Merge pull request #160 from mach3-software/feature_SaveYamlCofnig

Save Covariance in MCMC File

.github/workflows/CDImage.yml

@@ -39,17 +39,12 @@ jobs:
     - name: Log in to GitHub Container Registry
       run: echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin
 
-    - name: Set MACH3_VERSION
-      run: echo "MACH3_VERSION=${{ github.head_ref }}" >> "$GITHUB_ENV"
-      env:
-        GITHUB_HEAD_REF: ${{ github.head_ref }}
-
     - name: Build Docker image
       run: |
         if [ "${{ github.ref_type }}" == 'tag' ]; then
-          docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.os }}${{ github.ref_name }} --build-arg MACH3_VERSION="${MACH3_VERSION}"
+          docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.os }}${{ github.ref_name }} --build-arg MACH3_VERSION=${{ github.ref_name }}
         else
-          docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.tag_latest }} --build-arg MACH3_VERSION="develop"
+          docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.tag_latest }} --build-arg MACH3_VERSION=develop
         fi
 
     - name: Push Docker image

.github/workflows/CIBuild.yml

@@ -43,8 +43,5 @@ jobs:
     - name: Log in to GitHub Container Registry
       run: echo "${{ secrets.GITHUB_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin
 
-    - name: Set environment variable for MACH3_VERSION
-      run: echo "MACH3_VERSION=${{ github.head_ref }}" >> "$GITHUB_ENV"
-
     - name: Build the Docker image
-      run: docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.tag }} --build-arg MACH3_VERSION=${{ env.MACH3_VERSION }} --build-arg CMAKE_OPTIONS="${{ matrix.cmakeoptions }}"
+      run: docker build . --file ${{ matrix.file }} --tag ghcr.io/${{ github.repository_owner }}/mach3:${{ matrix.tag }} --build-arg MACH3_VERSION=${{ github.head_ref }} --build-arg CMAKE_OPTIONS="${{ matrix.cmakeoptions }}"

.github/workflows/CIValidations.yml

@@ -63,16 +63,15 @@ jobs:
     steps:
     - uses: actions/checkout@v4
 
+
     - name: Get MaCh3 Validations
       run: |
         cd /opt/
         git clone https://github.com/mach3-software/MaCh3Tutorial.git MaCh3Validations
         cd MaCh3Validations
         mkdir build
         cd build
-        cmake ../ -DMaCh3_Branch="${{ env.GITHUB_HEAD_REF }}"
-      env:
-        GITHUB_HEAD_REF: ${{ github.head_ref }}
+        cmake ../ -DMaCh3_Branch=${{ github.head_ref }}
 
     - name: Build MaCh3 Validations
       run: |

CONTRIBUTING.md

@@ -64,7 +64,16 @@ bool AsimovFit = GetFromManager<bool>(config[AsimovFit], false);
 ```
 
 ## double vs float?
-Some fits require lot's of RAM. Easiest and fastest solution to reduce RAM is use floats instead of doubles. MaCh3 has custom type like \_float\_  defined [here](https://github.com/mach3-software/MaCh3/blob/761cdc168663a6cfe659e4e3bab0d939bf715273/samplePDF/Structs.h#L9). \_float\_ is usually double unless \_LOW_MEMORY_STRUCTS\_ is defined at compilation level. Then \_float\_ will be actual float. By using \_float\_ one can flexibly change from one type to another. When developing it is advised to used these data types unless some data types are necessary due to desired precision code safety etc.
+Some fits require a lot of RAM. The easiest and fastest solution to reduce RAM
+is to use `float` instead of `double`.
+
+MaCh3 has a custom type defined as `_float_`, which is usually a `double`
+unless the `_LOW_MEMORY_STRUCTS_` directive is defined at the compilation
+level. When defined, `_float_` will be an actual `float`.
+
+By using `_float_`, one can flexibly change between these types. During
+development, it is advised to use these data types unless specific data
+types are necessary due to desired precision, code safety, etc.
 
 ## Error handling
 MaCh3 uses custom error handling implemented [here](https://github.com/mach3-software/MaCh3/blob/develop/manager/MaCh3Exception.h)

README.md

@@ -1,7 +1,15 @@
 # MaCh3 <img src="Doc/mach3logo.png" alt="MaCh3" align="center" width="100"/>
-The Markov Chain 3 flavour is a framework born in 2013 as a Bayesian MCMC fitter for [T2K](https://t2k-experiment.org/pl/) oscillation analysis. It has now been used for multiple T2K Oscillation analyses both at the Near and Far detectors throughout the years and is also used by the [DUNE](https://www.dunescience.org/) and [HK](https://www-sk.icrr.u-tokyo.ac.jp/en/hk/) oscillation analysis groups as well as for joint fits between T2K and NOvA and T2K and SK's atmospheric data.
 
-The framework has also evolved to allow non MCMC modules to interrogate the likelihoods implemented.
+The Markov Chain 3 flavour is a framework born in 2013 as a Bayesian MCMC
+fitter for [T2K](https://t2k-experiment.org/pl/) oscillation analysis. It has
+now been used for multiple T2K Oscillation analyses at both the Near and Far
+detectors throughout the years. The framework is also utilized by the
+[DUNE](https://www.dunescience.org/) and [HK](https://www-sk.icrr.u-tokyo.ac.jp/en/hk/)
+oscillation analysis groups. Additionally, it supports joint fits between T2K
+and NOvA, as well as T2K and SK's atmospheric data.
+
+The framework has also evolved to allow non-MCMC modules to interrogate the
+likelihoods implemented.
 
 [![License](https://img.shields.io/badge/License-BSD_3--Clause-blue.svg)](https://github.com/mach3-software/MaCh3/blob/develop/LICENSE.txt)
 [![Release](https://img.shields.io/github/release/mach3-software/MaCh3.svg)](https://github.com/mach3-software/MaCh3/releases/latest)
@@ -70,7 +78,7 @@ Additionally, you can build just the Python module by doing:
 
 ```bash
 pip install -t <install location> .
-``` 
+```
 The -t option specifies an install location which can be useful if you are on a computing cluster and don't have write access to the default install location. If you specify a non-standard location you will need to add it to your `PYTHONPATH` as above so that python can find the module.
 
 ## Multithreading

covariance/covarianceBase.cpp

@@ -32,57 +32,10 @@ covarianceBase::covarianceBase(const std::vector<std::string>& YAMLFile, const c
   if (pca) ConstructPCA();
 }
 
-// ********************************************
-covarianceBase::covarianceBase(const char *name, const char *file, int seed) : inputFile(std::string(file)), pca(false) {
-// ********************************************
-
-  #ifdef MULTITHREAD
-  if(seed != 0)
-  {
-    MACH3LOG_WARN("You have set seed to {}", seed);
-    MACH3LOG_WARN("And you are running with MULTITHREAD");
-    MACH3LOG_WARN("TRandom for each thread will have same seed");
-    MACH3LOG_WARN("This is fine if this was your intention");
-  }
-  #endif
-
-  init(name, file);
-  FirstPCAdpar = -999;
-  LastPCAdpar = -999;
-}
-
-// ********************************************
-covarianceBase::covarianceBase(const char *name, const char *file, int seed, double threshold, int firstpcapar, int lastpcapar) : inputFile(std::string(file)), pca(true), eigen_threshold(threshold), FirstPCAdpar(firstpcapar), LastPCAdpar(lastpcapar) {
-// ********************************************
-
-  if (threshold < 0 || threshold >= 1) {
-    MACH3LOG_INFO("NOTE: {} {}", name, file);
-    MACH3LOG_INFO("Principal component analysis but given the threshold for the principal components to be less than 0, or greater than (or equal to) 1. This will not work");
-    MACH3LOG_INFO("Please specify a number between 0 and 1");
-    MACH3LOG_INFO("You specified: ");
-    MACH3LOG_INFO("Am instead calling the usual non-PCA constructor...");
-    pca = false;
-  }
-#ifdef MULTITHREAD
-  if(seed != 0)
-  {
-    MACH3LOG_WARN("You have set seed to {}", seed);
-    MACH3LOG_WARN("And you are running with MULTITHREAD");
-    MACH3LOG_WARN("TRandom for each thread will have same seed");
-    MACH3LOG_WARN("This is fine if this was your intention");
-  }
-#endif
-  MACH3LOG_INFO("Constructing instance of covarianceBase");
-  init(name, file);
-  // Call the innocent helper function
-  if (pca) ConstructPCA();
-}
-
 // ********************************************
 //Destructor
 covarianceBase::~covarianceBase(){
 // ********************************************
-
   _fPreFitValue.clear();
   _fError.clear();
   _fCurrVal.clear();
@@ -846,7 +799,6 @@ void covarianceBase::printNominalCurrProp() {
 //                    false = don't evaluate likelihood (so run without a prior)
 double covarianceBase::CalcLikelihood() {
 // ********************************************
-
   double logL = 0.0;
   #ifdef MULTITHREAD
   #pragma omp parallel for reduction(+:logL)
@@ -869,7 +821,6 @@ double covarianceBase::CalcLikelihood() {
 // ********************************************
 int covarianceBase::CheckBounds() {
 // ********************************************
-
   int NOutside = 0;
   #ifdef MULTITHREAD
   #pragma omp parallel for reduction(+:NOutside)
@@ -1353,7 +1304,6 @@ void covarianceBase::makeClosestPosDef(TMatrixDSym *cov) {
 // ********************************************
 std::vector<double> covarianceBase::getNominalArray() {
 // ********************************************
-
   std::vector<double> nominal(_fNumPar);
   for (int i = 0; i < _fNumPar; ++i)
   {

covariance/covarianceBase.h

@@ -27,19 +27,7 @@ class covarianceBase {
   /// @param name Matrix name
   /// @param file Path to matrix root file
   covarianceBase(const char *name, const char *file);
-  /// @brief "Usual" constructors from root file with seed
-  /// @param name Matrix name
-  /// @param file Path to matrix root file
-  /// @param seed Seed for TRandom3
-  covarianceBase(const char *name, const char *file, int seed);
-  /// @brief Constructor For Eigen Value decomp
-  /// @param name Matrix name
-  /// @param file Path to matrix root file
-  /// @param seed Seed for TRandom3
-  /// @param threshold PCA threshold from 0 to 1. Default is -1 and means no PCA
-  /// @param FirstPCAdpar First PCA parameter that will be decomposed.
-  /// @param LastPCAdpar First PCA parameter that will be decomposed.
-  covarianceBase(const char *name, const char *file, int seed, double threshold, int FirstPCAdpar, int LastPCAdpar);
+
   /// @brief Destructor
   virtual ~covarianceBase();
 
@@ -355,6 +343,8 @@ class covarianceBase {
   /// @brief KS: Custom function to perform multiplication of matrix and single element which is thread safe
   inline double MatrixVectorMultiSingle(double** _restrict_ matrix, const double* _restrict_ vector, const int Length, const int i);
 
+  /// @brief Getter to return a copy of the YAML node
+  YAML::Node GetConfig() const { return _fYAMLDoc; }
 protected:
   /// @brief Initialisation of the class using matrix from root file
   void init(const char *name, const char *file);

manager/YamlHelper.h

@@ -154,6 +154,26 @@ inline YAML::Node TMacroToYAML(const TMacro& macro) {
   return yaml_node;
 }
 
+// **********************
+/// @brief Convert a YAML node to a ROOT TMacro object.
+/// @param yaml_node The YAML node to convert to a TMacro.
+/// @param name Name of TMacro that will be saved
+/// @return TMacro The TMacro object constructed from the YAML node.
+inline TMacro YAMLtoTMacro(const YAML::Node& yaml_node, const std::string& name) {
+// **********************
+  // Convert the YAML node to a string representation
+  std::string macro_string = YAMLtoSTRING(yaml_node);
+
+  std::cout<<macro_string<<std::endl;
+  // Create a TMacro object with the collected lines
+  TMacro macro(name.c_str(), name.c_str());
+  macro.AddLine(macro_string.c_str());
+
+  macro.Print();
+
+  return macro;
+}
+
 // **********************
 /// @brief Overrides the configuration settings based on provided arguments.
 ///

mcmc/FitterBase.cpp

@@ -295,6 +295,14 @@ void FitterBase::addSystObj(covarianceBase * const cov) {
   CorrMatrix->Write((cov->getName() + std::string("_Corr")).c_str());
   delete CorrMatrix;
 
+  // If we have yaml config file for covariance let's save it
+  YAML::Node Config = cov->GetConfig();
+  if(!Config.IsNull())
+  {
+    TMacro ConfigSave = YAMLtoTMacro(Config, (std::string("Config_") + cov->getName()));
+    ConfigSave.Write();
+  }
+
   outputFile->cd();
 
   return;
@@ -324,44 +332,12 @@ void FitterBase::addOscHandler(covarianceOsc * const oscf) {
     outputFile->cd();
   }
 
-  return;
-}
-
-// *************************
-// When using separate oscillations for neutrino and anti-neutrino
-void FitterBase::addOscHandler(covarianceOsc *oscf, covarianceOsc *oscf2) {
-// *************************
-
-  osc = oscf;
-  osc2 = oscf2;
-
-  if (save_nominal) {
-    CovFolder->cd();
-    std::vector<double> vec = oscf->getNominalArray();
-    size_t n = vec.size();
-    double *n_vec = new double[n];
-    for (size_t i = 0; i < n; ++i) {
-      n_vec[i] = vec[i];
-    }
-    TVectorT<double> t_vec(n, n_vec);
-    TString nameof = TString(oscf->getName());
-    nameof = nameof.Append("_nom");
-    t_vec.Write(nameof);
-
-    std::vector<double> vec2 = oscf2->getNominalArray();
-    size_t n2 = vec2.size();
-    double *n_vec2 = new double[n];
-    for (size_t i = 0; i < n; ++i) {
-      n_vec2[i] = vec2[i];
-    }
-    TVectorT<double> t_vec2(n2, n_vec2);
-    TString nameof2 = TString(oscf2->getName());
-    nameof2 = nameof2.Append("_2_nom");
-    t_vec2.Write(nameof2);
-    delete[] n_vec;
-    delete[] n_vec2;
-
-    outputFile->cd();
+  // If we have yaml config file for covariance let's save it
+  YAML::Node Config = oscf->GetConfig();
+  if(!Config.IsNull())
+  {
+    TMacro ConfigSave = YAMLtoTMacro(Config, (std::string("Config_") + oscf->getName()));
+    ConfigSave.Write();
   }
 
   return;

mcmc/FitterBase.h

@@ -41,11 +41,6 @@ class FitterBase {
   /// @param oscf A pointer to a covarianceOsc object for forward oscillations.
   void addOscHandler(covarianceOsc* oscf);
 
-  /// @brief Adds two oscillation handlers for covariance objects.
-  /// @param osca A pointer to a covarianceOsc object for the first oscillation.
-  /// @param oscb A pointer to a covarianceOsc object for the second oscillation.
-  void addOscHandler(covarianceOsc* osca, covarianceOsc* oscb);
-
   /// @brief The specific fitting algorithm implemented in this function depends on the derived class. It could be Markov Chain Monte Carlo (MCMC), MinuitFit, or another algorithm.
   virtual void runMCMC() = 0;
 
@@ -125,8 +120,6 @@ class FitterBase {
 
   /// handles oscillation parameters
   covarianceOsc *osc;
-  /// handles oscillation parameters
-  covarianceOsc *osc2;
 
   /// tells global time how long fit took
   TStopwatch* clock;