LCPQ/dft_tools
3
0
Fork 0
mirror of https://github.com/triqs/dft_tools synced 2025-01-12 05:58:18 +01:00
Code Issues Releases Wiki Activity

Made autocorrtime calculation from binning faster.

Browse Source 
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
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

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
View File

@ -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
View File

@ -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