double Optimize_Torsion_Parameters(int Idx_Soft_Tor)
{
double lb[N_TOR_PARA] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -100.0 }; /* lower bounds */
double ub[N_TOR_PARA] = { 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 100.0 }; /* lower bounds */
double Phase[32][5]={{0, 0, 0, 0, 0}, {0, 0, 0, 0, PI}, {0, 0, 0, PI, 0}, {0, 0, 0, PI, PI}, {0, 0, PI, 0, 0}, {0, 0, PI, 0, PI}, {0, 0, PI, PI, 0}, {0, 0, PI, PI, PI}, {0, PI, 0, 0, 0}, {0, PI, 0, 0, PI},
{0, PI, 0, PI, 0}, {0, PI, 0, PI, PI}, {0, PI, PI, 0, 0}, {0, PI, PI, 0, PI}, {0, PI, PI, PI, 0}, {0, PI, PI, PI, PI}, {PI, 0, 0, 0, 0}, {PI, 0, 0, 0, PI}, {PI, 0, 0, PI, 0}, {PI, 0, 0, PI, PI},
{PI, 0, PI, 0, 0}, {PI, 0, PI, 0, PI}, {PI, 0, PI, PI, 0}, {PI, 0, PI, PI, PI}, {PI, PI, 0, 0, 0}, {PI, PI, 0, 0, PI}, {PI, PI, 0, PI, 0}, {PI, PI, 0, PI, PI}, {PI, PI, PI, 0, 0}, {PI, PI, PI, 0, PI},
{PI, PI, PI, PI, 0}, {PI, PI, PI, PI, PI}};
nlopt_opt opt;
double Chi_SQ;
int i, j, Idx_Phi;
Chi_SQ_Min = 1.0E100;
opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
iseed = time(NULL);
ActiveRun = 0;
Chi_SQ_Min_Local[0] = 1.0E200;
FailCount = Iteration = 0;
Idx_Phi = IdxDihSelect[Idx_Soft_Tor];
Para_Tor[10] = 0.0;
for(i=0; i<N_TOR_PARA; i++) {
IsPara_Fixed[i] = 1;
}
IsPara_Fixed[N_TOR_PARA-1] = 0; // only optimize the last parameter
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt failed!\n");
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
nlopt_destroy(opt);
return Chi_SQ_Min;
}
double Callback_Eval_Gradient(unsigned n, const double *x, double *grad, void *my_func_data)
{
int n_Local;
double Chi_SQ;
n_Local = (int)n;
if(grad) {
Chi_SQ = CalGradient_Tor((double*)x, grad); //gradient will be assigned into objGrad automatically
}
else {
Chi_SQ = CalObjectiveFunction_Tor((double*)x);
}
Iteration++;
if(Chi_SQ < Chi_SQ_Min) {
Chi_SQ_Min = Chi_SQ;
if(Chi_SQ + 1.0E-5 > Chi_SQ_Min) {
FailCount++;
}
else {
FailCount = 0;
}
memcpy(Para_Best, x, sizeof(double)*n);
}
else {
FailCount++;
}
if(Chi_SQ < Chi_SQ_Min_Local[ActiveRun]) {
Chi_SQ_Min_Local[ActiveRun] = Chi_SQ;
memcpy(All_Para_Save[ActiveRun], x, sizeof(double)*n);
printf("Iter %6d :grad ? %d : ", Iteration, grad!=NULL );
for(int i=0; i<n;i++ ) {printf("%8.3f ", x[i] ); }
printf(" : %8.3f \n", Chi_SQ);
}
return Chi_SQ;
}
double CalGradient_Tor(double x[], double grad[]) // x - Para_Tor
{
int i;
double f, Phi;
f = CalObjectiveFunction_Tor(x);
memset(grad, 0, sizeof(double)*N_TOR_PARA);
for(i=0; i<nScan; i++) {
Phi = Phi_Scaned[i] * radianInv;
if(!IsPara_Fixed[0]) {
grad[0] += ( dE[i] * w_Point[i] * ( 1.0 + cos(1.0*Phi - x[1]) ) );
}
if(!IsPara_Fixed[2]) {
grad[2] += ( dE[i] * w_Point[i] * ( 1.0 + cos(2.0*Phi - x[3]) ) );
}
if(!IsPara_Fixed[4]) {
grad[4] += ( dE[i] * w_Point[i] * ( 1.0 + cos(3.0*Phi - x[5]) ) );
}
if(!IsPara_Fixed[6]) {
grad[6] += ( dE[i] * w_Point[i] * ( 1.0 + cos(4.0*Phi - x[7]) ) );
}
if(!IsPara_Fixed[8]) {
grad[8] += ( dE[i] * w_Point[i] * ( 1.0 + cos(6.0*Phi - x[9]) ) );
}
if(!IsPara_Fixed[10]) {
grad[10] += (dE[i] * w_Point[i]);
}
}
for(i=0; i<N_TOR_PARA; i++) {
grad[i] *= 2.0;
}
return f;
}
double Callback_Eval_Gradient(unsigned n, const double *x, double *grad, void *my_func_data)
{
int n_Local;
double Chi_SQ;
n_Local = (int)n;
if(grad) {
Chi_SQ = CalGradient_Tor((double*)x, grad); //gradient will be assigned into objGrad automatically
Iteration++;
if(Chi_SQ < Chi_SQ_Min) {
Chi_SQ_Min = Chi_SQ;
if(Chi_SQ + 1.0E-5 > Chi_SQ_Min) {
FailCount++;
}
else {
FailCount = 0;
}
memcpy(Para_Best, x, sizeof(double)*n);
}
else {
FailCount++;
}
if(Chi_SQ < Chi_SQ_Min_Local[ActiveRun]) {
Chi_SQ_Min_Local[ActiveRun] = Chi_SQ;
memcpy(All_Para_Save[ActiveRun], x, sizeof(double)*n);
}
}
else { // cal object function only
Chi_SQ = CalObjectiveFunction_Tor((double*)x);
}
return Chi_SQ;
}
double Optimize_Torsion_Parameters(void)
{
double lb[N_TOR_PARA] = {
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-20.0, -PI,
-100 };
double ub[N_TOR_PARA] = {
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+20.0, +PI,
+100 };
// double ub[N_TOR_PARA] = { 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 100.0 }; /* lower bounds */
nlopt_opt opt;
double Chi_SQ;
int i, j;
Chi_SQ_Min = 1.0E100;
for(i=0; i<NRUN; i++) { // was 32
ActiveRun = i;
Chi_SQ_Min_Local[i] = 1.0E200;
FailCount = Iteration = 0;
// for(j=0; j<5; j++) {
// Para_Tor[2*j] = 0.1+1.0*rand(iseed);
// }
for( i=0; i<11; i++ ) {
Para_Tor[i] = 0.;
IsPara_Fixed[i] = 0.;
} // inital values
//opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
printf("=== Fitting ===\n" );
opt = nlopt_create(NLOPT_LN_COBYLA, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt didn't converge %lf %lf\n Please check carefully the rotamer results\n",Chi_SQ_Min, Chi_SQ);
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
nlopt_destroy(opt);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
return Chi_SQ_Min;
}
double Optimize_Torsion_Parameters(void)
{
double lb[N_TOR_PARA] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -100.0 }; /* lower bounds */
double ub[N_TOR_PARA] = { 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 12.0, 100.0 }; /* lower bounds */
// double ub[N_TOR_PARA] = { 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 100.0 }; /* lower bounds */
double Phase[32][5]={{0, 0, 0, 0, 0}, {0, 0, 0, 0, PI}, {0, 0, 0, PI, 0}, {0, 0, 0, PI, PI}, {0, 0, PI, 0, 0}, {0, 0, PI, 0, PI}, {0, 0, PI, PI, 0}, {0, 0, PI, PI, PI}, {0, PI, 0, 0, 0}, {0, PI, 0, 0, PI},
{0, PI, 0, PI, 0}, {0, PI, 0, PI, PI}, {0, PI, PI, 0, 0}, {0, PI, PI, 0, PI}, {0, PI, PI, PI, 0}, {0, PI, PI, PI, PI}, {PI, 0, 0, 0, 0}, {PI, 0, 0, 0, PI}, {PI, 0, 0, PI, 0}, {PI, 0, 0, PI, PI},
{PI, 0, PI, 0, 0}, {PI, 0, PI, 0, PI}, {PI, 0, PI, PI, 0}, {PI, 0, PI, PI, PI}, {PI, PI, 0, 0, 0}, {PI, PI, 0, 0, PI}, {PI, PI, 0, PI, 0}, {PI, PI, 0, PI, PI}, {PI, PI, PI, 0, 0}, {PI, PI, PI, 0, PI},
{PI, PI, PI, PI, 0}, {PI, PI, PI, PI, PI}};
nlopt_opt opt;
double Chi_SQ;
int i, j;
Chi_SQ_Min = 1.0E100;
iseed = time(NULL);
for(i=0; i<32; i++) {
ActiveRun = i;
Chi_SQ_Min_Local[i] = 1.0E200;
FailCount = Iteration = 0;
// for(j=0; j<5; j++) {
// Para_Tor[2*j] = 0.1+1.0*rand(iseed);
// }
Para_Tor[0] = Para_Tor[2] = Para_Tor[4] = Para_Tor[6] = Para_Tor[8] = 1.0;
for(j=0; j<5; j++) {
Para_Tor[2*j+1] = Phase[i][j];
lb[2*j+1] = Para_Tor[2*j+1];
ub[2*j+1] = Para_Tor[2*j+1];
}
// Para_Tor[1] = Para_Tor[3] = Para_Tor[5] = Para_Tor[7] = Para_Tor[9] = 0.0;
Para_Tor[10] = 0.0;
IsPara_Fixed[1] = IsPara_Fixed[3] = IsPara_Fixed[5] = IsPara_Fixed[7] = IsPara_Fixed[9] = 1;
//for test
// IsPara_Fixed[6] = 1; Para_Tor[6] = 0.0;
opt = nlopt_create(NLOPT_LD_LBFGS, N_TOR_PARA);
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt, ub);
nlopt_set_min_objective(opt, Callback_Eval_Gradient, NULL);
nlopt_set_xtol_rel(opt, 1e-8);
if (nlopt_optimize(opt, Para_Tor, &Chi_SQ) < 0) {
printf("nlopt didn't converge %lf %lf\n Please check carefully the rotamer results\n",Chi_SQ_Min, Chi_SQ);
}
else {
printf("Chi_SQ_min = %lf Chi_SQ = %lf\n", Chi_SQ_Min, Chi_SQ);
}
nlopt_destroy(opt);
}
memcpy(Para_Tor, Para_Best, sizeof(double)*N_TOR_PARA);
CalObjectiveFunction_Tor(Para_Tor);
return Chi_SQ_Min;
}
