260 lines
6.8 KiB
C++
260 lines
6.8 KiB
C++
#include <sys/time.h>
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#include <unistd.h>
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#include <iostream>
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#include <iomanip>
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#include <vector>
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#include <cmath>
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#include <fstream>
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using namespace std;
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#include <gsl/gsl_sf_bessel.h>
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typedef vector<double> PDoubleVector;
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#define PI 3.14159265359
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// NR p.797
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void voltra(const double h, PDoubleVector &t, PDoubleVector ¶m, PDoubleVector &f,
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double g(const int, const PDoubleVector &, const PDoubleVector &, const PDoubleVector &), PDoubleVector &gi)
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{
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int i,j;
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double sum;
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int n = f.size();
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double a;
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t[0] = 0.0;
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f[0]=g(0,t,param,gi);
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for (i=1; i<n; i++) {
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sum = g(i,t,param,gi);
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sum += 0.5*h*param[2]*g(i,t,param,gi)*f[0];
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for (j=1; j<i; j++) {
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sum += h*param[2]*g(i-j,t,param,gi)*f[j];
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}
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a = 1.0-0.5*h*param[2]*g(0,t,param,gi);
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f[i]=sum/a;
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}
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}
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double g_gauss(const int i, const PDoubleVector &tvec, const PDoubleVector ¶m, const PDoubleVector &gi)
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{
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// param: 0=w0, 1=sigma, 2=nu
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double result;
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double t = tvec[i];
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double Dt2 = pow(param[1]*t, 2.0)/2.0;
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if (param[0] == 0.0) {
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result = 0.333333333333333333333333 + 0.66666666666666666666 * (1.0-2.0*Dt2) * exp(-Dt2);
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} else {
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result = 1.0 - 2.0*param[1]*param[1]/(param[0]*param[0])*(1.0-exp(-Dt2)*cos(param[0]*t)) +
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2.0*pow(param[1],4.0)/pow(param[0],3.0)*gi[i];
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}
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result *= exp(-param[2]*t);
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return result;
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}
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double g_lorentz(const int i, const PDoubleVector &tvec, const PDoubleVector ¶m, const PDoubleVector &gi)
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{
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// param: 0=w0, 1=lambda, 2=nu
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double result;
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double t = tvec[i];
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double at = param[1]*t;
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if (param[0] == 0.0) {
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result = 0.333333333333333333333333 + 0.66666666666666666666 * (1.0-at) * exp(-at);
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} else {
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double awL = param[1]/param[0];
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double wLt = param[0]*t;
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double expat = exp(-param[1]*t);
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result = 1.0 - awL*gsl_sf_bessel_j1(wLt)*expat - awL*awL*(gsl_sf_bessel_j0(wLt)*expat-1.0) -
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(1.0+awL*awL)*param[1]*gi[i];
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}
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result *= exp(-param[2]*t);
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return result;
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}
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void calc_gi_gauss(const double h, PDoubleVector &t, PDoubleVector ¶m, PDoubleVector &f)
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{
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// if w0=0 nothing to be done
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if (param[0] == 0.0)
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return;
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double dtHalf = h/2.0;
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PDoubleVector hh(t.size());
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hh[0] = 0.0;
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f[0] = 0.0;
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for (unsigned int i=1; i<t.size(); i++) {
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hh[i] = exp(-0.5*pow(param[1]*t[i],2.0))*sin(param[0]*t[i]);
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f[i] = f[i-1] + dtHalf*(hh[i]+hh[i-1]);
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}
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}
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void calc_gi_lorentz(const double h, PDoubleVector &t, PDoubleVector ¶m, PDoubleVector &f)
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{
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// if w0=0 nothing to be done
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if (param[0] == 0.0)
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return;
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double dtHalf = h/2.0;
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PDoubleVector hh(t.size());
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hh[0] = 0.0;
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f[0] = 0.0;
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for (unsigned int i=1; i<t.size(); i++) {
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hh[i] = gsl_sf_bessel_j0(param[0]*t[i]) * exp(-param[1]*t[i]);
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f[i] = f[i-1] + dtHalf*(hh[i]+hh[i-1]);
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}
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}
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int main(int argc, char *argv[])
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{
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bool useKeren = false;
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if (argc < 4) {
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cout << endl << "usage: dynGaussKT_LF w0 width nu [G|L N]";
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cout << endl << " w0: external field in Mc/s";
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cout << endl << " width: static field width in Mc/s";
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cout << endl << " nu: hopping rate in Mc/s";
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cout << endl << " G/L: G=Gaussian field distribution; L=Lorentzain field distribution";
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cout << endl << " if G/L not given, G is set as default";
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cout << endl << " N: number of sampling points";
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cout << endl << " if N is not given, calc N internally";
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cout << endl << endl;
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return 0;
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}
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PDoubleVector param(3);
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const double Tmax = 15.0;
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unsigned int N;
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bool gaussian = true;
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// feed parameter vector
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param[0] = atof(argv[1]); // w0
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param[1] = atof(argv[2]); // width
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param[2] = atof(argv[3]); // nu
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if (argc == 6) {
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N = atoi(argv[5]); // N
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} else {
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// w0 criteria, i.e. w0 T = 2 pi, ts = T/16, N = Tmax/ts, if N < 300, N == 300
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double val = 8.0/PI*Tmax*param[0];
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if (val < 300)
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N = 300;
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else
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N = static_cast<unsigned int>(val);
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// nu/Delta criteria
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if (param[1] != 0.0) { // Delta != 0
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val = param[2]/param[1]; // nu/Delta
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if (val > 5.0) {
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useKeren = true;
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N = 3000;
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}
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}
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}
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if (argc > 4) {
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if (*argv[4] == 'L') {
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gaussian = false;
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}
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}
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char fln[128];
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if (gaussian)
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snprintf(fln, sizeof(fln), "dynKT_LF_w0_%1.1f_width%1.1f_nu%1.1f_N%d_G.dat", param[0], param[1], param[2], N);
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else
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snprintf(fln, sizeof(fln), "dynKT_LF_w0_%1.1f_width%1.1f_nu%1.1f_N%d_L.dat", param[0], param[1], param[2], N);
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const double H = Tmax/N;
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PDoubleVector t(N);
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PDoubleVector f(N);
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PDoubleVector gi(N);
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PDoubleVector keren(N);
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// get start time
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struct timeval tv_start, tv_stop;
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double t1, t2;
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gettimeofday(&tv_start, 0);
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// feed time vector
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for (unsigned int i=0; i<N; i++) {
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t[i] = H*i;
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}
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if (gaussian) {
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calc_gi_gauss(H, t, param, gi);
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} else {
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calc_gi_lorentz(H, t, param, gi);
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}
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gettimeofday(&tv_stop, 0);
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t1 = (tv_stop.tv_sec - tv_start.tv_sec)*1000.0 + (tv_stop.tv_usec - tv_start.tv_usec)/1000.0;
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gettimeofday(&tv_start, 0);
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if (gaussian) {
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voltra(H, t, param, f, g_gauss, gi);
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} else {
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voltra(H, t, param, f, g_lorentz, gi);
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}
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// get stop time
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gettimeofday(&tv_stop, 0);
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t2 = (tv_stop.tv_sec - tv_start.tv_sec)*1000.0 + (tv_stop.tv_usec - tv_start.tv_usec)/1000.0;
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// calculate keren LF
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double w02, nu2, width2, Gamma_t;
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for (unsigned int i=0; i<t.size(); i++) {
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w02 = pow(param[0], 2.0);
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width2 = pow(param[1], 2.0);
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nu2 = pow(param[2], 2.0);
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Gamma_t = 2.0*width2/pow(w02+nu2,2.0)*((w02+nu2)*param[2]*t[i]+(w02-nu2)*(1.0-exp(-param[2]*t[i])*cos(param[0]*t[i]))-2.0*param[2]*param[0]*exp(-param[2]*t[i])*sin(param[0]*t[i]));
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if (gaussian)
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keren[i] = exp(-Gamma_t);
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else
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keren[i] = exp(-sqrt(2.0*Gamma_t));
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}
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ofstream fout;
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// open mlog-file
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fout.open(fln, iostream::out);
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if (!fout.is_open()) {
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return -1;
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}
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if (gaussian) {
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if (useKeren)
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fout << "# use Keren = true" << endl;
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else
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fout << "# use Keren = false" << endl;
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}
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fout << "# N = " << N << endl;
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if (gaussian) {
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fout << "# Gaussian field distribution" << endl;
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fout << "# w0 = " << param[0] << ", sigma = " << param[1] << ", nu = " << param[2] << endl;
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} else {
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fout << "# Lorentzian field distribution" << endl;
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fout << "# w0 = " << param[0] << ", lambda = " << param[1] << ", nu = " << param[2] << endl;
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}
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fout << "# calculation time: t1 = " << t1 << " (ms), t2 = " << t2 << " (ms)" << endl;
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fout << "# time" << setw(13) << "Pz_dyn_LF" << setw(13) << "g" << setw(13) << "gi" << setw(13) << "keren" << endl;
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fout << fixed << setprecision(6);
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for (unsigned int nn=0; nn<N; nn++) {
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fout << setw(12) << t[nn] << setw(13) << f[nn] << setw(13) << g_gauss(nn,t,param,gi) << setw(13) << gi[nn] << setw(13) << keren[nn];
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fout << endl;
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}
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fout.close();
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return 0;
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}
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