mirror of
https://github.com/triqs/dft_tools
synced 2024-12-26 06:14:14 +01:00
e1c113b745
- evaluator - G(k,tau) is real - partial_eval for matrix_valued functions - details : simplifying traits (using decay_t)
124 lines
6.8 KiB
C++
124 lines
6.8 KiB
C++
/*******************************************************************************
|
|
*
|
|
* TRIQS: a Toolbox for Research in Interacting Quantum Systems
|
|
*
|
|
* Copyright (C) 2013 by O. Parcollet
|
|
*
|
|
* TRIQS is free software: you can redistribute it and/or modify it under the
|
|
* terms of the GNU General Public License as published by the Free Software
|
|
* Foundation, either version 3 of the License, or (at your option) any later
|
|
* version.
|
|
*
|
|
* TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
|
|
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
|
|
* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
|
|
* details.
|
|
*
|
|
* You should have received a copy of the GNU General Public License along with
|
|
* TRIQS. If not, see <http://www.gnu.org/licenses/>.
|
|
*
|
|
******************************************************************************/
|
|
#ifndef TRIQS_GF_CURRY_H
|
|
#define TRIQS_GF_CURRY_H
|
|
#include "./product.hpp"
|
|
namespace triqs { namespace gfs {
|
|
|
|
template<typename F> struct lambda_valued {};
|
|
|
|
namespace gfs_implementation {
|
|
|
|
/// --------------------------- data access ---------------------------------
|
|
|
|
template<typename Opt, typename F, typename M> struct data_proxy<M,lambda_valued<F>,Opt> : data_proxy_lambda<F> {};
|
|
|
|
/// --------------------------- Factories ---------------------------------
|
|
|
|
template<typename F, typename Opt, typename ... Ms>
|
|
struct factories<cartesian_product<Ms...>, lambda_valued<F>, Opt> {};
|
|
|
|
/// --------------------------- partial_eval ---------------------------------
|
|
// partial_eval<0> (g, 1) returns : x -> g(1,x)
|
|
// partial_eval<1> (g, 3) returns : x -> g(x,3)
|
|
|
|
// a technical trait: from a tuple of mesh, return the mesh (either M if it is a tuple of size 1, or the corresponding cartesian_product<M..>).
|
|
template<typename ... Ms> struct cart_prod_impl;
|
|
template<typename ... Ms> using cart_prod = typename cart_prod_impl<Ms...>::type;
|
|
template<typename ... Ms> struct cart_prod_impl<std::tuple<Ms...>> { using type = cartesian_product<Ms...>;};
|
|
template<typename M> struct cart_prod_impl<std::tuple<M>> { using type = M;};
|
|
|
|
template<typename M0, typename M1, typename ...M> auto rm_tuple_of_size_one(std::tuple<M0,M1,M...> const & t) DECL_AND_RETURN(t);
|
|
template<typename M> auto rm_tuple_of_size_one(std::tuple<M> const & t) DECL_AND_RETURN(std::get<0>(t));
|
|
|
|
// as_tuple leaves a tuple intact and wrap everything else in a tuple...
|
|
template<typename T> std::tuple<T> as_tuple(T && x) { return std::tuple<T> {std::forward<T>(x)};}
|
|
template<typename ... T> std::tuple<T...> as_tuple(std::tuple<T...> && x) { return std::forward<T...>(x);}
|
|
template<typename ... T> std::tuple<T...> const & as_tuple(std::tuple<T...> const & x) { return x;}
|
|
template<typename ... T> std::tuple<T...> & as_tuple(std::tuple<T...> & x) { return x;}
|
|
|
|
template <int... pos, typename Opt, typename Target, bool IsConst, typename IT, typename... Ms>
|
|
gf_view<cart_prod<triqs::tuple::filter_out_t<std::tuple<Ms...>, pos...>>, Target, Opt, IsConst>
|
|
partial_eval(gf_view<cartesian_product<Ms...>, Target, Opt, IsConst> g, IT index) {
|
|
// meshes of the returned gf_view : just drop the mesh of the evaluated variables
|
|
auto meshes_tuple_partial = triqs::tuple::filter_out<pos...>(g.mesh().components());
|
|
// a view of the array of g, with the dimension sizeof...(Ms)
|
|
auto arr = reinterpret_linear_array(g.mesh(),g.data()); // NO the second () forces a view
|
|
// now rebuild a tuple of the size sizeof...(Ms), containing the indices and range at the position of evaluated variables.
|
|
auto arr_args = triqs::tuple::inverse_filter<sizeof...(Ms),pos...>(as_tuple(index), arrays::range());
|
|
// from it, we make a slice of the array of g, corresponding to the data of the returned gf_view
|
|
auto arr2 = triqs::tuple::apply(arr, std::tuple_cat(arr_args, std::make_tuple(arrays::ellipsis{})));
|
|
// finally, we build the view on this data.
|
|
using r_t = gf_view< cart_prod< triqs::tuple::filter_out_t<std::tuple<Ms...>, pos...>> ,Target, Opt,IsConst>;
|
|
return r_t{ rm_tuple_of_size_one(meshes_tuple_partial), arr2, typename r_t::singularity_non_view_t{}, typename r_t::symmetry_t{} };
|
|
}
|
|
|
|
template <int... pos, typename Opt, typename Target, typename IT, typename... Ms>
|
|
gf_view<cart_prod<triqs::tuple::filter_out_t<std::tuple<Ms...>, pos...>>, Target, Opt, false>
|
|
partial_eval(gf<cartesian_product<Ms...>, Target, Opt> & g, IT index) {
|
|
return partial_eval<pos...>(g(),index);
|
|
}
|
|
|
|
template <int... pos, typename Opt, typename Target, typename IT, typename... Ms>
|
|
gf_view<cart_prod<triqs::tuple::filter_out_t<std::tuple<Ms...>, pos...>>, Target, Opt, true>
|
|
partial_eval(gf<cartesian_product<Ms...>, Target, Opt> const& g, IT index) {
|
|
return partial_eval<pos...>(g(),index);
|
|
}
|
|
|
|
/// --------------------------- curry ---------------------------------
|
|
// curry<0>(g) returns : x-> y... -> g(x,y...)
|
|
// curry<1>(g) returns : y-> x,z... -> g(x,y,z...)
|
|
|
|
// to adapt the partial_eval as a polymorphic lambda (replace by a lambda in c++14)
|
|
template<typename Gview, int ... pos> struct curry_polymorphic_lambda {
|
|
Gview g;
|
|
template<typename ...I> auto operator()(I ... i) const DECL_AND_RETURN(partial_eval<pos...>(g,std::make_tuple(i...)));
|
|
friend int get_shape(curry_polymorphic_lambda const&) { return 0;}// no shape here, but needed for compilation
|
|
//void resize(int){}
|
|
};
|
|
|
|
// curry function ...
|
|
template <int... pos, typename Target, typename Opt, bool IsConst, typename... Ms>
|
|
gf_view<cart_prod<triqs::tuple::filter_t<std::tuple<Ms...>, pos...>>,
|
|
lambda_valued<curry_polymorphic_lambda<gf_view<cartesian_product<Ms...>, Target, Opt,IsConst>, pos...>>, Opt, IsConst>
|
|
curry(gf_view<cartesian_product<Ms...>, Target, Opt, IsConst> g) {
|
|
// pick up the meshed corresponding to the curryed variables
|
|
auto meshes_tuple = triqs::tuple::filter<pos...>(g.mesh().components());
|
|
// building the view
|
|
return {rm_tuple_of_size_one(meshes_tuple),curry_polymorphic_lambda<gf_view<cartesian_product<Ms...>, Target,Opt,IsConst>, pos ...>{g}, nothing(), nothing()};
|
|
//using m_t = gf_mesh< cart_prod< triqs::tuple::filter_t<std::tuple<Ms...>,pos...>>>;
|
|
//return {triqs::tuple::apply_construct<m_t>(meshes_tuple),curry_polymorphic_lambda<gf_view<cartesian_product<Ms...>, Target,Opt>, pos ...>{g}, nothing(), nothing()};
|
|
};
|
|
|
|
template <int... pos, typename Target, typename Opt, typename... Ms>
|
|
auto curry(gf<cartesian_product<Ms...>, Target, Opt> & g) DECL_AND_RETURN(curry<pos...>(g()));
|
|
|
|
template <int... pos, typename Target, typename Opt, typename... Ms>
|
|
auto curry(gf<cartesian_product<Ms...>, Target, Opt> const & g) DECL_AND_RETURN(curry<pos...>(g()));
|
|
|
|
} // gf_implementation
|
|
using gfs_implementation::partial_eval;
|
|
using gfs_implementation::curry;
|
|
}}
|
|
#endif
|
|
|
|
|