refactored covariance function

mlmc/conf/mlmc_elliptic.conf

@@ -39,7 +39,7 @@ MainVerbose = 1
 MCVerbose = 2
 MLMCVerbose = 2
 PDEVerbose = 1
-GeneratorVerbose = 0
+GeneratorVerbose = 1
 
 GeneratorPlotting = 4
 MCPlotting = 3
@@ -51,7 +51,7 @@ sigma = 1.0
 norm_p = 2
 lambda1 = 0.15
 lambda2 = 0.15
-alpha = 1.0
+smoothing = 1.0
 evtol = 1e-10
 
 # Other

mlmc/src/stochastics/CovarianceFunction.h

@@ -3,18 +3,18 @@
 
 class CovarianceFunction {
 public:
-    double sigma;
-    int norm_p;
-    double lambda1;
-    double lambda2;  // Has no influence on 1D
-    double alpha;
+    double sigma = 1.0;
+    int norm_p = 2;
+    double lambda1 = 0.15;
+    double lambda2 = 0.15;  // Has no influence on 1D
+    double smoothing = 1.0;
 
     CovarianceFunction() {
-        ReadConfig(Settings, "sigma", sigma);
-        ReadConfig(Settings, "norm_p", norm_p);
-        ReadConfig(Settings, "lambda1", lambda1);
-        ReadConfig(Settings, "lambda2", lambda2);
-        ReadConfig(Settings, "alpha", alpha);
+        config.get("sigma", sigma);
+        config.get("norm_p", norm_p);
+        config.get( "lambda1", lambda1);
+        config.get( "lambda2", lambda2);
+        config.get( "smoothing", smoothing);
     }
 
     virtual double covariance_fct(double *tau) = 0;
@@ -26,7 +26,7 @@ class CovarianceFunction1D : CovarianceFunction {
 public:
     double covariance_fct(double *tau) override {
         tau[0] /= lambda1;
-        return pow(sigma, 2) * exp(-pow(norm(tau), alpha));
+        return pow(sigma, 2) * exp(-pow(norm(tau), smoothing));
     }
 
     double norm(const double *x) override {
@@ -39,7 +39,7 @@ public:
     double covariance_fct(double *tau) override {
         tau[0] /= lambda1;
         tau[1] /= lambda2;
-        return pow(sigma, 2) * exp(-pow(norm(tau), alpha));
+        return pow(sigma, 2) * exp(-pow(norm(tau), smoothing));
     }
 
     double norm(const double *x) override {