Removes "problemCells" from the code

Author: DrPaulSharp

3rdParty/mcmcstat/%runDram.m

@@ -1,4 +1,4 @@
-function  [problemStruct,problem,result,bayesResults] = runDram(problemStruct,problemCells,problemLimits,priors,controls)
+function  [problemStruct,problem,result,bayesResults] = runDram(problemStruct,problemLimits,priors,controls)
 
 checks = controls.checks;
 [problemStruct,fitNames] = packParams(problemStruct,problemLimits,checks);
@@ -49,7 +49,7 @@
 burnin = controls.burnin;
 adaptint = 100;%controls.adaptint;
 
-problem = {problemStruct ; controls ; problemLimits ; problemCells};
+problem = {problemStruct ; controls ; problemLimits};
 
 output = runBayes(loop,nsimu,burnin,adaptint,params,problem);
 
@@ -63,7 +63,7 @@
 
 problemStruct.fitParams = output.bestParams;
 problemStruct = unpackParams(problemStruct,checks);
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 % Pre-processor directives for Matlab Coder.
 coder.varsize('problem.ssubs',[Inf 1],[1 0]);

3rdParty/mcmcstat/refModel.m

@@ -33,11 +33,10 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 
 problemStruct.fitParams = pars;
 problemStruct = unpackParams(problemStruct,controls.checks);
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 ySim = result.reflectivity{contrast};
 

3rdParty/mcmcstat/refModel_scaled.m

@@ -36,15 +36,14 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 
 pars = theta;
 constr = problemStruct.fitLimits;
 pars = unscalePars(pars,constr);
 
 problemStruct.fitParams = pars;
 problemStruct = unpackParams(problemStruct,controls.checks);
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 ySim = result.reflectivity{contrast};
 

3rdParty/mcmcstat/reflectivity_fitModel.m

@@ -9,12 +9,11 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 
 
 problemStruct.fitParams = pars;
 problemStruct = unpackParams(problemStruct,controls.checks);
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 ss = result.calculationResults.sumChi;
 

3rdParty/mcmcstat/reflectivity_fitModel_scaled.m

@@ -7,7 +7,6 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 
 pars = theta;           % Current parameter values from mcmcstat
 constr = problemStruct.fitLimits;
@@ -16,7 +15,7 @@
 problemStruct.fitParams = pars;
 problemStruct = unpackParams(problemStruct,controls.checks);
 
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 ss = result.calculationResults.sumChi;
 

3rdParty/mcmcstat/runBayes.m

@@ -3,7 +3,6 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 
 display = controls.display;
 
@@ -91,7 +90,7 @@
 % 
 % problemStruct.fitParams = output.bestParams;
 % problemStruct = unpackParams(problemStruct,controls.checks);
-% result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+% result = reflectivityCalculation(problemStruct,problemLimits,controls);
 % 
 % output.bestFits = result.reflectivity;
 % output.shiftedData = problemStruct.data;

3rdParty/mcmcstat/runDram.m

@@ -1,4 +1,4 @@
-function  [problemStruct,outProblem,result,bayesResults] = runDram(problemStruct,problemCells,problemLimits,controls,allPriors)
+function  [problemStruct,outProblem,result,bayesResults] = runDram(problemStruct,problemLimits,controls,allPriors)
 
 %#codegen
 
@@ -151,7 +151,7 @@
 
 output = runBayes(loop,nsimu,burnin,adaptint,params,problem,controls);
 
-[problemStruct,result,bayesResults] = processBayes(output,problemStruct,problemCells,problemLimits,controls);
+[problemStruct,result,bayesResults] = processBayes(output,problemStruct,problemLimits,controls);
 
 % problemStruct.fitParams = bayesResults.bestParamsMean;
 
@@ -170,15 +170,15 @@
 % % Calulate Max best fit curves
 % problemStruct.fitParams = bestParamsMax;
 % problemStruct = unpackParams(problemStruct,controls.checks);
-% result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+% result = reflectivityCalculation(problemStruct,problemLimits,controls);
 % bestFitMax_Ref = result.reflectivity;
 % bestFitMax_Sld = result.sldProfiles;
 % bestFitMax_chi = result.calculationResultss.sumChi;
 % 
 % % Calculate 'mean' best fit curves
 % problemStruct.fitParams = bestParamsMean;
 % problemStruct = unpackParams(problemStruct,controls.checks);
-% result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+% result = reflectivityCalculation(problemStruct,problemLimits,controls);
 % bestFitMean_Ref = result.reflectivity;
 % bestFitMean_Sld = result.sldProfiles;
 % bestFitMean_chi = result.calculationResultss.sumChi;

3rdParty/mcmcstat/sldModel.m

@@ -27,12 +27,11 @@
 problemStruct = problem{1};
 controls = problem{2};
 problemLimits = problem{3};
-problemCells = problem{4};
 controls.calcSldDuringFit = true;
 
 problemStruct.fitParams = pars;
 problemStruct = unpackParams(problemStruct,controls.checks);
-result = reflectivityCalculation(problemStruct,problemCells,problemLimits,controls);
+result = reflectivityCalculation(problemStruct,problemLimits,controls);
 
 sld = result.sldProfiles{contrast};
 

3rdParty/paramonte/pmLogFunction.m

@@ -3,7 +3,6 @@
     properties 
 
         problemStruct;
-        problemCells;
         problemLimits;
         priors;
         controls;
@@ -25,7 +24,7 @@
 
             problem = unpackParams(problem,obj.controls.checks);
 
-            result = reflectivityCalculation_mex(problem,obj.problemCells,obj.problemLimits,obj.controls);
+            result = reflectivityCalculation_mex(problem,obj.problemLimits,obj.controls);
             chi = result.calculationResults.sumChi;
             logFuncVal = -chi/2;
 

3rdParty/paramonte/processParamonteRuns.m

@@ -5,7 +5,7 @@
 % 
 % controls = controlsClass();
 
-[problemStruct,problemCells,problemLimits,~,controls] = parseClassToStructs(problem,controls);
+[problemStruct,problemLimits,~,controls] = parseClassToStructs(problem,controls);
 
 [problemStruct,fitNames] = packParams(problemStruct,problemLimits,controls.checks);
 
@@ -41,7 +41,7 @@
 bayesOutputs.data = problemStruct.data;
 bayesOutputs.results.mean = mean(unscaledChain);
 
-[problemStruct,result,bayesResults] = processBayes(bayesOutputs,problemStruct,problemCells,problemLimits,controls);
+[problemStruct,result,bayesResults] = processBayes(bayesOutputs,problemStruct,problemLimits,controls);
 bayesResults.chain = unscaledChain;
 
 result = mergeStructs(result,bayesResults);