ddc0173671
Basic handling of constraints now works in factor graphs, assuming there is only one constraint on any given variable.
2009-11-10 04:36:07 +00:00
a7b711db37
Removed constraint variations on graphs/factors
2009-11-10 04:33:39 +00:00
2c37c94b5d
Replaced the householder transform with the weighted system
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Removed constrained components from makefile, they will disappear shortly
2009-11-09 21:34:20 +00:00
03985d16f6
Fixed equality checking with NaNs in Matrix
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removed extraneous print statement in Vector
2009-11-09 16:57:30 +00:00
01ee9246d7
fix Matlab toolbox to work with Frank's recent changes to gtsam.
2009-11-09 16:53:13 +00:00
1ae81b59d8
Fixed vector comparisons that will erroneously return true when there are NaN values.
2009-11-09 16:47:37 +00:00
a3de1964d7
BIG CHANGE:
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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
7bd40e836d
Cleaned up and added test for VSLAMFactor
2009-11-09 04:46:34 +00:00
e340178de5
Easy constructor
2009-11-09 04:46:08 +00:00
dd1b023ca9
Fixed special case for root
2009-11-09 04:45:38 +00:00
cc22e82ca6
Joint densities (covariances) now done. Was exceedingly easy :-)
2009-11-09 00:13:44 +00:00
3464c6a36f
Create from a single string
2009-11-08 22:51:29 +00:00
86173b66af
Clique marginal and dramatically simplified single variable marginal.
2009-11-08 22:51:12 +00:00
10e618f360
New function marginals. Also: combine entire Bayes nets with push_back and push_front. And finally: some convenience constructors in GaussianBayesNet.
2009-11-08 22:50:26 +00:00
58007a8167
Working recursive (but not cached) shortcut.
2009-11-08 04:41:01 +00:00
d1b8925617
Construct symbolic version of any Bayes net
2009-11-08 04:39:54 +00:00
532be063f9
new templated function combine
2009-11-08 02:50:19 +00:00
93da9e0f2c
pop_front
2009-11-08 02:49:18 +00:00
cc5a2c3183
Renamed double-templated functions to _eliminate and _eliminateOne, and created FactorGraph-specific eliminateOne methods to make life easier
2009-11-07 21:03:30 +00:00
df3e5f2416
BIG: eliminate and eliminateOne now doubly templated functions, not methods.
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Minor: Standardized on new shared_ptr naming convention:
shared_factor -> sharedFactor
conditional_ptr -> sharedConditional
node_ptr -> sharedClique
2009-11-07 19:31:39 +00:00
f5d186522e
Standardized on new shared_ptr naming convention
2009-11-07 17:24:05 +00:00
6339b5d19d
Made Node public
2009-11-07 15:58:45 +00:00
7ef9ed950b
Improved performance of matrix scaling in LinearFactor::matrix_augmented
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Added matrix scaling functions to scale either the rows or columns by values from a vector
2009-11-06 13:43:39 +00:00
cd313e2f82
operator[] to retrieve clique
2009-11-06 05:55:29 +00:00
e1716a39cd
Two changes: LinearFactor::sparse and LinearFactorGraph:sparse, and renamed VariableSet -> Dimensions, which is now a map from keys to integer variable dimensions. Merged in from the "sparse" branch created with Viorela.
2009-11-06 05:43:03 +00:00
fb74ef03b2
Added to LinearFactor a matrix_augmented() function to get a single augmented matrix [A b]
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Removed extra copying in LinearFactor::eliminate()
2009-11-05 15:08:58 +00:00
6c5603de0c
Fixed remaining LinearFactor unit tests
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Added equality check for Variable
2009-11-05 13:52:12 +00:00
d9289d14b3
marginals on any scalar now work
2009-11-05 08:06:32 +00:00
beabb62f29
More informative print
2009-11-05 08:05:54 +00:00
bd54c39a73
Fixed bug in smoother example
2009-11-05 08:05:34 +00:00
e87c19ed7a
ConditionalGaussian now stores sigmas
2009-11-05 06:59:59 +00:00
88b8f4e16b
fixed unit test
2009-11-05 06:34:43 +00:00
cabcda5a96
marginal compiles and runs for frontal node in clique
2009-11-05 06:30:50 +00:00
7f516394df
Added dummy argument to work around compile conundrum
2009-11-05 06:30:10 +00:00
06f07420d1
back()
2009-11-05 06:29:32 +00:00
11fcd5a69d
KISS: just a map of pointers in BayesTree now
2009-11-05 05:29:47 +00:00
3d334401f5
Constructor from BayesNet now in FactorGraph base class
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FactorGraph::eliminate
Removed eliminate_partially
2009-11-05 04:56:59 +00:00
e650676da7
Moved header to .h to fix MATLAB toolbox compilation
2009-11-05 03:51:08 +00:00
3b258be8c4
about a dozen changes to make Matlab toolbox work again, but one error remains having to do with the forward declaration of class GaussianBayesNet.
2009-11-05 03:26:04 +00:00
0ef7fe4a01
changed case of foreach ( it was capitals before and will not compile on linux )
2009-11-04 22:19:16 +00:00
e2414561be
Merged r895:900 from branch weightedQR - LinearFactorGraph now has sigmas and ConditionalGaussian now has precisions
2009-11-04 20:59:16 +00:00
4865edb883
Removed debug code, added marginal function
2009-11-04 03:22:29 +00:00
e9d942f81e
BayesNet is now list-based for fast bi-directional access
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SLOW O(n) random access operator[key] provided
(should maybe be called [at] as it does bounds checking)
I also fixed a bug in equals.
2009-11-03 06:29:56 +00:00
eab038651e
Renamed BayesNet::insert -> push_back. BayesTree now uses Bayes nets as nodes.
2009-11-02 05:17:44 +00:00
a8d267c4ca
Small change necessitating lots of edits: Conditionals now include key of random variable
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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
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.
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The main renaming that happened is
BayesChain -> BayesNet
ChordalBayesNet -> GaussianBayesNet == BayesNet<ConditionalGaussian>
SymbolicBayesChain -> SymbolicBayesNet == BayesNet<SymbolicConditional>
2009-10-31 19:53:20 +00:00
921cb0a8fc
Got rid of (defunct) "dump" methods
2009-10-31 17:13:36 +00:00
c046fed37c
Bayes tree constructor implemented and tested with ASIA, as well as smoother example from frankcvs meeting
2009-10-31 16:57:36 +00:00
1e5a2d692a
const
2009-10-31 16:56:06 +00:00
040f407b0b
Removed constructor, use eliminate
2009-10-31 16:55:44 +00:00
Alex Cunningham
Chris Beall
Frank Dellaert
Manohar Paluri
Richard Roberts