Unverified Commit 321d0397 authored by Peter Doak's avatar Peter Doak Committed by GitHub
Browse files

Merge pull request #260 from PDoakORNL/autocorrelation_testing 

adding missing test and writes from autocorrelation branch
parents 81ad9b40 55e70874

include/dca/phys/dca_loop/dca_loop.hpp

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@@ -173,6 +173,8 @@ void DcaLoop<ParametersType, DcaDataType, MCIntegratorType, DIST>::write() { 
#endif



  if (concurrency.id() == concurrency.first()) {

    parameters.write(*output_file_);

    MOMS.write(*output_file_);

    monte_carlo_integrator_.write(*output_file_);

    DCA_info_struct.write(*output_file_);

    output_file_->close_file();

test/unit/math/CMakeLists.txt

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@@ -4,4 +4,5 @@ add_subdirectory(function_transform) 
add_subdirectory(nfft)

add_subdirectory(random)

add_subdirectory(statistical_testing)

add_subdirectory(statistics)

add_subdirectory(util)

test/unit/math/statistics/CMakeLists.txt

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dca_add_gtest(autocorrelation_test

        FAST

        GTEST_MAIN

        LIBS)

test/unit/math/statistics/autocorrelation_test.cpp

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// Copyright (C) 2019 ETH Zurich

// Copyright (C) 2019 UT-Battelle, LLC

// All rights reserved.

//

// See LICENSE for terms of usage.

// See CITATION.md for citation guidelines, if DCA++ is used for scientific publications.

//

// Author: Giovanni Balduzzi (gbalduzz@itp.phys.ethz.ch)

//

// This file tests autocorrelation.hpp by generating a time series of known autocorrelation time.



#include "dca/math/statistics/autocorrelation.hpp"



#include <random>

#include "gtest/gtest.h"



TEST(AutocorrelationTest, All) {

  const std::vector<double> tau_exp_vals{1, 5, 3};

  const std::vector<double> means{0, 1, -1};

  const std::vector<double> stdevs{1, 0.5, 2};



  const int n_samples = 5e4;



  std::mt19937_64 rng(42);



  for (int test_id = 0; test_id < tau_exp_vals.size(); ++test_id) {

    const double tau_exp = tau_exp_vals[test_id];



    std::vector<double> independent_series(n_samples);

    std::normal_distribution<double> distro(means[test_id], stdevs[test_id]);



    const int n_corr = 100;

    dca::math::statistics::Autocorrelation<double> autocorr(n_corr);



    // Compute and accumulate time series.

    for (auto& x : independent_series) {

      x = distro(rng);

    }



    for (int i = n_corr; i < independent_series.size(); ++i) {

      double correlated = 0;



      for (int j = i - n_corr; j <= i; ++j) {

        correlated += std::exp(-(i - j) / tau_exp) * independent_series[j];

      }



      autocorr.addSample(correlated);

    }



    // See: http://www.hep.fsu.edu/~berg/teach/mcmc08/material/lecture07mcmc3.pdf

    const auto tau_integrated = 1. + (2 * std::exp(-1. / tau_exp)) / (1 - std::exp(-1. / tau_exp));



    const double tau_computed = autocorr.computeAutocorrelationTime();



    const double rel_diff = 2 * (tau_computed - tau_integrated) / (tau_computed + tau_integrated);

    EXPECT_NEAR(rel_diff, 0, 0.1);

  }

}



TEST(AutocorrelationTest, ComplexCompiles) {

  dca::math::statistics::Autocorrelation<std::complex<float>> corr(10);



  corr.addSample(std::complex<float>(1, 0));

  corr.addSample(std::complex<float>(1, -1));



  // Note: this computation will fail to converge.

  corr.computeAutocorrelationTime();

}

test/unit/phys/dca_step/cluster_solver/shared_tools/interpolation/g0_interpolation_gpu_test.cpp

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// Copyright (C) 2019 ETH Zurich

// Copyright (C) 2019 UT-Battelle, LLC

// All rights reserved.

//

// See LICENSE.txt for terms of usage.

// See CITATION.txt for citation guidelines if you use this code for scientific publications.

//

// Author: Giovanni Balduzzi (gbalduzz@gitp.phys.ethz.ch)

//



#include <cmath>

#include <mutex>