summaryrefslogtreecommitdiff
path: root/thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp')
-rw-r--r--thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp98
1 files changed, 98 insertions, 0 deletions
diff --git a/thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp b/thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp
new file mode 100644
index 0000000000..b3664faa4e
--- /dev/null
+++ b/thirdparty/bullet/src/LinearMath/btPolarDecomposition.cpp
@@ -0,0 +1,98 @@
+#include "btPolarDecomposition.h"
+#include "btMinMax.h"
+
+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);
+ }
+}
+
+
+
+btPolarDecomposition::btPolarDecomposition(btScalar tolerance, unsigned int 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;
+}
+
+unsigned int btPolarDecomposition::maxIterations() const
+{
+ return m_maxIterations;
+}
+
+unsigned int polarDecompose(const btMatrix3x3& a, btMatrix3x3& u, btMatrix3x3& h)
+{
+ static btPolarDecomposition polar;
+ return polar.decompose(a, u, h);
+}
+