void
manager::start_file(const string& file, client *cl, bool temp)
{
pthread_setspecific(client_key, cl);
scheduler_type sched_type(SCHED_SERIAL_UI);
try {
router rout(1, 0, NULL, is_mpi_sched(sched_type));
machine mac(file, rout, 1, sched_type);
cl->all = mac.get_all();
LOG_PROGRAM_RUNNING();
if(temp) {
delete_temp_file(file);
}
mac.start();
LOG_PROGRAM_STOPPED();
} catch(std::exception& e) {
cerr << e.what() << endl;
}
client_mtx.lock();
cl->all = NULL;
client_mtx.unlock();
}
BSONObj MozJSImplScope::callThreadArgs(const BSONObj& args) {
MozJSEntry entry(this);
JS::RootedValue function(_context);
ValueReader(_context, &function).fromBSONElement(args.firstElement(), args, true);
int argc = args.nFields() - 1;
JS::AutoValueVector argv(_context);
BSONObjIterator it(args);
it.next();
JS::RootedValue value(_context);
for (int i = 0; i < argc; ++i) {
ValueReader(_context, &value).fromBSONElement(*it, args, true);
argv.append(value);
it.next();
}
JS::RootedValue out(_context);
JS::RootedObject thisv(_context);
_checkErrorState(JS::Call(_context, thisv, function, argv, &out), false, true);
JS::RootedObject rout(_context, JS_NewPlainObject(_context));
ObjectWrapper wout(_context, rout);
wout.setValue("ret", out);
return wout.toBSON();
}
// compute distances from rows of inmat1 to rows of inmat2
RcppExport SEXP rthpdist(SEXP inmat1,SEXP inmat2, SEXP nthreads)
{
Rcpp::NumericMatrix im1(inmat1);
Rcpp::NumericMatrix im2(inmat2);
int nr1 = im1.nrow();
int nc = im1.ncol();
int nr2 = im2.nrow();
#if RTH_OMP
omp_set_num_threads(INT(nthreads));
#elif RTH_TBB
// tbb::task_scheduler_init init(INT(nthreads));
// for unknown reasons, this code does not work under TBB
return Rcpp::wrap(-1);
#endif
thrust::device_vector<double> dmat1(im1.begin(),im1.end());
thrust::device_vector<double> dmat2(im2.begin(),im2.end());
// make space for the output
thrust::device_vector<double> ddst(nr1*nr2);
// iterators for row number of inmat1
thrust::counting_iterator<int> iseqb(0);
thrust::counting_iterator<int> iseqe = iseqb + nr1;
// for each i in [iseqb,iseqe) find the distances from row i in inmat1
// to all rows of inmat2
thrust::for_each(iseqb,iseqe,
do1ival(dmat1.begin(),dmat2.begin(),ddst.begin(),nr1,nc,nr2));
Rcpp::NumericMatrix rout(nr1,nr2);
thrust::copy(ddst.begin(),ddst.end(),rout.begin());
return rout;
}
int main()
{
cout << setiosflags(ios::uppercase);
ofstream out("RandomData.out");
out << setiosflags(ios::uppercase);
ofstream rout("Random.out");
rout << setiosflags(ios::uppercase);
//NUR FUER DEBUGZWECKE
double x, a;
double x1, x2, h, n, xu, xi1, xi2;
cin >> x >> a;
cin >> x1 >> x2 >> n;
h = (x2 -x1)/n;
cout << "+++ PARAMETER RANDOM +++" << endl;
cout << "x = " << x << endl;
cout << "a = " << a << endl;
cout << '\v' ;
cout << "x1 = " << x1 << endl;
cout << "x2 = " << x2 << endl;
cout << "h = " << h << endl;
cout << "n = " << n << endl;
for(int i = 0;i <= n; i++)
{
xu = x1 + i * h;
xi1 = Xi1(xu); // mit N default
double fr1 = f1(xu) + 0.01 * xi1;
double s1_rel = fabs(fr1 - f1(xu))/fabs(f1(xu));
s1_rel *= 100.0;
xi2 = Xi2(xu);
double fr2 = f1(xu) + 0.01 * xi2;
double s2_rel = fabs(fr2 - f1(xu))/fabs(f1(xu));
s2_rel *= 100.0;
double xi3 = Xi3(xu);
double fr3 = f1(xu) + 0.01 * xi3;
double s3_rel = fabs(fr3 - f1(xu))/fabs(f1(xu));
s3_rel *= 100.0;
out << xu << '\t' << f1(xu) << '\t' << fr1 <<'\t' << fr2 << '\t' << fr3 << '\t' << s1_rel <<'\t' << s2_rel <<'\t' << s3_rel << endl;
rout << xu << '\t' << xi1 <<'\t' << xi2 <<'\t' << xi3 << endl;
}
return 0;
}
void rvdsp(rvector b , int n){
int i,n1;
n1=n ;
printf("\n") ;
for( i=0 ; i<n1 ; i++ ){
rout(b[i]) ;
printf("\n") ;
}
}
void rmdsp(rmatrix a , int n){
int i,j,n1;
n1=n ;
printf("\n") ;
for( i=0 ; i<n1 ; i++ ){
for ( j=0 ; j<n1 ; j++){
rout(a[i][j]) ;
}
printf("\n") ;
}
}
void bob::ap::Ceps::addDerivative(const blitz::Array<double,2>& input, blitz::Array<double,2>& output) const
{
// Initialize output to zero
output = 0.;
const int n_frames = input.extent(0);
blitz::Range rall = blitz::Range::all();
// Fill in the inner part as follows:
// \f$output[i] += \sum_{l=1}^{DW} l * (input[i+l] - input[i-l])\f$
for (int l=1; l<=(int)m_delta_win; ++l) {
blitz::Range rout(l,n_frames-l-1);
blitz::Range rp(2*l,n_frames-1);
blitz::Range rn(0,n_frames-2*l-1);
output(rout,rall) += l*(input(rp,rall) - input(rn,rall));
}
const double factor = m_delta_win*(m_delta_win+1)/2;
// Continue to fill the left boundary part as follows:
// \f$output[i] += (\sum_{l=1+i}^{DW} l*input[i+l]) - (\sum_{l=i+1}^{DW}l)*input[0])\f$
for (int i=0; i<(int)m_delta_win; ++i) {
output(i,rall) -= (factor - i*(i+1)/2) * input(0,rall);
for (int l=1+i; l<=(int)m_delta_win; ++l) {
output(i,rall) += l*(input(i+l,rall));
}
}
// Continue to fill the right boundary part as follows:
// \f$output[i] += (\sum_{l=Nframes-1-i}^{DW}l)*input[Nframes-1]) - (\sum_{l=Nframes-1-i}^{DW} l*input[i-l])\f$
for (int i=n_frames-(int)m_delta_win; i<n_frames; ++i) {
int ii = (n_frames-1)-i;
output(i,rall) += (factor - ii*(ii+1)/2) * input(n_frames-1,rall);
for (int l=1+ii; l<=(int)m_delta_win; ++l) {
output(i,rall) -= l*input(i-l,rall);
}
}
// Sum of the integer squared from 1 to delta_win
// pavel - remove division for the sake of compitability with Matlab code of RFFC features comparison paper
//const double sum = m_delta_win*(m_delta_win+1)*(2*m_delta_win+1)/3;
//output /= sum;
}
int main()
{
cout << setiosflags(ios::uppercase);
ofstream out1("Daten_Gauss.out");
out1 << setiosflags(ios::uppercase);
ofstream out("LIP.out");
out << setiosflags(ios::uppercase);
ofstream outs("Y2D.out");
outs << setiosflags(ios::uppercase);
ofstream rout("REGLIP_Gauss.out");
rout << setiosflags(ios::uppercase);
cout << "*** Imaginaerteilgleichung ***" << endl;
cout << "*** Filter: Gauss ***" << endl;
mp_init();
cout << "*** Precision = " << mpipl << " ***" << endl;
int M, N, MD;
double xa, xb, x1, x2, xr1, xr2, h, step, step2, b1, dfactor, dpi;
mp_real b, mpx1, mpx2, mpstep, mpx;
dpi = 4.0 * atan(1.0);
mp_real pi = mppic; // pi aus der Bibliothek !!!
mp_real pi2 = pi * pi;
static mp_real factor;
cin >> b1;
cin >> xa >> xb >> MD;
cin >> x1 >> x2 >> M;
cin >> xr1 >> xr2 >> N ;
cout << '\v';
/* KERNELARRY ANFANG */
mp_real* const mpregKern = new mp_real [M+1];
b = mp_real(b1);
mpx1 = mp_real(x1);
mpx2 = mp_real(x2);
mpstep = (mpx2 - mpx1)/mp_real(M);
/* Vorfaktor */
factor = mp_real(2.0)*b/power(pi,mp_real(1.5));
factor *= exp(mp_real(0.25) * pi2 * b * b);
dfactor = 2.0 * (b1/pow(dpi,1.5)) * exp(b1*b1*dpi*dpi*.25);
cout << "*** Begin: Init. Kernel *** " << endl;
cout << "b1 = " << b1 << endl;
cout << "b = " << b ;
cout << "x1 = " << x1 << endl; /* Anfangs-/Endpunkt der Regularisierung */
cout << "x2 = " << x2 << endl;
cout << "M = " << M << endl;
cout << "h = " << mpstep;
cout << "factor = " << factor ;
cout << "dfactor = " << dfactor << endl;
for(int i = 0; i <= M; i++)
{
mpx = mpx1 + i * mpstep;
mpregKern[i] = mpregkerne2(mpx, b);
}
cout << "*** End: Init. Kernel *** " << endl;
/* KERNELARRY ENDE */
double x0, datlinpol, Error_splint, DataError, e2core;
/* Index der Vektoren beginnt mit 1 und *nicht* mit 0 */
double* y2d = dvector(1,MD); /* 2.Ableitung der SPL-Funktion */
double* data = dvector(1,MD); /* Datenvektor */
double* x = dvector(1,MD); /* x-Vektor */
/* Datenarrays fuellen */
h = (xb - xa)/(MD - 1);
double rho = MD/(xb -xa);
cout << '\v';
cout << "*** Begin: Init. Data-Array ***" << endl;
cout << "xa = " << xa << endl; /* Anfangs-/Endpunkte der Daten */
cout << "xb = " << xb << endl;
cout << "MD = " << MD << endl; /* Zahl der Datenpunkte */
cout << "h = " << h << endl;
cout << "rho = " << rho << endl;
x[1] = xa;
data[1] = e2data(xa);
for(int i = 2; i <= MD ; i++)
{
x[i] = xa + (i-1) * h;
data[i] = e2data(x[i]);
}
x[MD] = xb;
data[MD] = e2data(xb);
cout << "*** End: Init. Data-Array ***" << endl;
cout << '\v' ;
/* Kontrollausgabe, Datenausgabe */
for(int i = 1; i <= MD; i++)
{
DataError = fabs(data[i] - e2(x[i]))/fabs(e2(x[i]));
DataError *= 100.0;
out1 << i << '\t' << x[i] << '\t' << data[i] << '\t' << e2(x[i]) << '\t' << DataError << endl;
}
cout << "*** Begin: Interpol. *** " << endl;
intlinear(x,data,MD,y2d);
for(int i = 1; i <= MD; i++) outs << i << '\t' << y2d[i] << endl;
cout << "*** End: Interpol. *** " << endl;
cout << '\v';
for(int j = 0; j <= M; j++)
{
step = dble(mpstep);
x0 = x1 + j * step;
datlinpol = linint(x,data,y2d,MD,x0);
e2core = e2(x0);
Error_splint = fabs(datlinpol - e2core)/fabs(e2core);
Error_splint *= 100.0;
out << x0 << '\t' << datlinpol << '\t' << e2core << '\t' << Error_splint << endl;
}
/* REGULARISIERUNG */
double xi;
mp_real mp_regsum, mpdata, mpError, mpreg;
double regsum, Error, Reg;
step2 = (xr2 - xr1)/N;
cout <<"*** Begin: Regularisation ***" << endl;
cout << "b1 = " << b1 << endl;
cout << "b = " << b ;
cout << "x1 = " << xr1 << endl;
cout << "x2 = " << xr2 << endl;
cout << "N = " << N << endl;
cout << "h = " << step2 << endl;
cout << '\v' ;
for(int jj = 0; jj <= N; jj++)
{
mp_regsum = mp_real(0.0);
x0 = xr1 + jj * step2;
for(int j = 0; j <= M; j++)
{
xi = x1 + j * step;
xi = x0 - xi;
datlinpol = linint(x,data,y2d,MD,xi);
mpdata = mp_real(datlinpol);
mp_regsum += mpregKern[j] * mpdata;
}
mp_regsum *= mpstep;
mp_regsum *= factor;
mpreg = mpRegexakt(mp_real(x0),b);
mpError = abs(mp_regsum - mpreg)/abs(mpreg);
mpError *= mp_real(100.0);
regsum = dble(mp_regsum);
Error = dble(mpError);
Reg = dble(mpreg);
cout << x0 << endl;
cout << mpreg << mp_regsum << mpError << endl;
rout << x0 << '\t' << Reg << '\t' << regsum << '\t' << Error << '\t' << b1 << endl;
}
cout <<"*** End: Regularisation ***" << endl;
free_dvector(y2d,1,MD);
free_dvector(data,1,MD);
free_dvector(x,1,MD);
delete [] mpregKern;
return 0;
}
int main()
{
cout << setiosflags(ios::uppercase);
ofstream out("LIPGauss.out");
out << setiosflags(ios::uppercase);
ofstream out1("DATENGaussLip.out");
out1 << setiosflags(ios::uppercase);
ofstream outs("Y2D.out");
outs << setiosflags(ios::uppercase);
ofstream rout("RegGaussLIP.out");
rout << setiosflags(ios::uppercase);
cout << "*** Filter: Gauss *** " << endl;
cout << "*** Imaginaerteil *** " << endl;
mp_init();
cout << "*** Precision = " << mpipl << " ***" << endl;
// pi aus der Bibliothek !!!
mp_real pi = mppic;
mp_real pi2 = pi * pi;
static mp_real factor;
static double dpi = 4.0 * atan(1.0);
static double dfactor;
int M, MD, N;
double b1, xa, xb, h, x1, x2, hreg;
mp_real b;
/* Parameter einlesen */
cin >> b1;
cin >> xa >> xb >> MD;
cin >> hreg >> N;
cin >> x1 >> x2 >> M;
b = mp_real(b1);
/* Vorfaktor */
factor = mp_real(2.0)*b/power(pi,mp_real(1.5));
factor *= exp(mp_real(0.25) * pi2 * b * b);
dfactor = 2.0 * (b1/pow(dpi,1.5)) * exp(b1*b1*dpi*dpi*.25);
/* DATEN UND SPLINE-ROUTINE */
/* 1. Ableitung der Funktion an den Eckpunkten */
double yp1, ypn;
double x0, dataspl, Error_splint, DataError, e2core;
/* Index der Vektoren beginnt mit 1 und *nicht* mit 0 */
double* y2d = dvector(1,MD); /* 2.Ableitung der SPL-Funktion */
double* data = dvector(1,MD); /* Datenvektor */
double* x = dvector(1,MD); /* x-Vektor */
/* Nebenbedingung natuerliche Splinefunktion setzen */
yp1 = ypn = 1E30;
// yp1 = ypn = 0.0 ;
/* Datenarrays fuellen */
h = (xb - xa)/(MD - 1);
double rho = MD/(xb - xa);
cout << '\v';
cout << "*** Begin: Init. Data-Array ***" << endl;
cout << "xa = " << xa << endl; /* Anfangs-/Endpunkte der Daten */
cout << "xb = " << xb << endl;
cout << "MD = " << MD << endl; /* Zahl der Datenpunkte */
cout << "h = " << h << endl;
cout << "rho = " << rho << endl;
x[1] = xa;
data[1] = e2data(xa);
for(int i = 2; i <= MD ; i++)
{
x[i] = xa + (i-1) * h;
data[i] = e2data(x[i]);
//cout << i << '\t' << x[i] << '\t' << data[i] << '\t' << e2data(x[i]) << endl;
}
x[MD] = xb;
data[MD] = e2data(xb);
cout << "*** End: Init. Data-Array ***" << endl;
cout << '\v' ;
/* Kontrollausgabe, Datenausgabe */
for(int i = 1; i <= MD; i++)
{
DataError = fabs(data[i] - e2(x[i]))/fabs(e2(x[i]));
DataError *= 100.0;
out1 << i << '\t' << x[i] << '\t' << data[i] << '\t' << e2(x[i]) << '\t' << DataError << endl;
}
cout << "*** Begin: LinInt. *** " << endl;
intlinear(x,data,MD,y2d);
for(int i = 1; i <= MD; i++) outs << i << '\t' << y2d[i] << endl;
cout << "*** End: LinInt *** " << endl;
cout << '\v';
// static double step = (xb - xa)/MD;
double xmax = N * hreg ;
for(int j = 0; j <= (2 * N); j++)
{
x0 = j * hreg - xmax ;
dataspl = linint(x,data,y2d,MD,x0);
e2core = e2(x0);
Error_splint = fabs(dataspl - e2core)/fabs(e2core);
Error_splint *= 100.0;
// cout << x0 << '\t' << dataspl << '\t' << e2core << '\t' << Error_splint << endl;
out << x0 << '\t' << dataspl << '\t' << e2core << '\t' << Error_splint << endl;
}
/* REGULARISATION */
mp_real mp_regsum, mpdataup, mpdatadown , fu, fd, mpx0, zu, zd;
mp_real mpx1, mpx2;
mp_real mp_theoreg, mp_Error;
double theoreg, Errorel;
static mp_real mph = mp_real(hreg);
static mp_real mprstep;
double dregsum, x0d, dzu, dzd;
mpx1 = mp_real(x1);
mpx2 = mp_real(x2);
mprstep = (mpx2 - mpx1)/mp_real(M);
cout <<"*** Begin: Regularisation ***" << endl;
cout << "b = " << b1 << endl;
cout << "N = " << N << endl;
cout << "h = " << hreg << endl;
cout << "xmax = " << N * hreg << endl;
cout << "hreg = " << mph << endl;
cout << "x1 = " << x1 << endl;
cout << "x2 = " << x2 << endl;
cout << "h = " << mprstep << endl;
cout << "dFaktor = " << dfactor << endl;
cout << "Faktor = " << factor << endl;
for(int jj = 0; jj <= M; jj++)
{
mpx0 = mpx1 + jj * mprstep;
x0d = dble(mpx0);
mpdataup = mp_real(linint(x,data,y2d,MD,x0d));
mp_regsum = mpregkerne2(mpx0, mpx0 , b) * mpdataup;
for(int j = 1; j <= N; j++)
{
zu = mpx0 + j * mph;
dzu = dble(zu);
zd = mpx0 - j * mph;
dzd = dble(zd);
mpdataup = mp_real(linint(x,data,y2d,MD,dzu));
fu = mpregkerne2(zu,mpx0,b) * mpdataup;
mpdatadown = mp_real(linint(x,data,y2d,MD,dzd));
fd = mpregkerne2(zd,mpx0,b) * mpdatadown;
mp_regsum += (fu + fd) ;
}
mp_regsum *= mph;
mp_regsum *= factor;
mp_theoreg = mpRegexakt(mpx0, b);
mp_Error = abs(mp_regsum - mp_theoreg)/abs(mp_theoreg);
mp_Error *= mp_real(100.0);
dregsum = dble(mp_regsum);
theoreg = dble(mp_theoreg);
Errorel = dble(mp_Error);
cout << mpx0 << mp_theoreg << mp_regsum << mp_Error << endl;
rout << x0d << '\t' << theoreg << '\t' << dregsum << '\t' << Errorel << '\t' << b1 << endl;
}
cout <<"*** End: Regularisation ***" << endl;
return 0;
}
