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author | RĂ©mi Verschelde <rverschelde@gmail.com> | 2019-01-07 15:08:41 +0100 |
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committer | GitHub <noreply@github.com> | 2019-01-07 15:08:41 +0100 |
commit | dab650fcaa3eb37deee5118d678a3763ac78a58a (patch) | |
tree | 3131df01280f91a61b4721eed132a5b6b21881ba /thirdparty/bullet/LinearMath/btPolarDecomposition.cpp | |
parent | a3a537c2cf86ff4bf82385bbd17606654f8013c4 (diff) | |
parent | 22b7c9dfa80d0f7abca40f061865c2ab3c136a74 (diff) |
Merge pull request #24740 from OBKF/update-bullet-physics
Update Bullet physics to commit 126b676
Diffstat (limited to 'thirdparty/bullet/LinearMath/btPolarDecomposition.cpp')
-rw-r--r-- | thirdparty/bullet/LinearMath/btPolarDecomposition.cpp | 144 |
1 files changed, 70 insertions, 74 deletions
diff --git a/thirdparty/bullet/LinearMath/btPolarDecomposition.cpp b/thirdparty/bullet/LinearMath/btPolarDecomposition.cpp index b3664faa4e..d9c72a8014 100644 --- a/thirdparty/bullet/LinearMath/btPolarDecomposition.cpp +++ b/thirdparty/bullet/LinearMath/btPolarDecomposition.cpp @@ -3,96 +3,92 @@ namespace { - btScalar abs_column_sum(const btMatrix3x3& a, int i) - { - return btFabs(a[0][i]) + btFabs(a[1][i]) + btFabs(a[2][i]); - } - - btScalar abs_row_sum(const btMatrix3x3& a, int i) - { - return btFabs(a[i][0]) + btFabs(a[i][1]) + btFabs(a[i][2]); - } - - btScalar p1_norm(const btMatrix3x3& a) - { - const btScalar sum0 = abs_column_sum(a,0); - const btScalar sum1 = abs_column_sum(a,1); - const btScalar sum2 = abs_column_sum(a,2); - return btMax(btMax(sum0, sum1), sum2); - } - - btScalar pinf_norm(const btMatrix3x3& a) - { - const btScalar sum0 = abs_row_sum(a,0); - const btScalar sum1 = abs_row_sum(a,1); - const btScalar sum2 = abs_row_sum(a,2); - return btMax(btMax(sum0, sum1), sum2); - } +btScalar abs_column_sum(const btMatrix3x3& a, int i) +{ + return btFabs(a[0][i]) + btFabs(a[1][i]) + btFabs(a[2][i]); } +btScalar abs_row_sum(const btMatrix3x3& a, int i) +{ + return btFabs(a[i][0]) + btFabs(a[i][1]) + btFabs(a[i][2]); +} +btScalar p1_norm(const btMatrix3x3& a) +{ + const btScalar sum0 = abs_column_sum(a, 0); + const btScalar sum1 = abs_column_sum(a, 1); + const btScalar sum2 = abs_column_sum(a, 2); + return btMax(btMax(sum0, sum1), sum2); +} + +btScalar pinf_norm(const btMatrix3x3& a) +{ + const btScalar sum0 = abs_row_sum(a, 0); + const btScalar sum1 = abs_row_sum(a, 1); + const btScalar sum2 = abs_row_sum(a, 2); + return btMax(btMax(sum0, sum1), sum2); +} +} // namespace btPolarDecomposition::btPolarDecomposition(btScalar tolerance, unsigned int maxIterations) -: m_tolerance(tolerance) -, m_maxIterations(maxIterations) + : m_tolerance(tolerance), m_maxIterations(maxIterations) { } unsigned int btPolarDecomposition::decompose(const btMatrix3x3& a, btMatrix3x3& u, btMatrix3x3& h) const { - // Use the 'u' and 'h' matrices for intermediate calculations - u = a; - h = a.inverse(); - - for (unsigned int i = 0; i < m_maxIterations; ++i) - { - const btScalar h_1 = p1_norm(h); - const btScalar h_inf = pinf_norm(h); - const btScalar u_1 = p1_norm(u); - const btScalar u_inf = pinf_norm(u); - - const btScalar h_norm = h_1 * h_inf; - const btScalar u_norm = u_1 * u_inf; - - // The matrix is effectively singular so we cannot invert it - if (btFuzzyZero(h_norm) || btFuzzyZero(u_norm)) - break; - - const btScalar gamma = btPow(h_norm / u_norm, 0.25f); - const btScalar inv_gamma = btScalar(1.0) / gamma; - - // Determine the delta to 'u' - const btMatrix3x3 delta = (u * (gamma - btScalar(2.0)) + h.transpose() * inv_gamma) * btScalar(0.5); - - // Update the matrices - u += delta; - h = u.inverse(); - - // Check for convergence - if (p1_norm(delta) <= m_tolerance * u_1) - { - h = u.transpose() * a; - h = (h + h.transpose()) * 0.5; - return i; - } - } - - // The algorithm has failed to converge to the specified tolerance, but we - // want to make sure that the matrices returned are in the right form. - h = u.transpose() * a; - h = (h + h.transpose()) * 0.5; - - return m_maxIterations; + // Use the 'u' and 'h' matrices for intermediate calculations + u = a; + h = a.inverse(); + + for (unsigned int i = 0; i < m_maxIterations; ++i) + { + const btScalar h_1 = p1_norm(h); + const btScalar h_inf = pinf_norm(h); + const btScalar u_1 = p1_norm(u); + const btScalar u_inf = pinf_norm(u); + + const btScalar h_norm = h_1 * h_inf; + const btScalar u_norm = u_1 * u_inf; + + // The matrix is effectively singular so we cannot invert it + if (btFuzzyZero(h_norm) || btFuzzyZero(u_norm)) + break; + + const btScalar gamma = btPow(h_norm / u_norm, 0.25f); + const btScalar inv_gamma = btScalar(1.0) / gamma; + + // Determine the delta to 'u' + const btMatrix3x3 delta = (u * (gamma - btScalar(2.0)) + h.transpose() * inv_gamma) * btScalar(0.5); + + // Update the matrices + u += delta; + h = u.inverse(); + + // Check for convergence + if (p1_norm(delta) <= m_tolerance * u_1) + { + h = u.transpose() * a; + h = (h + h.transpose()) * 0.5; + return i; + } + } + + // The algorithm has failed to converge to the specified tolerance, but we + // want to make sure that the matrices returned are in the right form. + h = u.transpose() * a; + h = (h + h.transpose()) * 0.5; + + return m_maxIterations; } unsigned int btPolarDecomposition::maxIterations() const { - return m_maxIterations; + return m_maxIterations; } unsigned int polarDecompose(const btMatrix3x3& a, btMatrix3x3& u, btMatrix3x3& h) { - static btPolarDecomposition polar; - return polar.decompose(a, u, h); + static btPolarDecomposition polar; + return polar.decompose(a, u, h); } - |