From: Wolfgang Bangerth Date: Tue, 9 Mar 2010 16:08:38 +0000 (+0000) Subject: Make a bunch of arguments const references. X-Git-Tag: v8.0.0~6357 X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=d97e33c41a2cd2cb2d36a39e41c225440ba4b69b;p=dealii.git Make a bunch of arguments const references. git-svn-id: https://svn.dealii.org/trunk@20763 0785d39b-7218-0410-832d-ea1e28bc413d --- diff --git a/deal.II/lac/include/lac/precondition.h b/deal.II/lac/include/lac/precondition.h index 42c942ab80..57582ecf81 100644 --- a/deal.II/lac/include/lac/precondition.h +++ b/deal.II/lac/include/lac/precondition.h @@ -2,7 +2,7 @@ // $Id$ // Version: $Name$ // -// Copyright (C) 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2009 by the deal.II authors +// Copyright (C) 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2009, 2010 by the deal.II authors // // This file is subject to QPL and may not be distributed // without copyright and license information. Please refer @@ -136,7 +136,7 @@ class PreconditionRichardson : public Subscriptor /** * Change the relaxaton parameter. */ - void initialize (const AdditionalData parameters); + void initialize (const AdditionalData ¶meters); /** * Change the relaxaton parameter @@ -148,7 +148,7 @@ class PreconditionRichardson : public Subscriptor */ template void initialize (const MATRIX&, - const AdditionalData parameters); + const AdditionalData ¶meters); /** * Apply preconditioner. @@ -180,7 +180,7 @@ class PreconditionRichardson : public Subscriptor */ template void Tvmult_add (VECTOR&, const VECTOR&) const; - + private: /** * The relaxation parameter @@ -241,7 +241,7 @@ class PreconditionUseMatrix : public Subscriptor * function of the matrix. */ typedef void ( MATRIX::* function_ptr)(VECTOR&, const VECTOR&) const; - + /** * Constructor. * This constructor stores a @@ -253,7 +253,7 @@ class PreconditionUseMatrix : public Subscriptor */ PreconditionUseMatrix(const MATRIX &M, const function_ptr method); - + /** * Execute preconditioning. Calls the * function passed to the constructor @@ -268,7 +268,7 @@ class PreconditionUseMatrix : public Subscriptor * Pointer to the matrix in use. */ const MATRIX &matrix; - + /** * Pointer to the preconditioning * function. @@ -303,9 +303,9 @@ class PreconditionRelaxation : public Subscriptor /** * Relaxation parameter. */ - double relaxation; + double relaxation; }; - + /** * Initialize matrix and * relaxation parameter. The @@ -317,14 +317,14 @@ class PreconditionRelaxation : public Subscriptor * reasons. It defaults to 1. */ void initialize (const MATRIX &A, - AdditionalData parameters = AdditionalData()); - + const AdditionalData & parameters = AdditionalData()); + /** * Release the matrix and reset * its pointer. */ void clear(); - + protected: /** * Pointer to the matrix object. @@ -519,7 +519,7 @@ class PreconditionSSOR : public PreconditionRelaxation */ typedef PreconditionRelaxation BaseClass; - + /** * Initialize matrix and * relaxation parameter. The @@ -531,7 +531,7 @@ class PreconditionSSOR : public PreconditionRelaxation * reasons. It defaults to 1. */ void initialize (const MATRIX &A, - typename BaseClass::AdditionalData parameters = typename BaseClass::AdditionalData()); + const typename BaseClass::AdditionalData ¶meters = typename BaseClass::AdditionalData()); /** * Apply preconditioner. @@ -633,9 +633,9 @@ class PreconditionPSOR : public PreconditionRelaxation void initialize (const MATRIX &A, const std::vector &permutation, const std::vector &inverse_permutation, - typename PreconditionRelaxation::AdditionalData + const typename PreconditionRelaxation::AdditionalData & parameters = typename PreconditionRelaxation::AdditionalData()); - + /** * Apply preconditioner. */ @@ -729,7 +729,7 @@ class PreconditionLACSolver : public Subscriptor void initialize (SOLVER&, const MATRIX&, const PRECONDITION&); - + /** * Execute preconditioning. */ @@ -746,7 +746,7 @@ class PreconditionLACSolver : public Subscriptor * The matrix in use. */ SmartPointer > matrix; - + /** * The preconditioner to use. */ @@ -833,192 +833,192 @@ class PreconditionedMatrix : public Subscriptor template , class VECTOR=Vector > class PreconditionChebyshev : public Subscriptor { -public: - /** - * Standardized data struct to - * pipe additional parameters - * to the preconditioner. - */ - struct AdditionalData - { - /** - * Constructor. - */ - AdditionalData (const unsigned int degree = 0, - const double smoothing_range = 0., - const bool nonzero_starting = false, - const unsigned int eig_cg_n_iterations = 8, - const double eig_cg_residual = 1e-2); - - /** - * This determines the degree of the - * Chebyshev polynomial. The degree - * of the polynomial gives the number - * of matrix-vector products to be - * performed for one application of - * the vmult() operation. Degree zero - * corresponds to a damped Jacobi - * method. - */ - unsigned int degree; - - /** - * This sets the range between the - * largest eigenvalue in the matrix - * and the smallest eigenvalue to be - * treated. If the parameter is zero, - * an estimate for the largest and - * for the smallest eigenvalue will - * be calculated - * internally. Otherwise, the - * Chebyshev polynomial will act in - * the interval - * $[\lambda_\mathrm{max}/ - * \tt{smoothing\_range}, - * \lambda_\mathrm{max}]$, where - * $\lambda_\mathrm{max}$ is an - * estimate of the maximum eigenvalue - * of the matrix. A choice of - * smoothing_range between 5 - * and 20 is useful in case the - * preconditioner is used as a - * smoother in multigrid. - */ - double smoothing_range; - - /** - * When this flag is set to - * true, it enables the - * method vmult(dst, src) to - * use non-zero data in the vector - * dst, appending to it the - * Chebyshev corrections. This can be - * useful in some situations - * (e.g. when used for high-frequency - * error smoothing in a multigrid - * algorithm), but not the way the - * solver classes expect a - * preconditioner to work (where one - * ignores the content in - * dst for the - * preconditioner application). - */ - bool nonzero_starting; - - /** - * Maximum number of CG iterations - * performed for finding the maximum - * eigenvalue. - */ - unsigned int eig_cg_n_iterations; - - /** - * Tolerance for CG iterations - * performed for finding the maximum - * eigenvalue. - */ - double eig_cg_residual; - - /** - * Stores the inverse of the diagonal - * of the underlying matrix. - */ - VECTOR matrix_diagonal_inverse; - }; - - PreconditionChebyshev (); - - /** - * Initialize function. Takes the - * matrix which is used to form the - * preconditioner, and additional - * flags if there are any. This - * function works only if the input - * matrix has an operator - * el(i,i) for accessing all - * the elements in the - * diagonal. Alternatively, the - * diagonal can be supplied with the - * help of the AdditionalData field. - * - * This function calculates an - * estimate of the eigenvalue range - * of the matrix weighted by its - * diagonal using a modified CG - * iteration. - */ - void initialize (const MATRIX &matrix, - const AdditionalData &additional_data = AdditionalData()); - - /** - * Computes the action of the - * preconditioner on src, - * storing the result in - * dst. - */ - void vmult (VECTOR &dst, - const VECTOR &src) const; - - /** - * Computes the action of the - * transposed preconditioner on - * src, storing the result - * in dst. - */ - void Tvmult (VECTOR &dst, - const VECTOR &src) const; - - /** - * Resets the preconditioner. - */ - void clear (); - -private: - - /** - * A pointer to the underlying - * matrix. - */ + public: + /** + * Standardized data struct to + * pipe additional parameters + * to the preconditioner. + */ + struct AdditionalData + { + /** + * Constructor. + */ + AdditionalData (const unsigned int degree = 0, + const double smoothing_range = 0., + const bool nonzero_starting = false, + const unsigned int eig_cg_n_iterations = 8, + const double eig_cg_residual = 1e-2); + + /** + * This determines the degree of the + * Chebyshev polynomial. The degree + * of the polynomial gives the number + * of matrix-vector products to be + * performed for one application of + * the vmult() operation. Degree zero + * corresponds to a damped Jacobi + * method. + */ + unsigned int degree; + + /** + * This sets the range between the + * largest eigenvalue in the matrix + * and the smallest eigenvalue to be + * treated. If the parameter is zero, + * an estimate for the largest and + * for the smallest eigenvalue will + * be calculated + * internally. Otherwise, the + * Chebyshev polynomial will act in + * the interval + * $[\lambda_\mathrm{max}/ + * \tt{smoothing\_range}, + * \lambda_\mathrm{max}]$, where + * $\lambda_\mathrm{max}$ is an + * estimate of the maximum eigenvalue + * of the matrix. A choice of + * smoothing_range between 5 + * and 20 is useful in case the + * preconditioner is used as a + * smoother in multigrid. + */ + double smoothing_range; + + /** + * When this flag is set to + * true, it enables the + * method vmult(dst, src) to + * use non-zero data in the vector + * dst, appending to it the + * Chebyshev corrections. This can be + * useful in some situations + * (e.g. when used for high-frequency + * error smoothing in a multigrid + * algorithm), but not the way the + * solver classes expect a + * preconditioner to work (where one + * ignores the content in + * dst for the + * preconditioner application). + */ + bool nonzero_starting; + + /** + * Maximum number of CG iterations + * performed for finding the maximum + * eigenvalue. + */ + unsigned int eig_cg_n_iterations; + + /** + * Tolerance for CG iterations + * performed for finding the maximum + * eigenvalue. + */ + double eig_cg_residual; + + /** + * Stores the inverse of the diagonal + * of the underlying matrix. + */ + VECTOR matrix_diagonal_inverse; + }; + + PreconditionChebyshev (); + + /** + * Initialize function. Takes the + * matrix which is used to form the + * preconditioner, and additional + * flags if there are any. This + * function works only if the input + * matrix has an operator + * el(i,i) for accessing all + * the elements in the + * diagonal. Alternatively, the + * diagonal can be supplied with the + * help of the AdditionalData field. + * + * This function calculates an + * estimate of the eigenvalue range + * of the matrix weighted by its + * diagonal using a modified CG + * iteration. + */ + void initialize (const MATRIX &matrix, + const AdditionalData &additional_data = AdditionalData()); + + /** + * Computes the action of the + * preconditioner on src, + * storing the result in + * dst. + */ + void vmult (VECTOR &dst, + const VECTOR &src) const; + + /** + * Computes the action of the + * transposed preconditioner on + * src, storing the result + * in dst. + */ + void Tvmult (VECTOR &dst, + const VECTOR &src) const; + + /** + * Resets the preconditioner. + */ + void clear (); + + private: + + /** + * A pointer to the underlying + * matrix. + */ SmartPointer > matrix_ptr; - /** - * Internal vector used for the - * vmult operation. - */ - mutable VECTOR update1; - - /** - * Internal vector used for the - * vmult operation. - */ - mutable VECTOR update2; - - /** - * Stores the additional data - * provided to the initialize - * function. - */ - AdditionalData data; - - /** - * Average of the largest and - * smallest eigenvalue under - * consideration. - */ - double theta; - - /** - * Half the interval length between - * the largest and smallest - * eigenvalue under consideration. - */ - double delta; - - /** - * Stores whether the preconditioner - * has been set up. - */ - bool is_initialized; + /** + * Internal vector used for the + * vmult operation. + */ + mutable VECTOR update1; + + /** + * Internal vector used for the + * vmult operation. + */ + mutable VECTOR update2; + + /** + * Stores the additional data + * provided to the initialize + * function. + */ + AdditionalData data; + + /** + * Average of the largest and + * smallest eigenvalue under + * consideration. + */ + double theta; + + /** + * Half the interval length between + * the largest and smallest + * eigenvalue under consideration. + */ + double delta; + + /** + * Stores whether the preconditioner + * has been set up. + */ + bool is_initialized; }; @@ -1084,7 +1084,7 @@ PreconditionRichardson::PreconditionRichardson () inline void PreconditionRichardson::initialize ( - const PreconditionRichardson::AdditionalData parameters) + const PreconditionRichardson::AdditionalData ¶meters) { relaxation = parameters.relaxation; } @@ -1095,7 +1095,7 @@ template inline void PreconditionRichardson::initialize ( const MATRIX&, - const PreconditionRichardson::AdditionalData parameters) + const PreconditionRichardson::AdditionalData ¶meters) { relaxation = parameters.relaxation; } @@ -1139,7 +1139,7 @@ PreconditionRichardson::Tvmult_add (VECTOR &dst, const VECTOR &src) const template inline void PreconditionRelaxation::initialize (const MATRIX &rA, - AdditionalData parameters) + const AdditionalData ¶meters) { A = &rA; relaxation = parameters.relaxation; @@ -1250,23 +1250,23 @@ PreconditionSOR::Tstep (VECTOR &dst, const VECTOR &src) const template inline void PreconditionSSOR::initialize (const MATRIX &rA, - typename BaseClass::AdditionalData parameters) + const typename BaseClass::AdditionalData ¶meters) { this->PreconditionRelaxation::initialize (rA, parameters); // in case we have a SparseMatrix class, // we can extract information about the // diagonal. - const SparseMatrix * mat = - dynamic_cast *>(&*this->A); + const SparseMatrix * mat = + dynamic_cast *>(&*this->A); // calculate the positions first after // the diagonal. if (mat != 0) { - const std::size_t * rowstart_ptr = + const std::size_t * rowstart_ptr = mat->get_sparsity_pattern().get_rowstart_indices(); - const unsigned int * const colnums = + const unsigned int * const colnums = mat->get_sparsity_pattern().get_column_numbers(); const unsigned int n = this->A->n(); pos_right_of_diagonal.resize(n); @@ -1279,7 +1279,7 @@ PreconditionSSOR::initialize (const MATRIX &rA, // note: the first entry in each // line denotes the diagonal element, // which we need not check. - pos_right_of_diagonal[row] = + pos_right_of_diagonal[row] = std::lower_bound (&colnums[*rowstart_ptr+1], &colnums[*(rowstart_ptr+1)], row) @@ -1340,7 +1340,7 @@ PreconditionPSOR::initialize ( const MATRIX &rA, const std::vector &p, const std::vector &ip, - typename PreconditionRelaxation::AdditionalData parameters) + const typename PreconditionRelaxation::AdditionalData ¶meters) { permutation = &p; inverse_permutation = &ip; @@ -1434,7 +1434,7 @@ PreconditionLACSolver::vmult (VECTOR &dst, { Assert (solver !=0 && matrix != 0 && precondition != 0, ExcNotInitialized()); - + solver->solve(*matrix, dst, src, *precondition); } @@ -1530,7 +1530,7 @@ PreconditionChebyshev::PreconditionChebyshev () template inline -void +void PreconditionChebyshev::initialize (const MATRIX &matrix, const AdditionalData &additional_data) { @@ -1549,10 +1549,10 @@ PreconditionChebyshev::initialize (const MATRIX &matrix, // calculate largest eigenvalue using a // hand-tuned CG iteration on the matrix - // weighted by its diagonal. we start - // with a vector that consists of ones + // weighted by its diagonal. we start + // with a vector that consists of ones // only, weighted by the length. - // + // // TODO: can we obtain this with the // regular CG implementation? we would need // to read the logfile in that case, which @@ -1615,7 +1615,7 @@ PreconditionChebyshev::initialize (const MATRIX &matrix, // include a safety factor since the CG // method will in general not be converged const double beta = 1.2 * max_eigenvalue; - const double alpha = (data.smoothing_range > 0 ? + const double alpha = (data.smoothing_range > 0 ? max_eigenvalue / data.smoothing_range : max_eigenvalue / min_eigenvalue); delta = (beta-alpha)*0.5; @@ -1627,7 +1627,7 @@ PreconditionChebyshev::initialize (const MATRIX &matrix, template inline -void +void PreconditionChebyshev::vmult (VECTOR &dst, const VECTOR &src) const { @@ -1665,7 +1665,7 @@ PreconditionChebyshev::vmult (VECTOR &dst, template inline -void +void PreconditionChebyshev::Tvmult (VECTOR &dst, const VECTOR &src) const {