//============================================================================== // Copyright 2011-2014 Karsten Ahnert // Copyright 2011-2014 Mario Mulansky // Copyright 2014 LRI UMR 8623 CNRS/Univ Paris Sud XI // Copyright 2014 NumScale SAS // // Distributed under the Boost Software License, Version 1.0. // See accompanying file LICENSE.txt or copy at // http://www.boost.org/LICENSE_1_0.txt //============================================================================== #include #include #include #ifndef M_PI //not there on windows #define M_PI 3.141592653589793 //... #endif #include #include #include #include #include #include #include #include #include #include #include #include using namespace std; using namespace boost::numeric::odeint; template pair< T, T > calc_mean_field( const container_type &x ) { T cos_sum = 0.0 , sin_sum = 0.0; nt2::tie(cos_sum,sin_sum) = nt2::tie(nt2::mean( nt2::cos(x) ), nt2::mean( nt2::sin(x) )); T K = nt2::hypot(sin_sum,cos_sum); T Theta = nt2::atan2( sin_sum , cos_sum ); return make_pair( K , Theta ); } template struct phase_ensemble { typedef typename boost::dispatch::meta::as_integer::type int_type; container_type m_omega; T m_epsilon; phase_ensemble( const int_type n , T g = 1.0 , T epsilon = 1.0 ) : m_epsilon( epsilon ) { m_omega = nt2::zeros(nt2::of_size(n), nt2::meta::as_()); create_frequencies( g ); } void create_frequencies( T g ) { boost::mt19937 rng; boost::cauchy_distribution<> cauchy( 0.0 , g ); boost::variate_generator< boost::mt19937&, boost::cauchy_distribution<> > gen( rng , cauchy ); generate( m_omega.begin() , m_omega.end() , gen ); } void set_epsilon( T epsilon ) { m_epsilon = epsilon; } T get_epsilon( void ) const { return m_epsilon; } void operator()( const container_type &x , container_type &dxdt , T ) const { pair< T, T > mean = calc_mean_field( x ); dxdt = m_omega + m_epsilon * mean.first * nt2::sin( mean.second - x ); } }; template struct statistics_observer { typedef typename boost::dispatch::meta::as_integer::type int_type; T m_K_mean; int_type m_count; statistics_observer( void ) : m_K_mean( 0.0 ) , m_count( 0 ) { } template< class State > void operator()( const State &x , T t ) { pair< T, T > mean = calc_mean_field( x ); m_K_mean += mean.first; ++m_count; } T get_K_mean( void ) const { return ( m_count != 0 ) ? m_K_mean / T( m_count ) : 0.0 ; } void reset( void ) { m_K_mean = 0.0; m_count = 0; } }; template struct test_ode_table { typedef nt2::table array_type; typedef void experiment_is_immutable; typedef typename boost::dispatch::meta::as_integer::type int_type; test_ode_table ( ) : size_(16384), ensemble( size_ , 1.0 ), unif( 0.0 , 2.0 * M_PI ), gen( rng , unif ), obs() { x.resize(nt2::of_size(size_)); } void operator()() { for( T epsilon = 0.0 ; epsilon < 5.0 ; epsilon += 0.1 ) { ensemble.set_epsilon( epsilon ); obs.reset(); // start with random initial conditions generate( x.begin() , x.end() , gen ); // calculate some transients steps integrate_const( runge_kutta4< array_type, T >() , boost::ref( ensemble ) , x , T(0.0) , T(10.0) , dt ); // integrate and compute the statistics integrate_const( runge_kutta4< array_type, T >() , boost::ref( ensemble ) , x , T(0.0) , T(100.0) , dt , boost::ref( obs ) ); cout << epsilon << "\t" << obs.get_K_mean() << endl; } } friend std::ostream& operator<<(std::ostream& os, test_ode_table const& p) { return os << "(" << p.size() << ")"; } std::size_t size() const { return size_; } private: std::size_t size_; phase_ensemble ensemble; boost::uniform_real<> unif; array_type x; boost::mt19937 rng; boost::variate_generator< boost::mt19937&, boost::uniform_real<> > gen; statistics_observer obs; static const T dt = 0.1; }; int main() { std::cout<< " With T = [double] \n"; test_ode_table test_double; test_double(); std::cout<< " With T = [float] \n"; test_ode_table test_float; test_float(); }