cgal/QP_solver/include/CGAL/QP_solver/QP_solution_impl.h

735 lines
26 KiB
C++

// Copyright (c) 1997-2007 ETH Zurich (Switzerland).
// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
// 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.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
//
//
// Author(s) : Bernd Gaertner <gaertner@inf.ethz.ch>
#ifndef CGAL_QP_SOLUTION_IMPL_H
#define CGAL_QP_SOLUTION_IMPL_H
#include<iterator>
namespace CGAL {
// checks whether the solution actually solves program p
// this performs exactly the checks described in the doc
// of the class Quadratic_program_solution
// -----------------------------------------------------
template <typename ET>
template <class Program, typename Is_linear, typename Is_nonnegative>
bool Quadratic_program_solution<ET>::solves_program
(const Program& p,
Is_linear is_linear, Is_nonnegative is_nonnegative)
{
CGAL_qpe_assertion_msg(!is_void(), "Solution not initialized");
// first check whether the dimensions agree
int n = static_cast<int>(variable_numerators_end() - variable_numerators_begin());
if (n != p.get_n())
return error ("wrong number of variables");
int m = static_cast<int>(solver()->lambda_end() - solver()->lambda_begin());
if (m != p.get_m())
return error("wrong number of constraints");
// now distinguish between the three possible cases
switch (status()) {
case QP_OPTIMAL: {
std::vector<ET> ax_minus_b (m, et0); // d(Ax-b)
std::vector<ET> two_Dx (n, et0); // d(2Dx)
return
// the following fills ax_minus_b...
is_feasible (p, ax_minus_b, is_nonnegative) && // feasible?
// the following fills two_Dx...
is_value_correct (p, two_Dx, is_linear) && // obj. value?
is_optimal_1 (p) && // condition 1?
// ...and the following uses ax_minus_b
is_optimal_2 (p, ax_minus_b) && // condition 2?
// ...and the following uses two_Dx
is_optimal_3 (p, two_Dx, is_linear, is_nonnegative); // condition 3?
}
case QP_INFEASIBLE: {
std::vector<ET> lambda_a (n, et0); // lambda^TA
return
is_infeasible_1 (p) && // condition 1?
// the following fills lambda_a...
is_infeasible_2 (p, lambda_a, is_nonnegative) && // condition 2?
// ...and the following uses lambda_a
is_infeasible_3 (p, lambda_a, is_nonnegative); // condition 3?
}
case QP_UNBOUNDED: {
std::vector<ET> ax_minus_b (m, et0);
return
is_feasible (p, ax_minus_b, is_nonnegative) && // feasible?
is_unbounded_1 (p) && // condition 1?
is_unbounded_2 (p, is_nonnegative) && // condition 2?
is_unbounded_3 (p, is_linear); // condition 3?
}
default:
return error ("solution in undefined state");
}
}
// tests whether Ax ~ b is satisfied and computes d(Ax-b);
// precondition: ax_minus_b has length m and is zero
// ------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::are_constraints_feasible
(const Program& p,
typename std::vector<ET>& ax_minus_b)
{
typedef typename Program::B_iterator B_column_iterator;
typedef typename Program::R_iterator R_column_iterator;
// fill ax_minus_b (length m)
int m = p.get_m();
B_column_iterator b = p.get_b();
add_Az (p, variable_numerators_begin(), ax_minus_b); // d(Ax)
ET d = variables_common_denominator();
for (int i=0; i<m; ++i, ++b)
ax_minus_b[i] -= ET (*b) * d; // d(Ax-b)
// now validate constraints
if (d <= et0)
return error ("common variable denominator is negative");
R_column_iterator r = p.get_r();
for (int i=0; i<m; ++i, ++r)
switch (*r) {
case SMALLER: // <=
if (ax_minus_b[i] > et0) return error("inequality (<=) violated");
break;
case EQUAL: // ==
if (ax_minus_b[i] != et0) return error("inequality (==) violated");
break;
case LARGER: // >=
if (ax_minus_b[i] < et0) return error("inequality (>=) violated");
break;
}
return true;
}
// tests whether Ax ~ b, x >= 0 is satisfied and computes d(Ax-b)
// precondition: ax_minus_b has length m and is zero
// --------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_feasible
(const Program& p,
typename std::vector<ET>& ax_minus_b,
Tag_true /*is_nonnegative*/)
{
// test Ax ~ b
if (!are_constraints_feasible (p, ax_minus_b)) return false;
// test x >= 0
if (variables_common_denominator() <= et0)
return error ("common variable denominator is negative");
for (Variable_numerator_iterator v = variable_numerators_begin();
v < variable_numerators_end(); ++v)
if (*v < et0) return error("bound (>= 0) violated");
return true;
}
// tests whether Ax ~ b, l <= x <= u is satisfied and computes d(Ax-b)
// precondition: ax_minus_b has length m and is zero
// -------------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_feasible
(const Program& p,
typename std::vector<ET>& ax_minus_b,
Tag_false /*is_nonnegative*/)
{
// test Ax ~ b
if (!are_constraints_feasible (p, ax_minus_b)) return false; // (*)
// test l <= x <= u
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
typedef typename Program::FL_iterator FL_column_iterator;
typedef typename Program::L_iterator L_column_iterator;
typedef typename Program::FU_iterator FU_column_iterator;
typedef typename Program::U_iterator U_column_iterator;
FL_column_iterator fl = p.get_fl();
FU_column_iterator fu = p.get_fu();
L_column_iterator l = p.get_l();
U_column_iterator u = p.get_u();
for (Variable_numerator_iterator v = variable_numerators_begin();
v < variable_numerators_end(); ++v, ++fl, ++l, ++fu, ++u) {
if (*fl && (*v < ET(*l) * d))
return error("bound (>=l) violated");
if (*fu && (*v > ET(*u) * d))
return error("bound (<=u) violated");
}
return true;
}
// checks whether constraint type <= (>=) implies lambda >= (<=) 0
// ---------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_1
(const Program& p)
{
if (variables_common_denominator() <= et0)
return error ("wrong sign of optimality certificate");
typedef typename Program::R_iterator R_column_iterator;
int m = p.get_m();
R_column_iterator r = p.get_r();
Optimality_certificate_numerator_iterator opt =
optimality_certificate_numerators_begin();
for (int i=0; i<m; ++i, ++r, ++opt) {
if (*r == SMALLER && *opt < et0)
return error("constraint (<=) with lambda < 0");
if (*r == LARGER && *opt > et0)
return error("constraint (>=) with lambda > 0");
}
return true;
}
// checks whether constraint type <= (>=) implies lambda >= (<=) 0
// ---------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_infeasible_1
(const Program& p)
{
int m = p.get_m();
typedef typename Program::R_iterator R_column_iterator;
R_column_iterator r = p.get_r();
Infeasibility_certificate_iterator inf = infeasibility_certificate_begin();
for (int i=0; i<m; ++i, ++r, ++inf) {
if (*r == SMALLER && *inf < et0)
return error("constraint (<=) with lambda < 0");
if (*r == LARGER && *inf > et0)
return error("constraint (>=) with lambda > 0");
}
return true;
}
// checks whether lambda and Ax-b are complementary
// ------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_2
(const Program& p,
const typename std::vector<ET>& ax_minus_b)
{
int m = p.get_m();
Optimality_certificate_numerator_iterator opt =
optimality_certificate_numerators_begin();
for (int i=0; i<m; ++i, ++opt)
if (*opt != et0 && ax_minus_b[i] != et0)
return error("lambda and Ax-b are not complementary");
return true;
}
// checks whether (c^T + lambda^TA)_j >= (==) 0 if x_j = (>) 0
// -----------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_3
(const Program& p, std::vector<ET>& q,
Tag_true /*is_linear*/, Tag_true /*is_nonnegative*/)
{
int n = p.get_n(); // q = 0
add_c (p, q); // d c^T
add_zA (p, optimality_certificate_numerators_begin(), q); // d lambda^T A
Variable_numerator_iterator v = variable_numerators_begin();
for (int j=0; j<n; ++j, ++v) {
if (q[j] < et0)
return error("some (c^T + lambda^TA)_j is negative");
if (*v > et0 && q[j] > et0)
return error("(c^T + lambda^TA) and x are not complementary");
}
return true;
}
// checks whether (c^T + lambda^TA + 2x^TD)_j >= (==) 0 if x_j = (>) 0
// -------------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_3
(const Program& p, std::vector<ET>& q,
Tag_false /*is_linear*/, Tag_true /*is_nonnegative*/)
{
int n = p.get_n(); // q = 2Dx
add_c (p, q); // d * c^T
add_zA (p, optimality_certificate_numerators_begin(), q); // d * lambda^T A
Variable_numerator_iterator v = variable_numerators_begin();
for (int j=0; j<n; ++j, ++v) {
if (q[j] < et0)
return error("some (c^T + lambda^TA + 2Dx)_j is negative");
if (*v > et0 && q[j] > et0)
return error("(c^T + lambda^TA + 2Dx) and x are not complementary");
}
return true;
}
// checks whether (c^T + lambda^TA )_j >= (==, <=) 0 if
// x_j = l_j < u_j (l_j < x_j < u_j, l_j < u_j = x_j)
// ---------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_3
(const Program& p, std::vector<ET>& q,
Tag_true /*is_linear*/, Tag_false /*is_nonnegative*/)
{
int n = p.get_n(); // q = 0
add_c (p, q); // d * c^T
add_zA (p, optimality_certificate_numerators_begin(), q); // d * lambda^T A
typedef typename Program::FL_iterator FL_column_iterator;
typedef typename Program::L_iterator L_column_iterator;
typedef typename Program::FU_iterator FU_column_iterator;
typedef typename Program::U_iterator U_column_iterator;
FL_column_iterator fl = p.get_fl();
FU_column_iterator fu = p.get_fu();
L_column_iterator l = p.get_l();
U_column_iterator u = p.get_u();
Variable_numerator_iterator v = variable_numerators_begin();
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
for (int j=0; j<n; ++j, ++v, ++fl, ++l, ++fu, ++u) {
if (*fl && *v == ET(*l) * d && (!*fu || *l < *u) && q[j] < et0)
return error("x_j = l_j < u_j but (c^T + lambda^TA )_j < 0");
if ( (!*fl || *v > ET(*l) * d) && (!*fu || *v < ET(*u) * d) && q[j] != et0)
return error("l_j < x_j < u_j but (c^T + lambda^TA )_j != 0");
if (*fu && *v == ET(*u) * d && (!*fl || *l < *u) && q[j] > et0)
return error("x_j = u_j > l_j but (c^T + lambda^TA )_j > 0");
}
return true;
}
// checks whether (c^T + lambda^TA +2x^*D)_j >= (==, <=) 0 if
// x_j = l_j < u_j (l_j < x_j < u_j, l_j < u_j = x_j)
// ----------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_optimal_3
(const Program& p, std::vector<ET>& q,
Tag_false /*is_linear*/, Tag_false /*is_nonnegative*/)
{
int n = p.get_n(); // q = d * 2Dx
add_c (p, q); // d * c^T
add_zA (p, optimality_certificate_numerators_begin(), q); // d * lambda^T A
typedef typename Program::FL_iterator FL_column_iterator;
typedef typename Program::L_iterator L_column_iterator;
typedef typename Program::FU_iterator FU_column_iterator;
typedef typename Program::U_iterator U_column_iterator;
FL_column_iterator fl = p.get_fl();
FU_column_iterator fu = p.get_fu();
L_column_iterator l = p.get_l();
U_column_iterator u = p.get_u();
Variable_numerator_iterator v = variable_numerators_begin();
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
for (int j=0; j<n; ++j, ++v, ++fl, ++l, ++fu, ++u) {
if (*fl && *v == ET(*l) * d && (!*fu || *l < *u) && q[j] < et0)
return error("x_j = l_j < u_j but (c^T + lambda^TA + 2Dx)_j < 0");
if ( (!*fl || *v > ET(*l) * d) && (!*fu || *v < ET(*u) * d) && q[j] != et0)
return error("l_j < x_j < u_j but (c^T + lambda^TA + 2Dx)_j != 0");
if (*fu && *v == ET(*u) * d && (!*fl || *l < *u) && q[j] > et0)
return error("x_j = u_j > l_j but (c^T + lambda^TA + 2Dx)_j > 0");
}
return true;
}
// checks whether objective function value is c^T x + c_0, but
// leaves the vector q alone
// --------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_value_correct
(const Program& p, std::vector<ET>& /*q*/, Tag_true /*is_linear*/)
{
// check objective value c^T x + c_0
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
Variable_numerator_iterator v = variable_numerators_begin();
ET obj = d * ET(p.get_c0()); // d * c_0
typedef typename Program::C_iterator C_column_iterator;
C_column_iterator c = p.get_c();
int n = p.get_n();
for (int j=0; j<n; ++j, ++v, ++c)
obj += ET(*c) * *v; // d * c^T x
if (Quotient<ET>(obj, d) != objective_value())
return error ("optimal objective value c^T x + c_0 incorrect");
return true;
}
// checks whether objective function value is x^TDx + c^T x + c_0
// and fills the vector q with 2Dx
// --------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_value_correct
(const Program& p, std::vector<ET>& q, Tag_false /*is_linear*/)
{
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
Variable_numerator_iterator v = variable_numerators_begin();
int n = p.get_n();
add_two_Dz (p, v, q); // 2d * Dx
ET et2(2);
ET obj = et2 * d * d * ET(p.get_c0()); // 2d^2 * c_0
typedef typename Program::C_iterator C_column_iterator;
C_column_iterator c = p.get_c();
for (int j=0; j<n; ++j, ++v, ++c) {
obj += et2 * d * ET(*c) * *v; // 2d^2 * c^T x
obj += q[j] * *v; // 2d^2 * x^TDx
}
if (Quotient<ET>(obj, et2*d*d) != objective_value())
return error ("optimal objective value x^TDx + c^T x + c_0 incorrect");
return true;
}
// checks whether lambda^TA >= 0
// -----------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_infeasible_2
(const Program& p, typename std::vector<ET>& lambda_a,
Tag_true /*is_nonnegative*/)
{
// fill lambda_a
add_zA (p, infeasibility_certificate_begin(), lambda_a);
int n = p.get_n();
for (int j=0; j<n; ++j)
if (lambda_a[j] < et0)
return error ("(lambda^TA)_j < 0 for some j");
return true;
}
// checks whether lambda^TA >= 0 (<= 0) if u_j = infty (l_j = -infty)
// ------------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_infeasible_2
(const Program& p, typename std::vector<ET>& lambda_a,
Tag_false /*is_nonnegative*/)
{
// fill lambda_a
add_zA (p, infeasibility_certificate_begin(), lambda_a);
int n = p.get_n();
typedef typename Program::FL_iterator FL_column_iterator;
typedef typename Program::FU_iterator FU_column_iterator;
FL_column_iterator fl = p.get_fl();
FU_column_iterator fu = p.get_fu();
for (int j=0; j<n; ++j, ++fl, ++fu) {
if (!*fu && lambda_a[j] < et0)
return error ("u_j = infty but (lambda^TA)_j < 0");
if (!*fl && lambda_a[j] > et0)
return error ("l_j = -infty but (lambda^TA)_j > 0");
}
return true;
}
// checks whether lambda^T b < 0
// -----------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_infeasible_3
(const Program& p, const typename std::vector<ET>& /*lambda_a*/,
Tag_true /*is_nonnegative*/)
{
ET lambda_b(0);
int m = p.get_m();
typedef typename Program::B_iterator B_column_iterator;
B_column_iterator b = p.get_b();
Infeasibility_certificate_iterator inf = infeasibility_certificate_begin();
for (int i=0; i<m; ++i, ++b, ++inf)
lambda_b += ET(*b) * *inf;
if (lambda_b >= et0)
return error ("lambda_b >= 0");
return true;
}
// checks whether lambda^T b < \sum_{j: lambda^TA_j < 0}lambda^TA_j u_j +
// \sum_{j: lambda^TA_j > 0}lambda^TA_j l_j
// ----------------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_infeasible_3
(const Program& p, const typename std::vector<ET>& lambda_a,
Tag_false /*is_nonnegative*/)
{
ET lambda_b(0);
int m = p.get_m();
typedef typename Program::B_iterator B_column_iterator;
B_column_iterator b = p.get_b();
Infeasibility_certificate_iterator inf = infeasibility_certificate_begin();
for (int i=0; i<m; ++i, ++b, ++inf)
lambda_b += ET(*b) * *inf;
ET sum(0);
int n = p.get_n();
typedef typename Program::L_iterator L_column_iterator;
typedef typename Program::U_iterator U_column_iterator;
L_column_iterator l = p.get_l();
U_column_iterator u = p.get_u();
for (int j=0; j<n; ++j, ++l, ++u) {
if (lambda_a[j] < et0) sum += lambda_a[j] * ET(*u);
if (lambda_a[j] > et0) sum += lambda_a[j] * ET(*l);
}
// now compare
if (lambda_b >= sum)
return error("lambda^T b >= sum");
return true;
}
// checks whether (Aw)_i <= (>=, ==) 0 if i-th constraint is <= (>=, ==)
// ---------------------------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_unbounded_1
(const Program& p)
{
int m = p.get_m();
std::vector<ET> aw (m, et0);
add_Az (p, unboundedness_certificate_begin(), aw);
typedef typename Program::R_iterator R_column_iterator;
R_column_iterator r = p.get_r();
for (int i=0; i<m; ++i, ++r)
switch (*r) {
case SMALLER:
if (aw[i] > et0)
return error ("i-th constraint <= but (Aw)_i > 0");
break;
case EQUAL:
if (aw[i] != et0)
return error ("i-th constraint == but (Aw)_i != 0");
break;
case LARGER:
if (aw[i] < et0)
return error ("i-th constraint >= but (Aw)_i < 0");
break;
}
return true;
}
// checks whether w >= 0
// ---------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_unbounded_2
(const Program& p, Tag_true /*is_nonnegative*/)
{
int n = p.get_n();
Unboundedness_certificate_iterator unb = unboundedness_certificate_begin();
for (int j=0; j<n; ++j, ++unb)
if (*unb < et0)
return error ("some w_j < 0");
return true;
}
// checks whether w_j >= (<=) 0 if l_j (u_j) is finite
// ---------------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_unbounded_2
(const Program& p, Tag_false /*is_nonnegative*/)
{
int n = p.get_n();
typedef typename Program::FL_iterator FL_column_iterator;
typedef typename Program::FU_iterator FU_column_iterator;
FL_column_iterator fl = p.get_fl();
FU_column_iterator fu = p.get_fu();
Unboundedness_certificate_iterator unb = unboundedness_certificate_begin();
for (int j=0; j<n; ++j, ++unb, ++fl, ++fu) {
if (*fl && *unb < et0)
return error ("some l_j is finite but w_j < 0");
if (*fu && *unb > et0)
return error ("some u_j is finite but w_j > 0");
}
return true;
}
// checks whether c^Tw < 0
// -----------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_unbounded_3
(const Program& p, Tag_true /*is_linear*/)
{
ET cw(0);
int n = p.get_n();
typedef typename Program::C_iterator C_column_iterator;
C_column_iterator c = p.get_c();
Unboundedness_certificate_iterator unb = unboundedness_certificate_begin();
for (int j=0; j<n; ++j, ++c, ++unb)
cw += ET(*c) * *unb;
if (cw >= et0)
return error("c^Tw >= 0");
return true;
}
// checks whether w^TDw = 0 and (c^T + 2x^TD)w < 0
// -----------------------------------------------
template <typename ET>
template <typename Program>
bool Quadratic_program_solution<ET>::is_unbounded_3
(const Program& p, Tag_false /*is_linear*/)
{
int n = p.get_n();
std::vector<ET> two_dw (n, et0);
add_two_Dz(p, unboundedness_certificate_begin(), two_dw); // 2Dw
// check w^TDw = 0
Unboundedness_certificate_iterator unb = unboundedness_certificate_begin();
ET wdw(0);
for (int j=0; j<n; ++j, ++unb)
wdw += two_dw[j] * *unb;
if (wdw != et0)
return error("w^TDw != 0");
// check (c^T + 2x^TD)w = c^Tw + 2x^T Dw < 0
typedef typename Program::C_iterator C_column_iterator;
C_column_iterator c = p.get_c();
unb = unboundedness_certificate_begin();
Variable_numerator_iterator v = variable_numerators_begin();
ET d = variables_common_denominator();
if (d <= et0)
return error ("common variable denominator is negative");
ET res(0);
for (int j=0; j<n; ++j, ++c, ++unb, ++v)
res += ET(*c) * *unb * d + two_dw[j] * *v;
if (res >= 0)
return error("c^T + 2x^TD)w >= 0");
return true;
}
// computes the product of A with the n-vector given by z
// and adds the result to v; precondition: v has size m
// ------------------------------------------------------
template <typename ET>
template <typename Program, typename Z_iterator >
void Quadratic_program_solution<ET>::add_Az
(const Program& p, Z_iterator z, typename std::vector<ET>& v)
{
// iterator types
typedef typename Program::A_iterator
A_matrix_iterator;
typedef typename std::iterator_traits<A_matrix_iterator>::value_type
A_column_iterator;
// now compute the product
A_matrix_iterator a = p.get_a();
int n = p.get_n();
for (int j=0; j<n; ++j, ++a, ++z) {
if (!CGAL::is_zero(*z)) {
// add A_j * z_j to az
A_column_iterator a_j = *a;
for (int i=0; i<p.get_m(); ++i, ++a_j)
v[i] += *z * ET(*a_j);
}
}
}
// computes the product of 2D with the n-vector given by z
// and adds the result to v; precondition: v has size n
// -------------------------------------------------------
template <typename ET>
template <typename Program, typename Z_iterator >
void Quadratic_program_solution<ET>::add_two_Dz
(const Program& p, Z_iterator z, typename std::vector<ET>& v)
{
// we compute the contribution from the enries of D on or below
// the diagonal rowwise, and the remaining entries columnwise
typedef typename Program::D_iterator
D_matrix_iterator;
typedef typename std::iterator_traits<D_matrix_iterator>::value_type
D_row_iterator;
int n = p.get_n();
// make sure that we only handle the nonzero terms of z
std::vector<int> z_indices;
Z_iterator l = z;
for (int i=0; i<n; ++i, ++l)
if (*l != 0) z_indices.push_back(i);
// the rowwise contribution: on/below the diagonal
D_matrix_iterator d = p.get_d();
for (int i=0; i<n; ++i, ++d) {
// handle row i
D_row_iterator d_i = *d; // row i on/below diagonal
for (std::vector<int>::const_iterator
k = z_indices.begin(); k < z_indices.end(); ++k) {
int j = *k;
if (j <= i) v[i] += *(z+j) * ET (*(d_i+j));
}
}
// the columnwise contribution: above the diagonal
d = p.get_d();
for (std::vector<int>::const_iterator
k = z_indices.begin(); k < z_indices.end(); ++k) {
int j = *k;
// handle column j
D_row_iterator d_j = *(d+j); // column j above diagonal
for (int i=0; i<j; ++i, ++d_j)
v[i] += *(z+j) * ET (*d_j);
}
}
// computes the product of the m-vector given by z with the matrix
// A and adds the result to v; precondition: v has size n
// ----------------------------------------------------------------
template <typename ET>
template <typename Program, typename Z_iterator >
void Quadratic_program_solution<ET>::add_zA
(const Program& p, Z_iterator z, typename std::vector<ET>& v)
{
typedef typename Program::A_iterator
A_matrix_iterator;
typedef typename std::iterator_traits<A_matrix_iterator>::value_type
A_column_iterator;
A_matrix_iterator a = p.get_a();
int n = p.get_n();
int m = p.get_m();
// make sure that we only handle the nonzero terms of z
std::vector<int> z_indices; // indices of nonzero entries
Z_iterator l = z;
for (int i=0; i<m; ++i, ++l)
if (*l != 0) z_indices.push_back(i);
// now compute the product columnwise
for (int j=0; j<n; ++j, ++a) {
// add z^T * A_j to v[j]
A_column_iterator a_j = *a;
for (std::vector<int>::const_iterator
k = z_indices.begin(); k < z_indices.end(); ++k)
v[j] += *(z+*k) * ET(*(a_j+*k));
}
}
// adds d c^T to v; precondition: v has length n
// ---------------------------------------------
template <typename ET>
template <typename Program>
void Quadratic_program_solution<ET>::add_c
(const Program& p, typename std::vector<ET>& v)
{
int n = p.get_n();
typedef typename Program::C_iterator C_column_iterator;
C_column_iterator c = p.get_c();
ET d = variables_common_denominator();
for (int j=0; j<n; ++j, ++c)
v[j] += ET(*c) * d;
}
} //namespace CGAL
#endif // CGAL_QP_SOLUTION_IMPL_H