double E2()
{
switch(expr[start])
{
case '+':start++;return T()+E2();
case '-':start++;return -T()+E2();
default:return 0;
}
}
mat sift(const mat &H) {
imgpyr2 blurred;
imgpyr2 edges;
// 1) SIFT Scale-space extrema
int noctaves = 4, nscales = 5;
double sigma2 = 1.6;
lappyr2(blurred, edges, noctaves, nscales, sigma2);
const int radius = 1;
for (int i = 0; i < edges.size(); i++) {
for (int j = 1; j < edges[i].size() - 1; j++) {
// grab three blurred images from an octave
mat E1 = edges[i][j];
mat E0 = edges[i][j - 1];
mat E2 = edges[i][j + 1];
// for every pixel in E1, check to make sure that it
// is larger or smaller than all neighbors (local extrema)
bool max_ext = true;
bool min_ext = true;
for (int u = 0; u < E1.n_rows; u++) {
for (int v = 0; v < E1.n_cols; v++) {
if (u == 0 || v == 0 || u == E1.n_rows || v = E1.n_cols) {
E1(u, v) = 0;
}
// find the extrema in the images
for (int x = -radius; x <= radius; x++) {
for (int y = -radius; y <= radius; y++) {
if (E1(u, v) < E0(u + y, v + x) ||
E1(u, v) < E2(u + y, v + x) ||
E1(u, v) < E1(u + y, v + x)) {
max_ext = false;
}
if (E1(u, v) > E0(u + y, v + x) ||
E1(u, v) > E2(u + y, v + x) ||
E1(u, v) > E1(u + y, v + x)) {
min_ext = false;
}
}
}
E1(u, v) = max_ext || min_ext;
}
}
// once we have the image pyramids, then we can
// try to find the magnitude of the keypoint descriptor
}
}
// 2) Accurate Keypoint Localization
// use the Taylor method (later on)
// for now just return everything
// 3) Orientation Assignment
}
HRESULT CTDSThrough7ParameterPositionVector::SetModelParameters2 (double ha, double f)
{
m_DstSys.m_HA = ha;
m_DstSys.m_f = f;
m_DstSys.m_HB = HB(ha, f);
m_DstSys.m_e2 = E2(f);
m_DstSys.m_e12 = E12(f);
m_DstSys.m_e22 = E22(ha, HB(ha, f));
return S_OK;
}
static char *
rw_encrypt (const dckey *key, const char *msg)
{
const rw_pub *pk = (const rw_pub *) key;
mpz_t m;
char *res = NULL;
mpz_init (m);
if (pre_encrypt (m, msg, pk->nbits)) {
mpz_clear (m);
return NULL;
}
E1 (m, m, pk->n);
E2 (m, m, pk->n);
cat_mpz (&res, m);
mpz_clear (m);
return res;
}
bool Plane::rayIntersects(const RayTracing::Ray_t &ray, const float t0, const float t1, RayTracing::HitInfo_t &hitinfo) const
{
gml::vec3_t E1(0.0f, 0.0f, 2.0f);
gml::vec3_t E2(2.0f, 0.0f, 0.0f);
gml::vec3_t P = gml::cross( ray.d, E2 );
float detM = gml::dot(P, E1);
if (fabs(detM) < 1e-4)
{
return false;
}
gml::vec3_t T = gml::sub( ray.o, _verts[0] );
float u = gml::dot( P, T ) / detM;
if ( u < 0.0f || 1.0f < u )
{
return false;
}
gml::vec3_t TxE1 = gml::cross(T, E1);
float v = gml::dot( TxE1, ray.d ) / detM;
if ( v < 0.0f || 1.0f < v)
{
return false;
}
float t = gml::dot( TxE1, E2 ) / detM;
if (t < t0 || t1 < t)
{
return false;
}
hitinfo.hitDist = t;
hitinfo.plane.u = u;
hitinfo.plane.v = v;
return true;
}
//Spell３｢交差弾｣
void shot_E2(){
int t=spcount;
if(t>=120){
if(t%70==0){
E2();
se_flag[0]=1;
}
}
for(int i=0;i<BULLET_MAX;i++){//全弾分
if(bullet[i].flag>0){//登録されている弾があれば
if(30<bullet[i].cnt && bullet[i].cnt<120){//30〜120カウントなら
bullet[i].spd-=1.7/90.0;//90カウントかけて1.7減らす
bullet[i].angle+=(PI/4)/90.0*(bullet[i].state?-1:1);//90カウントかけて45°傾ける(stateで分離)
}
if(bullet[i].cnt==120)
bullet[i].state=3; //ダメージ減少補正
}
}
}
bool Plane::shadowsRay(const RayTracing::Ray_t &ray, const float t0, const float t1) const
{
gml::vec3_t E1(0.0f, 0.0f, 2.0f);
gml::vec3_t E2(2.0f, 0.0f, 0.0f);
gml::vec3_t P = gml::cross( ray.d, E2 );
float detM = gml::dot(P, E1);
if (fabs(detM) < 1e-4)
{
return false;
}
gml::vec3_t T = gml::sub( ray.o, _verts[0] );
float u = gml::dot( P, T ) / detM;
if ( u < 0.0f || 1.0f < u )
{
return false;
}
gml::vec3_t TxE1 = gml::cross(T, E1);
float v = gml::dot( TxE1, ray.d ) / detM;
if ( v < 0.0f || 1.0f < v)
{
return false;
}
float t = gml::dot( TxE1, E2 ) / detM;
if (t < t0 || t1 < t)
{
return false;
}
return true;
}
static int
rw_verify (const dckey *key, const char *msg, const char *sig)
{
const rw_pub *pk = (const rw_pub *) key;
sha1_ctx sc;
mpz_t m,s;
int ret;
mpz_init (s);
mpz_init (m);
if (read_mpz (&sig, s)) {
mpz_clear (s);
return 0;
}
E2 (m, s, pk->n);
D1 (m, m, pk->n);
sha1_init (&sc);
sha1_update (&sc, msg, strlen (msg));
ret = post_verify (&sc, m, pk->nbits);
mpz_clear (s);
mpz_clear (m);
return ret;
}
int KinZfitter::PerZ1Likelihood(double & l1, double & l2, double & lph1, double & lph2)
{
l1= 1.0; l2 = 1.0;
lph1 = 1.0; lph2 = 1.0;
if(debug_) cout<<"start Z1 refit"<<endl;
TLorentzVector Z1_1 = p4sZ1_[0]; TLorentzVector Z1_2 = p4sZ1_[1];
double RECOpT1 = Z1_1.Pt(); double RECOpT2 = Z1_2.Pt();
double pTerrZ1_1 = pTerrsZ1_[0]; double pTerrZ1_2 = pTerrsZ1_[1];
if(debug_)cout<<"pT1 "<<RECOpT1<<" pTerrZ1_1 "<<pTerrZ1_1<<endl;
if(debug_)cout<<"pT2 "<<RECOpT2<<" pTerrZ1_2 "<<pTerrZ1_2<<endl;
//////////////
TLorentzVector Z1_ph1, Z1_ph2;
double pTerrZ1_ph1, pTerrZ1_ph2;
double RECOpTph1, RECOpTph2;
TLorentzVector nullFourVector(0, 0, 0, 0);
Z1_ph1=nullFourVector; Z1_ph2=nullFourVector;
RECOpTph1 = 0; RECOpTph2 = 0;
pTerrZ1_ph1 = 0; pTerrZ1_ph2 = 0;
if(p4sZ1ph_.size()>=1){
Z1_ph1 = p4sZ1ph_[0]; pTerrZ1_ph1 = pTerrsZ1ph_[0];
RECOpTph1 = Z1_ph1.Pt();
if(debug_) cout<<"put in Z1 fsr photon 1 pT "<<RECOpTph1<<" pT err "<<pTerrZ1_ph1<<endl;
}
if(p4sZ1ph_.size()==2){
//if(debug_) cout<<"put in Z1 fsr photon 2"<<endl;
Z1_ph2 = p4sZ1ph_[1]; pTerrZ1_ph2 = pTerrsZ1ph_[1];
RECOpTph2 = Z1_ph2.Pt();
}
RooRealVar* pT1RECO = new RooRealVar("pT1RECO","pT1RECO", RECOpT1, 5, 500);
RooRealVar* pT2RECO = new RooRealVar("pT2RECO","pT2RECO", RECOpT2, 5, 500);
double RECOpT1min = max(5.0, RECOpT1-2*pTerrZ1_1);
double RECOpT2min = max(5.0, RECOpT2-2*pTerrZ1_2);
RooRealVar* pTph1RECO = new RooRealVar("pTph1RECO","pTph1RECO", RECOpTph1, 5, 500);
RooRealVar* pTph2RECO = new RooRealVar("pTph2RECO","pTph2RECO", RECOpTph2, 5, 500);
double RECOpTph1min = max(0.5, RECOpTph1-2*pTerrZ1_ph1);
double RECOpTph2min = max(0.5, RECOpTph2-2*pTerrZ1_ph2);
// observables pT1,2,ph1,ph2
RooRealVar* pT1 = new RooRealVar("pT1", "pT1FIT", RECOpT1, RECOpT1min, RECOpT1+2*pTerrZ1_1 );
RooRealVar* pT2 = new RooRealVar("pT2", "pT2FIT", RECOpT2, RECOpT2min, RECOpT2+2*pTerrZ1_2 );
RooRealVar* m1 = new RooRealVar("m1","m1", Z1_1.M());
RooRealVar* m2 = new RooRealVar("m2","m2", Z1_2.M());
if(debug_) cout<<"m1 "<<m1->getVal()<<" m2 "<<m2->getVal()<<endl;
double Vtheta1, Vphi1, Vtheta2, Vphi2;
Vtheta1 = (Z1_1).Theta(); Vtheta2 = (Z1_2).Theta();
Vphi1 = (Z1_1).Phi(); Vphi2 = (Z1_2).Phi();
RooRealVar* theta1 = new RooRealVar("theta1","theta1",Vtheta1);
RooRealVar* phi1 = new RooRealVar("phi1","phi1",Vphi1);
RooRealVar* theta2 = new RooRealVar("theta2","theta2",Vtheta2);
RooRealVar* phi2 = new RooRealVar("phi2","phi2",Vphi2);
// dot product to calculate (p1+p2+ph1+ph2).M()
RooFormulaVar E1("E1","TMath::Sqrt((@0*@0)/((TMath::Sin(@1))*(TMath::Sin(@1)))+@2*@2)",
RooArgList(*pT1,*theta1,*m1));
RooFormulaVar E2("E2","TMath::Sqrt((@0*@0)/((TMath::Sin(@1))*(TMath::Sin(@1)))+@2*@2)",
RooArgList(*pT2,*theta2,*m2));
if(debug_) cout<<"E1 "<<E1.getVal()<<"; E2 "<<E2.getVal()<<endl;
/////
RooRealVar* pTph1 = new RooRealVar("pTph1", "pTph1FIT", RECOpTph1, RECOpTph1min, RECOpTph1+2*pTerrZ1_ph1 );
RooRealVar* pTph2 = new RooRealVar("pTph2", "pTph2FIT", RECOpTph2, RECOpTph2min, RECOpTph2+2*pTerrZ1_ph2 );
double Vthetaph1, Vphiph1, Vthetaph2, Vphiph2;
Vthetaph1 = (Z1_ph1).Theta(); Vthetaph2 = (Z1_ph2).Theta();
Vphiph1 = (Z1_ph1).Phi(); Vphiph2 = (Z1_ph2).Phi();
RooRealVar* thetaph1 = new RooRealVar("thetaph1","thetaph1",Vthetaph1);
RooRealVar* phiph1 = new RooRealVar("phiph1","phiph1",Vphiph1);
RooRealVar* thetaph2 = new RooRealVar("thetaph2","thetaph2",Vthetaph2);
RooRealVar* phiph2 = new RooRealVar("phiph2","phi2",Vphiph2);
RooFormulaVar Eph1("Eph1","TMath::Sqrt((@0*@0)/((TMath::Sin(@1))*(TMath::Sin(@1))))",
RooArgList(*pTph1,*thetaph1));
RooFormulaVar Eph2("Eph2","TMath::Sqrt((@0*@0)/((TMath::Sin(@1))*(TMath::Sin(@1))))",
RooArgList(*pTph2,*thetaph2));
//// dot products of 4-vectors
// 3-vector DOT
RooFormulaVar* p1v3D2 = new RooFormulaVar("p1v3D2",
"@0*@1*( ((TMath::Cos(@2))*(TMath::Cos(@3)))/((TMath::Sin(@2))*(TMath::Sin(@3)))+(TMath::Cos(@4-@5)))",
RooArgList(*pT1,*pT2,*theta1,*theta2,*phi1,*phi2));
if(debug_) cout<<"p1 DOT p2 is "<<p1v3D2->getVal()<<endl;
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar p1D2("p1D2","@0*@1-@2",RooArgList(E1,E2,*p1v3D2));
//lep DOT fsrPhoton1
// 3-vector DOT
RooFormulaVar* p1v3Dph1 = new RooFormulaVar("p1v3Dph1",
"@0*@1*( (TMath::Cos(@2)*TMath::Cos(@3))/(TMath::Sin(@2)*TMath::Sin(@3))+TMath::Cos(@4-@5))",
RooArgList(*pT1,*pTph1,*theta1,*thetaph1,*phi1,*phiph1));
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar p1Dph1("p1Dph1","@0*@1-@2",RooArgList(E1,Eph1,*p1v3Dph1));
// 3-vector DOT
RooFormulaVar* p2v3Dph1 = new RooFormulaVar("p2v3Dph1",
"@0*@1*( (TMath::Cos(@2)*TMath::Cos(@3))/(TMath::Sin(@2)*TMath::Sin(@3))+TMath::Cos(@4-@5))",
RooArgList(*pT2,*pTph1,*theta2,*thetaph1,*phi2,*phiph1));
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar p2Dph1("p2Dph1","@0*@1-@2",RooArgList(E2,Eph1,*p2v3Dph1));
// lep DOT fsrPhoton2
// 3-vector DOT
RooFormulaVar* p1v3Dph2 = new RooFormulaVar("p1v3Dph2",
"@0*@1*( (TMath::Cos(@2)*TMath::Cos(@3))/(TMath::Sin(@2)*TMath::Sin(@3))+TMath::Cos(@4-@5))",
RooArgList(*pT1,*pTph2,*theta1,*thetaph2,*phi1,*phiph2));
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar p1Dph2("p1Dph2","@0*@1-@2",RooArgList(E1,Eph2,*p1v3Dph2));
// 3-vector DOT
RooFormulaVar* p2v3Dph2 = new RooFormulaVar("p2v3Dph2",
"@0*@1*( (TMath::Cos(@2)*TMath::Cos(@3))/(TMath::Sin(@2)*TMath::Sin(@3))+TMath::Cos(@4-@5))",
RooArgList(*pT2,*pTph2,*theta2,*thetaph2,*phi2,*phiph2));
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar p2Dph2("p2Dph2","@0*@1-@2",RooArgList(E2,Eph2,*p2v3Dph2));
// fsrPhoton1 DOT fsrPhoton2
// 3-vector DOT
RooFormulaVar* ph1v3Dph2 = new RooFormulaVar("ph1v3Dph2",
"@0*@1*( (TMath::Cos(@2)*TMath::Cos(@3))/(TMath::Sin(@2)*TMath::Sin(@3))+TMath::Cos(@4-@5))",
RooArgList(*pTph1,*pTph2,*thetaph1,*thetaph2,*phiph1,*phiph2));
// 4-vector DOT metric 1 -1 -1 -1
RooFormulaVar ph1Dph2("ph1Dph2","@0*@1-@2",RooArgList(Eph1,Eph2,*ph1v3Dph2));
// mZ1
RooFormulaVar* mZ1;
mZ1 = new RooFormulaVar("mZ1","TMath::Sqrt(2*@0+@1*@1+@2*@2)",RooArgList(p1D2,*m1,*m2));
if(p4sZ1ph_.size()==1)
mZ1 = new RooFormulaVar("mZ1","TMath::Sqrt(2*@0+2*@1+2*@2+@3*@3+@4*@4)",
RooArgList(p1D2, p1Dph1, p2Dph1, *m1,*m2));
if(p4sZ1ph_.size()==2)
mZ1 = new RooFormulaVar("mZ1","TMath::Sqrt(2*@0+2*@1+2*@2+2*@3+2*@4+2*@5+@6*@6+@7*@7)",
RooArgList(p1D2,p1Dph1,p2Dph1,p1Dph2,p2Dph2,ph1Dph2, *m1,*m2));
if(debug_) cout<<"mZ1 is "<<mZ1->getVal()<<endl;
// pTerrs, 1,2,ph1,ph2
RooRealVar sigmaZ1_1("sigmaZ1_1", "sigmaZ1_1", pTerrZ1_1);
RooRealVar sigmaZ1_2("sigmaZ1_2", "sigmaZ1_2", pTerrZ1_2);
RooRealVar sigmaZ1_ph1("sigmaZ1_ph1", "sigmaZ1_ph1", pTerrZ1_ph1);
RooRealVar sigmaZ1_ph2("sigmaZ1_ph2", "sigmaZ1_ph2", pTerrZ1_ph2);
// resolution for decay products
RooGaussian gauss1("gauss1","gaussian PDF", *pT1RECO, *pT1, sigmaZ1_1);
RooGaussian gauss2("gauss2","gaussian PDF", *pT2RECO, *pT2, sigmaZ1_2);
RooGaussian gaussph1("gaussph1","gaussian PDF", *pTph1RECO, *pTph1, sigmaZ1_ph1);
RooGaussian gaussph2("gaussph2","gaussian PDF", *pTph2RECO, *pTph2, sigmaZ1_ph2);
RooRealVar bwMean("bwMean", "m_{Z^{0}}", 91.187);
RooRealVar bwGamma("bwGamma", "#Gamma", 2.5);
RooRealVar sg("sg", "sg", sgVal_);
RooRealVar a("a", "a", aVal_);
RooRealVar n("n", "n", nVal_);
RooCBShape CB("CB","CB",*mZ1,bwMean,sg,a,n);
RooRealVar f("f","f", fVal_);
RooRealVar mean("mean","mean",meanVal_);
RooRealVar sigma("sigma","sigma",sigmaVal_);
RooRealVar f1("f1","f1",f1Val_);
RooGenericPdf RelBW("RelBW","1/( pow(mZ1*mZ1-bwMean*bwMean,2)+pow(mZ1,4)*pow(bwGamma/bwMean,2) )", RooArgSet(*mZ1,bwMean,bwGamma) );
RooAddPdf RelBWxCB("RelBWxCB","RelBWxCB", RelBW, CB, f);
RooGaussian gauss("gauss","gauss",*mZ1,mean,sigma);
RooAddPdf RelBWxCBxgauss("RelBWxCBxgauss","RelBWxCBxgauss", RelBWxCB, gauss, f1);
RooProdPdf *PDFRelBWxCBxgauss;
PDFRelBWxCBxgauss = new RooProdPdf("PDFRelBWxCBxgauss","PDFRelBWxCBxgauss",
RooArgList(gauss1, gauss2, RelBWxCBxgauss) );
if(p4sZ1ph_.size()==1)
PDFRelBWxCBxgauss = new RooProdPdf("PDFRelBWxCBxgauss","PDFRelBWxCBxgauss",
RooArgList(gauss1, gauss2, gaussph1, RelBWxCBxgauss) );
if(p4sZ1ph_.size()==2)
PDFRelBWxCBxgauss = new RooProdPdf("PDFRelBWxCBxgauss","PDFRelBWxCBxgauss",
RooArgList(gauss1, gauss2, gaussph1, gaussph2, RelBWxCBxgauss) );
// observable set
RooArgSet *rastmp;
rastmp = new RooArgSet(*pT1RECO,*pT2RECO);
if(p4sZ1ph_.size()==1)
rastmp = new RooArgSet(*pT1RECO,*pT2RECO,*pTph1RECO);
if(p4sZ1ph_.size()>=2)
rastmp = new RooArgSet(*pT1RECO,*pT2RECO,*pTph1RECO,*pTph2RECO);
RooDataSet* pTs = new RooDataSet("pTs","pTs", *rastmp);
pTs->add(*rastmp);
//RooAbsReal* nll;
//nll = PDFRelBWxCBxgauss->createNLL(*pTs);
//RooMinuit(*nll).migrad();
RooFitResult* r = PDFRelBWxCBxgauss->fitTo(*pTs,RooFit::Save(),RooFit::PrintLevel(-1));
const TMatrixDSym& covMatrix = r->covarianceMatrix();
const RooArgList& finalPars = r->floatParsFinal();
for (int i=0 ; i<finalPars.getSize(); i++){
TString name = TString(((RooRealVar*)finalPars.at(i))->GetName());
if(debug_) cout<<"name list of RooRealVar for covariance matrix "<<name<<endl;
}
int size = covMatrix.GetNcols();
//TMatrixDSym covMatrixTest_(size);
covMatrixZ1_.ResizeTo(size,size);
covMatrixZ1_ = covMatrix;
if(debug_) cout<<"save the covariance matrix"<<endl;
l1 = pT1->getVal()/RECOpT1; l2 = pT2->getVal()/RECOpT2;
double pTerrZ1REFIT1 = pT1->getError(); double pTerrZ1REFIT2 = pT2->getError();
pTerrsZ1REFIT_.push_back(pTerrZ1REFIT1);
pTerrsZ1REFIT_.push_back(pTerrZ1REFIT2);
if(p4sZ1ph_.size()>=1){
if(debug_) cout<<"set refit result for Z1 fsr photon 1"<<endl;
lph1 = pTph1->getVal()/RECOpTph1;
double pTerrZ1phREFIT1 = pTph1->getError();
if(debug_) cout<<"scale "<<lph1<<" pterr "<<pTerrZ1phREFIT1<<endl;
pTerrsZ1phREFIT_.push_back(pTerrZ1phREFIT1);
}
if(p4sZ1ph_.size()==2){
lph2 = pTph2->getVal()/RECOpTph2;
double pTerrZ1phREFIT2 = pTph2->getError();
pTerrsZ1phREFIT_.push_back(pTerrZ1phREFIT2);
}
//delete nll;
delete r;
delete mZ1;
delete pT1; delete pT2; delete pTph1; delete pTph2;
delete pT1RECO; delete pT2RECO; delete pTph1RECO; delete pTph2RECO;
delete ph1v3Dph2; delete p1v3Dph1; delete p2v3Dph1; delete p1v3Dph2; delete p2v3Dph2;
delete PDFRelBWxCBxgauss;
delete pTs;
delete rastmp;
if(debug_) cout<<"end Z1 refit"<<endl;
return 0;
}
size_t BadLineSegmentIntersection::calc( void *progress/*=0*/ )
{
map<IntersectedPoint_Derived*,int,ComparePoint>::iterator it;
double x,y;
for(int i=0;i<m_lineSegs.size()-1;i++)
{
for(int j=i+1;j<m_lineSegs.size();j++)
{
int intersected = m_lineSegs[i]->Intersection2Segment(*m_lineSegs[j],x,y);
//if(progress!=0) ;//progress->tick();
if(intersected==1)
{
IntersectedPoint_Derived* tmp=new IntersectedPoint_Derived(x,y);
it=m_mapPoints.find(tmp); ///Kiểm tra điểm này có trong danh sách giao điểm chưa
if(it!=m_mapPoints.end())
{ ///Nếu đã tồn tại thì thêm 2 đoạn đang xét vào danh sách những đoạn đi qua điểm này
it->first->AddLineToList(m_lineSegs[i]);
it->first->AddLineToList(m_lineSegs[j]);
delete tmp;
}
else
{
tmp->AddLineToList(m_lineSegs[i]);
tmp->AddLineToList(m_lineSegs[j]);
m_mapPoints.insert(pair<IntersectedPoint_Derived*,int>(tmp,0));
}
}
else
if(intersected==-1)
///Trường hợp 2 đoạn nằm trên 1 đường thẳng nhưng có chung đầu mút
{
IntersectedPoint_Derived D1(m_lineSegs[i]->x1,m_lineSegs[i]->y1);
IntersectedPoint_Derived D2(m_lineSegs[i]->x2,m_lineSegs[i]->y2);
IntersectedPoint_Derived E1(m_lineSegs[j]->x1,m_lineSegs[j]->y1);
IntersectedPoint_Derived E2(m_lineSegs[j]->x2,m_lineSegs[j]->y2);
if(D1==E2 )
{
IntersectedPoint_Derived *tmp=new IntersectedPoint_Derived(D1.x,D1.y);
tmp->AddLineToList(m_lineSegs[i]);
tmp->AddLineToList(m_lineSegs[j]);
m_mapPoints.insert(pair<IntersectedPoint_Derived*,int>(tmp,0));
}
if(D2==E1)
{
IntersectedPoint_Derived *tmp=new IntersectedPoint_Derived(D2.x,D2.y);
tmp->AddLineToList(m_lineSegs[i]);
tmp->AddLineToList(m_lineSegs[j]);
m_mapPoints.insert(pair<IntersectedPoint_Derived*,int>(tmp,0));
}
}
}
};
///copy cac diem tu Map tra ve vector
map<IntersectedPoint_Derived*,int,ComparePoint>::iterator it_2=m_mapPoints.begin();
while(it_2!=m_mapPoints.end())
{
m_IntersectedPoints.push_back(it_2->first);
it_2++;
}
return m_IntersectedPoints.size();
}
/// Adaptive Weights disparity computation.
///
/// The dissimilarity is computed putting adaptive weights on the raw cost.
/// \param im1,im2 the two color images
/// \param dMin,dMax disparity range
/// \param param raw cost computation parameters
/// \param disp1 output disparity map from image 1 to image 2
/// \param disp2 output disparity map from image 2 to image 1
void disparityAW(Image im1, Image im2,
int dMin, int dMax, const ParamDisparity& param,
Image& disp1, Image& disp2) {
const int width=im1.width(), height=im1.height();
const int r = param.radius;
#ifdef COMB_LEFT // Disparity range
const int nd = 1; // Do not compute useless weights in target image
#else
const int nd = dMax-dMin+1;
#endif
// Tabulated proximity weights (color distance)
const int maxL1 = im1.channels()*255; // Maximum L1 distance between colors
float* distC = new float[maxL1+1];
float e2=exp(-1/(im1.channels()*param.gammaCol));
distC[0]=1.0f;
for(int x=1; x<=maxL1; x++)
distC[x] = e2*distC[x-1]; // distC[x] = exp(-x/(c*gamma))
// Tabulated proximity weights (spatial distance)
const int dim=2*r+1; // window dimension
float *distP = new float[dim*dim], *d=distP;
for(int y=-r; y<=r; y++)
for(int x=-r; x<=r; x++)
*d++ = exp(-2.0f*sqrt((float)(x*x+y*y))/param.gammaPos);
Image* cost = costVolume(im1, im2, dMin, dMax, param);
// Images of dissimilarity 1->2 and 2->1
Image E1(width,height), E2(width,height);
std::fill_n(&E1(0,0), width*height, std::numeric_limits<float>::max());
std::fill_n(&E2(0,0), width*height, std::numeric_limits<float>::max());
#ifdef _OPENMP
#pragma omp parallel for
#endif
for(int y=0; y<height; y++) {
// Weight window in reference image
Image W1(dim,dim);
// Weight windows in target image for each disparity (useless for
// COMB_LEFT, but better to have readable code than multiplying #ifdef)
Image* weights2 = new Image[nd];
for(int d=0; d<nd; d++) {
weights2[d] = Image(dim,dim);
if(d+1<nd) // Support for dMax computed later
support(im2, d,y, r, distC, weights2[d]);
}
for(int x=0; x<width; x++) {
// Reference window weights
support(im1, x,y, r, distC, W1);
#ifndef COMB_LEFT // Weight window at disparity dMax in target image
support(im2, x+dMax,y, r, distC, weights2[(x+dMax-dMin)%nd]);
#endif
for(int d=dMin; d<=dMax; d++) {
if(0<=x+d && x+d<width) {
const Image& e = cost[d-dMin]; // Raw cost for disp. d
const Image& W2 = weights2[(x+d-dMin)%nd];
float E = costCombined(x, x+d, y, r, W1, W2, distP, e);
if(E1(x,y) > E) {
E1(x,y) = E;
disp1(x,y) = static_cast<float>(d);
}
if(E2(x+d,y) > E) {
E2(x+d,y) = E;
disp2(x+d,y)= -static_cast<float>(d);
}
}
}
}
delete [] weights2;
}
delete [] cost;
delete [] distC;
delete [] distP;
}
void TJerFile::GetDiffFile(const char *ASrcDir,const char *ADestDir,BList *Diff)
{
//-----------------------------------------
// We are looking for files not found in Dest...
//-----------------------------------------
BList ASrcList;
BList ADestList;
char name1[B_FILE_NAME_LENGTH];
char name2[B_FILE_NAME_LENGTH];
off_t Size1;
off_t Size2;
int32 CRC1,CRC2;
BPath P1;
BPath P2;
char *RelativePath1;
char *RelativePath2;
bool EntryFound = false;
entry_ref *buf_entry,*buf_entry2,*copy_entry;
BMessage *AMessage;
BFile *file2;
BFile *file1;
GetAllFile(ASrcDir,&ASrcList);
GetAllFile(ADestDir,&ADestList);
AMessage = new BMessage(B_RESET_STATUS_BAR);
AMessage->AddFloat("maximum",ASrcList.CountItems());
MyInvoker.Invoke(AMessage);
delete AMessage;
for (int ind=0;ind < ASrcList.CountItems();ind++ )
{
buf_entry = (entry_ref *)(ASrcList.ItemAt(ind));
if (buf_entry!=NULL)
{
BEntry E1(buf_entry);
E1.GetName(name1);
E1.GetPath(&P1);
GetRelativePath(ASrcDir,P1.Path(),&RelativePath1);
file1 = new BFile(buf_entry,B_READ_ONLY);
// printf("Checking file ....%s \n",P1.Path());
// The Message is put here to update when the link files are found too.
AMessage = new BMessage(B_UPDATE_STATUS_BAR);
AMessage->AddFloat("delta",1.0);
AMessage->AddString("text","Checking...");
AMessage->AddString("trailingtext",P1.Path());
MyInvoker.Invoke(AMessage);
delete AMessage;
if (file1->InitCheck()==B_NO_ERROR) //Because of linkfiles....
{
try
{
file1->GetSize(&Size1);
if (CalculateCRC==true)
{
printf("CRC Calculation First File...\n");
CRC1 = CRCFile(file1);
}
// printf("Checking file ....%s Size: %d CRC: %d \n",P1.Path(),Size1,CRC1);
EntryFound = false;
}
catch(GeneralException &e)
{
delete file1;
printf("Exception in File1...");
throw;
}
delete file1;
for (int ind2=0;ind2 < ADestList.CountItems();ind2++ )
{
buf_entry2 = (entry_ref *)(ADestList.ItemAt(ind2));
if (buf_entry2!=NULL)
{
BEntry E2(buf_entry2);
E2.GetName(name2);
E2.GetPath(&P2);
GetRelativePath(ADestDir,P2.Path(),&RelativePath2);
if ((strcmp(name1,name2)==0) && (strcmp(RelativePath1,RelativePath2)==0))
{
// printf("name1 : %s, name2 : %s \n",name1,name2);
// printf("RP1 : %s, RP2 : %s \n",RelativePath1,RelativePath2);
// printf("PAth1 : %s, Path2 : %s \n",P1.Path(),P2.Path());
file2 = new BFile(buf_entry2,B_READ_ONLY);
file2->GetSize(&Size2);
// printf("Size2 %d\n",Size2);
if (Size1==Size2)
{
//CRC Test
try
{
if (CalculateCRC==true)
{
printf("CRC Calculation Second File...\n");
CRC2 = CRCFile(file2);
if (CRC1==CRC2)
{
EntryFound = true;
delete file2;
break; //Data found...
}
}
}
catch(GeneralException &e)
{
printf("Error in GetDiffFile %s\n",P2.Path());
throw;
}
}
delete file2;
}
}
}
if (EntryFound==false)
{
copy_entry = new entry_ref;
*copy_entry = *buf_entry;
Diff->AddItem(copy_entry);
/* BMessage AMessage(GET_FILES);
AMessage.AddRef("ref",copy_entry);
int result = MyInvoker.Invoke(&AMessage);
if (result!= B_OK)
{
if (result == B_BAD_PORT_ID)
{
ShowMessage("Bad Port");
}
else
if (result == B_TIMED_OUT)
{
ShowMessage("TIMED_OUT");
}
else
ShowMessage("Other Error");
}
*/
}
} // End of InitCheck
}
}
// Just to let the main loop that we have finished checking... for the moment we only
// use it to test if the OutLineList is void....
/*
BMessage AMessage2(END_CHECKING);
int result2 = MyInvoker.Invoke(&AMessage2);
if (result2!= B_OK)
{
if (result2 == B_BAD_PORT_ID)
{
ShowMessage("Bad Port");
}
else
if (result2 == B_TIMED_OUT)
{
ShowMessage("TIMED_OUT");
}
else
ShowMessage("Other Error");
}
*/
}
DOUBLE check_tilt_pairs(DOUBLE rot1, DOUBLE tilt1, DOUBLE psi1,
DOUBLE &alpha, DOUBLE &tilt_angle, DOUBLE &beta)
{
// Transformation matrices
Matrix1D<DOUBLE> axis(3);
Matrix2D<DOUBLE> E1, E2;
axis.resize(3);
DOUBLE aux, sine_tilt_angle;
DOUBLE rot2 = alpha, tilt2 = tilt_angle, psi2 = beta;
// Calculate the transformation from one setting to the second one.
Euler_angles2matrix(psi1, tilt1, rot1, E1);
Euler_angles2matrix(psi2, tilt2, rot2, E2);
E2 = E2 * E1.inv();
// Get the tilt angle (and its sine)
aux = ( E2(0,0) + E2(1,1) + E2(2,2) - 1. ) / 2.;
if (ABS(aux) - 1. > XMIPP_EQUAL_ACCURACY)
REPORT_ERROR("BUG: aux>1");
tilt_angle = ACOSD(aux);
sine_tilt_angle = 2. * SIND(tilt_angle);
// Get the tilt axis direction in angles alpha and beta
if (sine_tilt_angle > XMIPP_EQUAL_ACCURACY)
{
axis(0) = ( E2(2,1) - E2(1,2) ) / sine_tilt_angle;
axis(1) = ( E2(0,2) - E2(2,0) ) / sine_tilt_angle;
axis(2) = ( E2(1,0) - E2(0,1) ) / sine_tilt_angle;
}
else
{
axis(0) = axis(1) = 0.;
axis(2) = 1.;
}
// Apply E1.inv() to the axis to get everyone in the same coordinate system again
axis = E1.inv() * axis;
// Convert to alpha and beta angle
Euler_direction2angles(axis, alpha, beta);
// Enforce positive beta: choose the other Euler angle combination to express the same direction
if (beta < 0.)
{
beta = -beta;
alpha+= 180.;
}
// Let alpha go from 0 to 360 degrees
alpha = realWRAP(alpha, 0., 360.);
// Return the value that needs to be optimized
DOUBLE minimizer=0.;
if (exp_beta < 999.)
minimizer = ABS(beta - exp_beta);
if (exp_tilt < 999.)
minimizer += ABS(tilt_angle - exp_tilt);
return minimizer;
}
/* Subroutine */ int slaebz_(integer *ijob, integer *nitmax, integer *n,
integer *mmax, integer *minp, integer *nbmin, real *abstol, real *
reltol, real *pivmin, real *d, real *e, real *e2, integer *nval, real
*ab, real *c, integer *mout, integer *nab, real *work, integer *iwork,
integer *info)
{
/* -- LAPACK auxiliary routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
SLAEBZ contains the iteration loops which compute and use the
function N(w), which is the count of eigenvalues of a symmetric
tridiagonal matrix T less than or equal to its argument w. It
performs a choice of two types of loops:
IJOB=1, followed by
IJOB=2: It takes as input a list of intervals and returns a list of
sufficiently small intervals whose union contains the same
eigenvalues as the union of the original intervals.
The input intervals are (AB(j,1),AB(j,2)], j=1,...,MINP.
The output interval (AB(j,1),AB(j,2)] will contain
eigenvalues NAB(j,1)+1,...,NAB(j,2), where 1 <= j <= MOUT.
IJOB=3: It performs a binary search in each input interval
(AB(j,1),AB(j,2)] for a point w(j) such that
N(w(j))=NVAL(j), and uses C(j) as the starting point of
the search. If such a w(j) is found, then on output
AB(j,1)=AB(j,2)=w. If no such w(j) is found, then on output
(AB(j,1),AB(j,2)] will be a small interval containing the
point where N(w) jumps through NVAL(j), unless that point
lies outside the initial interval.
Note that the intervals are in all cases half-open intervals,
i.e., of the form (a,b] , which includes b but not a .
To avoid underflow, the matrix should be scaled so that its largest
element is no greater than overflow**(1/2) * underflow**(1/4)
in absolute value. To assure the most accurate computation
of small eigenvalues, the matrix should be scaled to be
not much smaller than that, either.
See W. Kahan "Accurate Eigenvalues of a Symmetric Tridiagonal
VISMatrix", Report CS41, Computer Science Dept., Stanford
University, July 21, 1966
Note: the arguments are, in general, *not* checked for unreasonable
values.
Arguments
=========
IJOB (input) INTEGER
Specifies what is to be done:
= 1: Compute NAB for the initial intervals.
= 2: Perform bisection iteration to find eigenvalues of T.
= 3: Perform bisection iteration to invert N(w), i.e.,
to find a point which has a specified number of
eigenvalues of T to its left.
Other values will cause SLAEBZ to return with INFO=-1.
NITMAX (input) INTEGER
The maximum number of "levels" of bisection to be
performed, i.e., an interval of width W will not be made
smaller than 2^(-NITMAX) * W. If not all intervals
have converged after NITMAX iterations, then INFO is set
to the number of non-converged intervals.
N (input) INTEGER
The dimension n of the tridiagonal matrix T. It must be at
least 1.
MMAX (input) INTEGER
The maximum number of intervals. If more than MMAX intervals
are generated, then SLAEBZ will quit with INFO=MMAX+1.
MINP (input) INTEGER
The initial number of intervals. It may not be greater than
MMAX.
NBMIN (input) INTEGER
The smallest number of intervals that should be processed
using a vector loop. If zero, then only the scalar loop
will be used.
ABSTOL (input) REAL
The minimum (absolute) width of an interval. When an
interval is narrower than ABSTOL, or than RELTOL times the
larger (in magnitude) endpoint, then it is considered to be
sufficiently small, i.e., converged. This must be at least
zero.
RELTOL (input) REAL
The minimum relative width of an interval. When an interval
is narrower than ABSTOL, or than RELTOL times the larger (in
magnitude) endpoint, then it is considered to be
sufficiently small, i.e., converged. Note: this should
always be at least radix*machine epsilon.
PIVMIN (input) REAL
The minimum absolute value of a "pivot" in the Sturm
sequence loop. This *must* be at least max |e(j)**2| *
safe_min and at least safe_min, where safe_min is at least
the smallest number that can divide one without overflow.
D (input) REAL array, dimension (N)
The diagonal elements of the tridiagonal matrix T.
E (input) REAL array, dimension (N)
The offdiagonal elements of the tridiagonal matrix T in
positions 1 through N-1. E(N) is arbitrary.
E2 (input) REAL array, dimension (N)
The squares of the offdiagonal elements of the tridiagonal
matrix T. E2(N) is ignored.
NVAL (input/output) INTEGER array, dimension (MINP)
If IJOB=1 or 2, not referenced.
If IJOB=3, the desired values of N(w). The elements of NVAL
will be reordered to correspond with the intervals in AB.
Thus, NVAL(j) on output will not, in general be the same as
NVAL(j) on input, but it will correspond with the interval
(AB(j,1),AB(j,2)] on output.
AB (input/output) REAL array, dimension (MMAX,2)
The endpoints of the intervals. AB(j,1) is a(j), the left
endpoint of the j-th interval, and AB(j,2) is b(j), the
right endpoint of the j-th interval. The input intervals
will, in general, be modified, split, and reordered by the
calculation.
C (input/output) REAL array, dimension (MMAX)
If IJOB=1, ignored.
If IJOB=2, workspace.
If IJOB=3, then on input C(j) should be initialized to the
first search point in the binary search.
MOUT (output) INTEGER
If IJOB=1, the number of eigenvalues in the intervals.
If IJOB=2 or 3, the number of intervals output.
If IJOB=3, MOUT will equal MINP.
NAB (input/output) INTEGER array, dimension (MMAX,2)
If IJOB=1, then on output NAB(i,j) will be set to N(AB(i,j)).
If IJOB=2, then on input, NAB(i,j) should be set. It must
satisfy the condition:
N(AB(i,1)) <= NAB(i,1) <= NAB(i,2) <= N(AB(i,2)),
which means that in interval i only eigenvalues
NAB(i,1)+1,...,NAB(i,2) will be considered. Usually,
NAB(i,j)=N(AB(i,j)), from a previous call to SLAEBZ with
IJOB=1.
On output, NAB(i,j) will contain
max(na(k),min(nb(k),N(AB(i,j)))), where k is the index of
the input interval that the output interval
(AB(j,1),AB(j,2)] came from, and na(k) and nb(k) are the
the input values of NAB(k,1) and NAB(k,2).
If IJOB=3, then on output, NAB(i,j) contains N(AB(i,j)),
unless N(w) > NVAL(i) for all search points w , in which
case NAB(i,1) will not be modified, i.e., the output
value will be the same as the input value (modulo
reorderings -- see NVAL and AB), or unless N(w) < NVAL(i)
for all search points w , in which case NAB(i,2) will
not be modified. Normally, NAB should be set to some
distinctive value(s) before SLAEBZ is called.
WORK (workspace) REAL array, dimension (MMAX)
Workspace.
IWORK (workspace) INTEGER array, dimension (MMAX)
Workspace.
INFO (output) INTEGER
= 0: All intervals converged.
= 1--MMAX: The last INFO intervals did not converge.
= MMAX+1: More than MMAX intervals were generated.
Further Details
===============
This routine is intended to be called only by other LAPACK
routines, thus the interface is less user-friendly. It is intended
for two purposes:
(a) finding eigenvalues. In this case, SLAEBZ should have one or
more initial intervals set up in AB, and SLAEBZ should be called
with IJOB=1. This sets up NAB, and also counts the eigenvalues.
Intervals with no eigenvalues would usually be thrown out at
this point. Also, if not all the eigenvalues in an interval i
are desired, NAB(i,1) can be increased or NAB(i,2) decreased.
For example, set NAB(i,1)=NAB(i,2)-1 to get the largest
eigenvalue. SLAEBZ is then called with IJOB=2 and MMAX
no smaller than the value of MOUT returned by the call with
IJOB=1. After this (IJOB=2) call, eigenvalues NAB(i,1)+1
through NAB(i,2) are approximately AB(i,1) (or AB(i,2)) to the
tolerance specified by ABSTOL and RELTOL.
(b) finding an interval (a',b'] containing eigenvalues w(f),...,w(l).
In this case, start with a Gershgorin interval (a,b). Set up
AB to contain 2 search intervals, both initially (a,b). One
NVAL element should contain f-1 and the other should contain l
, while C should contain a and b, resp. NAB(i,1) should be -1
and NAB(i,2) should be N+1, to flag an error if the desired
interval does not lie in (a,b). SLAEBZ is then called with
IJOB=3. On exit, if w(f-1) < w(f), then one of the intervals --
j -- will have AB(j,1)=AB(j,2) and NAB(j,1)=NAB(j,2)=f-1, while
if, to the specified tolerance, w(f-k)=...=w(f+r), k > 0 and r
>= 0, then the interval will have N(AB(j,1))=NAB(j,1)=f-k and
N(AB(j,2))=NAB(j,2)=f+r. The cases w(l) < w(l+1) and
w(l-r)=...=w(l+k) are handled similarly.
=====================================================================
Check for Errors
Parameter adjustments
Function Body */
/* System generated locals */
integer nab_dim1, nab_offset, ab_dim1, ab_offset, i__1, i__2, i__3, i__4,
i__5, i__6;
real r__1, r__2, r__3, r__4;
/* Local variables */
static integer itmp1, itmp2, j, kfnew, klnew, kf, ji, kl, jp, jit;
static real tmp1, tmp2;
#define D(I) d[(I)-1]
#define E(I) e[(I)-1]
#define E2(I) e2[(I)-1]
#define NVAL(I) nval[(I)-1]
#define C(I) c[(I)-1]
#define WORK(I) work[(I)-1]
#define IWORK(I) iwork[(I)-1]
#define NAB(I,J) nab[(I)-1 + ((J)-1)* ( *mmax)]
#define AB(I,J) ab[(I)-1 + ((J)-1)* ( *mmax)]
*info = 0;
if (*ijob < 1 || *ijob > 3) {
*info = -1;
return 0;
}
/* Initialize NAB */
if (*ijob == 1) {
/* Compute the number of eigenvalues in the initial intervals.
*/
*mout = 0;
i__1 = *minp;
for (ji = 1; ji <= *minp; ++ji) {
for (jp = 1; jp <= 2; ++jp) {
tmp1 = D(1) - AB(ji,jp);
if (dabs(tmp1) < *pivmin) {
tmp1 = -(doublereal)(*pivmin);
}
NAB(ji,jp) = 0;
if (tmp1 <= 0.f) {
NAB(ji,jp) = 1;
}
i__2 = *n;
for (j = 2; j <= *n; ++j) {
tmp1 = D(j) - E2(j - 1) / tmp1 - AB(ji,jp);
if (dabs(tmp1) < *pivmin) {
tmp1 = -(doublereal)(*pivmin);
}
if (tmp1 <= 0.f) {
++NAB(ji,jp);
}
/* L10: */
}
/* L20: */
}
*mout = *mout + NAB(ji,2) - NAB(ji,1);
/* L30: */
}
return 0;
}
/* Initialize for loop
KF and KL have the following meaning:
Intervals 1,...,KF-1 have converged.
Intervals KF,...,KL still need to be refined. */
kf = 1;
kl = *minp;
/* If IJOB=2, initialize C.
If IJOB=3, use the user-supplied starting point. */
if (*ijob == 2) {
i__1 = *minp;
for (ji = 1; ji <= *minp; ++ji) {
C(ji) = (AB(ji,1) + AB(ji,2)) * .5f;
/* L40: */
}
}
/* Iteration loop */
i__1 = *nitmax;
for (jit = 1; jit <= *nitmax; ++jit) {
/* Loop over intervals */
if (kl - kf + 1 >= *nbmin && *nbmin > 0) {
/* Begin of Parallel Version of the loop */
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
/* Compute N(c), the number of eigenvalues less t
han c */
WORK(ji) = D(1) - C(ji);
IWORK(ji) = 0;
if (WORK(ji) <= *pivmin) {
IWORK(ji) = 1;
/* Computing MIN */
r__1 = WORK(ji), r__2 = -(doublereal)(*pivmin);
WORK(ji) = dmin(r__1,r__2);
}
i__3 = *n;
for (j = 2; j <= *n; ++j) {
WORK(ji) = D(j) - E2(j - 1) / WORK(ji) - C(ji);
if (WORK(ji) <= *pivmin) {
++IWORK(ji);
/* Computing MIN */
r__1 = WORK(ji), r__2 = -(doublereal)(*pivmin);
WORK(ji) = dmin(r__1,r__2);
}
/* L50: */
}
/* L60: */
}
if (*ijob <= 2) {
/* IJOB=2: Choose all intervals containing eigenv
alues. */
klnew = kl;
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
/* Insure that N(w) is monotone
Computing MIN
Computing MAX */
i__5 = NAB(ji,1), i__6 = IWORK(ji);
i__3 = NAB(ji,2), i__4 = max(i__5,i__6);
IWORK(ji) = min(i__3,i__4);
/* Update the Queue -- add intervals if bo
th halves
contain eigenvalues. */
if (IWORK(ji) == NAB(ji,2)) {
/* No eigenvalue in the upper inter
val:
just use the lower interval. */
AB(ji,2) = C(ji);
} else if (IWORK(ji) == NAB(ji,1)) {
/* No eigenvalue in the lower inter
val:
just use the upper interval. */
AB(ji,1) = C(ji);
} else {
++klnew;
if (klnew <= *mmax) {
/* Eigenvalue in both interv
als -- add upper to
queue. */
AB(klnew,2) = AB(ji,2);
NAB(klnew,2) = NAB(ji,2);
AB(klnew,1) = C(ji);
NAB(klnew,1) = IWORK(ji);
AB(ji,2) = C(ji);
NAB(ji,2) = IWORK(ji);
} else {
*info = *mmax + 1;
}
}
/* L70: */
}
if (*info != 0) {
return 0;
}
kl = klnew;
} else {
/* IJOB=3: Binary search. Keep only the interval
containing
w s.t. N(w) = NVAL */
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
if (IWORK(ji) <= NVAL(ji)) {
AB(ji,1) = C(ji);
NAB(ji,1) = IWORK(ji);
}
if (IWORK(ji) >= NVAL(ji)) {
AB(ji,2) = C(ji);
NAB(ji,2) = IWORK(ji);
}
/* L80: */
}
}
} else {
/* End of Parallel Version of the loop
Begin of Serial Version of the loop */
klnew = kl;
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
/* Compute N(w), the number of eigenvalues less t
han w */
tmp1 = C(ji);
tmp2 = D(1) - tmp1;
itmp1 = 0;
if (tmp2 <= *pivmin) {
itmp1 = 1;
/* Computing MIN */
r__1 = tmp2, r__2 = -(doublereal)(*pivmin);
tmp2 = dmin(r__1,r__2);
}
/* A series of compiler directives to defeat vect
orization
for the next loop
$PL$ CMCHAR=' '
DIR$ NEXTSCALAR
$DIR SCALAR
DIR$ NEXT SCALAR
VD$L NOVECTOR
DEC$ NOVECTOR
VD$ NOVECTOR
VDIR NOVECTOR
VOCL LOOP,SCALAR
IBM PREFER SCALAR
$PL$ CMCHAR='*' */
i__3 = *n;
for (j = 2; j <= *n; ++j) {
tmp2 = D(j) - E2(j - 1) / tmp2 - tmp1;
if (tmp2 <= *pivmin) {
++itmp1;
/* Computing MIN */
r__1 = tmp2, r__2 = -(doublereal)(*pivmin);
tmp2 = dmin(r__1,r__2);
}
/* L90: */
}
if (*ijob <= 2) {
/* IJOB=2: Choose all intervals containing
eigenvalues.
Insure that N(w) is monotone
Computing MIN
Computing MAX */
i__5 = NAB(ji,1);
i__3 = NAB(ji,2), i__4 = max(i__5,itmp1);
itmp1 = min(i__3,i__4);
/* Update the Queue -- add intervals if bo
th halves
contain eigenvalues. */
if (itmp1 == NAB(ji,2)) {
/* No eigenvalue in the upper inter
val:
just use the lower interval. */
AB(ji,2) = tmp1;
} else if (itmp1 == NAB(ji,1)) {
/* No eigenvalue in the lower inter
val:
just use the upper interval. */
AB(ji,1) = tmp1;
} else if (klnew < *mmax) {
/* Eigenvalue in both intervals --
add upper to queue. */
++klnew;
AB(klnew,2) = AB(ji,2);
NAB(klnew,2) = NAB(ji,2);
AB(klnew,1) = tmp1;
NAB(klnew,1) = itmp1;
AB(ji,2) = tmp1;
NAB(ji,2) = itmp1;
} else {
*info = *mmax + 1;
return 0;
}
} else {
/* IJOB=3: Binary search. Keep only the i
nterval
containing w s.t. N(w) = NVAL
*/
if (itmp1 <= NVAL(ji)) {
AB(ji,1) = tmp1;
NAB(ji,1) = itmp1;
}
if (itmp1 >= NVAL(ji)) {
AB(ji,2) = tmp1;
NAB(ji,2) = itmp1;
}
}
/* L100: */
}
kl = klnew;
/* End of Serial Version of the loop */
}
/* Check for convergence */
kfnew = kf;
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
tmp1 = (r__1 = AB(ji,2) - AB(ji,1), dabs(
r__1));
/* Computing MAX */
r__3 = (r__1 = AB(ji,2), dabs(r__1)), r__4 = (r__2
= AB(ji,1), dabs(r__2));
tmp2 = dmax(r__3,r__4);
/* Computing MAX */
r__1 = max(*abstol,*pivmin), r__2 = *reltol * tmp2;
if (tmp1 < dmax(r__1,r__2) || NAB(ji,1) >= NAB(ji,2)) {
/* Converged -- Swap with position KFNEW,
then increment KFNEW */
if (ji > kfnew) {
tmp1 = AB(ji,1);
tmp2 = AB(ji,2);
itmp1 = NAB(ji,1);
itmp2 = NAB(ji,2);
AB(ji,1) = AB(kfnew,1);
AB(ji,2) = AB(kfnew,2);
NAB(ji,1) = NAB(kfnew,1);
NAB(ji,2) = NAB(kfnew,2);
AB(kfnew,1) = tmp1;
AB(kfnew,2) = tmp2;
NAB(kfnew,1) = itmp1;
NAB(kfnew,2) = itmp2;
if (*ijob == 3) {
itmp1 = NVAL(ji);
NVAL(ji) = NVAL(kfnew);
NVAL(kfnew) = itmp1;
}
}
++kfnew;
}
/* L110: */
}
kf = kfnew;
/* Choose Midpoints */
i__2 = kl;
for (ji = kf; ji <= kl; ++ji) {
C(ji) = (AB(ji,1) + AB(ji,2)) * .5f;
/* L120: */
}
/* If no more intervals to refine, quit. */
if (kf > kl) {
goto L140;
}
/* L130: */
}
/* Converged */
L140:
/* Computing MAX */
i__1 = kl + 1 - kf;
*info = max(i__1,0);
*mout = kl;
return 0;
/* End of SLAEBZ */
} /* slaebz_ */
double E()
{
return T()+E2();
}