " << idx << ":" << std::endl << std::setw(10) << cg(idx)
<< " " << std::setw(10) << fdgc(idx) << " " << varname[idx]);
}
}
