Remove TODO from Transform::computeScaleRotation()
Upon investigation, `JacobiSVD` is significantly faster than `BDCSVD`
for small matrices (twice as fast for 2x2, 20% faster for 3x3,
1% faster for 10x10). Since the majority of cases will be small,
let's stick with `JacobiSVD`. See !361.
diff --git a/Eigen/src/Geometry/Transform.h b/Eigen/src/Geometry/Transform.h
index 7497b31..7d258c0 100644
--- a/Eigen/src/Geometry/Transform.h
+++ b/Eigen/src/Geometry/Transform.h
@@ -1097,7 +1097,7 @@
template<typename RotationMatrixType, typename ScalingMatrixType>
EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
{
- // TODO: investigate BDCSVD implementation.
+ // Note that JacobiSVD is faster than BDCSVD for small matrices.
JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant() < Scalar(0) ? Scalar(-1) : Scalar(1); // so x has absolute value 1
@@ -1127,7 +1127,7 @@
template<typename ScalingMatrixType, typename RotationMatrixType>
EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
{
- // TODO: investigate BDCSVD implementation.
+ // Note that JacobiSVD is faster than BDCSVD for small matrices.
JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant() < Scalar(0) ? Scalar(-1) : Scalar(1); // so x has absolute value 1
