This is a big edit but with no templates involed, so it should not be a big deal.
New namespace gtsam::noiseModel collects all noise models, which provide efficient whitening and chain-rule implementation needed for optimization. The class hierarchy gives us the ability to use models from full covariances to i.i.d. unit variance noise with a single interface, where the latter will be much cheaper.
From now on, all non-linear factors take a shared_ptr to a Gaussian noise model. This is done through the parameter (const sharedGaussian& model). The use of a shared pointer allows us to share one noise models for thousands of factors, if applicable.
Just like Richard's Symbol change, there is a compile flag GTSAM_MAGIC_GAUSSIAN which allows you to use doubles, vectors, or matrices to created noise models on the fly. You have to set it to the correct dimension. Use of this is *not* encouraged and the flag will disappear after some good soul fixed all unit tests.
* Factors are now templated on the configuration type. Factor Graphs are now templated on the factor type and configuration type.
* LinearFactor is a factor on an FGConfig.
* LinearFactorGraph uses LinearFactor and FGConfig.
* NonLinearFactor is still templated on Config.
* NonLinearFactorGraph uses NonLinearFactors, but is still templated on Config.
* Tests and VSLAMFactor have been updated to reflect those changes.
(1) FactorGraph and NonlinearOptimizer now no longer have a .cpp file, but a -inl.h file as in [http://google-styleguide.googlecode.com/svn/trunk/cppguide.xml Google's C++ Style Guide]. This means if you expect to instantiate one of the functions in a cpp file, you have to include the -inl.h file.
(1) getOrdering is now in FactorGraph, and the non-linear version does *not* take a config anymore.
Long version: I made this change because colamd works on the graph structure alone, and should not depend on the type of graph. Instead, because getOrdering happened to implemented in LinearFactorGraph first, the non-linear version converted to a linear factor graph (at the cost of an unnecessary linearization), and then threw all that away to call colamd. To implement this in a key-neutral way (a hidden agenda), i had to modify the keys_ type to a list, so a lot of changes resulted from that.