undocumented internal parameter sigma_min for experiments

Author: stevengj

src/algs/mma/ccsa_quadratic.c

@@ -219,7 +219,7 @@ nlopt_result ccsa_quadratic_minimize(
      double *minf,
      nlopt_stopping *stop,
      nlopt_opt dual_opt, int inner_maxeval, unsigned verbose, double rho_init,
-	 int inner_gradients, int always_improve,
+	 int inner_gradients, int always_improve, double sigma_min,
 	 const double *sigma_init)
 {
      nlopt_result ret = NLOPT_SUCCESS;
@@ -330,6 +330,7 @@ nlopt_result ccsa_quadratic_minimize(
 	       sigma[j] = 1.0; /* arbitrary default */
 	  else
 	       sigma[j] = 0.5 * (ub[j] - lb[j]);
+		sigma[j] = MAX(sigma[j], sigma_min);
      }
      rho = rho_init;
      for (i = 0; i < m; ++i) {
@@ -585,6 +586,7 @@ nlopt_result ccsa_quadratic_minimize(
 			    0.01*(ub-lb), which seems unnecessarily large */
 			 sigma[j] = MAX(sigma[j], 1e-8*(ub[j]-lb[j]));
 		    }
+			sigma[j] = MAX(sigma[j], sigma_min);
 	       }
 	       for (j = 0; j < MIN(verbose, n); ++j)
 		    printf("                 CCSA sigma[%u] -> %g\n",

src/algs/mma/mma.c

@@ -149,7 +149,7 @@ nlopt_result mma_minimize(unsigned n, nlopt_func f, void *f_data,
 			  double *minf,
 			  nlopt_stopping *stop,
 			  nlopt_opt dual_opt, int inner_maxeval, unsigned verbose, double rho_init,
-			  int inner_gradients, int always_improve,
+			  int inner_gradients, int always_improve, double sigma_min,
 			  const double *sigma_init)
 {
      nlopt_result ret = NLOPT_SUCCESS;
@@ -206,6 +206,7 @@ nlopt_result mma_minimize(unsigned n, nlopt_func f, void *f_data,
 	       sigma[j] = 1.0; /* arbitrary default */
 	  else
 	       sigma[j] = 0.5 * (ub[j] - lb[j]);
+	  sigma[j] = MAX(sigma[j], sigma_min);
      }
      rho = rho_init;
      for (i = 0; i < m; ++i) {
@@ -437,6 +438,7 @@ nlopt_result mma_minimize(unsigned n, nlopt_func f, void *f_data,
 			 sigma[j] = MIN(sigma[j], 10*(ub[j]-lb[j]));
 			 sigma[j] = MAX(sigma[j], 0.01*(ub[j]-lb[j]));
 		    }
+			sigma[j] = MAX(sigma[j], sigma_min);
 	       }
 	       for (j = 0; j < MIN(verbose, n); ++j)
 		    printf("                 MMA sigma[%u] -> %g\n",

src/algs/mma/mma.h

@@ -41,7 +41,7 @@ nlopt_result mma_minimize(unsigned n, nlopt_func f, void *f_data,
 			  double *minf,
 			  nlopt_stopping *stop,
 			  nlopt_opt dual_opt, int inner_maxeval, unsigned verbose, double rho_init,
-                 int inner_gradients, int always_improve,
+                 int inner_gradients, int always_improve, double sigma_min,
                  const double *sigma_init);
 
 nlopt_result ccsa_quadratic_minimize(
@@ -55,7 +55,7 @@ nlopt_result ccsa_quadratic_minimize(
      double *minf,
      nlopt_stopping *stop,
      nlopt_opt dual_opt, int inner_maxeval, unsigned verbose, double rho_init,
-     int inner_gradients, int always_improve,
+     int inner_gradients, int always_improve, double sigma_min,
      const double *sigma_init);
 
 #ifdef __cplusplus

src/api/optimize.c

@@ -800,6 +800,7 @@ static nlopt_result nlopt_optimize_(nlopt_opt opt, double *x, double *minf)
             double rho_init = nlopt_get_param(opt, "rho_init",1.0);
             int inner_gradients = (int)nlopt_get_param(opt, "inner_gradients",1);
             int always_improve = (int)nlopt_get_param(opt, "always_improve",1);
+            double sigma_min = nlopt_get_param(opt, "sigma_min",0.0);
             nlopt_opt dual_opt;
             nlopt_result ret;
 
@@ -809,6 +810,8 @@ static nlopt_result nlopt_optimize_(nlopt_opt opt, double *x, double *minf)
                 RETURN_ERR(NLOPT_INVALID_ARGS, opt, "inner_gradients must be 0 or 1");
             if (always_improve != 0 && always_improve != 1)
                 RETURN_ERR(NLOPT_INVALID_ARGS, opt, "always_improve must be 0 or 1");
+            if (sigma_min < 0.0)
+                RETURN_ERR(NLOPT_INVALID_ARGS, opt, "sigma_min must be non-negative");
             verbosity = verbosity < 0 ? 0 : verbosity;
 
 #define LO(param, def) (opt->local_opt ? opt->local_opt->param : (def))
@@ -823,9 +826,9 @@ static nlopt_result nlopt_optimize_(nlopt_opt opt, double *x, double *minf)
             nlopt_set_maxeval(dual_opt, (int)nlopt_get_param(opt, "dual_maxeval", LO(maxeval, 100000)));
 #undef LO
             if (algorithm == NLOPT_LD_MMA)
-                ret = mma_minimize(n, f, f_data, opt->m, opt->fc, lb, ub, x, minf, &stop, dual_opt, inner_maxeval, (unsigned)verbosity, rho_init, inner_gradients, always_improve, opt->dx);
+                ret = mma_minimize(n, f, f_data, opt->m, opt->fc, lb, ub, x, minf, &stop, dual_opt, inner_maxeval, (unsigned)verbosity, rho_init, inner_gradients, always_improve, sigma_min, opt->dx);
             else
-                ret = ccsa_quadratic_minimize(n, f, f_data, opt->m, opt->fc, opt->pre, lb, ub, x, minf, &stop, dual_opt, inner_maxeval, (unsigned)verbosity, rho_init, inner_gradients, always_improve, opt->dx);
+                ret = ccsa_quadratic_minimize(n, f, f_data, opt->m, opt->fc, opt->pre, lb, ub, x, minf, &stop, dual_opt, inner_maxeval, (unsigned)verbosity, rho_init, inner_gradients, always_improve, sigma_min, opt->dx);
             nlopt_destroy(dual_opt);
             return ret;
         }