[[Imported from SVN: r7412]]

[[Imported from SVN: r7391]]

[[Imported from SVN: r7390]]

Be smarter about when to compute what.  This speeds up assembly of the Hessian for harmonic maps from R^3 to S^2 by a factor of 3

[[Imported from SVN: r7389]]

[[Imported from SVN: r7388]]

Remove class specializations.  The old implementation for the UnitVector class will handle all cases

[[Imported from SVN: r7380]]

[[Imported from SVN: r7379]]

[[Imported from SVN: r7378]]

[[Imported from SVN: r7374]]

Remove a few specializations.  From now on we will assume that all target spaces can be parametrized by some sort of global embedding.  I don't see a case coming where that is not general enough

[[Imported from SVN: r7373]]

[[Imported from SVN: r7366]]

[[Imported from SVN: r7365]]

Solve the minimization problems for the evaluation of gfe functions really down to machine precision.  This appears to make the overall algorithm much more stable

[[Imported from SVN: r7355]]

[[Imported from SVN: r7354]]

[[Imported from SVN: r7353]]

[[Imported from SVN: r7352]]

[[Imported from SVN: r7351]]

[[Imported from SVN: r7350]]

[[Imported from SVN: r7348]]

[[Imported from SVN: r7346]]

[[Imported from SVN: r7345]]

[[Imported from SVN: r7344]]

[[Imported from SVN: r7342]]

[[Imported from SVN: r7341]]

[[Imported from SVN: r7338]]

[[Imported from SVN: r7314]]

[[Imported from SVN: r7313]]

[[Imported from SVN: r7312]]

[[Imported from SVN: r7311]]

[[Imported from SVN: r7286]]

instead of a singular value decomposition.  This makes computing
a Hesse matrix roughly 20% faster.

[[Imported from SVN: r7232]]

using a finite-difference approximation only for the derivative
of the gfe gradients wrt coefficients.

[[Imported from SVN: r7230]]

[[Imported from SVN: r7229]]

[[Imported from SVN: r7228]]

[[Imported from SVN: r7227]]

[[Imported from SVN: r7225]]

[[Imported from SVN: r7206]]

[[Imported from SVN: r7205]]

[[Imported from SVN: r7196]]

[[Imported from SVN: r7195]]