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);
 }
-