Commit dea8257e authored by Martin Marinov's avatar Martin Marinov

Merge remote-tracking branch 'origin/warning_fixes'

parents 957aeb32 54dc54db
......@@ -28,7 +28,7 @@ if (MSVC)
add_definitions(-DNOMINMAX)
# add_definitions(-DIL_STD) #set CPLEX to use its STL interface, change this?!
add_definitions(/W1) #add appropriate warnings flags for this project, the compilation raises to too may warnings
add_definitions(/W3) #add appropriate warnings flags for this project, the compilation raises to too may warnings
add_definitions(/MP) #build on all cores
endif (MSVC)
......
......@@ -17,6 +17,9 @@
//== INCLUDES =================================================================
#include <iostream>
#include <Base/Code/Quality.hh>
LOW_CODE_QUALITY_SECTION_BEGIN
#include <Eigen/Eigen>
#if EIGEN_VERSION_AT_LEAST(3,1,0)
......@@ -26,6 +29,7 @@
#include <unsupported/Eigen/CholmodSupport>
#endif
#include <Eigen/Sparse>
LOW_CODE_QUALITY_SECTION_END
//== FORWARDDECLARATIONS ======================================================
......
......@@ -63,9 +63,9 @@ public:
COMISO::StopWatch sw; sw.start();
// number of unknowns
int n = _quadratic_problem->n_unknowns();
size_t n = _quadratic_problem->n_unknowns();
// number of constraints
int m = _b.size();
size_t m = _b.size();
std::cerr << "optmize via AQP with " << n << " unknowns and " << m << " linear constraints" << std::endl;
......@@ -193,7 +193,7 @@ protected:
double backtracking_line_search(NProblemInterface* _quadratic_problem, NProblemInterface* _nonlinear_problem, VectorD& _x, VectorD& _g, VectorD& _dx, double& _rel_df, double _t_start = 1.0)
{
int n = _x.size();
size_t n = _x.size();
// pre-compute objective
double fx = _quadratic_problem->eval_f(_x.data()) + _nonlinear_problem->eval_f(_x.data());
......
......@@ -150,7 +150,7 @@ bool solve_impl(
DEB_warning_if(!_problem->constant_gradient(), 1,
"CBCSolver received a problem with non-constant gradient!");
const int n_rows = _constraints.size(); // Constraints #
const size_t n_rows = _constraints.size(); // Constraints #
const int n_cols = _problem->n_unknowns(); // Unknowns #
// expand the variable types from discrete mtrx array
......
......@@ -50,7 +50,7 @@ solve(NProblemInterface* _problem,
//----------------------------------------------
// 2. setup constraints
//----------------------------------------------
int n = _problem->n_unknowns();
std::size_t n = _problem->n_unknowns();
gmm::row_matrix< gmm::wsvector< double > > C(_constraints.size(), n+1);
int n_constraints = 0;
......
......@@ -26,11 +26,10 @@ namespace COMISO {
/// Default constructor
ConeConstraint::ConeConstraint()
: NConstraintInterface(NConstraintInterface::NC_GREATER_EQUAL)
: NConstraintInterface(NConstraintInterface::NC_GREATER_EQUAL),
i_(1), c_(1.0)
{
Q_.clear();
i_ = 1.0;
c_ = 1.0;
}
// cone constraint of the form -> 0.5*(c_ * x(i_)^2 - x^T Q_ x) >= 0
......
......@@ -62,8 +62,8 @@ remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstrain
if(_constraints.empty()) return;
// 1. copy (normalized) data into gmm dynamic sparse matrix
unsigned int n(_constraints[0]->n_unknowns());
unsigned int m(_constraints.size());
size_t n(_constraints[0]->n_unknowns());
size_t m(_constraints.size());
std::vector<double> x(n, 0.0);
NConstraintInterface::SVectorNC g;
RMatrixGMM A;
......@@ -92,27 +92,28 @@ remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstrain
// 3. initialize priorityqueue for sorting
// init priority queue
MutablePriorityQueueT<unsigned int, unsigned int> queue;
MutablePriorityQueueT<gmm::size_type, gmm::size_type> queue;
queue.clear(m);
for(unsigned int i=0; i<m; ++i)
for (gmm::size_type i = 0; i<m; ++i)
{
int cur_nnz = gmm::nnz( gmm::mat_row(A,i));
if( A(i,n) != 0.0) --cur_nnz;
gmm::size_type cur_nnz = gmm::nnz( gmm::mat_row(A,i));
if (A(i,n) != 0.0)
--cur_nnz;
queue.update(i, cur_nnz);
}
// track row status -1=undecided, 0=remove, 1=keep
std::vector<int> row_status(m, -1);
std::vector<int> keep;
std::vector<gmm::size_type> keep;
// std::vector<int> remove;
// for all conditions
while(!queue.empty())
{
// get next row
unsigned int i = queue.get_next();
unsigned int j = find_max_abs_coeff(A.row(i));
gmm::size_type i = queue.get_next();
gmm::size_type j = find_max_abs_coeff(A.row(i));
double aij = A(i,j);
if(std::abs(aij) <= _eps)
{
......@@ -145,7 +146,7 @@ remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstrain
if( row_status[c_it.index()] == -1) // only process unvisited rows
{
// row idx
int k = c_it.index();
gmm::size_type k = c_it.index();
double s = -(*c_it)/aij;
add_row_simultaneously( k, s, row, A, Ac, _eps);
......@@ -153,8 +154,9 @@ remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstrain
A( k, j) = 0;
Ac(k, j) = 0;
int cur_nnz = gmm::nnz( gmm::mat_row(A,k));
if( A(k,n) != 0.0) --cur_nnz;
gmm::size_type cur_nnz = gmm::nnz( gmm::mat_row(A,k));
if( A(k,n) != 0.0)
--cur_nnz;
queue.update(k, cur_nnz);
}
......@@ -177,12 +179,12 @@ remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstrain
//-----------------------------------------------------------------------------
unsigned int
gmm::size_type
ConstraintTools::
find_max_abs_coeff(SVectorGMM& _v)
{
unsigned int n = _v.size();
unsigned int imax(0);
size_t n = _v.size();
gmm::size_type imax(0);
double vmax(0.0);
gmm::linalg_traits<SVectorGMM>::const_iterator c_it = gmm::vect_const_begin(_v);
......@@ -205,7 +207,7 @@ find_max_abs_coeff(SVectorGMM& _v)
void
ConstraintTools::
add_row_simultaneously( int _row_i,
add_row_simultaneously( gmm::size_type _row_i,
double _coeff,
SVectorGMM& _row,
RMatrixGMM& _rmat,
......
......@@ -58,13 +58,13 @@ public:
static void remove_dependent_linear_constraints(std::vector<NConstraintInterface*>& _constraints, const double _eps = 1e-8);
// same as above but assumes already that all constraints are linear equality constraints
static void remove_dependent_linear_constraints_only_linear_equality( std::vector<NConstraintInterface*>& _constraints, const double _eps = 1e-8);
static void remove_dependent_linear_constraints_only_linear_equality(std::vector<NConstraintInterface*>& _constraints, const double _eps = 1e-8);
private:
static unsigned int find_max_abs_coeff(SVectorGMM& _v);
static gmm::size_type find_max_abs_coeff(SVectorGMM& _v);
static void add_row_simultaneously( int _row_i,
static void add_row_simultaneously( gmm::size_type _row_i,
double _coeff,
SVectorGMM& _row,
RMatrixGMM& _rmat,
......
......@@ -72,7 +72,7 @@ void FiniteElementProblem::eval_hessian ( const double* _x, SMatrixNP& _H)
fe_sets_[i]->accumulate_hessian(_x, triplets_);
// set data
_H.resize(n_unknowns(), n_unknowns());
_H.resize(static_cast<int>(n_unknowns()), static_cast<int>(n_unknowns()));
_H.setFromTriplets(triplets_.begin(), triplets_.end());
}
......
......@@ -187,8 +187,8 @@ public:
for(unsigned int j=0; j<triplets_.size(); ++j)
{
// add re-indexed Triplet
_triplets.push_back(Triplet( instances_.index(i,triplets_[j].row()),
instances_.index(i,triplets_[j].col()),
_triplets.push_back(Triplet( (int)instances_.index(i,triplets_[j].row()),
(int)instances_.index(i,triplets_[j].col()),
triplets_[j].value() ));
}
}
......
......@@ -43,12 +43,12 @@ int LinearConstraint::n_unknowns()
return coeffs_.innerSize();
}
void LinearConstraint::resize(const unsigned int _n)
void LinearConstraint::resize(const std::size_t _n)
{
if(coeffs_.innerSize() != (int)_n)
if(coeffs_.innerSize() != static_cast<std::ptrdiff_t>(_n))
{
// resize while maintaining all values in range
SVectorNC coeffs_new(_n);
SVectorNC coeffs_new(static_cast<int>(_n));
coeffs_new.setZero();
coeffs_new.reserve(coeffs_.nonZeros());
......
......@@ -55,7 +55,7 @@ public:
// resize coefficient vector = #unknowns
// maintain all values in range
void resize(const unsigned int _n);
void resize(const std::size_t _n);
// clear to zero constraint 0 =_type 0
void clear();
......
......@@ -14,9 +14,13 @@
#include <CoMISo/Config/CoMISoDefines.hh>
#include "NConstraintInterface.hh"
#include "LinearConstraint.hh"
#include <Base/Code/Quality.hh>
LOW_CODE_QUALITY_SECTION_BEGIN
#include <Eigen/StdVector>
#include <Eigen/Dense>
#include <Eigen/Sparse>
LOW_CODE_QUALITY_SECTION_END
//== FORWARDDECLARATIONS ======================================================
......
......@@ -8,7 +8,7 @@
namespace COMISO {
LinearProblem::LinearProblem (unsigned int _dimension)
LinearProblem::LinearProblem (std::size_t _dimension)
{
// resize and zero elements
coeffs_.resize(_dimension,0.0);
......@@ -19,9 +19,9 @@ LinearProblem::~LinearProblem()
{
}
int LinearProblem::n_unknowns()
int LinearProblem::n_unknowns()
{
return coeffs_.size();
return static_cast<int>(coeffs_.size());
}
void LinearProblem::initial_x(double* _x)
......
......@@ -43,7 +43,7 @@ class COMISODLLEXPORT LinearProblem : public NProblemInterface
public:
/// Default constructor
LinearProblem (unsigned int _dimension = 0);
LinearProblem (std::size_t _dimension = 0);
/// Destructor
virtual ~LinearProblem();
......
......@@ -18,8 +18,11 @@
#include "SuperSparseMatrixT.hh"
#include <Base/Code/Quality.hh>
LOW_CODE_QUALITY_SECTION_BEGIN
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#include <Eigen/Sparse>
LOW_CODE_QUALITY_SECTION_END
//== FORWARDDECLARATIONS ======================================================
......
......@@ -101,10 +101,10 @@ bool NProblemIPOPT::get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
Index& nnz_h_lag, IndexStyleEnum& index_style)
{
// number of variables
n = problem_->n_unknowns();
n = static_cast<Index>(problem_->n_unknowns());
// number of constraints
m = constraints_.size();
m = static_cast<Index>(constraints_.size());
// get non-zeros of hessian of lagrangian and jacobi of constraints
nnz_jac_g = 0;
......@@ -546,7 +546,7 @@ bool NProblemGmmIPOPT::get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
n = problem_->n_unknowns();
// number of constraints
m = constraints_.size();
m = static_cast<Index>(constraints_.size());
// get nonzero structure
std::vector<double> x(n);
......@@ -582,7 +582,7 @@ bool NProblemGmmIPOPT::get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
if( i >= (int)v_it.index())
{
h_lag_iRow_.push_back(i);
h_lag_jCol_.push_back(v_it.index());
h_lag_jCol_.push_back(static_cast<int>(v_it.index()));
++nnz_h_lag;
}
}
......
......@@ -15,14 +15,17 @@
//== INCLUDES =================================================================
#include <Base/Code/Quality.hh>
#include <iostream>
#include <cfloat>
LOW_CODE_QUALITY_SECTION_BEGIN
#include <Eigen/Eigen>
#if !(EIGEN_VERSION_AT_LEAST(3,1,0))
#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
#endif
#include <Eigen/Sparse>
LOW_CODE_QUALITY_SECTION_END
#include <CoMISo/Config/CoMISoDefines.hh>
......
......@@ -122,9 +122,9 @@ int NewtonSolver::solve(NProblemInterface* _problem, const SMatrixD& _A,
DEB_time_func_def;
// number of unknowns
const int n = _problem->n_unknowns();
size_t n = _problem->n_unknowns();
// number of constraints
const int m = _b.size();
size_t m = _b.size();
DEB_line(2, "optimize via Newton with " << n << " unknowns and " << m <<
" linear constraints");
......@@ -311,7 +311,7 @@ double NewtonSolver::backtracking_line_search(NProblemInterface* _problem,
double& _fx, const double _t_start)
{
DEB_enter_func;
int n = _x.size();
size_t n = _x.size();
// pre-compute objective
double fx = _problem->eval_f(_x.data());
......
......@@ -5,9 +5,12 @@
#include <CoMISo/Utils/StopWatch.hh>
#include <vector>
#include <CoMISo/NSolver/NProblemInterface.hh>
#include <Base/Code/Quality.hh>
LOW_CODE_QUALITY_SECTION_BEGIN
#include <Eigen/Eigen>
#include <Eigen/Core>
#include <Eigen/Sparse>
LOW_CODE_QUALITY_SECTION_END
//== NAMESPACES ===============================================================
......
......@@ -82,7 +82,7 @@ bool CholmodSolver::calc_system( const std::vector<int>& _colptr,
rowind_ = _rowind;
values_ = _values;
int n = colptr_.size()-1;
size_t n = colptr_.size()-1;
cholmod_sparse matA;
......@@ -167,7 +167,7 @@ bool CholmodSolver::calc_system_prepare_pattern( const std::vector<int>& _col
rowind_ = _rowind;
values_ = _values;
int n = colptr_.size()-1;
size_t n = colptr_.size() - 1;
// setup matrix matA
cholmod_sparse matA;
......@@ -282,7 +282,7 @@ bool CholmodSolver::update_system( const std::vector<int>& _colptr,
colptr_ = _colptr;
rowind_ = _rowind;
values_ = _values;
int n = colptr_.size()-1;
size_t n = colptr_.size() - 1;
cholmod_sparse matA;
......@@ -329,7 +329,7 @@ bool CholmodSolver::update_downdate_factor( const std::vector<int>& _colptr,
rowind_ = _rowind;
values_ = _values;
int n = colptr_.size()-1;
size_t n = colptr_.size() - 1;
cholmod_sparse matA;
......@@ -387,7 +387,7 @@ bool CholmodSolver::update_downdate_factor( const std::vector<int>& _colptr,
bool CholmodSolver::solve( double * _x, double * _b)
{
const unsigned int n = mp_L->n;
const size_t n = mp_L->n;
cholmod_dense *x, b;
......
......@@ -303,13 +303,13 @@ public:
private:
template<class RowT, class MatrixT>
void add_row( int _row_i,
double _coeff,
RowT _row,
MatrixT& _mat );
void add_row( gmm::size_type _row_i,
double _coeff,
RowT _row,
MatrixT& _mat );
template<class RowT, class RMatrixT, class CMatrixT>
void add_row_simultaneously( int _row_i,
void add_row_simultaneously( gmm::size_type _row_i,
double _coeff,
RowT _row,
RMatrixT& _rmat,
......
......@@ -217,10 +217,9 @@ solve(
if( _show_miso_settings)
miso_.show_options_dialog();
int nrows = gmm::mat_nrows(_A);
int ncols = gmm::mat_ncols(_A);
int ncons = gmm::mat_nrows(_constraints);
gmm::size_type nrows = gmm::mat_nrows(_A);
gmm::size_type ncols = gmm::mat_ncols(_A);
gmm::size_type ncons = gmm::mat_nrows(_constraints);
DEB_out_if( _show_timings, 1, "Initital dimension: " << nrows << " x " << ncols
<< ", number of constraints: " << ncons
......@@ -290,8 +289,8 @@ resolve(
// COMISO_GMM::factored_to_quadratic(_B, A, rhs);
//TODO only compute rhs, not complete A for efficiency
unsigned int m = gmm::mat_nrows(_B);
unsigned int n = gmm::mat_ncols(_B);
gmm::size_type m = gmm::mat_nrows(_B);
gmm::size_type n = gmm::mat_ncols(_B);
typedef typename gmm::linalg_traits<RMatrixT>::const_sub_row_type CRowT;
typedef typename gmm::linalg_traits<RMatrixT>::sub_row_type RowT;
......@@ -349,8 +348,8 @@ resolve(
gmm::mult(rhs_update_table_.D_, *_constraint_rhs, rhs_update_table_.cur_constraint_rhs_);
// update rhs of stored constraints
unsigned int nc = gmm::mat_ncols(rhs_update_table_.constraints_p_);
for(unsigned int i=0; i<rhs_update_table_.cur_constraint_rhs_.size(); ++i)
gmm::size_type nc = gmm::mat_ncols(rhs_update_table_.constraints_p_);
for(gmm::size_type i=0; i<rhs_update_table_.cur_constraint_rhs_.size(); ++i)
rhs_update_table_.constraints_p_(i,nc-1) = -rhs_update_table_.cur_constraint_rhs_[i];
}
if(_rhs)
......@@ -397,14 +396,14 @@ make_constraints_independent(
{
DEB_enter_func;
// setup linear transformation for rhs, start with identity
unsigned int nr = gmm::mat_nrows(_constraints);
gmm::size_type nr = gmm::mat_nrows(_constraints);
gmm::resize(rhs_update_table_.D_, nr, nr);
gmm::clear(rhs_update_table_.D_);
for(unsigned int i=0; i<nr; ++i) rhs_update_table_.D_(i,i) = 1.0;
for(gmm::size_type i=0; i<nr; ++i) rhs_update_table_.D_(i,i) = 1.0;
// Base::StopWatch sw;
// number of variables
int n_vars = gmm::mat_ncols(_constraints);
const gmm::size_type n_vars = gmm::mat_ncols(_constraints);
// TODO Check: HZ added 14.08.09
_c_elim.clear();
......@@ -453,7 +452,7 @@ make_constraints_independent(
for(; row_it != row_end; ++row_it)
{
int cur_j = row_it.index();
int cur_j = static_cast<int>(row_it.index());
// do not use the constant part
if( cur_j != n_vars - 1 )
{
......@@ -462,7 +461,7 @@ make_constraints_independent(
{
if( fabs(*row_it) > max_elim_val)
{
elim_j = cur_j;
elim_j = (int)cur_j;
max_elim_val = fabs(*row_it);
}
//break;
......@@ -473,19 +472,18 @@ make_constraints_independent(
// gcd
// if the coefficient of an integer variable is not an integer, then
// the variable most problably will not be (expect if all coeffs are the same, e.g. 0.5)
if( (double(int(cur_row_val))- cur_row_val) != 0.0)
{
// std::cerr << __FUNCTION__ << " Warning: coefficient of integer variable is NOT integer: "
// << cur_row_val << std::endl;
gcd_update_valid = false;
}
if ((double(int(cur_row_val))- cur_row_val) != 0.0)
{
DEB_warning(2, "coefficient of integer variable is NOT integer : " << cur_row_val)
gcd_update_valid = false;
}
v_gcd[n_ints] = cur_row_val;
v_gcd[n_ints] = static_cast<int>(cur_row_val);
++n_ints;
// store integer closest to 1, must be greater than epsilon_
if( fabs(cur_row_val-1.0) < elim_val && cur_row_val > epsilon_)
{
{
elim_int_j = cur_j;
elim_val = fabs(cur_row_val-1.0);
}
......@@ -558,7 +556,7 @@ make_constraints_independent(
// sw.start();
double val = -(*c_it)/elim_val_cur;
add_row_simultaneously( c_it.index(), val, gmm::mat_row(_constraints, i), _constraints, constraints_c);
add_row_simultaneously((int)c_it.index(), val, gmm::mat_row(_constraints, i), _constraints, constraints_c);
// make sure the eliminated entry is 0 on all other rows and not 1e-17
_constraints( c_it.index(), elim_j) = 0;
constraints_c(c_it.index(), elim_j) = 0;
......@@ -586,14 +584,17 @@ make_constraints_independent_reordering(
{
DEB_enter_func;
// setup linear transformation for rhs, start with identity
unsigned int nr = gmm::mat_nrows(_constraints);
gmm::size_type nr = gmm::mat_nrows(_constraints);
gmm::resize(rhs_update_table_.D_, nr, nr);
gmm::clear(rhs_update_table_.D_);
for(unsigned int i=0; i<nr; ++i) rhs_update_table_.D_(i,i) = 1.0;
for(gmm::size_type i=0; i<nr; ++i)
rhs_update_table_.D_(i,i) = 1.0;
// Base::StopWatch sw;
// number of variables
int n_vars = gmm::mat_ncols(_constraints);
// AF: Why was n_vars signed? Can it be zero? Later we subtract 1
const gmm::size_type n_vars = gmm::mat_ncols(_constraints);
// TODO Check: HZ added 14.08.09
_c_elim.clear();
......@@ -601,7 +602,7 @@ make_constraints_independent_reordering(
// build round map
std::vector<bool> roundmap( n_vars, false);
for(unsigned int i=0; i<_idx_to_round.size(); ++i)
for(size_t i=0; i<_idx_to_round.size(); ++i)
roundmap[_idx_to_round[i]] = true;
// copy constraints into column matrix (for faster update via iterators)
......@@ -613,17 +614,19 @@ make_constraints_independent_reordering(
// init priority queue
MutablePriorityQueueT<unsigned int, unsigned int> queue;
queue.clear( nr );
queue.clear( static_cast<int>(nr) );
for(unsigned int i=0; i<nr; ++i)
{
int cur_nnz = gmm::nnz( gmm::mat_row(_constraints,i));
if( _constraints(i,n_vars-1) != 0.0) --cur_nnz;
gmm::size_type cur_nnz = gmm::nnz( gmm::mat_row(_constraints,i));
if( _constraints(i,n_vars-1) != 0.0)
--cur_nnz;
queue.update(i, cur_nnz);
queue.update(i, static_cast<int>(cur_nnz));
}
std::vector<bool> row_visited(nr, false);
std::vector<unsigned int> row_ordering; row_ordering.reserve(nr);
std::vector<gmm::size_type> row_ordering;
row_ordering.reserve(nr);
// for all conditions
......@@ -663,16 +666,16 @@ make_constraints_independent_reordering(
for(; row_it != row_end; ++row_it)
{
int cur_j = row_it.index();
int cur_j = static_cast<int>(row_it.index());
// do not use the constant part
if( cur_j != n_vars - 1 )
if (cur_j != n_vars - 1)
{
// found real valued var? -> finished (UPDATE: no not any more, find biggest real value to avoid x/1e-13)
if( !roundmap[ cur_j ])
if (!roundmap[ cur_j ])
{
if( fabs(*row_it) > max_elim_val)
if (fabs(*row_it) > max_elim_val)
{
elim_j = cur_j;
elim_j = (int)cur_j;
max_elim_val = fabs(*row_it);
}
//break;
......@@ -683,20 +686,19 @@ make_constraints_independent_reordering(
// gcd
// if the coefficient of an integer variable is not an integer, then
// the variable most problably will not be (expect if all coeffs are the same, e.g. 0.5)
if( (double(int(cur_row_val))- cur_row_val) != 0.0)