113 lines
3.4 KiB
C++
113 lines
3.4 KiB
C++
|
/*
|
||
|
Written by Xuchen Han <xuchenhan2015@u.northwestern.edu>
|
||
|
|
||
|
Bullet Continuous Collision Detection and Physics Library
|
||
|
Copyright (c) 2019 Google Inc. http://bulletphysics.org
|
||
|
This software is provided 'as-is', without any express or implied warranty.
|
||
|
In no event will the authors be held liable for any damages arising from the use of this software.
|
||
|
Permission is granted to anyone to use this software for any purpose,
|
||
|
including commercial applications, and to alter it and redistribute it freely,
|
||
|
subject to the following restrictions:
|
||
|
1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. If you use this software in a product, an acknowledgment in the product documentation would be appreciated but is not required.
|
||
|
2. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software.
|
||
|
3. This notice may not be removed or altered from any source distribution.
|
||
|
*/
|
||
|
|
||
|
#ifndef BT_CONJUGATE_RESIDUAL_H
|
||
|
#define BT_CONJUGATE_RESIDUAL_H
|
||
|
#include "btKrylovSolver.h"
|
||
|
|
||
|
template <class MatrixX>
|
||
|
class btConjugateResidual : public btKrylovSolver<MatrixX>
|
||
|
{
|
||
|
typedef btAlignedObjectArray<btVector3> TVStack;
|
||
|
typedef btKrylovSolver<MatrixX> Base;
|
||
|
TVStack r, p, z, temp_p, temp_r, best_x;
|
||
|
// temp_r = A*r
|
||
|
// temp_p = A*p
|
||
|
// z = M^(-1) * temp_p = M^(-1) * A * p
|
||
|
btScalar best_r;
|
||
|
|
||
|
public:
|
||
|
btConjugateResidual(const int max_it_in)
|
||
|
: Base(max_it_in, 1e-8)
|
||
|
{
|
||
|
}
|
||
|
|
||
|
virtual ~btConjugateResidual() {}
|
||
|
|
||
|
// return the number of iterations taken
|
||
|
int solve(MatrixX& A, TVStack& x, const TVStack& b, bool verbose = false)
|
||
|
{
|
||
|
BT_PROFILE("CRSolve");
|
||
|
btAssert(x.size() == b.size());
|
||
|
reinitialize(b);
|
||
|
// r = b - A * x --with assigned dof zeroed out
|
||
|
A.multiply(x, temp_r); // borrow temp_r here to store A*x
|
||
|
r = this->sub(b, temp_r);
|
||
|
// z = M^(-1) * r
|
||
|
A.precondition(r, z); // borrow z to store preconditioned r
|
||
|
r = z;
|
||
|
btScalar residual_norm = this->norm(r);
|
||
|
if (residual_norm <= Base::m_tolerance)
|
||
|
{
|
||
|
return 0;
|
||
|
}
|
||
|
p = r;
|
||
|
btScalar r_dot_Ar, r_dot_Ar_new;
|
||
|
// temp_p = A*p
|
||
|
A.multiply(p, temp_p);
|
||
|
// temp_r = A*r
|
||
|
temp_r = temp_p;
|
||
|
r_dot_Ar = this->dot(r, temp_r);
|
||
|
for (int k = 1; k <= Base::m_maxIterations; k++)
|
||
|
{
|
||
|
// z = M^(-1) * Ap
|
||
|
A.precondition(temp_p, z);
|
||
|
// alpha = r^T * A * r / (Ap)^T * M^-1 * Ap)
|
||
|
btScalar alpha = r_dot_Ar / this->dot(temp_p, z);
|
||
|
// x += alpha * p;
|
||
|
this->multAndAddTo(alpha, p, x);
|
||
|
// r -= alpha * z;
|
||
|
this->multAndAddTo(-alpha, z, r);
|
||
|
btScalar norm_r = this->norm(r);
|
||
|
if (norm_r < best_r)
|
||
|
{
|
||
|
best_x = x;
|
||
|
best_r = norm_r;
|
||
|
if (norm_r < Base::m_tolerance)
|
||
|
{
|
||
|
return k;
|
||
|
}
|
||
|
}
|
||
|
// temp_r = A * r;
|
||
|
A.multiply(r, temp_r);
|
||
|
r_dot_Ar_new = this->dot(r, temp_r);
|
||
|
btScalar beta = r_dot_Ar_new / r_dot_Ar;
|
||
|
r_dot_Ar = r_dot_Ar_new;
|
||
|
// p = beta*p + r;
|
||
|
p = this->multAndAdd(beta, p, r);
|
||
|
// temp_p = beta*temp_p + temp_r;
|
||
|
temp_p = this->multAndAdd(beta, temp_p, temp_r);
|
||
|
}
|
||
|
if (verbose)
|
||
|
{
|
||
|
std::cout << "ConjugateResidual max iterations reached, residual = " << best_r << std::endl;
|
||
|
}
|
||
|
x = best_x;
|
||
|
return Base::m_maxIterations;
|
||
|
}
|
||
|
|
||
|
void reinitialize(const TVStack& b)
|
||
|
{
|
||
|
r.resize(b.size());
|
||
|
p.resize(b.size());
|
||
|
z.resize(b.size());
|
||
|
temp_p.resize(b.size());
|
||
|
temp_r.resize(b.size());
|
||
|
best_x.resize(b.size());
|
||
|
best_r = SIMD_INFINITY;
|
||
|
}
|
||
|
};
|
||
|
#endif /* btConjugateResidual_h */
|