This simplifies Bayes nets quite a bit. Also created a Conditional base class, derived classes ConditionalGaussian and SymbolicConditional
Finally, some changes were needed because I moved some headers to .cpp
smallExample was changed to include two of the examples used in testConstrainedLinearFactorGraph
ConditionalGaussian was changed to make solve() virtual, as this is necessary for ConstrainedConditionalGaussian
''Limitations: ''
* Any given node can only have one constraint on it, but constraints can be of arbitrary size
* Constraints can only be specified as a blockwise system, where each block must be square and invertible to support arbitrary elimination orderings.
* ConstrainedNonlinearFactorGraph is disabled until a better solution for handling constraints in the nonlinear case is determined.
Manohar Paluri
Frank Dellaert
Richard Roberts
Alex Cunningham