Refactors contrasts class and struct (#179)

* Renames field of "priors" struct

* Renames "nba" and "nbs" to "bulkIn" and "bulkOut" respectively in "contrastsClass.m"

* Refactors "getNames" routines

* Renames fields in contrasts struct

* Renames contrasts fields in "parseClassToStructs"

* Renames "packpriors.m" and "unpackpriors.m" to camel case

* Fixes priors bug

3rdParty/mcmcstat/%runDram.m

@@ -2,14 +2,14 @@
 debug = 0;
 
 checks = controls.checks;
-[problemDef,fitNames] = packparams(problemDef,problemDefCells,problemDefLimits,checks);
+[problemDef,fitNames] = packParams(problemDef,problemDefCells,problemDefLimits,checks);
 %fitPriors = packPriors(priors,checks);
 
 % Seed the Random Number Generator
 rng(0);
 
 
-%fitPriors = packpriors(priors,checks);
+%fitPriors = packPriors(priors,checks);
 
 %First deal with priors.
 %Make uniform priors from the
@@ -66,7 +66,7 @@
 bayesResults.predlims = output.predlims;
 
 problemDef.fitpars = output.bestPars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 [problem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 
 % Pre-processor directives for Matlab Coder.

3rdParty/mcmcstat/refModel.m

@@ -36,7 +36,7 @@
 problemDefCells = problem{4};
 
 problemDef.fitpars = pars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 [problem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 
 ySim = result{1}{contrast};

3rdParty/mcmcstat/refModel_scaled.m

@@ -43,7 +43,7 @@
 pars = unscalePars(pars,constr);
 
 problemDef.fitpars = pars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 [problem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 
 ySim = result{1}{contrast};

3rdParty/mcmcstat/reflectivity_fitModel.m

@@ -13,7 +13,7 @@
 
 
 problemDef.fitpars = pars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 %setappdata(0,'problem',problem);
 %problem = reflectivityCalculation(problem);
 [problemDef,result] = reflectivityCalculation(problemDef,problemDefCells,controls);

3rdParty/mcmcstat/reflectivity_fitModel_scaled.m

@@ -14,7 +14,7 @@
 pars = unscalePars(pars,constr);
 
 problemDef.fitpars = pars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 %setappdata(0,'problem',problem);
 %problem = reflectivityCalculation(problem);
 [problemDef,result] = reflectivityCalculation(problemDef,problemDefCells,controls);

3rdParty/mcmcstat/runBayes.m

@@ -90,7 +90,7 @@
 % outSld = mcmcpred_compile_sld(results,chain,[],data,problem,500);
 % 
 % problemDef.fitpars = output.bestPars;
-% problemDef = unpackparams(problemDef,controls);
+% problemDef = unpackParams(problemDef,controls);
 % [problem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 % 
 % output.bestFits = result{1};

3rdParty/mcmcstat/runDram.m

@@ -5,13 +5,13 @@
 %coder.varsize('problemDef.contrastBacks',[1 Inf],[0 1]);
 
 checks = controls.checks;
-[problemDef,fitNames] = packparams(problemDef,problemDefCells,problemDefLimits,checks);
+[problemDef,fitNames] = packParams(problemDef,problemDefCells,problemDefLimits,checks);
 %fitPriors = packPriors(priors,checks);
 
 % Seed the Random Number Generator
 rng(0);
 
-%fitPriors = packpriors(priors,checks);
+%fitPriors = packPriors(priors,checks);
 
 %First deal with priors.
 prior = {};
@@ -23,83 +23,83 @@
     params{i} = cell(1,6);
 end
 
-% We have a list of 'fitPars' which is created by packparams.m
-% packparams doesn't do the same for our priors however. So we need 
+% We have a list of 'fitPars' which is created by packParams.m
+% packParams doesn't do the same for our priors however. So we need 
 % to make an array of the priors for the fitted parameters 
 % so that we can then build the params array for the algorithm
 
 % Put all the priors into one array
 % ** This won't work for code generation **
-% priorsGroup = [priors.paramPriors ; ...
-%     priors.backgroundParamPriors ; ...
-%     priors.resolutionParamPriors ; ...
-%     priors.bulkInPriors ; ...
-%     priors.bulkOutPriors ; ...
-%     priors.qzshiftPriors ; 
-%     priors.scalefactorPriors];
-
-% totalNumber = size(priors.paramPriors,1) + size(priors.backgroundParamPriors,1) + ...
-%     size(priors.resolutionParamPriors,1) + size(priors.bulkInPriors,1) + size(priors.bulkOutPriors,1) + ...
-%     size(priors.qzshiftPriors,1) + size(priors.scalefactorPriors,1);
+% priorsGroup = [priors.param ; ...
+%     priors.backgroundParam ; ...
+%     priors.resolutionParam ; ...
+%     priors.bulkIn ; ...
+%     priors.bulkOut ; ...
+%     priors.qzshift ; 
+%     priors.scalefactor];
+
+% totalNumber = size(priors.param,1) + size(priors.backgroundParam,1) + ...
+%     size(priors.resolutionParam,1) + size(priors.bulkIn,1) + size(priors.bulkOut,1) + ...
+%     size(priors.qzshift,1) + size(priors.scalefactor,1);
 
 % Expand the individual cells..
 %allPriors = cell(totalNumber,2);    %Will be a char type....
 % allPriors = strings(totalNumber,2);
 % allPriorVals = cell(totalNumber,2);
 % cellCount = 1;
-% for i = 1:size(priors.paramPriors,1)
-%     allPriors(cellCount,1) = string(priors.paramPriors{i}{1});
-%     allPriors(cellCount,2) = string(priors.paramPriors{i}{2});
-%     allPriorVals{cellCount,1} = priors.paramPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.paramPriors{i}{4};
+% for i = 1:size(priors.param,1)
+%     allPriors(cellCount,1) = string(priors.param{i}{1});
+%     allPriors(cellCount,2) = string(priors.param{i}{2});
+%     allPriorVals{cellCount,1} = priors.param{i}{3};
+%     allPriorVals{cellCount,2} = priors.param{i}{4};
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.backgroundParamPriors,1)
-%     allPriors(cellCount,1) = priors.backgroundParamPriors{i}{1};
-%     allPriors(cellCount,2) = priors.backgroundParamPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.backgroundParamPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.backgroundParamPriors{i}{4};
+% for i = 1:size(priors.backgroundParam,1)
+%     allPriors(cellCount,1) = priors.backgroundParam{i}{1};
+%     allPriors(cellCount,2) = priors.backgroundParam{i}{2};
+%     allPriorVals{cellCount,1} = priors.backgroundParam{i}{3};
+%     allPriorVals{cellCount,2} = priors.backgroundParam{i}{4};
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.resolutionParamPriors,1)
-%     allPriors(cellCount,1) = priors.resolutionParamPriors{i}{1};
-%     allPriors(cellCount,2) = priors.resolutionParamPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.resolutionParamPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.resolutionParamPriors{i}{4};
+% for i = 1:size(priors.resolutionParam,1)
+%     allPriors(cellCount,1) = priors.resolutionParam{i}{1};
+%     allPriors(cellCount,2) = priors.resolutionParam{i}{2};
+%     allPriorVals{cellCount,1} = priors.resolutionParam{i}{3};
+%     allPriorVals{cellCount,2} = priors.resolutionParam{i}{4};
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.bulkInPriors,1)
-%     allPriors(cellCount,1) = priors.bulkInPriors{i}{1};
-%     allPriors(cellCount,2) = priors.bulkInPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.bulkInPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.bulkInPriors{i}{4}; 
+% for i = 1:size(priors.bulkIn,1)
+%     allPriors(cellCount,1) = priors.bulkIn{i}{1};
+%     allPriors(cellCount,2) = priors.bulkIn{i}{2};
+%     allPriorVals{cellCount,1} = priors.bulkIn{i}{3};
+%     allPriorVals{cellCount,2} = priors.bulkIn{i}{4}; 
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.bulkOutPriors,1)
-%     allPriors(cellCount,1) = priors.bulkOutPriors{i}{1};
-%     allPriors(cellCount,2) = priors.bulkOutPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.bulkOutPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.bulkOutPriors{i}{4};
+% for i = 1:size(priors.bulkOut,1)
+%     allPriors(cellCount,1) = priors.bulkOut{i}{1};
+%     allPriors(cellCount,2) = priors.bulkOut{i}{2};
+%     allPriorVals{cellCount,1} = priors.bulkOut{i}{3};
+%     allPriorVals{cellCount,2} = priors.bulkOut{i}{4};
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.qzshiftPriors,1)
-%     allPriors(cellCount,1) = priors.qzshiftPriors{i}{1};
-%     allPriors(cellCount,2) = priors.qzshiftPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.qzshiftPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.qzshiftPriors{i}{4};
+% for i = 1:size(priors.qzshift,1)
+%     allPriors(cellCount,1) = priors.qzshift{i}{1};
+%     allPriors(cellCount,2) = priors.qzshift{i}{2};
+%     allPriorVals{cellCount,1} = priors.qzshift{i}{3};
+%     allPriorVals{cellCount,2} = priors.qzshift{i}{4};
 %     cellCount = cellCount + 1;
 % end
 % 
-% for i = 1:size(priors.scalefactorPriors,1)
-%     allPriors(cellCount,1) = priors.scalefactorPriors{i}{1};
-%     allPriors(cellCount,2) = priors.scalefactorPriors{i}{2};
-%     allPriorVals{cellCount,1} = priors.scalefactorPriors{i}{3};
-%     allPriorVals{cellCount,2} = priors.scalefactorPriors{i}{4};
+% for i = 1:size(priors.scalefactor,1)
+%     allPriors(cellCount,1) = priors.scalefactor{i}{1};
+%     allPriors(cellCount,2) = priors.scalefactor{i}{2};
+%     allPriorVals{cellCount,1} = priors.scalefactor{i}{3};
+%     allPriorVals{cellCount,2} = priors.scalefactor{i}{4};
 %     cellCount = cellCount + 1;
 % end
 
@@ -171,15 +171,15 @@
 % 
 % % Calulate Max best fit curves
 % problemDef.fitpars = bestPars_max;
-% problemDef = unpackparams(problemDef,controls);
+% problemDef = unpackParams(problemDef,controls);
 % [outProblem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 % bestFitMax_Ref = result(1);
 % bestFitMax_Sld = result(5);
 % bestFitMax_chi = outProblem.calculations.sum_chi;
 % 
 % % Calculate 'mean' best fit curves
 % problemDef.fitpars = bestPars_mean;
-% problemDef = unpackparams(problemDef,controls);
+% problemDef = unpackParams(problemDef,controls);
 % [outProblem,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 % bestFitMean_Ref = result(1);
 % bestFitMean_Sld = result(5);

3rdParty/mcmcstat/sldModel.m

@@ -31,7 +31,7 @@
 controls.calcSldDuringFit = true;
 
 problemDef.fitpars = pars;
-problemDef = unpackparams(problemDef,controls);
+problemDef = unpackParams(problemDef,controls);
 [~,result] = reflectivityCalculation(problemDef,problemDefCells,controls);
 
 sld = result{5}{contrast};

3rdParty/paramonte/pmLogFunction.m

@@ -23,7 +23,7 @@
                 problem = unscalePars(problem);
             end
 
-            problem = unpackparams(problem,obj.controls);
+            problem = unpackParams(problem,obj.controls);
 
             [outProblem,~] = reflectivityCalculation_mex(problem,obj.problemDefCells,obj.controls);
             chi = outProblem.calculations.sum_chi;

3rdParty/paramonte/processParamonteRuns.m

@@ -7,7 +7,7 @@
 
 [problemDef,problemDefCells,problemDefLimits,~,controls] = parseClassToStructs(problem,controls);
 
-[problemDef,fitNames] = packparams(problemDef,problemDefCells,problemDefLimits,controls.checks);
+[problemDef,fitNames] = packParams(problemDef,problemDefCells,problemDefLimits,controls.checks);
 
 pm = paramonte();
 pmpd = pm.ParaDRAM();
@@ -55,7 +55,7 @@
 
 result = mergeStructs(result,bayesResults);
 
-[~,fitNames] = packparams(problemDef,problemDefCells,problemDefLimits,controls.checks);
+[~,fitNames] = packParams(problemDef,problemDefCells,problemDefLimits,controls.checks);
 result.fitNames = fitNames;
 
 outProblemDef = parseOutToProjectClass(problem,problemDef);

API/RAT.m

@@ -1,7 +1,7 @@
 function [outProblemDef,result] = RAT(problemDefInput,controls)
 
 [problemDef,problemDefCells,problemDefLimits,priors,controls] = parseClassToStructs(problemDefInput,controls);
-[problemDef,~] = packparams(problemDef,problemDefCells,problemDefLimits,controls.checks);
+[problemDef,~] = packParams(problemDef,problemDefCells,problemDefLimits,controls.checks);
 
 % Set controls.calCls always to 1
 % if we are doing customXY
@@ -45,7 +45,7 @@
     result = mergeStructs(result,bayesResults);
 end
 
-[~,fitNames] = packparams(problemDef,problemDefCells,problemDefLimits,controls.checks);
+[~,fitNames] = packParams(problemDef,problemDefCells,problemDefLimits,controls.checks);
 result.fitNames = fitNames;
 
 outProblemDef = parseOutToProjectClass(problemDefInput,outProblemStruct);