//------------------------------------------------------------------------------
void MfLowRankApproximation::initialize()
{
double dx;
double constValue;
double endValue;
double constEnd;
double epsilon;
dx = grid.DX;
try {
nOrbitals = cfg->lookup("spatialDiscretization.nSpatialOrbitals");
constEnd = cfg->lookup("meanFieldIntegrator.lowRankApproximation.constEnd");
constValue = cfg->lookup("meanFieldIntegrator.lowRankApproximation.constValue");
endValue = cfg->lookup("meanFieldIntegrator.lowRankApproximation.endValue");
epsilon = cfg->lookup("meanFieldIntegrator.lowRankApproximation.epsilon");
} catch (const SettingNotFoundException &nfex) {
cerr << "MfLowRankApproximation::Error reading entry from config object." << endl;
exit(EXIT_FAILURE);
}
int nConst = constEnd/dx;
int constCenter = nGrid/2;
Vxy = zeros(nGrid, nGrid);
for(uint p=0; p<potential.size(); p++) {
for(int i=0; i<nGrid; i++) {
for(int j=0; j<nGrid; j++) {
Vxy(i, j) += potential[p]->evaluate(i, j);
}
}
}
// Using a simple discretization equal to the discretization of
// the system.
mat h = hExactSpatial();
// mat h = hPiecewiseLinear();
mat Q = eye(nGrid,nGrid);
// Using a consant weight in the center of the potential
// and a linear decrease from the center.
vec g = gLinear(nGrid, constCenter, nConst, constValue, endValue);
mat C = cMatrix(g, h, dx);
vec lambda;
mat eigvec;
eig_sym(lambda, eigvec, inv(C.t())*Vxy*inv(C));
mat Ut = C.t()*eigvec;
mat QU = inv(Q)*Ut;
// Sorting the eigenvalues by absoulte value and finding the number
// of eigenvalues with abs(eigenval(i)) > epsilon
uvec indices = sort_index(abs(lambda), 1);
M = -1;
for(uint m=0; m <lambda.n_rows; m++) {
cout << abs(lambda(indices(m))) << endl;
if(abs(lambda(indices(m))) < epsilon) {
M = m;
break;
}
}
// cout << min(abs(lambda)) << endl;
// cout << "hei" << endl;
// cout << lambda << endl;
// M = 63;
if(M < 0) {
cerr << "MfLowRankApproximation:: no eigenvalues < epsilon found."
<< " Try setting epsilon to a higher number" << endl;
exit(EXIT_FAILURE);
}
eigenval = zeros(M);
for(int m=0; m <M; m++) {
eigenval(m) = lambda(indices(m));
}
// Calculating the U matrix
U = zeros(nGrid, M);
for(int m=0; m < M; m++) {
for(uint j=0; j<h.n_rows; j++) {
U(j,m) = 0;
for(uint i=0; i<h.n_cols; i++) {
U(j,m) += h(j,i)*QU(i,indices(m));
}
}
}
cout << "MfLowRankApproximation:: Trunction of eigenvalues at M = " << M << endl;
#if 1 // For testing the low rank approximation's accuracy
mat appV = zeros(nGrid, nGrid);
for(int i=0; i<nGrid; i++) {
for(int j=0; j<nGrid; j++) {
appV(i,j) = 0;
for(int m=0; m<M; m++) {
appV(i,j) += eigenval(m)*U(i,m)*U(j,m);
}
}
}
mat diffV = abs(Vxy - appV);
cout << "max_err = " << max(max(abs(Vxy - appV))) << endl;
diffV.save("../DATA/diffV.mat");
appV.save("../DATA/Vapp.mat");
Vxy.save("../DATA/Vex.mat");
cout << nGrid << endl;
// exit(EXIT_SUCCESS);
#endif
cout << "test" << endl;
Vm = zeros<cx_vec>(M);
Vqr = zeros<cx_vec>(nGrid);
}
void VideoFluids::trackVelocity(Matrix& Zn1,Matrix& Zn,Matrix& U,Matrix& V)
{
Matrix Zx(height,width),Zy(height,width),ZZx(height,width),ZZy(height,width),Zt(height,width),ZZt(height,width),ZZtx(height,width),ZZty(height,width);
Matrix Au1(height,width),Au2(height,width),Av1(height,width),Av2(height,width);
Matrix Z2x(height,width),Z2y(height,width),Z2(height,width);
Matrix Cu(height,width),Cv(height,width);
Matrix tmp(height,width),tmp1(height,width);
Matrix U_old(height,width),V_old(height,width),Ux(height,width),Uy(height,width),Vx(height,width),Vy(height,width),Uax(height,width),Uay(height,width),Vax(height,width),Vay(height,width),Uxy(height,width),Vxy(height,width);
Matrix Coe(height,width);
Zt = Zn;
Zt -= Zn1;
DotMul(Zn,Zt,ZZt);
Zn.output("Zn.txt");
Zn1.output("Zn1.txt");
Zt.output("Zt.txt");
Partial(ZZt,ZZtx,AXIS_X);
Partial(ZZt,ZZty,AXIS_Y);
Partial(Zn,Zx,AXIS_X);
Partial(Zn,Zy,AXIS_Y);
DotMul(Zn,Zx,ZZx);
DotMul(Zn,Zy,ZZy);
DotMul(Zx,Zx,Au1);
Partial(ZZx,tmp,AXIS_X);
Au1-=tmp;
DotMul(Zn,Zn,tmp);
Au1+=tmp;
Au1+=2*alpha*alpha;
DotMul(Zx,Zy,Au2);
Partial(ZZy,tmp,AXIS_X);
Au2-=tmp;
DotMul(Zx,Zy,Av1);
Partial(ZZx,tmp,AXIS_Y);
Av1-=tmp;
DotMul(Zy,Zy,Av2);
Partial(ZZy,tmp,AXIS_Y);
Av2-=tmp;
DotMul(Zn,Zn,tmp);
Av2+=tmp;
Av2+=2*alpha*alpha;
DotMul(Zn,Zn,Z2);
Partial(Z2,Z2x,AXIS_X);
Partial(Z2,Z2y,AXIS_Y);
for (int i = 0;i<height;i++)
for (int j = 0;j<width;j++)
Coe[i][j] = 1.0/(Au1[i][j]*Av2[i][j]-Au2[i][j]*Av1[i][j]);
U = 0.0;
V = 0.0;
for (int iter_time = 0;iter_time<iterationTime;iter_time++)
{
V_old = V;
U_old = U;
Partial(U,Ux,AXIS_X);
Partial(U,Uy,AXIS_Y);
Partial(V,Vx,AXIS_X);
Partial(V,Vy,AXIS_Y);
Partial(Vx,Vxy,AXIS_Y);
Partial(Ux,Uxy,AXIS_Y);
Average(U,Uax,AXIS_X);
Average(U,Uay,AXIS_Y);
Average(V,Vax,AXIS_X);
Average(V,Vay,AXIS_Y);
DotMul(Z2x,Ux,Cu);
DotMul(ZZy,Vx,tmp);
Cu += tmp;
tmp = ZZx*-1;
tmp+=Z2x;
DotMul(tmp,Vy,tmp1);
Cu+=tmp1;
tmp = Z2;
tmp+=alpha*alpha;
DotMul(tmp,Uax,tmp1);
Cu+=tmp1;
tmp1=Uay;
tmp1*=alpha*alpha;
Cu+=tmp1;
DotMul(Z2,Vxy,tmp1);
Cu+=tmp1;
DotMul(Zx,Zt,tmp);
Cu-=tmp;
Cu+=ZZtx;
DotMul(Z2y,Vy,Cv);
DotMul(ZZx,Uy,tmp);
Cv += tmp;
tmp = ZZy;
tmp*=-1;
tmp+=Z2y;
DotMul(tmp,Ux,tmp1);
Cv+=tmp1;
tmp = Z2;
tmp+=alpha*alpha;
DotMul(tmp,Vay,tmp1);
Cv+=tmp1;
tmp1=Vax;
tmp1*=alpha*alpha;
Cv+=tmp1;
DotMul(Z2,Uxy,tmp1);
Cv+=tmp1;
DotMul(Zy,Zt,tmp);
Cv-=tmp;
Cv+=ZZty;
for (int i = 0;i<height;i++)
for (int j = 0;j<width;j++)
{
U[i][j] = Coe[i][j]*(Av2[i][j]*Cu[i][j]-Au2[i][j]*Cv[i][j]);
V[i][j] = Coe[i][j]*(-Av1[i][j]*Cu[i][j]+Au1[i][j]*Cv[i][j]);
}
for (int i = 0;i<height;i++)
{
U[i][0] = U[i][1];
U[i][width-1] = U[i][width-2];
V[i][0] = V[i][1];
V[i][width-1] =V[i][width-2];
}
for (int i = 0;i<width;i++)
{
U[0][i] = U[1][i];
U[height-1][i] = U[height-2][i];
V[0][i] = V[1][i];
V[height-1][i] =V[height-2][i];
}
FILE* fp;
// Au1.output("Au1.txt");
// Au2.output("Au2.txt");
// Av1.output("Av1.txt");
// Av2.output("Av2.txt");
// Cu.output("Cu.txt");
// Cv.output("Cv.txt");
float d1 = Difference(U,U_old);
float d2 = Difference(V,V_old);
// U.output("U.txt");
// U_old.output("U_old.txt");
// V.output("V.txt");
cout<<d1<<' '<<d2<<endl;
if (d1<iterationTorlerance && d2<iterationTorlerance)
break;
}
U.output("U.txt");
cv::Mat showV(height,width,CV_8UC3);
float lowv=10000000,lowu=10000000,highu=-10000000,highv=-1000000;
for(int j=0;j<height;j++){
for(int k=0;k<width;k++){
if(U[j][k]>highu)
highu=U[j][k];
if(U[j][k]<lowu)
lowu=U[j][k];
if(V[j][k]>highv)
highv=V[j][k];
if(V[j][k]<lowv)
lowv=V[j][k];
}
}
for(int j=0;j<height;j++){
for(int k=0;k<width;k++){
//printf("%d %d\n",j,k);
//if(sfs_list[i][j][k]<low)
// showH.at<uchar>(j,k)=0;
//else
float u=(U[j][k]-lowu)/(highu-lowu);
float v=(V[j][k]-lowv)/(highv-lowv);
if(u>0.5)
showV.at<cv::Vec3b>(j,k)[2]=255;
else
showV.at<cv::Vec3b>(j,k)[2]=255*u;
if(v>0.5){
showV.at<cv::Vec3b>(j,k)[0]=255;
showV.at<cv::Vec3b>(j,k)[1]=255*(1-v);
}
else{
showV.at<cv::Vec3b>(j,k)[1]=255;
showV.at<cv::Vec3b>(j,k)[0]=255*v;
}
}
}
cv::imwrite("testV.bmp",showV);
printf("show you");
}
