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authorRémi Verschelde <rverschelde@gmail.com>2020-01-08 18:05:43 +0100
committerRémi Verschelde <rverschelde@gmail.com>2020-01-08 18:05:43 +0100
commit29e07dfa4e42b871ee30e398b1c35d1aea68cd57 (patch)
tree77cf7199b8f656302f600ac1c98506042924a1e8 /thirdparty/bullet/BulletSoftBody/btConjugateGradient.h
parent98222130bfe5ec90c1030c2d1e4554e990c5e0f9 (diff)
bullet: Sync with upstream 2.89
This allows distro unbundling again for distros that ship Bullet 2.89+.
Diffstat (limited to 'thirdparty/bullet/BulletSoftBody/btConjugateGradient.h')
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diff --git a/thirdparty/bullet/BulletSoftBody/btConjugateGradient.h b/thirdparty/bullet/BulletSoftBody/btConjugateGradient.h
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+/*
+ 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_GRADIENT_H
+#define BT_CONJUGATE_GRADIENT_H
+#include <iostream>
+#include <cmath>
+#include <limits>
+#include <LinearMath/btAlignedObjectArray.h>
+#include <LinearMath/btVector3.h>
+#include "LinearMath/btQuickprof.h"
+template <class MatrixX>
+class btConjugateGradient
+{
+ typedef btAlignedObjectArray<btVector3> TVStack;
+ TVStack r,p,z,temp;
+ int max_iterations;
+ btScalar tolerance_squared;
+public:
+ btConjugateGradient(const int max_it_in)
+ : max_iterations(max_it_in)
+ {
+ tolerance_squared = 1e-5;
+ }
+
+ virtual ~btConjugateGradient(){}
+
+ // return the number of iterations taken
+ int solve(MatrixX& A, TVStack& x, const TVStack& b, bool verbose = false)
+ {
+ BT_PROFILE("CGSolve");
+ btAssert(x.size() == b.size());
+ reinitialize(b);
+ // r = b - A * x --with assigned dof zeroed out
+ A.multiply(x, temp);
+ r = sub(b, temp);
+ A.project(r);
+ // z = M^(-1) * r
+ A.precondition(r, z);
+ A.project(z);
+ btScalar r_dot_z = dot(z,r);
+ if (r_dot_z <= tolerance_squared) {
+ if (verbose)
+ {
+ std::cout << "Iteration = 0" << std::endl;
+ std::cout << "Two norm of the residual = " << r_dot_z << std::endl;
+ }
+ return 0;
+ }
+ p = z;
+ btScalar r_dot_z_new = r_dot_z;
+ for (int k = 1; k <= max_iterations; k++) {
+ // temp = A*p
+ A.multiply(p, temp);
+ A.project(temp);
+ if (dot(p,temp) < SIMD_EPSILON)
+ {
+ if (verbose)
+ std::cout << "Encountered negative direction in CG!" << std::endl;
+ if (k == 1)
+ {
+ x = b;
+ }
+ return k;
+ }
+ // alpha = r^T * z / (p^T * A * p)
+ btScalar alpha = r_dot_z_new / dot(p, temp);
+ // x += alpha * p;
+ multAndAddTo(alpha, p, x);
+ // r -= alpha * temp;
+ multAndAddTo(-alpha, temp, r);
+ // z = M^(-1) * r
+ A.precondition(r, z);
+ r_dot_z = r_dot_z_new;
+ r_dot_z_new = dot(r,z);
+ if (r_dot_z_new < tolerance_squared) {
+ if (verbose)
+ {
+ std::cout << "ConjugateGradient iterations " << k << std::endl;
+ }
+ return k;
+ }
+
+ btScalar beta = r_dot_z_new/r_dot_z;
+ p = multAndAdd(beta, p, z);
+ }
+ if (verbose)
+ {
+ std::cout << "ConjugateGradient max iterations reached " << max_iterations << std::endl;
+ }
+ return max_iterations;
+ }
+
+ void reinitialize(const TVStack& b)
+ {
+ r.resize(b.size());
+ p.resize(b.size());
+ z.resize(b.size());
+ temp.resize(b.size());
+ }
+
+ TVStack sub(const TVStack& a, const TVStack& b)
+ {
+ // c = a-b
+ btAssert(a.size() == b.size());
+ TVStack c;
+ c.resize(a.size());
+ for (int i = 0; i < a.size(); ++i)
+ {
+ c[i] = a[i] - b[i];
+ }
+ return c;
+ }
+
+ btScalar squaredNorm(const TVStack& a)
+ {
+ return dot(a,a);
+ }
+
+ btScalar dot(const TVStack& a, const TVStack& b)
+ {
+ btScalar ans(0);
+ for (int i = 0; i < a.size(); ++i)
+ ans += a[i].dot(b[i]);
+ return ans;
+ }
+
+ void multAndAddTo(btScalar s, const TVStack& a, TVStack& result)
+ {
+// result += s*a
+ btAssert(a.size() == result.size());
+ for (int i = 0; i < a.size(); ++i)
+ result[i] += s * a[i];
+ }
+
+ TVStack multAndAdd(btScalar s, const TVStack& a, const TVStack& b)
+ {
+ // result = a*s + b
+ TVStack result;
+ result.resize(a.size());
+ for (int i = 0; i < a.size(); ++i)
+ result[i] = s * a[i] + b[i];
+ return result;
+ }
+};
+#endif /* btConjugateGradient_h */