#include #include #include #include #include "tron.h" #ifndef min template static inline T min(T x,T y) { return (x static inline T max(T x,T y) { return (x>y)?x:y; } #endif #ifdef __cplusplus extern "C" { #endif extern double dnrm2_(int *, double *, int *); extern double ddot_(int *, double *, int *, double *, int *); extern int daxpy_(int *, double *, double *, int *, double *, int *); extern int dscal_(int *, double *, double *, int *); #ifdef __cplusplus } #endif static void default_print(const char *buf) { fputs(buf,stdout); fflush(stdout); } void TRON::info(const char *fmt,...) { char buf[BUFSIZ]; va_list ap; va_start(ap,fmt); vsprintf(buf,fmt,ap); va_end(ap); (*tron_print_string)(buf); } TRON::TRON(const function *fun_obj, double eps, int max_iter) { this->fun_obj=const_cast(fun_obj); this->eps=eps; this->max_iter=max_iter; tron_print_string = default_print; } TRON::~TRON() { } void TRON::tron(double *w) { // Parameters for updating the iterates. double eta0 = 1e-4, eta1 = 0.25, eta2 = 0.75; // Parameters for updating the trust region size delta. double sigma1 = 0.25, sigma2 = 0.5, sigma3 = 4; int n = fun_obj->get_nr_variable(); int i, cg_iter; double delta, snorm, one=1.0; double alpha, f, fnew, prered, actred, gs; int search = 1, iter = 1, inc = 1; double *s = new double[n]; double *r = new double[n]; double *w_new = new double[n]; double *g = new double[n]; for (i=0; ifun(w); fun_obj->grad(w, g); delta = dnrm2_(&n, g, &inc); double gnorm1 = delta; double gnorm = gnorm1; if (gnorm <= eps*gnorm1) search = 0; iter = 1; while (iter <= max_iter && search) { cg_iter = trcg(delta, g, s, r); memcpy(w_new, w, sizeof(double)*n); daxpy_(&n, &one, s, &inc, w_new, &inc); gs = ddot_(&n, g, &inc, s, &inc); prered = -0.5*(gs-ddot_(&n, s, &inc, r, &inc)); fnew = fun_obj->fun(w_new); // Compute the actual reduction. actred = f - fnew; // On the first iteration, adjust the initial step bound. snorm = dnrm2_(&n, s, &inc); if (iter == 1) delta = min(delta, snorm); // Compute prediction alpha*snorm of the step. if (fnew - f - gs <= 0) alpha = sigma3; else alpha = max(sigma1, -0.5*(gs/(fnew - f - gs))); // Update the trust region bound according to the ratio of actual to predicted reduction. if (actred < eta0*prered) delta = min(max(alpha, sigma1)*snorm, sigma2*delta); else if (actred < eta1*prered) delta = max(sigma1*delta, min(alpha*snorm, sigma2*delta)); else if (actred < eta2*prered) delta = max(sigma1*delta, min(alpha*snorm, sigma3*delta)); else delta = max(delta, min(alpha*snorm, sigma3*delta)); info("iter %2d act %5.3e pre %5.3e delta %5.3e f %5.3e |g| %5.3e CG %3d\n", iter, actred, prered, delta, f, gnorm, cg_iter); if (actred > eta0*prered) { iter++; memcpy(w, w_new, sizeof(double)*n); f = fnew; fun_obj->grad(w, g); gnorm = dnrm2_(&n, g, &inc); if (gnorm <= eps*gnorm1) break; } if (f < -1.0e+32) { info("WARNING: f < -1.0e+32\n"); break; } if (fabs(actred) <= 0 && prered <= 0) { info("WARNING: actred and prered <= 0\n"); break; } if (fabs(actred) <= 1.0e-12*fabs(f) && fabs(prered) <= 1.0e-12*fabs(f)) { info("WARNING: actred and prered too small\n"); break; } } delete[] g; delete[] r; delete[] w_new; delete[] s; } int TRON::trcg(double delta, double *g, double *s, double *r) { int i, inc = 1; int n = fun_obj->get_nr_variable(); double one = 1; double *d = new double[n]; double *Hd = new double[n]; double rTr, rnewTrnew, alpha, beta, cgtol; for (i=0; iHv(d, Hd); alpha = rTr/ddot_(&n, d, &inc, Hd, &inc); daxpy_(&n, &alpha, d, &inc, s, &inc); if (dnrm2_(&n, s, &inc) > delta) { info("cg reaches trust region boundary\n"); alpha = -alpha; daxpy_(&n, &alpha, d, &inc, s, &inc); double std = ddot_(&n, s, &inc, d, &inc); double sts = ddot_(&n, s, &inc, s, &inc); double dtd = ddot_(&n, d, &inc, d, &inc); double dsq = delta*delta; double rad = sqrt(std*std + dtd*(dsq-sts)); if (std >= 0) alpha = (dsq - sts)/(std + rad); else alpha = (rad - std)/dtd; daxpy_(&n, &alpha, d, &inc, s, &inc); alpha = -alpha; daxpy_(&n, &alpha, Hd, &inc, r, &inc); break; } alpha = -alpha; daxpy_(&n, &alpha, Hd, &inc, r, &inc); rnewTrnew = ddot_(&n, r, &inc, r, &inc); beta = rnewTrnew/rTr; dscal_(&n, &beta, d, &inc); daxpy_(&n, &one, r, &inc, d, &inc); rTr = rnewTrnew; } delete[] d; delete[] Hd; return(cg_iter); } double TRON::norm_inf(int n, double *x) { double dmax = fabs(x[0]); for (int i=1; i= dmax) dmax = fabs(x[i]); return(dmax); } void TRON::set_print_string(void (*print_string) (const char *buf)) { tron_print_string = print_string; }