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Made autocorrtime calculation from binning faster.

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Bin size is doubled at each step to converge faster and reuse previous binned series.
This commit is contained in:
tayral 2014-03-12 11:28:25 +00:00 committed by Olivier Parcollet
parent 0e23db7f92
commit 2c6da6a35a
3 changed files with 48 additions and 5 deletions
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12
test/triqs/statistics/autocorrelation_time.cpp
View File

@ -2,6 +2,7 @@
#include <triqs/statistics.hpp>
#include "./correlated_gaussian.hpp"
#include <iostream>
#include <ctime>
#define TEST(X) std::cout << BOOST_PP_STRINGIZE((X)) << " ---> "<< (X) <<std::endl<<std::endl;
using namespace triqs::statistics;
@ -31,13 +32,20 @@ void test_1(int argc, char ** argv){
correlated_gaussian_vector(A, seed, L);
double intrinsic_variance = 1;
auto t1 = clock();
TEST( autocorrelation_time(A));
//std::cout << "time = " << double( clock()-t1)/CLOCKS_PER_SEC << std::endl;
//t1 = clock();
TEST( autocorrelation_time_from_binning(A,intrinsic_variance));
TEST( autocorrelation_time_from_binning(A));
//std::cout << "time = " << double( clock()-t1)/CLOCKS_PER_SEC << std::endl;
//t1 = clock();
//TEST( autocorrelation_time_from_binning2(A));
//std::cout << "time = " << double( clock()-t1)/CLOCKS_PER_SEC << std::endl;
}
void test_2(int argc, char ** argv){
int N=10000, L=40;
int N=100000, L=40;
if(argc==3){
N = atoi(argv[1]); //size
L = atoi(argv[2]); //autocorrelation time
@ -50,6 +58,8 @@ void test_2(int argc, char ** argv){
observable<double> V;
for (auto & x:A) V << x;
TEST(autocorrelation_time(V));
TEST(autocorrelation_time_from_binning(V));
//TEST(autocorrelation_time_from_binning2(V));
TEST(autocorrelation_time(V*V));
}

8
test/triqs/statistics/autocorrelation_time.output
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@ -6,9 +6,11 @@ L = 100
(autocorrelation_time_from_binning(A,intrinsic_variance)) ---> 80.2806
(autocorrelation_time_from_binning(A)) ---> 106.764
(autocorrelation_time_from_binning(A)) ---> 95.7671
(autocorrelation_time(V)) ---> 41
(autocorrelation_time(V)) ---> 40
(autocorrelation_time(V*V)) ---> 40
(autocorrelation_time_from_binning(V)) ---> 38.0031
(autocorrelation_time(V*V)) ---> 37

33
triqs/statistics/statistics.hpp
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@ -437,7 +437,7 @@ namespace statistics {
// ------ Auto-correlation time from binning --------------------
template <typename TimeSeries> double autocorrelation_time_from_binning(TimeSeries const& A) {
template <typename TimeSeries> double autocorrelation_time_from_binning2(TimeSeries const& A) {
auto size = make_immutable_time_series(A).size();
double var1 = empirical_variance(make_immutable_time_series(A));
@ -462,5 +462,36 @@ namespace statistics {
}
return empirical_average(t);
}
template<typename TimeSeries>
double t_cor(TimeSeries const & A, int bin_size, double var1){
double var = empirical_variance(A);
return .5 * var / var1 * bin_size;
}
template <typename TimeSeries> double autocorrelation_time_from_binning(TimeSeries const& A) {
auto size = make_immutable_time_series(A).size();
double var1 = empirical_variance(make_immutable_time_series(A));
int B = 2;
auto Ab=make_binned_series(A,2);
double autocorr_time = t_cor(Ab, B, var1);
double slope = 1.;
int small_slope_count = 0;
std::vector<double> t;
while (small_slope_count < 5 && B < size / 10) {
B*=2;
Ab=make_binned_series(Ab,2);
double t_cor_new = t_cor(Ab, B, var1);
slope = (std::abs(t_cor_new - autocorr_time) / autocorr_time);
if (slope < .5*1e-1) small_slope_count++;
if (small_slope_count > 0) t.push_back(t_cor_new);
autocorr_time = t_cor_new;
//std::cout << B << "\t" << t_cor_new << "\t" << slope << std::endl;
}
if (t.size()>0) {return empirical_average(t);}
else{ std::cout << "autocorrelation time not converged!!" << std::endl; return autocorr_time;}
}
} // namespace statistics
} // triqs