Commit 6b22e2ce authored by Max Lyon's avatar Max Lyon
Browse files

more int/size_t fixes

parent f3c59a17
......@@ -63,9 +63,9 @@ public:
COMISO::StopWatch sw; sw.start();
// number of unknowns
int n = _quadratic_problem->n_unknowns();
auto n = _quadratic_problem->n_unknowns();
// number of constraints
int m = _b.size();
auto 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();
auto n = _x.size();
// pre-compute objective
double fx = _quadratic_problem->eval_f(_x.data()) + _nonlinear_problem->eval_f(_x.data());
......
......@@ -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,
......
......@@ -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() ));
}
}
......
......@@ -122,9 +122,9 @@ int NewtonSolver::solve(NProblemInterface* _problem, const SMatrixD& _A,
DEB_time_func_def;
// number of unknowns
int n = _problem->n_unknowns();
size_t n = _problem->n_unknowns();
// number of constraints
int m = _b.size();
size_t m = _b.size();
DEB_line(2, "optimize via Newton with " << n << " unknowns and " << m << " linear constraints");
......@@ -280,7 +280,7 @@ 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());
......
......@@ -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;
......
......@@ -217,7 +217,6 @@ solve(
if( _show_miso_settings)
miso_.show_options_dialog();
gmm::size_type nrows = gmm::mat_nrows(_A);
gmm::size_type ncols = gmm::mat_ncols(_A);
gmm::size_type ncons = gmm::mat_nrows(_constraints);
......@@ -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;
......@@ -473,10 +472,9 @@ 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)
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;
DEB_warning(2, "coefficient of integer variable is NOT integer : " << cur_row_val)
gcd_update_valid = false;
}
......@@ -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;
......@@ -589,7 +587,9 @@ make_constraints_independent_reordering(
gmm::size_type nr = gmm::mat_nrows(_constraints);
gmm::resize(rhs_update_table_.D_, nr, nr);
gmm::clear(rhs_update_table_.D_);
for(gmm::size_type 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
......@@ -602,7 +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)
......@@ -618,13 +618,15 @@ make_constraints_independent_reordering(
for(unsigned int i=0; i<nr; ++i)
{
gmm::size_type cur_nnz = gmm::nnz( gmm::mat_row(_constraints,i));
if( _constraints(i,n_vars-1) != 0.0) --cur_nnz;
if( _constraints(i,n_vars-1) != 0.0)
--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
......@@ -632,7 +634,7 @@ make_constraints_independent_reordering(
while(!queue.empty())
{
// get next row
unsigned int i = queue.get_next();
auto i = queue.get_next();
row_ordering.push_back(i);
row_visited[i] = true;
......@@ -666,14 +668,14 @@ make_constraints_independent_reordering(
{
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;
......@@ -684,10 +686,9 @@ 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)
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;
DEB_warning(2, "coefficient of integer variable is NOT integer : " << cur_row_val);
gcd_update_valid = false;
}
......@@ -697,7 +698,7 @@ make_constraints_independent_reordering(
// 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_int_j = (int)cur_j;
elim_val = fabs(cur_row_val-1.0);
}
}
......@@ -735,7 +736,7 @@ make_constraints_independent_reordering(
if( do_gcd_ && gcd_update_valid)
{
// perform gcd update
bool gcd_ok = update_constraint_gcd( _constraints, i, elim_j, v_gcd, n_ints);
bool gcd_ok = update_constraint_gcd( _constraints, (int)i, elim_j, v_gcd, n_ints);
DEB_warning_if( !gcd_ok && (noisy_ > 0), 1, " GCD update failed! "
<< DEB_os_str(gmm::mat_const_row(_constraints, i)) )
}
......@@ -756,7 +757,7 @@ make_constraints_independent_reordering(
// is this condition dependent?
if( elim_j != -1 )
if (elim_j != -1)
{
// get elim variable value
double elim_val_cur = _constraints(i, elim_j);
......@@ -768,20 +769,22 @@ make_constraints_independent_reordering(
typename gmm::linalg_traits<CVector>::const_iterator c_it = gmm::vect_const_begin(col);
typename gmm::linalg_traits<CVector>::const_iterator c_end = gmm::vect_const_end(col);
for(; c_it != c_end; ++c_it)
// if( c_it.index() > i)
if( !row_visited[c_it.index()])
for (; c_it != c_end; ++c_it)
{
// sw.start();
double val = -(*c_it)/elim_val_cur;
add_row_simultaneously( c_it.index(), val, gmm::mat_row(_constraints, i), _constraints, constraints_c);
// if( c_it.index() > i)
if (!row_visited[c_it.index()])
{
// sw.start();
double val = -(*c_it) / elim_val_cur;
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_it.index(), elim_j) = 0;
constraints_c(c_it.index(), elim_j) = 0;
gmm::size_type cur_idx = c_it.index();
gmm::size_type cur_nnz = gmm::nnz( gmm::mat_row(_constraints,cur_idx));
if( _constraints(cur_idx,n_vars-1) != 0.0) --cur_nnz;
if( _constraints(cur_idx,n_vars-1) != 0.0)
--cur_nnz;
queue.update(static_cast<int>(cur_idx),
static_cast<int>(cur_nnz));
......@@ -792,6 +795,7 @@ make_constraints_independent_reordering(
}
}
}
}
// // check result
// for(unsigned int i=0; i<row_visited.size(); ++i)
// if( !row_visited[i])
......@@ -862,7 +866,7 @@ update_constraint_gcd( RMatrixT& _constraints,
gmm::size_type cur_j = row_it.index();
_constraints(_row_i, cur_j) = (*row_it)/i_gcd;
}
gmm::size_type elim_coeff = static_cast<gmm::size_type>(abs(_constraints(_row_i, _elim_j)));
gmm::size_type elim_coeff = static_cast<gmm::size_type>(std::abs(_constraints(_row_i, _elim_j)));
DEB_error_if( elim_coeff != 1, "elimination coefficient " << elim_coeff
<< " will (most probably) NOT lead to an integer solution!")
return true;
......@@ -1261,7 +1265,7 @@ restore_eliminated_vars( RMatrixT& _constraints,
}
// reverse iterate
for(int i= static_cast<int>(_c_elim.size())-1; i>=0; --i) // AF: Can this be negative?
for(int i = static_cast<int>(_c_elim.size())-1; i>=0; --i) // AF: Can this be negative?
{
int cur_var = _c_elim[i];
......
......@@ -289,8 +289,8 @@ void get_ccs_symmetric_data( const MatrixT& _mat,
std::vector<INTT>& _rowind,
std::vector<INTT>& _colptr )
{
unsigned int m = gmm::mat_nrows( _mat );
unsigned int n = gmm::mat_ncols( _mat );
gmm::size_type m = gmm::mat_nrows( _mat );
gmm::size_type n = gmm::mat_ncols( _mat );
gmm::csc_matrix<REALT> csc_mat( m,n );
gmm::copy( _mat, csc_mat );
......
......@@ -77,7 +77,7 @@ bool SparseQRSolver::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;
......@@ -162,7 +162,7 @@ bool SparseQRSolver::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;
......@@ -199,7 +199,7 @@ bool SparseQRSolver::update_system( const std::vector<Int>& _colptr,
bool SparseQRSolver::solve( double * _x, double * _b)
{
const unsigned int n = colptr_.size() - 1;
const size_t n = colptr_.size() - 1;
cholmod_dense *x, *Qtb, b;
......
......@@ -78,7 +78,7 @@ bool UMFPACKSolver::calc_system( const std::vector<int>& _colptr,
rowind_ = _rowind;
values_ = _values;
int n = colptr_.size()-1;
int n = (int)colptr_.size() - 1;
// clean up
if( symbolic_ )
......
......@@ -67,7 +67,7 @@ public:
~MutablePriorityQueueT() {}
// reset timestamps
void clear(int _n)
void clear(size_t _n)
{
timestamp_.clear();
timestamp_.resize(_n,0);
......
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