Commit Graph

19 Commits (81a353dd2c42d29225be4f64db16aabad51e062e)

Author SHA1 Message Date
Alex Cunningham 2c37c94b5d Replaced the householder transform with the weighted system
Removed constrained components from makefile, they will disappear shortly
2009-11-09 21:34:20 +00:00
Frank Dellaert a3de1964d7 BIG CHANGE:
1) eliminate methods no longer return a shared pointer. Shared pointers are good for Factors and Conditionals (which are also non-copyable), because these are often passed around under the hood. However, a BayesNet is simple a list of shared pointers and hence does not cost a lot to return as an object (which is compiler-optimized anyway: there is no copy). So, the signature of all eliminate methods changed to simply return a BayesNet<> object (not a shared pointer).

2) GaussianBayesNet::optimize is now replaced by optimize(GaussianBayesNet) and returns a VectorConfig and not a shared pointer

3) GaussianBayesNet and SymbolicBayesNet are now simply typedefs, not derived classes. This is desirable because the BayesTree class uses templated methods that return BayesNet<Conditional>, not a specific BayesNet derived class.
2009-11-09 07:04:26 +00:00
Frank Dellaert bd54c39a73 Fixed bug in smoother example 2009-11-05 08:05:34 +00:00
Richard Roberts e2414561be Merged r895:900 from branch weightedQR - LinearFactorGraph now has sigmas and ConditionalGaussian now has precisions 2009-11-04 20:59:16 +00:00
Frank Dellaert eab038651e Renamed BayesNet::insert -> push_back. BayesTree now uses Bayes nets as nodes. 2009-11-02 05:17:44 +00:00
Frank Dellaert a8d267c4ca Small change necessitating lots of edits: Conditionals now include key of random variable
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
2009-11-02 03:50:30 +00:00
Frank Dellaert 943b692a6b BIG CHANGE: I got rid of the BayesChain/ChordalBayesNet classes and we now simply have a BayesNet class. It will just happen to be chordal when it is the result of an elimination. This will simplify a lot of things.
The main renaming that happened is

BayesChain -> BayesNet
ChordalBayesNet -> GaussianBayesNet == BayesNet<ConditionalGaussian>
SymbolicBayesChain -> SymbolicBayesNet == BayesNet<SymbolicConditional>
2009-10-31 19:53:20 +00:00
Frank Dellaert 68d2f81f0a Smoother now creates x1...xT, not x0 anymore 2009-10-31 16:54:38 +00:00
Frank Dellaert 4d9ff77249 moved timing example here from EasySLAM 2009-10-27 13:34:36 +00:00
Frank Dellaert 3792c79706 Fixed NonlinearFactor2 equals and added some unit tests for equals 2009-10-24 20:01:47 +00:00
Chris Beall 52bedcad3a order 1 factors by using map 2009-10-22 21:33:00 +00:00
Frank Dellaert 0d66ee8f72 comments only 2009-10-15 14:56:40 +00:00
Alex Cunningham 7d0a30c20f Renamed FGConfig to VectorConfig in gtsam, easylib, EasySLAM, and mast. 2009-10-14 20:39:59 +00:00
Alex Cunningham 8f20523e7f ConstrainedLinearFactorGraphs now handles multiple constraints on a node properly.
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
2009-10-14 15:32:05 +00:00
Alex Cunningham 66dac8a52f Generalized constraint handling to create a LinearConstraint which implements linear equality constraints that can be eliminated as a part of a ConstrainedLinearFactorGraph. DeltaFunction has been changed to be a ConstrainedConditionalGaussian, which has a more robust solve() function. The new tests no longer use the "constrained" example from smallExample, so those functions have been commented.
''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.
2009-10-08 13:57:22 +00:00
Frank Dellaert 989f290c99 '''BIG CHANGE''': avoid converting back and to FGConfigs by templating on configuration type. Details:
* 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.
2009-10-06 18:25:04 +00:00
Frank Dellaert 68e20eec2c 2 BIG 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.
2009-09-13 04:13:03 +00:00
Frank Dellaert ead3d03866 BIG: replaced optimize in NonlinearFactorGraph with specialized NonlinearOptimizer object. This does away with the artificial ErrorVectorConfig and the like as NonlinearOptimizer is templated and can use "exmap", the exponential map defined for any differentiable manifold. 2009-09-09 04:43:04 +00:00
Richard Roberts d80fa24a9f Fixing directory structure 2009-08-21 22:23:24 +00:00