Merge branch 'rand-start-pts-v2' of github.com:kmohrman/HiggsAnalysis…

…-CombinedLimit into kmohrman-rand-start-pts

docs/part3/nonstandard.md

@@ -1052,7 +1052,9 @@ In case you see an excess somewhere in your analysis, you can evaluate the look-
 To calculate the look-elsewhere effect for a single parameter (in this case the mass of the resonance), you can follow the instructions below. Note that these instructions assume you have a workspace that is parametric in your resonance mass $m$, otherwise you need to fit each background toy with separate workspaces. We will assume the local significance for your excess is $\sigma$. 
 
    * Generate background-only toys	`combine ws.root -M GenerateOnly --toysFrequentist -m 16.5 -t 100 --saveToys --expectSignal=0`. The output will be something like `higgsCombineTest.GenerateOnly.mH16.5.123456.root`.
+
    * For each toy, calculate the significance for a predefined range (e.g $m\in [10,35]$ GeV) in steps suitable to the resolution (e.g. 1 GeV). For  `toy_1` the procedure would be: `for i in $(seq 10 35); do combine ws.root -M Significance --redefineSignalPOI r --freezeParameters MH --setParameter MH=$i -n $i -D higgsCombineTest.GenerateOnly.mH16.5.123456.root:toys/toy_1`. Calculate the maximum significance over all of these mass points - call this $\sigma_{max}$.
+
    * Count how many toys have a maximum significance larger than the local one for your observed excess. This fraction of toys with $\sigma_{max}>\sigma$ is the global p-value. 
 
 You can find more tutorials on the LEE [here](https://indico.cern.ch/event/456547/contributions/1126036/attachments/1188691/1724680/20151117_comb_tutorial_Lee.pdf)

interface/MultiDimFit.h

@@ -23,6 +23,8 @@ class MultiDimFit : public FitterAlgoBase {
   }
   virtual void applyOptions(const boost::program_options::variables_map &vm) ;
 
+  friend class RandStartPt;
+
 protected:
   virtual bool runSpecific(RooWorkspace *w, RooStats::ModelConfig *mc_s, RooStats::ModelConfig *mc_b, RooAbsData &data, double &limit, double &limitErr, const double *hint);
 
@@ -67,6 +69,10 @@ class MultiDimFit : public FitterAlgoBase {
   static std::string robustHesseLoad_;
   static std::string robustHesseSave_;
 
+  static int pointsRandProf_;
+  static std::string setParameterRandomInitialValueRanges_;
+  static int randPointsSeed_;
+
   static std::string saveSpecifiedFuncs_;
   static std::string saveSpecifiedNuis_;
   static std::string saveSpecifiedIndex_;
@@ -83,6 +89,7 @@ class MultiDimFit : public FitterAlgoBase {
   static std::vector<float>        specifiedVals_;
   static RooArgList                specifiedList_;
   static bool saveInactivePOI_;
+  static bool skipDefaultStart_;
   // initialize variables
   void initOnce(RooWorkspace *w, RooStats::ModelConfig *mc_s) ;
 
@@ -95,6 +102,9 @@ class MultiDimFit : public FitterAlgoBase {
   void doStitch2D(RooWorkspace *w, RooAbsReal &nll) ;
   void doImpact(RooFitResult &res, RooAbsReal &nll) ;
 
+  std::map<std::string, std::vector<float>> getRangesDictFromInString(std::string) ;
+
+
   // utilities
   /// for each RooRealVar, set a range 'box' from the PL profiling all other parameters
   void doBox(RooAbsReal &nll, double cl, const char *name="box", bool commitPoints=true) ;

interface/RandStartPt.h

@@ -0,0 +1,45 @@
+#ifndef HiggsAnalysis_CombinedLimit_RandStartPt_h
+#define HiggsAnalaysis_CombinedLimit_RandStartPt_h
+
+#include "HiggsAnalysis/CombinedLimit/interface/CascadeMinimizer.h"
+#include "HiggsAnalysis/CombinedLimit/interface/MultiDimFit.h"
+
+#include <vector>
+#include <string>
+#include "RooRealVar.h"
+#include "RooAbsReal.h"
+#include "RooArgSet.h"
+#include "RooCategory.h"
+
+class RandStartPt {
+  private:
+      RooAbsReal& nll_;
+      std::vector<RooRealVar* > &specifiedvars_;
+      std::vector<float> &specifiedvals_;
+      bool skipdefaultstart_;
+      std::string parameterRandInitialValranges_;
+      int numrandpts_;
+      int verbosity_;
+      bool fastscan_;
+      bool hasmaxdeltaNLLforprof_;
+      float maxdeltaNLLforprof_;
+      std::vector<std::string> &specifiednuis_;
+      std::vector<std::string> &specifiedfuncnames_;
+      std::vector<RooAbsReal*> &specifiedfunc_;
+      std::vector<float> &specifiedfuncvals_; 
+      std::vector<std::string> &specifiedcatnames_; 
+      std::vector<RooCategory*> &specifiedcat_; 
+      std::vector<int> &specifiedcatvals_;
+      unsigned int nOtherFloatingPOI_;
+  public:
+      RandStartPt(RooAbsReal& nll, std::vector<RooRealVar* > &specifiedvars, std::vector<float> &specifiedvals, bool skipdefaultstart, std::string parameterRandInitialValranges, int numrandpts, int verbose, bool fastscan, bool hasmaxdeltaNLLforprof, float maxdeltaNLLforprof, std::vector<std::string> &specifiednuis, std::vector<std::string> &specifiedfuncnames, std::vector<RooAbsReal*> &specifiedfunc, std::vector<float> &specifiedfuncvals, std::vector<std::string> &specifiedcatnames, std::vector<RooCategory*> &specifiedcat, std::vector<int> &specifiedcatvals, unsigned int nOtherFloatingPOI);
+      std::map<std::string, std::vector<float>> getRangesDictFromInString(std::string params_ranges_string_in);
+      std::vector<std::vector<float>> vectorOfPointsToTry ();
+      void commitBestNLLVal(unsigned int idx, float &nllVal, double &probVal);
+      void setProfPOIvalues(unsigned int startptIdx, std::vector<std::vector<float>> &nested_vector_of_wc_vals);
+      void setValSpecifiedObjs();
+      void doRandomStartPt1DGridScan(double &xval, unsigned int poiSize, std::vector<float> &poival, std::vector<RooRealVar* > &poivars, std::unique_ptr <RooArgSet> &param, RooArgSet &snap, float &deltaNLL, double &nll_init, CascadeMinimizer &minimObj);
+      void doRandomStartPt2DGridScan(double &xval, double &yval, unsigned int poiSize, std::vector<float> &poival, std::vector<RooRealVar* > &poivars, std::unique_ptr <RooArgSet> &param, RooArgSet &snap, float &deltaNLL, double &nll_init, MultiDimFit::GridType gridType, double deltaX, double deltaY, CascadeMinimizer &minimObj);
+
+};
+#endif