Calibrate kernel defaults

DominikKamp · DominikKamp · commit 11323c2abf14 · 2025-09-21T12:38:38.000+02:00
diff --git a/src/parameters.cpp b/src/parameters.cpp
@@ -30,15 +30,15 @@
 
 /* Nonparametric process "parameters" */
 const std::string KERNEL_NAME = "kMaternARD5";
-const double KERNEL_THETA    = 1.0;
-const double KERNEL_SIGMA    = 10.0;
-const std::string MEAN_NAME = "mConst";
-const double MEAN_MU         = 1.0;
-const double MEAN_SIGMA      = 1000.0;
-const double PRIOR_ALPHA     = 1.0;
-const double PRIOR_BETA      = 1.0;
-const double DEFAULT_SIGMA   = 1.0;
-const double DEFAULT_NOISE   = 1e-6;
+const double KERNEL_THETA     = -3.0;
+const double KERNEL_SIGMA     = 10.0;
+const std::string MEAN_NAME   = "mConst";
+const double MEAN_MU          = 1.0;
+const double MEAN_SIGMA       = 1000.0;
+const double PRIOR_ALPHA      = 1.0;
+const double PRIOR_BETA       = 1.0;
+const double DEFAULT_SIGMA    = 1.0;
+const double DEFAULT_NOISE    = 1e-6;
 
 /* Algorithm parameters */
 const size_t DEFAULT_ITERATIONS         = 190;
diff --git a/src/posterior_empirical.cpp b/src/posterior_empirical.cpp
@@ -51,9 +51,10 @@ namespace bayesopt
 	kOptimizer->setAlgorithm(COMBINED);
 	kOptimizer->setMaxEvals(20*nhp);
       }
-    //Limits in log space
-    kOptimizer->setLimits(svectord(nhp,-6.0),svectord(nhp,1.0));
-  } 
+
+    // limits in log space
+    kOptimizer->setLimits(svectord(nhp, -6.0), svectord(nhp, 0.0));
+  }
 
   EmpiricalBayes::~EmpiricalBayes()
   { } // Default destructor
