mirror of
https://github.com/triqs/dft_tools
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87dc9aeaa5
- binning, jackknife, autocorrelation, observable. - DRAFT only : in development, debug. Doc to be written.
33 lines
1.3 KiB
C++
33 lines
1.3 KiB
C++
#pragma once
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#include <boost/random/variate_generator.hpp>
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#include <boost/random/mersenne_twister.hpp>
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#include <boost/random/normal_distribution.hpp>
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using uint = unsigned int;
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template <typename TimeSeries> void boost_independent_gaussian_vector(TimeSeries& t, int seed) {
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boost::variate_generator<boost::mt19937, boost::normal_distribution<>> generator((boost::mt19937(seed)),
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(boost::normal_distribution<>()));
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for (size_t i = 0; i < t.size(); ++i) t[i] = generator();
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}
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template <typename TimeSeries> void correlated_gaussian_vector(TimeSeries& t, int seed, size_t correlation_length) {
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boost_independent_gaussian_vector(t, seed);
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TimeSeries B(t.size());
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B[0] = t[0];
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double f = exp(-1. / correlation_length);
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for (size_t i = 1; i < t.size(); i++) B[i] = f * B[i - 1] + sqrt(1 - f * f) * t[i];
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t = B;
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}
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template <typename TimeSeries> void correlated_gaussian_vector(TimeSeries& t, int seed, size_t correlation_length, double avg) {
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boost_independent_gaussian_vector(t, seed);
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TimeSeries B(t.size());
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B[0] = t[0];
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double f = exp(-1. / correlation_length);
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for (size_t i = 1; i < t.size(); i++) B[i] = f * B[i - 1] + sqrt(1 - f * f) * t[i];
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t = B;
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for (size_t i = 1; i < t.size(); i++) t[i] = t[i] + avg;
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}
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