FullParallelMultiindexGaussianSampling.cpp

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#include "MUQ/SamplingAlgorithms/SLMCMC.h"
#include "MUQ/SamplingAlgorithms/GreedyMLMCMC.h"
#include "MUQ/SamplingAlgorithms/MIMCMC.h"
 
#include "MUQ/Modeling/Distributions/Gaussian.h"
#include "MUQ/Modeling/Distributions/Density.h"
 
#include "MUQ/SamplingAlgorithms/MHKernel.h"
#include "MUQ/SamplingAlgorithms/MHProposal.h"
#include "MUQ/SamplingAlgorithms/CrankNicolsonProposal.h"
#include "MUQ/SamplingAlgorithms/SamplingProblem.h"
#include "MUQ/SamplingAlgorithms/SubsamplingMIProposal.h"
 
#include "MUQ/SamplingAlgorithms/MIComponentFactory.h"
 
#include <boost/property_tree/ptree.hpp>
 
namespace pt = boost::property_tree;
using namespace muq::Modeling;
using namespace muq::SamplingAlgorithms;
using namespace muq::Utilities;
 
#include "MUQ/SamplingAlgorithms/ParallelMIMCMCWorker.h"
#include "MUQ/SamplingAlgorithms/ParallelFixedSamplesMIMCMC.h"
 
#include "ParallelProblem.h"
 
 
int main(int argc, char **argv){
 
  spdlog::set_level(spdlog::level::debug);
 
  MPI_Init(&argc, &argv);
 
  pt::ptree pt;
  pt.put("NumSamples_0_0", 1e3);
  pt.put("NumSamples_0_1", 5e2);
  pt.put("NumSamples_0_2", 1e2);
  pt.put("NumSamples_1_0", 5e2);
  pt.put("NumSamples_1_1", 5e2);
  pt.put("NumSamples_1_2", 1e2);
  pt.put("NumSamples_2_0", 1e2);
  pt.put("NumSamples_2_1", 1e2);
  pt.put("NumSamples_2_2", 1e2);
  pt.put("MCMC.BurnIn", 1e1);
  pt.put("MLMCMC.Subsampling_0_0", 5);
  pt.put("MLMCMC.Subsampling_0_1", 5);
  pt.put("MLMCMC.Subsampling_0_2", 5);
  pt.put("MLMCMC.Subsampling_1_0", 5);
  pt.put("MLMCMC.Subsampling_1_1", 5);
  pt.put("MLMCMC.Subsampling_1_2", 5);
  pt.put("MLMCMC.Subsampling_2_0", 5);
  pt.put("MLMCMC.Subsampling_2_1", 5);
  pt.put("MLMCMC.Subsampling_2_2", 5);
  pt.put("MLMCMC.Scheduling", true);
 
  auto comm = std::make_shared<parcer::Communicator>(MPI_COMM_WORLD);
 
 
  auto componentFactory = std::make_shared<MyMIComponentFactory>(pt);
  StaticLoadBalancingMIMCMC parallelMIMCMC (pt, componentFactory);
 
  // if (comm->GetRank() == 0) {
  //   spdlog::info("Starting parallel run");
  //   parallelMIMCMC.Run();
  //   spdlog::info("Parallel run finished");
  //   Eigen::VectorXd meanQOI = parallelMIMCMC.GetQOIs()->Mean();
  //   std::cout << "mean QOI: " << meanQOI.transpose() << std::endl;
  // }
  parallelMIMCMC.Finalize();
 
  MPI_Finalize();
}