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dft_tools/triqs/gfs/data_proxies.hpp

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/*******************************************************************************
*
* TRIQS: a Toolbox for Research in Interacting Quantum Systems
*
* Copyright (C) 2012 by M. Ferrero, 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_DATA_PROXIES_H
#define TRIQS_GF_DATA_PROXIES_H
#include <triqs/utility/first_include.hpp>
#include <utility>
#include <triqs/arrays.hpp>
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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//#include "./matrix_view_proxy.hpp"
#include "../arrays/matrix_tensor_proxy.hpp"
namespace triqs { namespace gfs {
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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//---------------------------- generic case array of dim R----------------------------------
template<typename T, int R> struct data_proxy_array {
/// The storage
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typedef arrays::array<T, R> storage_t;
typedef typename storage_t::view_type storage_view_t;
typedef typename storage_t::const_view_type storage_const_view_t;
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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/// The data access
auto operator()(storage_t& data, long i) const DECL_AND_RETURN(arrays::make_tensor_proxy(data, i));
auto operator()(storage_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_tensor_proxy(data, i));
auto operator()(storage_view_t& data, long i) const DECL_AND_RETURN(arrays::make_tensor_proxy(data, i));
auto operator()(storage_view_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_tensor_proxy(data, i));
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auto operator()(storage_const_view_t& data, long i) const DECL_AND_RETURN(arrays::make_const_tensor_proxy(data, i));
auto operator()(storage_const_view_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_tensor_proxy(data, i));
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
2013-10-16 23:55:26 +02:00
#ifdef TRIQS_GF_DATA_PROXIES_WITH_SIMPLE_VIEWS
auto operator()(storage_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_view_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_view_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
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auto operator()(storage_const_view_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_const_view_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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#endif
template<typename S, typename RHS> static void assign_to_scalar (S & data, RHS && rhs) { data() = std::forward<RHS>(rhs);}
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template <typename ST, typename RHS> static void rebind(ST& data, RHS&& rhs) { data.rebind(rhs.data()); }
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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};
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
2013-10-16 23:55:26 +02:00
//---------------------------- 3d array : returns matrices in this case ! ----------------------------------
template<typename T> struct data_proxy_array<T,3> {
/// The storage
typedef arrays::array<T,3> storage_t;
typedef typename storage_t::view_type storage_view_t;
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typedef typename storage_t::const_view_type storage_const_view_t;
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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/// The data access
auto operator()(storage_t& data, long i) const DECL_AND_RETURN(arrays::make_matrix_proxy(data, i));
auto operator()(storage_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_matrix_proxy(data, i));
auto operator()(storage_view_t& data, long i) const DECL_AND_RETURN(arrays::make_matrix_proxy(data, i));
auto operator()(storage_view_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_matrix_proxy(data, i));
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auto operator()(storage_const_view_t& data, long i) const DECL_AND_RETURN(arrays::make_const_matrix_proxy(data, i));
auto operator()(storage_const_view_t const& data, long i) const DECL_AND_RETURN(arrays::make_const_matrix_proxy(data, i));
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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#ifdef TRIQS_DATA_PROXIES_OLD_MATRIX_VIEW_PROXY
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arrays::matrix_view_proxy<storage_t,0> operator()(storage_t & data, size_t i) const { return arrays::matrix_view_proxy<storage_t,0>(data,i); }
arrays::const_matrix_view_proxy<storage_t,0> operator()(storage_t const & data, size_t i) const { return arrays::const_matrix_view_proxy<storage_t,0>(data,i); }
arrays::matrix_view_proxy<storage_view_t,0> operator()(storage_view_t & data, size_t i) const { return arrays::matrix_view_proxy<storage_view_t,0>(data,i); }
arrays::const_matrix_view_proxy<storage_view_t,0> operator()(storage_view_t const & data, size_t i) const { return arrays::const_matrix_view_proxy<storage_view_t,0>(data,i); }
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
2013-10-16 23:55:26 +02:00
#endif
#ifdef TRIQS_GF_DATA_PROXIES_WITH_SIMPLE_VIEWS
auto operator()(storage_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_view_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_view_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
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auto operator()(storage_const_view_t & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
auto operator()(storage_const_view_t const & data, size_t i) const DECL_AND_RETURN(data(i,arrays::ellipsis()));
[API change] gf : factories -> constructors - Make more general constructors for the gf. gf( mesh, target_shape_t) - remove the old make_gf for the basic gf. - 2 var non generic gf removed. - clean evaluator - add tensor_valued - add a simple vertex test. - clean specialisation - Fix bug introduced in 1906dc3 - forgot to resize the gf in new version of operator = - Fix make_singularity in gf.hpp - clean resize in operator = - update h5 read/write for block gf - changed a bit the general trait to save *all* the gf. - allows a more general specialization, then a correct for blocks - NOT FINISHED : need to save the block indice for python. How to reread ? Currently it read the blocks names and reconstitute the mesh from it. Is it sufficient ? - clean block constructors - block constructors simplest possible : an int for the number of blocks - rest in free factories. - fixed the generic constructor from GfType for the regular type : only enable iif GfType is ImmutableGreenFunction - multivar. fix linear index in C, and h5 format - linear index now correctly flatten in C mode (was in fortran mode), using a simple reverse of the tuple in the folding. - fix the h5 read write of the multivar fonctions in order to write an array on dimension # variables + dim_target i.e. without flattening the indices of the meshes. Easier for later data analysis, e.g. in Python. - merge matrix/tensor_valued. improve factories - matrix_valued now = tensor_valued<2> (simplifies generic code for h5). - factories_one_var -> factories : this is the generic case ... only a few specialization, code is simpler. - clef expression call with rvalue for *this - generalize matrix_proxy to tensor and clean - clean exception catch in tests - exception catching catch in need in test because the silly OS X does not print anything, just "exception occurred". Very convenient for the developer... - BUT, one MUST add return 1, or the make test will *pass* !! - --> systematically replace the catch by a macro TRIQS_CATCH_AND_ABORT which return a non zero error code. - exception : curry_and_fourier which does not work at this stage (mesh incompatible). - gf: clean draft of gf 2 times - comment the python interface for the moment. - rm useless tests
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#endif
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template <typename S, typename RHS> static void assign_to_scalar(S& data, RHS&& rhs) { data() = std::forward<RHS>(rhs); }
template <typename ST, typename RHS> static void rebind(ST& data, RHS&& rhs) { data.rebind(rhs.data()); }
};
//---------------------------- 1d array ----------------------------------
template<typename T> struct data_proxy_array<T,1>{
/// The storage
typedef arrays::array<T,1> storage_t;
typedef typename storage_t::view_type storage_view_t;
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typedef typename storage_t::const_view_type storage_const_view_t;
/// The data access
auto operator()(storage_t & data,size_t i) const -> decltype(data(i)) { return data(i);}
auto operator()(storage_t const & data,size_t i) const -> decltype(data(i)) { return data(i);}
auto operator()(storage_view_t & data,size_t i) const -> decltype(data(i)) { return data(i);}
auto operator()(storage_view_t const & data,size_t i) const -> decltype(data(i)) { return data(i);}
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auto operator()(storage_const_view_t & data,size_t i) const -> decltype(data(i)) { return data(i);}
auto operator()(storage_const_view_t const & data,size_t i) const -> decltype(data(i)) { return data(i);}
template<typename S, typename RHS> static void assign_to_scalar (S & data, RHS && rhs) { data() = std::forward<RHS>(rhs);}
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template <typename ST, typename RHS> static void rebind(ST& data, RHS&& rhs) { data.rebind(rhs.data()); }
};
//---------------------------- vector ----------------------------------
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template<typename V> struct view_proxy : public V {
view_proxy() : V(typename V::regular_type()) {}
view_proxy(V const &v) : V(v){};
view_proxy(view_proxy const & p) : V(p) {};
template<typename ... Args> explicit view_proxy(Args && ... args) : V (std::forward<Args>(args)...){}
view_proxy & operator = ( view_proxy const & cp ) { this->rebind(cp); return *this;}
view_proxy & operator = ( V const & v ) { this->rebind(v); return *this;}
using V::operator=;
//template<typename X> view_proxy & operator = (X && x) { V::operator=( std::forward<X>(x) ); return *this;}
};
template<typename T> struct data_proxy_vector {
typedef typename T::view_type Tv;
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typedef typename T::const_view_type Tcv;
/// The storage
typedef std::vector<T> storage_t;
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typedef std::vector<view_proxy<Tv>> storage_view_t;
typedef std::vector<view_proxy<Tcv>> storage_const_view_t;
/// The data access
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T & operator()(storage_t & data, size_t i) { return data[i];}
T const & operator()(storage_t const & data, size_t i) const { return data[i];}
Tv & operator()(storage_view_t & data, size_t i) { return data[i];}
Tv const & operator()(storage_view_t const & data, size_t i) const { return data[i];}
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Tcv & operator()(storage_const_view_t & data, size_t i) { return data[i];}
Tcv const & operator()(storage_const_view_t const & data, size_t i) const { return data[i];}
/*Tv operator()(storage_view_t & data, size_t i) const { return data[i];}
Tv operator()(storage_view_t const & data, size_t i) const { return data[i];}
Tcv operator()(storage_const_view_t & data, size_t i) const { return data[i];}
Tcv operator()(storage_const_view_t const & data, size_t i) const { return data[i];}
*/
template<typename S, typename RHS> static void assign_to_scalar (S & data, RHS && rhs) {for (size_t i =0; i<data.size(); ++i) data[i] = rhs;}
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template <typename ST, typename RHS> static void rebind(ST& data, RHS&& rhs) { data.clear(); for (auto & x : rhs.data()) data.push_back(x);}
};
//---------------------------- lambda ----------------------------------
template<typename F> struct data_proxy_lambda {
/// The storage
typedef F storage_t;
typedef F storage_view_t;
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typedef F storage_const_view_t;
/// The data access
auto operator()(storage_t & data, size_t i) DECL_AND_RETURN( data(i));
auto operator()(storage_t const & data, size_t i) const DECL_AND_RETURN( data(i));
template<typename S, typename RHS> static void assign_to_scalar (S & data, RHS && rhs) = delete;
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template <typename ST, typename RHS> static void rebind(ST& data, RHS&& rhs) = delete;
};
}}
#endif