--- trunk/gadget/simann.cc	2016/05/25 16:36:33	19
+++ trunk/gadget/simann.cc	2017/04/07 09:20:55	20
@@ -436,7 +436,8 @@
 //}
 
 
-#ifdef SPECULATIVE
+#ifdef _OPENMP
+//#ifdef SPECULATIVE
 void OptInfoSimann::OptimiseLikelihoodOMP() {
 
   //set initial values
@@ -738,6 +739,7 @@
       x[i] = bestx[i];
   }
 }
+//#endif
 #endif
 
 // calcule a new point
@@ -803,14 +805,17 @@
 }
 
 /// Represents the function that computes how good the parameters are
-double evaluate_f(const DoubleVector& params) {
-	double trialf;
 #ifdef _OPENMP
+double evaluate_par_f(const DoubleVector& params) {
+	double trialf;
 	int id = omp_get_thread_num ();
 	trialf = EcoSystems[id]->SimulateAndUpdate(params);
-#else
-	trialf = EcoSystem->SimulateAndUpdate(params);
+  return -trialf;
+}
 #endif
+double evaluate_f(const DoubleVector& params) {
+	double trialf;
+	trialf = EcoSystem->SimulateAndUpdate(params);
   return -trialf;
 }
 
@@ -1009,7 +1014,8 @@
 }
 
 
-void OptInfoSimann::OptimiseLikelihood() {
+#ifdef _OPENMP
+void OptInfoSimann::OptimiseLikelihoodREP() {
 
 	//set initial values
 
@@ -1035,11 +1041,10 @@
 	EcoSystem->resetVariables(); //JMB need to reset variables in case they have been scaled
 	if (scale) {
 		EcoSystem->scaleVariables();
-#ifdef _OPENMP
+	
 		int numThr = omp_get_max_threads ( );
 		for(i = 0; i < numThr; i++) // scale the variables for the ecosystem of every thread
 			EcoSystems[i]->scaleVariables();
-#endif
 	}
 	EcoSystem->getOptScaledValues(x);
 	EcoSystem->getOptLowerBounds(lowerb);
@@ -1084,17 +1089,91 @@
 	Siman s(seed, seedM, seedP, nvars, nt, ns, param, &x, &lowerb, &upperb, vm, t, rt, (1.0 / ns),
 			tempcheck, simanneps, fstar, lratio, uratio, cs, &bestx, scale, &converge, &score);
 
-	ReproducibleSearch<Siman, DoubleVector, ControlClass, evaluate_f, buildNewParams_f>
+	ReproducibleSearch<Siman, DoubleVector, ControlClass, evaluate_par_f, buildNewParams_f>
 	pa(s, x, simanniter);
 
-#ifdef _OPENMP
 	// OpenMP parallelization
 	int numThr = omp_get_max_threads ( );
 	pa.paral_opt_omp(funcval,numThr,numThr);
-#else
+	iters = pa.iterations();
+
+}
+#endif
+void OptInfoSimann::OptimiseLikelihood() {
+
+	//set initial values
+
+	double tmp, p, pp;
+	double funcval, trialf;
+	int a, i, j, k, l, quit;
+	int rchange, rcheck, rnumber; //Used to randomise the order of the parameters
+
+	handle.logMessage(LOGINFO,
+			"\nStarting Simulated Annealing optimisation algorithm\n");
+	int nvars = EcoSystem->numOptVariables();
+	DoubleVector x(nvars);
+	DoubleVector init(nvars);
+	DoubleVector trialx(nvars, 0.0);
+	DoubleVector bestx(nvars);
+	DoubleVector scalex(nvars);
+	DoubleVector lowerb(nvars);
+	DoubleVector upperb(nvars);
+	DoubleVector fstar(tempcheck);
+	DoubleVector vm(nvars, vminit);
+	IntVector param(nvars, 0);
+
+	EcoSystem->resetVariables(); //JMB need to reset variables in case they have been scaled
+	if (scale) {
+		EcoSystem->scaleVariables();
+	}
+	EcoSystem->getOptScaledValues(x);
+	EcoSystem->getOptLowerBounds(lowerb);
+	EcoSystem->getOptUpperBounds(upperb);
+	EcoSystem->getOptInitialValues(init);
+
+	for (i = 0; i < nvars; i++) {
+		bestx[i] = x[i];
+		param[i] = i;
+	}
+
+	if (scale) {
+		for (i = 0; i < nvars; i++) {
+			scalex[i] = x[i];
+			// Scaling the bounds, because the parameters are scaled
+			lowerb[i] = lowerb[i] / init[i];
+			upperb[i] = upperb[i] / init[i];
+			if (lowerb[i] > upperb[i]) {
+				tmp = lowerb[i];
+				lowerb[i] = upperb[i];
+				upperb[i] = tmp;
+			}
+		}
+	}
+
+	//funcval is the function value at x
+	funcval = EcoSystem->SimulateAndUpdate(x);
+	if (funcval != funcval) { //check for NaN
+		handle.logMessage(LOGINFO,
+				"Error starting Simulated Annealing optimisation with f(x) = infinity");
+		converge = -1;
+		iters = 1;
+		return;
+	}
+
+	//the function is to be minimised so switch the sign of funcval (and trialf)
+	funcval = -funcval;
+	cs /= lratio;  //JMB save processing time
+	for (i = 0; i < tempcheck; i++)
+		fstar[i] = funcval;
+
+	Siman s(seed, seedM, seedP, nvars, nt, ns, param, &x, &lowerb, &upperb, vm, t, rt, (1.0 / ns),
+			tempcheck, simanneps, fstar, lratio, uratio, cs, &bestx, scale, &converge, &score);
+
+	ReproducibleSearch<Siman, DoubleVector, ControlClass, evaluate_f, buildNewParams_f>
+	pa(s, x, simanniter);
+
 	// sequential code
 	pa.seq_opt(funcval);
-#endif
 	iters = pa.iterations();
 
 }
@@ -1102,3 +1181,7 @@
 
 
 
+
+
+
+