Mercurial > fem-fenics-eugenio
view src/assemble_system.cc @ 166:40ae9e5dfb93
Use the uBLAS for an estimation of the nnz elements for excess.
author | gedeone-octave <marcovass89@hotmail.it> |
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date | Sat, 05 Oct 2013 22:27:03 +0100 |
parents | 5fe2a157f4eb |
children | 3895c8d4c066 |
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/* Copyright (C) 2013 Marco Vassallo <gedeone-octave@users.sourceforge.net> This program 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. This program 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 this program; if not, see <http://www.gnu.org/licenses/>. */ #include "form.h" #include "boundarycondition.h" DEFUN_DLD (assemble_system, args, nargout, "-*- texinfo -*-\n\ @deftypefn {Function File} {[@var{A}], [@var{b}], [@var{x}(Optional)]} = \ assemble_system (@var{form a}, @var{form L}, @var{DirichletBC}(Optional), @var{...}) \n\ The input arguments are\n\ @itemize @bullet\n\ @item @var{form a} the bilinear form to assemble.\n\ @item @var{form a} the linear form to assemble.\n\ @item @var{DirichletBC} represents the optional BC that you wish to apply to\n\ the system. If more than one BC has to be applied, just list them.\n\ @end itemize \n\ The output @var{A} is a discretized representation of the system:\n\ @itemize @bullet\n\ @item @var{A} is the sparse Matrix corresponding to the @var{form a}\n\ @item @var{A} is the Vector corresponding to the @var{form L}\n\ @end itemize \n\ If you need to apply boundary condition to a system for a nonlinear problem \n\ then you should provide as 3rd argument the vector and you will receive it back\n\ as the third output argument. For an example of this situation, you can look\n\ the example HyperElasticity.m\n\ @seealso{BilinearForm, LinearForm, ResidualForm, JacobianForm}\n\ @end deftypefn") { int nargin = args.length (); octave_value_list retval; if (! form_type_loaded) { form::register_type (); form_type_loaded = true; mlock (); } if (! boundarycondition_type_loaded) { boundarycondition::register_type (); boundarycondition_type_loaded = true; mlock (); } if (nargout == 2) { if (nargin < 2) print_usage (); else { if (args(0).type_id () == form::static_type_id () && args(1).type_id () == form::static_type_id ()) { const form & frm1 = static_cast<const form&> (args(0).get_rep ()); const form & frm2 = static_cast<const form&> (args(1).get_rep ()); if (! error_state) { const dolfin::Form & a = frm1.get_form (); const dolfin::Form & b = frm2.get_form (); a.check (); b.check (); if (a.rank () == 2 && b.rank () == 1) { dolfin::Matrix A; dolfin::assemble (A, a); dolfin::Vector B; dolfin::assemble (B, b); for (std::size_t i = 2; i < nargin; ++i) { if (args(i).type_id () == boundarycondition::static_type_id ()) { const boundarycondition & bc = static_cast<const boundarycondition&> (args(i).get_rep ()); const std::vector<boost::shared_ptr <const dolfin::DirichletBC> > & pbc = bc.get_bc (); for (std::size_t j = 0; j < pbc.size (); ++j) pbc[j]->apply(A, B); } else error ("assemble_system: unknown argument type"); } // It provides an estimation for excess of nnz elements boost::tuples::tuple<const std::size_t*, const std::size_t*, const double*, int> aa = A.data (); int nnz = aa.get<3> (); std::cout << "Assembling Matrix from the bilinear form..." << std::endl; std::size_t nr = A.size (0), nc = A.size (1); std::vector<double> data_tmp; std::vector<std::size_t> cidx_tmp; octave_idx_type dims = nnz, nz = 0, ii = 0; ColumnVector ridx (dims), cidx (dims), data (dims); for (std::size_t i = 0; i < nr; ++i) { A.getrow (i, cidx_tmp, data_tmp); nz += cidx_tmp.size (); if (dims < nz) { dims = 1.2 * ((nr * nz) / (i + 1));; ridx.resize (dims); cidx.resize (dims); data.resize (dims); } for (octave_idx_type j = 0; j < cidx_tmp.size (); ++j) { ridx.xelem (ii + j) = i + 1; cidx.xelem (ii + j) = cidx_tmp [j] + 1; data.xelem (ii + j) = data_tmp [j]; } ii = nz; } ridx.resize (ii); cidx.resize (ii); data.resize (ii); SparseMatrix sm (data, ridx, cidx, nr, nc); retval(0) = sm; std::cout << "Assembling Vector from the linear form..." << std::endl; dim_vector dim; dim.resize (2); dim(0) = B.size (); dim(1) = 1; Array<double> myb (dim); for (std::size_t i = 0; i < B.size (); ++i) myb.xelem (i) = B[i]; retval(1) = myb; } } else error ("assemble_system: unknown size"); } } } else if (nargout == 3) { std::cout << "Assemble_system: apply boundary condition to a vector for a nonlinear problem..." << std::endl; if (nargin < 3) print_usage (); else { if (args(0).type_id () == form::static_type_id () && args(1).type_id () == form::static_type_id ()) { const form & frm1 = static_cast<const form&> (args(0).get_rep ()); const form & frm2 = static_cast<const form&> (args(1).get_rep ()); const Array<double> myx = args(2).array_value (); if (! error_state) { const dolfin::Form & a = frm1.get_form (); const dolfin::Form & b = frm2.get_form (); a.check (); b.check (); if (a.rank () == 2 && b.rank () == 1) { dolfin::Matrix A; dolfin::assemble (A, a); dolfin::Vector B; dolfin::assemble (B, b); dolfin::Vector x (myx.length ()); for (std::size_t i = 0; i < myx.length (); ++i) x.setitem (i, myx.xelem (i)); for (std::size_t i = 3; i < nargin; ++i) { if (args(i).type_id () == boundarycondition::static_type_id ()) { const boundarycondition & bc = static_cast<const boundarycondition&> (args(i).get_rep ()); const std::vector<boost::shared_ptr <const dolfin::DirichletBC> > & pbc = bc.get_bc (); for (std::size_t j = 0; j < pbc.size (); ++j) pbc[j]->apply(A, B, x); } else error ("assemble_system: unknown argument type"); } // It provides an estimation for excess of nnz elements boost::tuples::tuple<const std::size_t*, const std::size_t*, const double*, int> aa = A.data (); int nnz = aa.get<3> (); std::cout << "Assembling Matrix from the bilinear form..." << std::endl; std::size_t nr = A.size (0), nc = A.size (1); std::vector<double> data_tmp; std::vector<std::size_t> cidx_tmp; octave_idx_type dims = nnz, nz = 0, ii = 0; ColumnVector ridx (dims), cidx (dims), data (dims); for (std::size_t i = 0; i < nr; ++i) { A.getrow (i, cidx_tmp, data_tmp); nz += cidx_tmp.size (); if (dims < nz) { dims = 1.2 * ((nr * nz) / (i + 1));; ridx.resize (dims); cidx.resize (dims); data.resize (dims); } for (octave_idx_type j = 0; j < cidx_tmp.size (); ++j) { ridx.xelem (ii + j) = i + 1; cidx.xelem (ii + j) = cidx_tmp [j] + 1; data.xelem (ii + j) = data_tmp [j]; } ii = nz; } ridx.resize (ii); cidx.resize (ii); data.resize (ii); SparseMatrix sm (data, ridx, cidx, nr, nc); retval(0) = sm; std::cout << "Assembling Vector from the linear form..." << std::endl; dim_vector dim; dim.resize (2); dim(0) = B.size (); dim(1) = 1; Array<double> myb (dim), myc (dim); for (std::size_t i = 0; i < B.size (); ++i) { myb.xelem (i) = B[i]; myc.xelem (i) = x[i]; } retval(1) = myb; retval(2) = myc; } } else error ("assemble_system: unknown size"); } } } return retval; }