/* evaluate the integrals for the given m[] using the cached values in vc,
storing the integrals in val[], the error estimate in err[], and the
dimension to subdivide next (the largest error contribution) in *mi */
static void eval_integral(valcache vc, const unsigned *m,
unsigned fdim, unsigned dim, double V,
unsigned *mi, double *val, double *err, double *val1)
{
double maxerr = 0;
unsigned i, j;
evals(vc, m, dim, fdim, dim, V, val);
/* error estimates along each dimension by comparing val with
lower-order rule in that dimension; overall (conservative)
error estimate from maximum error of lower-order rules. */
memset(err, 0, sizeof(double) * fdim);
*mi = 0;
for (i = 0; i < dim; ++i) {
double emax = 0;
evals(vc, m, i, fdim, dim, V, val1);
for (j = 0; j < fdim; ++j) {
double e = fabs(val[j] - val1[j]);
if (e > emax) emax = e;
if (e > err[j]) err[j] = e;
}
if (emax > maxerr) {
maxerr = emax;
*mi = i;
}
}
/* printf("eval: %g +/- %g (dim %u)\n", val[0], err[0], *mi); */
}
vec PolyTrajectoryGenerator::evaluateByCoefficientsMultiple(vec x, int sampleCount, vec coeff) {
int coeffDegree = this->getBasisFunctionCount();
vec evals(sampleCount);
for(int i = 0; i < sampleCount; ++i) {
evals(i) = evaluateByCoefficientsSingle(x(i), coeff);
}
return evals;
}
tensor2D eigenVectors(const tensor2D& t)
{
vector2D evals(eigenValues(t));
tensor2D evs
(
eigenVector(t, evals.x()),
eigenVector(t, evals.y())
);
return evs;
}
tensor eigenVectors(const symmTensor& t)
{
vector evals(eigenValues(t));
tensor evs
(
eigenVector(t, evals.x()),
eigenVector(t, evals.y()),
eigenVector(t, evals.z())
);
return evs;
}
sexpr import(const std::vector<sexpr>& a, environment* env)
{
if (a.size() < 1)
throw std::invalid_argument("<import>: Wrong number of arguments");
auto path = a[0].get<lisp_string>();
std::ifstream file(path);
if (!file)
throw std::invalid_argument("<import>: File not found: " + path);
std::regex reg("([;]{2,}.*$)");
std::string line;
std::string content;
while (std::getline(file, line)) {
content += std::regex_replace(line, reg, "");
}
return evals(parse(tokenize(content)), env);
}
Vector3f FlyingLayer::RotationMatrixToVector(const Matrix3x3f& rotationMatrix) const {
static const float epsilon = 1e-6;
const float cs = (rotationMatrix.trace() - 1.0)*0.5;
if (cs > 1.0 - epsilon) {
return Vector3f::Zero();
} else if (cs < epsilon - 1.0) {
Eigen::SelfAdjointEigenSolver<Matrix3x3f> evals(rotationMatrix, Eigen::ComputeEigenvectors);
Vector3f rotVector = evals.eigenvectors().col(2).transpose();
return rotVector.normalized()*M_PI;
} else {
const float sn = std::sqrt(1.0 - cs*cs);
const float angle = std::acos(cs);
const float multiplier = angle * 0.5 / sn;
return Vector3f((rotationMatrix(2, 1) - rotationMatrix(1, 2))*multiplier,
(rotationMatrix(0, 2) - rotationMatrix(2, 0))*multiplier,
(rotationMatrix(1, 0) - rotationMatrix(0, 1))*multiplier);
}
}
EigenTypes::Vector3f MathUtility::RotationMatrixToVector(const EigenTypes::Matrix3x3f& rotationMatrix) {
static const float epsilon = 1e-6f;
const float cs = (rotationMatrix.trace() - 1.0f)*0.5f;
if (cs > 1.0f - epsilon) {
return EigenTypes::Vector3f::Zero();
} else if (cs < epsilon - 1.0f) {
Eigen::SelfAdjointEigenSolver<EigenTypes::Matrix3x3f> evals(rotationMatrix, Eigen::ComputeEigenvectors);
EigenTypes::Vector3f rotVector = evals.eigenvectors().col(2).transpose();
return rotVector.normalized()*(float)M_PI;
} else {
const float sn = std::sqrt(1.0f - cs*cs);
const float angle = std::acos(cs);
const float multiplier = angle * 0.5f / sn;
return EigenTypes::Vector3f((rotationMatrix(2, 1) - rotationMatrix(1, 2))*multiplier,
(rotationMatrix(0, 2) - rotationMatrix(2, 0))*multiplier,
(rotationMatrix(1, 0) - rotationMatrix(0, 1))*multiplier);
}
}
/**
* \ingroup eigen
* Eigenvectors
* \param m \f$m\f$
* \return a variable matrix with the
* eigenvectors of \f$m\f$ stored in its columns.
*/
dmatrix eigenvectors(const dmatrix &m)
{
if (m.rowsize() != m.colsize())
{
cerr <<
"error -- non square matrix passed to dmatrix eigenvectors(const dmatrix& m)\n";
ad_exit(1);
}
int rmin = m.rowmin();
int rmax = m.rowmax();
dmatrix evecs(rmin, rmax, rmin, rmax);
dvector evals(rmin, rmax);
eigens(m, evecs, evals);
return evecs;
}
vector<EquityResult> ShowdownEnumerator::calculateEquity (const vector<CardDistribution>& dists,
const CardSet& board,
boost::shared_ptr<PokerHandEvaluator> peval) const
{
if (peval.get() == NULL)
throw runtime_error("ShowdownEnumerator, null evaluator");
assert(dists.size() > 1);
const size_t ndists = dists.size();
vector<EquityResult> results(ndists, EquityResult());
size_t handsize = peval->handSize();
// the dsizes vector is a list of the sizes of the player hand
// distributions
vector<size_t> dsizes;
for (size_t i=0; i<ndists; i++)
{
assert(dists[i].size() > 0);
dsizes.push_back (dists[i].size());
}
// need to figure out the board stuff, we'll be rolling the board into
// the partitions to make enumeration easier down the line.
size_t nboards = 0;
size_t boardsize = peval->boardSize();
if (boardsize > 0)
nboards++;
// for the most part, these are allocated here to avoid contant stack
// reallocation as we cycle through the inner loops
SimpleDeck deck;
CardSet dead;
double weight;
vector<CardSet> ehands (ndists+nboards);
vector<size_t> parts (ndists+nboards);
vector<CardSet> cardPartitions (ndists+nboards);
vector<PokerHandEvaluation> evals (ndists); // NO BOARD
// copy quickness
CardSet * copydest = &ehands[0];
CardSet * copysrc = &cardPartitions[0];
size_t ncopy = (ndists+nboards)*sizeof(CardSet);
Odometer o(dsizes);
do
{
// colect all the cards being used by the players, skip out in the
// case of card duplication
bool disjoint = true;
dead.clear ();
weight = 1.0;
for (size_t i=0; i<ndists+nboards; i++)
{
if (i<ndists)
{
cardPartitions[i] = dists[i][o[i]];
parts[i] = handsize-cardPartitions[i].size();
weight *= dists[i][cardPartitions[i]];
}
else
{
// this allows us to have board distributions in the future
cardPartitions[i] = board;
parts[i] = boardsize-cardPartitions[i].size();
}
disjoint = disjoint && dead.disjoint(cardPartitions[i]);
dead |= cardPartitions[i];
}
if (disjoint)
{
deck.reset ();
deck.remove (dead);
PartitionEnumerator2 pe(deck.size(), parts);
do
{
// we use memcpy here for a little speed bonus
memcpy (copydest, copysrc, ncopy);
for (size_t p=0; p<ndists+nboards; p++)
ehands[p] |= deck.peek(pe.getMask (p));
// TODO: do we need this if/else, or can we just use the if
// clause? A: need to rework tracking of whether a board is needed
if (nboards > 0)
peval->evaluateShowdown (ehands, ehands[ndists], evals, results, weight);
else
peval->evaluateShowdown (ehands, board, evals, results, weight);
}
while (pe.next ());
}
}
while (o.next ());
return results;
}
void
MultiAppProjectionTransfer::execute()
{
_console << "Beginning projection transfer " << name() << std::endl;
getAppInfo();
////////////////////
// We are going to project the solutions by solving some linear systems. In
// order to assemble the systems, we need to evaluate the "from" domain
// solutions at quadrature points in the "to" domain. Some parallel
// communication is necessary because each processor doesn't necessarily have
// all the "from" information it needs to set its "to" values. We don't want
// to use a bunch of big all-to-all broadcasts, so we'll use bounding boxes to
// figure out which processors have the information we need and only
// communicate with those processors.
//
// Each processor will
// 1. Check its local quadrature points in the "to" domains to see which
// "from" domains they might be in.
// 2. Send quadrature points to the processors with "from" domains that might
// contain those points.
// 3. Recieve quadrature points from other processors, evaluate its mesh
// functions at those points, and send the values back to the proper
// processor
// 4. Recieve mesh function evaluations from all relevant processors and
// decide which one to use at every quadrature point (the lowest global app
// index always wins)
// 5. And use the mesh function evaluations to assemble and solve an L2
// projection system on its local elements.
////////////////////
////////////////////
// For every combination of global "from" problem and local "to" problem, find
// which "from" bounding boxes overlap with which "to" elements. Keep track
// of which processors own bounding boxes that overlap with which elements.
// Build vectors of quadrature points to send to other processors for mesh
// function evaluations.
////////////////////
// Get the bounding boxes for the "from" domains.
std::vector<MeshTools::BoundingBox> bboxes = getFromBoundingBoxes();
// Figure out how many "from" domains each processor owns.
std::vector<unsigned int> froms_per_proc = getFromsPerProc();
std::vector<std::vector<Point> > outgoing_qps(n_processors());
std::vector<std::map<std::pair<unsigned int, unsigned int>, unsigned int> > element_index_map(n_processors());
// element_index_map[i_to, element_id] = index
// outgoing_qps[index] is the first quadrature point in element
if (! _qps_cached)
{
for (unsigned int i_to = 0; i_to < _to_problems.size(); i_to++)
{
MeshBase & to_mesh = _to_meshes[i_to]->getMesh();
LinearImplicitSystem & system = * _proj_sys[i_to];
FEType fe_type = system.variable_type(0);
std::unique_ptr<FEBase> fe(FEBase::build(to_mesh.mesh_dimension(), fe_type));
QGauss qrule(to_mesh.mesh_dimension(), fe_type.default_quadrature_order());
fe->attach_quadrature_rule(&qrule);
const std::vector<Point> & xyz = fe->get_xyz();
MeshBase::const_element_iterator el = to_mesh.local_elements_begin();
const MeshBase::const_element_iterator end_el = to_mesh.local_elements_end();
unsigned int from0 = 0;
for (processor_id_type i_proc = 0;
i_proc < n_processors();
from0 += froms_per_proc[i_proc], i_proc++)
{
for (el = to_mesh.local_elements_begin(); el != end_el; el++)
{
const Elem* elem = *el;
fe->reinit (elem);
bool qp_hit = false;
for (unsigned int i_from = 0;
i_from < froms_per_proc[i_proc] && ! qp_hit; i_from++)
{
for (unsigned int qp = 0;
qp < qrule.n_points() && ! qp_hit; qp ++)
{
Point qpt = xyz[qp];
if (bboxes[from0 + i_from].contains_point(qpt + _to_positions[i_to]))
qp_hit = true;
}
}
if (qp_hit)
{
// The selected processor's bounding box contains at least one
// quadrature point from this element. Send all qps from this element
// and remember where they are in the array using the map.
std::pair<unsigned int, unsigned int> key(i_to, elem->id());
element_index_map[i_proc][key] = outgoing_qps[i_proc].size();
for (unsigned int qp = 0; qp < qrule.n_points(); qp ++)
{
Point qpt = xyz[qp];
outgoing_qps[i_proc].push_back(qpt + _to_positions[i_to]);
}
}
}
}
}
if (_fixed_meshes)
_cached_index_map = element_index_map;
}
else
{
element_index_map = _cached_index_map;
}
////////////////////
// Request quadrature point evaluations from other processors and handle
// requests sent to this processor.
////////////////////
// Non-blocking send quadrature points to other processors.
std::vector<Parallel::Request> send_qps(n_processors());
if (! _qps_cached)
for (processor_id_type i_proc = 0; i_proc < n_processors(); i_proc++)
if (i_proc != processor_id())
_communicator.send(i_proc, outgoing_qps[i_proc], send_qps[i_proc]);
// Get the local bounding boxes.
std::vector<MeshTools::BoundingBox> local_bboxes(froms_per_proc[processor_id()]);
{
// Find the index to the first of this processor's local bounding boxes.
unsigned int local_start = 0;
for (processor_id_type i_proc = 0;
i_proc < n_processors() && i_proc != processor_id();
i_proc++)
local_start += froms_per_proc[i_proc];
// Extract the local bounding boxes.
for (unsigned int i_from = 0; i_from < froms_per_proc[processor_id()]; i_from++)
local_bboxes[i_from] = bboxes[local_start + i_from];
}
// Setup the local mesh functions.
std::vector<MeshFunction *> local_meshfuns(froms_per_proc[processor_id()], NULL);
for (unsigned int i_from = 0; i_from < _from_problems.size(); i_from++)
{
FEProblemBase & from_problem = *_from_problems[i_from];
MooseVariable & from_var = from_problem.getVariable(0, _from_var_name);
System & from_sys = from_var.sys().system();
unsigned int from_var_num = from_sys.variable_number(from_var.name());
MeshFunction * from_func = new MeshFunction(from_problem.es(),
*from_sys.current_local_solution, from_sys.get_dof_map(), from_var_num);
from_func->init(Trees::ELEMENTS);
from_func->enable_out_of_mesh_mode(OutOfMeshValue);
local_meshfuns[i_from] = from_func;
}
// Recieve quadrature points from other processors, evaluate mesh frunctions
// at those points, and send the values back.
std::vector<Parallel::Request> send_evals(n_processors());
std::vector<Parallel::Request> send_ids(n_processors());
std::vector<std::vector<Real> > outgoing_evals(n_processors());
std::vector<std::vector<unsigned int> > outgoing_ids(n_processors());
std::vector<std::vector<Real> > incoming_evals(n_processors());
std::vector<std::vector<unsigned int> > incoming_app_ids(n_processors());
for (processor_id_type i_proc = 0; i_proc < n_processors(); i_proc++)
{
// Use the cached qps if they're available.
std::vector<Point> incoming_qps;
if (! _qps_cached)
{
if (i_proc == processor_id())
incoming_qps = outgoing_qps[i_proc];
else
_communicator.receive(i_proc, incoming_qps);
// Cache these qps for later if _fixed_meshes
if (_fixed_meshes)
_cached_qps[i_proc] = incoming_qps;
}
else
{
incoming_qps = _cached_qps[i_proc];
}
outgoing_evals[i_proc].resize(incoming_qps.size(), OutOfMeshValue);
if (_direction == FROM_MULTIAPP)
outgoing_ids[i_proc].resize(incoming_qps.size(), libMesh::invalid_uint);
for (unsigned int qp = 0; qp < incoming_qps.size(); qp++)
{
Point qpt = incoming_qps[qp];
// Loop until we've found the lowest-ranked app that actually contains
// the quadrature point.
for (unsigned int i_from = 0; i_from < _from_problems.size(); i_from++)
{
if (local_bboxes[i_from].contains_point(qpt))
{
outgoing_evals[i_proc][qp] = (* local_meshfuns[i_from])(qpt - _from_positions[i_from]);
if (_direction == FROM_MULTIAPP)
outgoing_ids[i_proc][qp] = _local2global_map[i_from];
}
}
}
if (i_proc == processor_id())
{
incoming_evals[i_proc] = outgoing_evals[i_proc];
if (_direction == FROM_MULTIAPP)
incoming_app_ids[i_proc] = outgoing_ids[i_proc];
}
else
{
_communicator.send(i_proc, outgoing_evals[i_proc], send_evals[i_proc]);
if (_direction == FROM_MULTIAPP)
_communicator.send(i_proc, outgoing_ids[i_proc], send_ids[i_proc]);
}
}
////////////////////
// Gather all of the qp evaluations and pick out the best ones for each qp.
////////////////////
for (processor_id_type i_proc = 0; i_proc < n_processors(); i_proc++)
{
if (i_proc == processor_id())
continue;
_communicator.receive(i_proc, incoming_evals[i_proc]);
if (_direction == FROM_MULTIAPP)
_communicator.receive(i_proc, incoming_app_ids[i_proc]);
}
std::vector<std::vector<Real> > final_evals(_to_problems.size());
std::vector<std::map<unsigned int, unsigned int> > trimmed_element_maps(_to_problems.size());
for (unsigned int i_to = 0; i_to < _to_problems.size(); i_to++)
{
MeshBase & to_mesh = _to_meshes[i_to]->getMesh();
LinearImplicitSystem & system = * _proj_sys[i_to];
FEType fe_type = system.variable_type(0);
std::unique_ptr<FEBase> fe(FEBase::build(to_mesh.mesh_dimension(), fe_type));
QGauss qrule(to_mesh.mesh_dimension(), fe_type.default_quadrature_order());
fe->attach_quadrature_rule(&qrule);
const std::vector<Point> & xyz = fe->get_xyz();
MeshBase::const_element_iterator el = to_mesh.local_elements_begin();
const MeshBase::const_element_iterator end_el = to_mesh.local_elements_end();
for (el = to_mesh.active_local_elements_begin(); el != end_el; el++)
{
const Elem* elem = *el;
fe->reinit (elem);
bool element_is_evaled = false;
std::vector<Real> evals(qrule.n_points(), 0.);
for (unsigned int qp = 0; qp < qrule.n_points(); qp++)
{
Point qpt = xyz[qp];
unsigned int lowest_app_rank = libMesh::invalid_uint;
for (unsigned int i_proc = 0; i_proc < n_processors(); i_proc++)
{
// Ignore the selected processor if the element wasn't found in it's
// bounding box.
std::map<std::pair<unsigned int, unsigned int>, unsigned int> & map = element_index_map[i_proc];
std::pair<unsigned int, unsigned int> key(i_to, elem->id());
if (map.find(key) == map.end())
continue;
unsigned int qp0 = map[key];
// Ignore the selected processor if it's app has a higher rank than the
// previously found lowest app rank.
if (_direction == FROM_MULTIAPP)
if (incoming_app_ids[i_proc][qp0 + qp] >= lowest_app_rank)
continue;
// Ignore the selected processor if the qp was actually outside the
// processor's subapp's mesh.
if (incoming_evals[i_proc][qp0 + qp] == OutOfMeshValue)
continue;
// This is the best meshfunction evaluation so far, save it.
element_is_evaled = true;
evals[qp] = incoming_evals[i_proc][qp0 + qp];
}
}
// If we found good evaluations for any of the qps in this element, save
// those evaluations for later.
if (element_is_evaled)
{
trimmed_element_maps[i_to][elem->id()] = final_evals[i_to].size();
for (unsigned int qp = 0; qp < qrule.n_points(); qp++)
final_evals[i_to].push_back(evals[qp]);
}
}
}
////////////////////
// We now have just one or zero mesh function values at all of our local
// quadrature points. Stash those values (and a map linking them to element
// ids) in the equation systems parameters and project the solution.
////////////////////
for (unsigned int i_to = 0; i_to < _to_problems.size(); i_to++)
{
_to_es[i_to]->parameters.set<std::vector<Real>*>("final_evals") = & final_evals[i_to];
_to_es[i_to]->parameters.set<std::map<unsigned int, unsigned int>*>("element_map") = & trimmed_element_maps[i_to];
projectSolution(i_to);
_to_es[i_to]->parameters.set<std::vector<Real>*>("final_evals") = NULL;
_to_es[i_to]->parameters.set<std::map<unsigned int, unsigned int>*>("element_map") = NULL;
}
for (unsigned int i = 0; i < _from_problems.size(); i++)
delete local_meshfuns[i];
// Make sure all our sends succeeded.
for (processor_id_type i_proc = 0; i_proc < n_processors(); i_proc++)
{
if (i_proc == processor_id())
continue;
if (! _qps_cached)
send_qps[i_proc].wait();
send_evals[i_proc].wait();
if (_direction == FROM_MULTIAPP)
send_ids[i_proc].wait();
}
if (_fixed_meshes)
_qps_cached = true;
_console << "Finished projection transfer " << name() << std::endl;
}
void exec(const char *str, char *err)
{
// this function executes a given instruction.
// all important functions are done from here.
int eval(const char *str);
void * evals(const char *str, const char data_type);
strcpy(err,""); /* empty error container string */
char *exp = NULL; /* string containing evaluation expression */
char *asgn = NULL; /* string containing assignment variable name */
char data_type = '\0'; /* data type of variable to evaluate */
/* assignment analysis & error handling */
if((asgn=(char *)(malloc(sizeof(char)*
(strlen(str)+1))))==NULL) allocerr(); *asgn='\0';
if(prechar(asgn,str,"=")=='=') /* check for = operator */
{
/* ok, it is a variable assignment */
strtrm(asgn,' ','S');
if((*asgn==0)||(strlen(asgn)==0))
{
/* error: assignment string is empty */
strcpy(err,"Assignment variable is not specified.");
free(asgn);
return;
}
else /* assignment string is NOT empty */
{
char isid[2] = {'\0','\0'};
/* check identifier validity*/
isid[0] = id_check(asgn);
if(isid[0]!=0) /* error: is not an identifier */
{
if(isid[0]==1) /* error: var name starts with a number */
{
strcpy(err,"Variable name cannot start with a number.");
}
else if(isid[0]==32) /* error: var name contains spaces */
{
strcpy(err,"Variable name cannot contain spaces.");
}
else /* error: var name has illegal chars*/
{
strcpy(err,"Variable name cannot contain [");
strcat(err,isid);
strcat(err,"] character.");
}
free(asgn);
return;
}
else /* success: assignment string is valid */
{
/* allocate string exp */
if((exp=(char *)(malloc(sizeof(char)*
(strlen(str)+1))))==NULL) allocerr(); *exp='\0';
/* now split the equation to get the exp. */
postchar(exp,str,"=");
strtrm(exp,' ','S');
// find out the data type of the assignment
// variable & store it in char data_type
}
}
}
else /* there is no assigment involved */
{
/* allocate string exp */
if((exp=(char *)(malloc(sizeof(char)*
(strlen(str)+1))))==NULL) allocerr(); *exp='\0';
strcpy(exp,str);
strtrm(exp,' ','S');
/* de-allocate asgn */
free(asgn);
asgn = NULL;
}
/* variable assignment */
if(asgn!=NULL)
{
/* possible variable data types */
long *i = NULL; // <- (int)
short *n = NULL; // <- (int-)
char *c = NULL; // <- (chr)
double *d = NULL; // <- (real)
float *f = NULL; // <- (real-)
unsigned long *j = NULL; // <- (int+)
unsigned short *m = NULL; // <- (int-+)
unsigned char *a = NULL; // <- (chr+)
switch(data_type)
{
case 'i':
break;
default:
strcpy(err,"Fatal Data Transfer Error on [");
strcat(err,asgn);
strcat(err,"] variable.");
}
/* de-allocate memory of data type */
switch(data_type)
{
case 'i':
free(i);
i = NULL;
break;
case 'n':
free(n);
n = NULL;
break;
case 'c':
free(c);
c = NULL;
break;
case 'd':
free(d);
d = NULL;
break;
case 'f':
free(f);
f = NULL;
break;
case 'j':
free(j);
j = NULL;
break;
case 'm':
free(m);
m = NULL;
break;
case 'a':
free(a);
a = NULL;
break;
}
/* de-allocate asgn */
free(asgn);
asgn = NULL;
}
else /* no assigment */
{
// if there is no assignment then integer is considered
// to be the default assignment data type for evaluation.
puts("");
int _i=0;
_i = eval(exp);
printf("eval: %d\n",_i);
data_type = 'i';
long *i = NULL;
i=(long *)(evals(exp,data_type));
printf("evals: %ld\n",*i);
free(i);
i = NULL;
void evali(const char *str, char *err, int *eval);
evali(exp,err,&_i);
printf("evali: %d\n",_i);
printf("evali was invoked %d time(s).\n",evali_count);
evali_count = 0;
}
free(exp);
exp = NULL;
}
int
main(int argc, const char *argv[]) {
const char *me;
hestOpt *hopt=NULL;
airArray *mop;
double _tt[6], tt[7], ss, pp[3], qq[4], rot[9], mat1[9], mat2[9], tmp,
evalA[3], evecA[9], evalB[3], evecB[9];
int roots;
mop = airMopNew();
me = argv[0];
hestOptAdd(&hopt, NULL, "m00 m01 m02 m11 m12 m22",
airTypeDouble, 6, 6, _tt, NULL, "symmtric matrix coeffs");
hestOptAdd(&hopt, "p", "vec", airTypeDouble, 3, 3, pp, "0 0 0",
"rotation as P vector");
hestOptAdd(&hopt, "s", "scl", airTypeDouble, 1, 1, &ss, "1.0",
"scaling");
hestParseOrDie(hopt, argc-1, argv+1, NULL,
me, info, AIR_TRUE, AIR_TRUE, AIR_TRUE);
airMopAdd(mop, hopt, (airMopper)hestOptFree, airMopAlways);
airMopAdd(mop, hopt, (airMopper)hestParseFree, airMopAlways);
ELL_6V_COPY(tt + 1, _tt);
tt[0] = 1.0;
TEN_T_SCALE(tt, ss, tt);
ELL_4V_SET(qq, 1, pp[0], pp[1], pp[2]);
ELL_4V_NORM(qq, qq, tmp);
ell_q_to_3m_d(rot, qq);
printf("%s: rot\n", me);
printf(" %g %g %g\n", rot[0], rot[1], rot[2]);
printf(" %g %g %g\n", rot[3], rot[4], rot[5]);
printf(" %g %g %g\n", rot[6], rot[7], rot[8]);
TEN_T2M(mat1, tt);
ell_3m_mul_d(mat2, rot, mat1);
ELL_3M_TRANSPOSE_IP(rot, tmp);
ell_3m_mul_d(mat1, mat2, rot);
TEN_M2T(tt, mat1);
printf("input matrix = \n %g %g %g\n %g %g\n %g\n",
tt[1], tt[2], tt[3], tt[4], tt[5], tt[6]);
printf("================== tenEigensolve_d ==================\n");
roots = tenEigensolve_d(evalA, evecA, tt);
printf("%s roots\n", airEnumStr(ell_cubic_root, roots));
testeigen(tt, evalA, evecA);
printf("================== new eigensolve ==================\n");
roots = evals(evalB, tt[1], tt[2], tt[3], tt[4], tt[5], tt[6]);
printf("%s roots: %g %g %g\n", airEnumStr(ell_cubic_root, roots),
evalB[0], evalB[1], evalB[2]);
roots = evals_evecs(evalB, evecB,
tt[1], tt[2], tt[3], tt[4], tt[5], tt[6]);
printf("%s roots\n", airEnumStr(ell_cubic_root, roots));
testeigen(tt, evalB, evecB);
airMopOkay(mop);
return 0;
}
//A is an antisymmetric matrix and B is the output rotation matrix
void make_rotation_matrix_notworking(const Array2 <doublevar> & A,
Array2 <doublevar> & B) {
int n=A.GetDim(0);
assert(A.GetDim(1)==n);
B.Resize(n,n);
Array2 <dcomplex> skew(n,n),VL(n,n),VR(n,n);
Array1 <dcomplex> evals(n);
for(int i=0; i< n; i++) {
for(int j=0; j < n; j++) {
skew(i,j)=A(i,j);
}
}
GeneralizedEigenSystemSolverComplexGeneralMatrices(skew,evals,VL,VR);
cout << "evals " << endl;
for(int i=0; i< n; i++) cout << evals(i) << " ";
cout << endl;
cout << "VR " << endl;
for(int i=0; i< n; i++) {
for(int j=0; j< n; j++) {
cout << VR(i,j) << " ";
}
cout << endl;
}
cout << "VL " << endl;
for(int i=0; i< n; i++) {
for(int j=0; j< n; j++) {
cout << VL(i,j) << " ";
}
cout << endl;
}
//this is horribly inefficient,most likely
skew=dcomplex(0.0,0.); //we don't need that any more so we reuse it
Array2 <dcomplex> work(n,n);
work=dcomplex(0.0,0.);
for(int i=0; i< n; i++) {
skew(i,i)=exp(evals(i));
}
for(int i=0; i< n; i++) {
for(int j=0; j<n; j++) {
for(int k=0; k< n; k++) {
work(i,k)+=skew(i,j)*VR(j,k);
}
}
}
skew=dcomplex(0.,0.);
for(int i=0; i< n; i++) {
for(int j=0; j<n; j++) {
for(int k=0; k< n; k++) {
//skew(i,k)+=conj(VL(i,j))*work(j,k);
skew(i,k)=conj(VR(j,i))*work(j,k);
}
}
}
cout << "rotation " << endl;
for(int i=0; i< n; i++) {
for(int j=0; j< n; j++) {
cout << skew(i,j) << " ";
}
cout << endl;
}
}
int main(int argc, char *argv[]) {
if(argc != 6 && argc != 7) {
printf("usage: rrg N n s D seed (id_string)\n");
return 1;
}
time_t t1,t2,tI,tF;
ITensor U,Dg,P,S;
Index ei;
// RRG structure parameters
const int N = atoi(argv[1]); // should be n*(power of 2)
const int n = atoi(argv[2]); // initial blocking size
int w = n; // block size (scales with m)
int ll = 0; // lambda block index
int m = 0; // RG scale factor
// AGSP and subspace parameters
const double t = 0.3; // Trotter temperature
const int M = 100; // num Trotter steps
const int k = 1; // power of Trotter op (just use 1)
const int s = atoi(argv[3]); // formal s param
const int D = atoi(argv[4]); // formal D param
// computational settings
const bool doI = true; // diag restricted Hamiltonian iteratively?
// setup random sampling
std::random_device r;
const int seed = atoi(argv[5]);
fprintf(stderr,"seed is %d\n",seed);
std::mt19937 gen(seed);
std::uniform_real_distribution<double> udist(0.0,1.0);
FILE *sxfl,*syfl,*szfl,*gsfl;
char id[128],sxnm[256],synm[256],sznm[256],gsnm[256];
if(argc == 6) sprintf(id,"rrg-L%d-s%d-D%d",N,s,D);
else sprintf(id,"%s",argv[6]);
strcat(sxnm,id); strcat(sxnm,"-sx.dat");
strcat(synm,id); strcat(synm,"-sy.dat");
strcat(sznm,id); strcat(sznm,"-sz.dat");
strcat(gsnm,id); strcat(gsnm,"-gs.dat");
sxfl = fopen(sxnm,"a");
syfl = fopen(synm,"a");
szfl = fopen(sznm,"a");
gsfl = fopen(gsnm,"a");
// initialize Hilbert subspaces for each level m = 0,...,log(N/n)
vector<SpinHalf> hsps;
for(int x = n ; x <= N ; x *= 2) hsps.push_back(SpinHalf(x));
SpinHalf hs = hsps.back();
// generate product basis over m=0 Hilbert space
auto p = int(pow(2,n));
vector<MPS> V1;
for(int i = 0 ; i < p ; ++i) {
InitState istate(hsps[0],"Dn");
for(int j = 1 ; j <= n ; ++j)
if(i/(int)pow(2,j-1)%2) istate.set(j,"Up");
V1.push_back(MPS(istate));
}
MPS bSpaceL(hsps[0]);
MPS bSpaceR(hsps[0]);
makeVS(V1,bSpaceL,LEFT);
makeVS(V1,bSpaceR,RIGHT);
// Hamiltonian parameters
const double Gamma = 2.0;
vector<double> J(2*(N-1));
fprintf(stdout,"# Hamiltonian terms Jx1,Jy1,Jx2,... (seed=%d)\n",seed);
for(int i = 0 ; i < N-1 ; ++i) {
J[2*i+0] = pow(udist(gen),Gamma);
J[2*i+1] = pow(udist(gen),Gamma);
fprintf(stdout,"%16.14f,%16.14f",J[2*i],J[2*i+1]);
if(i != N-2) fprintf(stdout,",");
}
fprintf(stdout,"\n");
fflush(stdout);
// initialize H for full system and extract block Hamiltonians
AutoMPO autoH(hs);
std::stringstream sts;
auto out = std::cout.rdbuf(sts.rdbuf());
vector<vector<MPO> > Hs(hsps.size());
for(int i = 1 ; i < N ; ++i) {
autoH += (J[2*(i-1)]-J[2*(i-1)+1]),"S+",i,"S+",i+1;
autoH += (J[2*(i-1)]-J[2*(i-1)+1]),"S-",i,"S-",i+1;
autoH += (J[2*(i-1)]+J[2*(i-1)+1]),"S+",i,"S-",i+1;
autoH += (J[2*(i-1)]+J[2*(i-1)+1]),"S-",i,"S+",i+1;
}
auto H = toMPO<ITensor>(autoH,{"Exact",true});
std::cout.rdbuf(out);
for(auto i : args(hsps)) extractBlocks(autoH,Hs[i],hsps[i]);
vector<MPO> prodSz,prodSx,projSzUp,projSzDn,projSxUp,projSxDn;
for(auto& it : hsps) {
auto curSz = sysOp(it,"Sz",2.0).toMPO(); prodSz.push_back(curSz);
auto curSx = sysOp(it,"Sx",2.0).toMPO(); prodSx.push_back(curSx);
auto curSzUp = sysOp(it,"Id").toMPO(); curSzUp.plusEq(curSz); curSzUp /= 2.0;
auto curSzDn = sysOp(it,"Id").toMPO(); curSzDn.plusEq(-1.0*curSz); curSzDn /= 2.0;
auto curSxUp = sysOp(it,"Id").toMPO(); curSxUp.plusEq(curSx); curSxUp /= 2.0;
auto curSxDn = sysOp(it,"Id").toMPO(); curSxDn.plusEq(-1.0*curSx); curSxDn /= 2.0;
projSzUp.push_back(curSzUp); projSzDn.push_back(curSzDn);
projSxUp.push_back(curSxUp); projSxDn.push_back(curSxDn);
}
// approximate the thermal operator exp(-H/t)^k using Trotter
// and MPO multiplication; temperature of K is k/t
time(&tI);
MPO eH(hs);
twoLocalTrotter(eH,t,M,autoH);
auto K = eH;
for(int i = 1 ; i < k ; ++i) {
nmultMPO(eH,K,K,{"Cutoff",eps,"Maxm",MAXBD});
K.Aref(1) *= 1.0/norm(K.A(1));
}
// INITIALIZATION: reduce dimension by sampling from initial basis, either
// bSpaceL or bSpaceR depending on how the merge will work
vector<MPS> Spre;
for(ll = 0 ; ll < N/n ; ll++) {
auto xs = ll % 2 ? 1 : n; // location of dangling Select index
auto cur = ll % 2 ? bSpaceR : bSpaceL;
Index si("ext",s,Select);
// return orthonormal basis of evecs
auto eigs = diagHermitian(-overlapT(cur,Hs[0][ll],cur),P,S,{"Maxm",s});
cur.Aref(xs) *= P*delta(commonIndex(P,S),si);
regauge(cur,xs,{"Truncate",false});
Spre.push_back(cur);
}
time(&t2);
fprintf(stderr,"initialization: %.f s\n",difftime(t2,tI));
// ITERATION: proceed through RRG hierarchy, increasing the scale m
vector<MPS> Spost;
for(m = 0 ; (int)Spre.size() > 1 ; ++m,w*=2) {
fprintf(stderr,"Level %d (w = %d)\n",m,w);
auto hs = hsps[m];
auto DD = D;//max(4,D/(int(log2(N/n)-m)));
auto thr = 1e-8;
Spost.clear();
// EXPAND STEP: for each block, expand dimension of subspace with AGSP operators
for(ll = 0 ; ll < N/w ; ++ll) {
MPO A(hs) , Hc = Hs[m][ll];
MPS pre = Spre[ll] , ret(hs);
int xs = ll % 2 ? 1 : w;
// STEP 1: extract filtering operators A from AGSP K
time(&t1);
restrictMPO(K,A,w*ll+1,DD,ll%2);
time(&t2);
fprintf(stderr,"trunc AGSP: %.f s\n",difftime(t2,t1));
// STEP 2: expand subspace using the mapping A:pre->ret
time(&t1);
ret = applyMPO(A,pre,ll%2,{"Cutoff",eps,"Maxm",MAXBD});
time(&t2);
fprintf(stderr,"apply AGSP: %.f s\n",difftime(t2,t1));
// rotate into principal components of subspace, poxsibly reducing dimension
// and stabilizing numerics, then store subspace in eigenbasis of block H
time(&t1);
diagHermitian(overlapT(ret,ret),U,Dg,{"Cutoff",thr});
time(&t2);
ei = Index("ext",int(commonIndex(Dg,U)),Select);
Dg.apply(invsqrt);
ret.Aref(xs) *= dag(U)*Dg*delta(prime(commonIndex(Dg,U)),ei);
fprintf(stderr,"rotate MPS: %.f s\n",difftime(t2,t1));
auto eigs = diagHermitian(-overlapT(ret,Hs[m][ll],ret),P,S);
ret.Aref(xs) *= P*delta(commonIndex(P,S),ei);
ret.Aref(xs) *= 1.0/sqrt(overlapT(ret,ret).real(ei(1),prime(ei)(1)));
regauge(ret,xs,{"Cutoff",eps});
fprintf(stderr,"max m: %d\n",maxM(ret));
Spost.push_back(ret);
}
// MERGE/REDUCE STEP: construct tensor subspace, sample to reduce dimension
Spre.clear();
for(ll = 0 ; ll < N/w ; ll+=2) {
auto spL = Spost[ll]; // L subspace
auto spR = Spost[ll+1]; // R subspace
// STEP 1: find s lowest eigenpairs of restricted H
time(&t1);
auto tpH = tensorProdContract(spL,spR,Hs[m+1][ll/2]);
tensorProdH<ITensor> resH(tpH);
resH.diag(s,doI);
P = resH.eigenvectors();
time(&t2);
fprintf(stderr,"diag restricted H: %.f s\n",difftime(t2,t1));
// STEP 2: tensor viable sets on each side and reduce dimension
MPS ret(hsps[m+1]);
time(&t1);
tensorProduct(spL,spR,ret,P,(ll/2)%2);
time(&t2);
fprintf(stderr,"tensor product (ll=%d): %.f s\n",ll,difftime(t2,t1));
Spre.push_back(ret);
}
}
// EXIT: extract two lowest energy candidate states to determine gap
auto res = Spre[0];
auto fi = Index("ext",s/2,Select);
vector<MPS> resSz = {res,res};
// project to Sz sectors of the eigenspace
diagHermitian(overlapT(res,prodSz[m],res),U,Dg);
resSz[0].Aref(N) *= U*delta(commonIndex(U,Dg),fi);
diagHermitian(overlapT(res,-1.0*prodSz[m],res),U,Dg);
resSz[1].Aref(N) *= U*delta(commonIndex(U,Dg),fi);
vector<MPS> evecs(2);
for(int i : range(2)) {
auto fc = resSz[i];
// diagonalize H within the Sz sectors
auto eigs = diagHermitian(-overlapT(fc,H,fc),P,S);
fc.Aref(N) *= (P*setElt(commonIndex(P,S)(1)));
fc.orthogonalize({"Cutoff",epx,"Maxm",MAXBD});
fc.normalize();
if(i == 0)
fprintf(stderr,"RRG gs energy: %17.14f\n",overlap(fc,H,fc));
evecs[i] = fc;
}
time(&t2);
Real vz,vx;
vz = overlap(evecs[0],prodSz[m],evecs[0]); vx = overlap(evecs[0],prodSx[m],evecs[0]);
fprintf(stderr,"Vz,vx of 0 is: %17.14f,%17.14f\n",vz,vx);
vz = overlap(evecs[1],prodSz[m],evecs[1]); vx = overlap(evecs[1],prodSx[m],evecs[1]);
fprintf(stderr,"Vz,vx of 1 is: %17.14f,%17.14f\n",vz,vx);
int x1_up = (vx > 0.0 ? 1 : 0);
evecs[0] = exactApplyMPO(evecs[0],projSzUp[m],{"Cutoff",epx});
evecs[0] = exactApplyMPO(evecs[0],projSxUp[m],{"Cutoff",epx});
evecs[1] = exactApplyMPO(evecs[1],projSzDn[m],{"Cutoff",epx});
evecs[1] = exactApplyMPO(evecs[1],(x1_up?projSxUp[m]:projSxDn[m]),{"Cutoff",epx});
for(auto& it : evecs) it.normalize();
fprintf(stderr,"gs candidate energy: %17.14f\nRRG BD ",overlap(evecs[0],H,evecs[0]));
for(const auto& it : evecs) fprintf(stderr,"%d ",maxM(it));
fprintf(stderr,"\telapsed: %.f s\n",difftime(t2,tI));
// CLEANUP: use DMRG to improve discovered evecs
vector<Real> evals(2),e_prev(2);
int max_iter = 30 , used_max = 0;
Real flr = 1e-13 , over_conv = 1e-1 , gap = 1.0 , conv = over_conv*gap , max_conv = 1.0;
for(int i = 0 ; i < (int)evecs.size() ; ++i) evals[i] = overlap(evecs[i],H,evecs[i]);
for(int i = 0 ; (i < 2 || conv < max_conv) && i < max_iter ; ++i) {
e_prev = evals;
time(&t1);
evals = dmrgMPO(H,evecs,8,{"Penalty",0.1,"Cutoff",epx});
time(&t2);
gap = evals[1]-evals[0];
max_conv = 0.0;
for(auto& j : range(2))
if(fabs(e_prev[j]-evals[j]) > max_conv) max_conv = e_prev[j]-evals[j];
fprintf(stderr,"DMRG BD ");
for(const auto& it : evecs) fprintf(stderr,"%3d ",maxM(it));
fprintf(stderr,"\tgap: %e\tconv=%9.2e,%9.2e\telapsed: %.f s\n",gap,
e_prev[0]-evals[0],e_prev[1]-evals[1],difftime(t2,t1));
conv = max(over_conv*gap,flr);
if(i == max_iter) used_max = 1;
}
for(int i = 0 ; i < (int)evecs.size() ; ++i) {
vz = overlap(evecs[i],prodSz[m],evecs[i]); vx = overlap(evecs[i],prodSx[m],evecs[i]);
fprintf(stderr,"Vz,vx of %d is: %12.9f,%12.9f\n",i,vz,vx);
}
evecs[0] = exactApplyMPO(evecs[0],projSzUp[m],{"Cutoff",1e-16});
evecs[0] = exactApplyMPO(evecs[0],projSxUp[m],{"Cutoff",1e-16});
evecs[1] = exactApplyMPO(evecs[1],projSzDn[m],{"Cutoff",1e-16});
evecs[1] = exactApplyMPO(evecs[1],(x1_up?projSxUp[m]:projSxDn[m]),{"Cutoff",1e-16});
for(auto& it : evecs) it.normalize();
for(auto i : range(evecs.size())) evals[i] = overlap(evecs[i],H,evecs[i]);
time(&tF);
auto gsR = evecs[0];
auto ee = measEE(gsR,N/2);
gap = evals[1]-evals[0];
fprintf(stderr,"gs: %17.14f gap: %15.9e ee: %10.8f\n",evals[0],gap,ee);
fprintf(gsfl,"# GS data (L=%d s=%d D=%d seed=%d time=%.f)\n",N,s,D,seed,difftime(tF,tI));
if(used_max) fprintf(gsfl,"# WARNING max iterations reached\n");
fprintf(gsfl,"%17.14f\t%15.9e\t%10.8f\n",evals[0],gap,ee);
// Compute two-point correlation functions in ground state via usual MPS method
fprintf(sxfl,"# SxSx corr matrix (L=%d s=%d D=%d seed=%d)\n",N,s,D,seed);
fprintf(syfl,"# SySy corr matrix (L=%d s=%d D=%d seed=%d)\n",N,s,D,seed);
fprintf(szfl,"# SzSz corr matrix (L=%d s=%d D=%d seed=%d)\n",N,s,D,seed);
for(int i = 1 ; i <= N ; ++i) {
gsR.position(i,{"Cutoff",0.0});
auto SxA = hs.op("Sx",i); auto SyA = hs.op("Sy",i); auto SzA = hs.op("Sz",i);
for(int j = 1 ; j <= N ; ++j) {
if(j <= i) {
fprintf(sxfl,"%15.12f\t",0.0);
fprintf(syfl,"%15.12f\t",0.0);
fprintf(szfl,"%15.12f\t",0.0);
} else {
auto SxB = hs.op("Sx",j); auto SyB = hs.op("Sy",j); auto SzB = hs.op("Sz",j);
fprintf(sxfl,"%15.12f\t",measOp(gsR,SxA,i,SxB,j));
fprintf(syfl,"%15.12f\t",measOp(gsR,SyA,i,SyB,j));
fprintf(szfl,"%15.12f\t",measOp(gsR,SzA,i,SzB,j));
}
}
fprintf(sxfl,"\n");
fprintf(syfl,"\n");
fprintf(szfl,"\n");
}
fclose(sxfl);
fclose(syfl);
fclose(szfl);
fclose(gsfl);
return 0;
}
void ContactAngle2::doFrame(int frame) {
StuntDouble* sd;
int i;
// set up the bins for density analysis
Mat3x3d hmat = info_->getSnapshotManager()->getCurrentSnapshot()->getHmat();
RealType len = std::min(hmat(0, 0), hmat(1, 1));
RealType zLen = hmat(2,2);
RealType dr = len / (RealType) nRBins_;
RealType dz = zLen / (RealType) nZBins_;
std::vector<std::vector<RealType> > histo;
histo.resize(nRBins_);
for (unsigned int i = 0; i < histo.size(); ++i){
histo[i].resize(nZBins_);
std::fill(histo[i].begin(), histo[i].end(), 0.0);
}
if (evaluator1_.isDynamic()) {
seleMan1_.setSelectionSet(evaluator1_.evaluate());
}
Vector3d com(centroidX_, centroidY_, solidZ_);
// now that we have the centroid, we can make cylindrical density maps
Vector3d pos;
RealType r;
RealType z;
for (sd = seleMan1_.beginSelected(i); sd != NULL;
sd = seleMan1_.nextSelected(i)) {
pos = sd->getPos() - com;
// r goes from zero upwards
r = sqrt(pow(pos.x(), 2) + pow(pos.y(), 2));
// z is possibly symmetric around 0
z = pos.z();
int whichRBin = int(r / dr);
int whichZBin = int( (zLen/2.0 + z) / dz);
if ((whichRBin < int(nRBins_)) && (whichZBin >= 0)
&& (whichZBin < int(nZBins_))) {
histo[whichRBin][whichZBin] += sd->getMass();
}
}
for(unsigned int i = 0 ; i < histo.size(); ++i){
RealType rL = i * dr;
RealType rU = rL + dr;
RealType volSlice = NumericConstant::PI * dz * (( rU*rU ) - ( rL*rL ));
for (unsigned int j = 0; j < histo[i].size(); ++j) {
histo[i][j] *= PhysicalConstants::densityConvert / volSlice;
}
}
std::vector<Vector<RealType, 2> > points;
points.clear();
for (unsigned int j = 0; j < nZBins_; ++j) {
// The z coordinates were measured relative to the selection
// center of mass. However, we're interested in the elevation
// above the solid surface. Also, the binning was done around
// zero with enough bins to cover the zLength of the box:
RealType thez = com.z() - solidZ_ - zLen/2.0 + dz * (j + 0.5);
bool aboveThresh = false;
bool foundThresh = false;
int rloc = 0;
for (std::size_t i = 0; i < nRBins_; ++i) {
if (histo[i][j] >= threshDens_) aboveThresh = true;
if (aboveThresh && (histo[i][j] <= threshDens_)) {
rloc = i;
foundThresh = true;
aboveThresh = false;
}
}
if (foundThresh) {
Vector<RealType,2> point;
point[0] = dr*(rloc+0.5);
point[1] = thez;
if (thez > bufferLength_) {
points.push_back( point );
}
}
}
int numPoints = points.size();
// Compute the average of the data points.
Vector<RealType, 2> average = points[0];
int i0;
for (i0 = 1; i0 < numPoints; ++i0) {
average += points[i0];
}
RealType invNumPoints = ((RealType)1)/(RealType)numPoints;
average *= invNumPoints;
DynamicRectMatrix<RealType> mat(4, 4);
int row, col;
for (row = 0; row < 4; ++row) {
for (col = 0; col < 4; ++col){
mat(row,col) = 0.0;
}
}
for (int i = 0; i < numPoints; ++i) {
RealType x = points[i][0];
RealType y = points[i][1];
RealType x2 = x*x;
RealType y2 = y*y;
RealType xy = x*y;
RealType r2 = x2+y2;
RealType xr2 = x*r2;
RealType yr2 = y*r2;
RealType r4 = r2*r2;
mat(0,1) += x;
mat(0,2) += y;
mat(0,3) += r2;
mat(1,1) += x2;
mat(1,2) += xy;
mat(1,3) += xr2;
mat(2,2) += y2;
mat(2,3) += yr2;
mat(3,3) += r4;
}
mat(0,0) = (RealType)numPoints;
for (row = 0; row < 4; ++row) {
for (col = 0; col < row; ++col) {
mat(row,col) = mat(col,row);
}
}
for (row = 0; row < 4; ++row) {
for (col = 0; col < 4; ++col) {
mat(row,col) *= invNumPoints;
}
}
JAMA::Eigenvalue<RealType> eigensystem(mat);
DynamicRectMatrix<RealType> evects(4, 4);
DynamicVector<RealType> evals(4);
eigensystem.getRealEigenvalues(evals);
eigensystem.getV(evects);
DynamicVector<RealType> evector = evects.getColumn(0);
RealType inv = ((RealType)1)/evector[3]; // beware zero divide
RealType coeff[3];
for (row = 0; row < 3; ++row) {
coeff[row] = inv*evector[row];
}
Vector<RealType, 2> center;
center[0] = -((RealType)0.5)*coeff[1];
center[1] = -((RealType)0.5)*coeff[2];
RealType radius = sqrt(fabs(center[0]*center[0] + center[1]*center[1]
- coeff[0]));
int i1;
for (i1 = 0; i1 < 100; ++i1) {
// Update the iterates.
Vector<RealType, 2> current = center;
// Compute average L, dL/da, dL/db.
RealType lenAverage = (RealType)0;
Vector<RealType, 2> derLenAverage = Vector<RealType, 2>(0.0);
for (i0 = 0; i0 < numPoints; ++i0) {
Vector<RealType, 2> diff = points[i0] - center;
RealType length = diff.length();
if (length > 1e-6) {
lenAverage += length;
RealType invLength = ((RealType)1)/length;
derLenAverage -= invLength*diff;
}
}
lenAverage *= invNumPoints;
derLenAverage *= invNumPoints;
center = average + lenAverage*derLenAverage;
radius = lenAverage;
Vector<RealType, 2> diff = center - current;
if (fabs(diff[0]) <= 1e-6 && fabs(diff[1]) <= 1e-6) {
break;
}
}
RealType zCen = center[1];
RealType rDrop = radius;
RealType ca;
if (fabs(zCen) > rDrop) {
ca = 180.0;
} else {
ca = 90.0 + asin(zCen/rDrop)*(180.0/M_PI);
}
values_.push_back( ca );
}
