32586ad175
wrap keys for GaussianFactor
2014-10-19 00:35:18 -04:00
3227766569
small comment typo
2014-10-19 00:35:01 -04:00
b0d95c0a36
check if a JacobianFactor has a dual variable
2014-10-17 13:31:35 -04:00
4be24f4f70
add adjointMap and expmap/logmap derivatives for Pose2
2014-10-17 13:30:57 -04:00
8722c9cf68
small comment
2014-10-17 13:30:32 -04:00
78d9a8cab8
fix empty factors bug
2014-09-25 11:18:51 -04:00
11969b32f6
fix gradient and gradientAtZero for linear constrained Jacobian, optionally scaled by the dual variables
2014-09-24 22:19:47 -04:00
43a8de01c1
Merge remote-tracking branch 'origin/feature/quadratic_programming' into feature/quadratic_programming
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Conflicts:
.cproject
.gitignore
gtsam/linear/GaussianFactorGraph.cpp
gtsam/linear/GaussianFactorGraph.h
gtsam/linear/HessianFactor.cpp
gtsam/linear/JacobianFactor.h
gtsam/linear/QPSolver.cpp
gtsam/linear/tests/testQPSolver.cpp
gtsam/nonlinear/NonlinearFactor.h
2014-09-14 01:45:27 -04:00
df1eede30c
Produce a graph of dual-scaled Hessians of each factor: -lambda*H, used for solving nonlinear equality constraints with SQP.
2014-09-13 01:37:17 -04:00
20fb8ab77d
Build a dual graph to compute dual values for equality constrained factors
2014-09-13 01:36:04 -04:00
4ca9d5757f
Support optional dual key for constrained Jacobian and nonlinear factors. Default boost::none for unconstrained factors.
2014-09-13 01:34:33 -04:00
5e8c36b3ca
compute gradient wrt a key
2014-09-13 01:31:49 -04:00
0dcb3e209d
add macro TEST_DISABLED for disabling tests without commenting them out
2014-09-13 01:29:25 -04:00
6d697f2c92
heuristic in EliminationPreferCholesky to work around the Indeterminant exception while solving linear constrained systems.
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Instead of turning Hessian factors into Jacobian factors -- so that they can be eliminated with constrained Jacobian factors using the special QR in Constrained's noise model -- we combine all Hessian factors, eliminate the variable first to have a conditional and a new factor 1, then combine the constrained Jacobians with this conditional (also a Jacobian) to eliminate again, producing the final conditional, and a new factor 2. The two new factors are then combined into a new Hessian factor to be returned.
2014-09-11 14:51:35 -04:00
f8126dbf78
fix .cproject after rebasing
2014-08-06 22:41:35 -04:00
af54d39b13
ignore build folder
2014-08-06 11:10:36 -04:00
779a21c2c4
A small example showing that Hessian matrices in Lie groups might not be symmetric
2014-08-06 11:10:36 -04:00
3778e3c928
constructors for JacobianFactor up to 6-ary for testing in matlab
2014-08-06 11:10:36 -04:00
ecb896ef03
move Adjoint to cpp and enable EXP_MAP
2014-08-06 11:10:36 -04:00
c6d541741b
more comments and debug info
2014-08-06 11:10:36 -04:00
47ed9f3687
matlab code to reproduce test results
2014-08-06 11:10:36 -04:00
4037d1ec1a
wrap QPSolver
2014-08-06 11:10:35 -04:00
cc2ba1792d
add detailed comments for the new EliminatePreferCholesky
2014-08-06 11:10:35 -04:00
a7c0d10862
disable two warning options in METIS which are not understood by my clang compiler.
2014-08-06 11:10:35 -04:00
2895b0515c
Support non positive definite Hessian factors while doing EliminatePreferCholesky with some constrained factors.
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Currently, when eliminating a constrained variable, EliminatePreferCholesky converts every other factors to JacobianFactor before doing the special QR factorization for constrained variables. Unfortunately, after a constrained nonlinear graph is linearized, new hessian factors from constraints, multiplied with the dual variable (-lambda*\hessian{c} terms in the Lagrangian objective function), might become negative definite, thus cannot be converted to JacobianFactors.
Following EliminateCholesky, this version of EliminatePreferCholesky for constrained var gathers all unconstrained factors into a big joint HessianFactor before converting it into a JacobianFactor to be eliminiated by QR together with the other constrained factors.
Of course, this might not solve the non-positive-definite problem entirely, because (1) the original hessian factors might be non-positive definite and (2) large strange value of lambdas might cause the joint factor non-positive definite [is this true?]. But at least, this will help in typical cases.
2014-08-06 11:09:25 -04:00
2fd3cf1bd0
unittest for QPSolver without initial point
2014-08-06 11:08:43 -04:00
882a1fe22f
first unittest finding QP's feasible initial point works
2014-08-06 11:08:43 -04:00
c91ab4a276
fix bugs in variable's columnNo index when passing to lpsolve. Obviously lpsolve modifies the raw buffer we pass to it!
2014-08-06 11:08:43 -04:00
c637a75ebf
add lp_solve and the gtsam LPSolver interface
2014-08-06 11:08:43 -04:00
e16efaab2c
QPSolver now returns dual values after solving. This can be used as a guessed dual value for the nonlinear level
2014-08-06 10:55:27 -04:00
cb7153a9d2
move detailed comments to the cpp file. An important comment about an Eigen's exception when converting a jacobian to a hessian factor, probably due to a bug in clang compiler.
2014-08-06 10:55:27 -04:00
fc63f540db
remove support for embedded lagrangian part to constraint's jacobian matrices. It's very hacky!
2014-08-06 10:55:27 -04:00
db93f4137c
dexp and dexpInv for Point2 and Rot2
2014-08-06 10:55:26 -04:00
ba870a1998
create VectorValues with all 1.0
2014-08-06 10:55:26 -04:00
b56a3426ad
important bug fix in building dual graph when finding the variable dimension from its first factor in the factor indices.
2014-08-06 10:55:25 -04:00
b8a2223572
make Jacobian/Hessian cast functions static to use them in other places. TODO: move them to GaussianFactor
2014-08-06 10:55:25 -04:00
416111b0ef
size() should return size_t not Key
2014-08-06 10:55:24 -04:00
4681c05063
build dualgraph supports least-squares multipliers
2014-08-06 10:55:24 -04:00
075817b31a
add build dir to GTSAM_INCLUDE_DIR so projects built with gtsam build tree can find <gtsam/config.h>
2014-08-06 10:55:24 -04:00
bb7522c947
Fix gtsam's old segfault bug in JacobianFactor::isConstrained: return false if it has no noisemodel. Test Nocedal06book, example 16.4, pg 475 passed.
2014-08-06 10:55:23 -04:00
37079417d1
Test with Matlab's QP example
2014-08-06 10:55:23 -04:00
befe397f7a
disable printing
2014-08-06 10:55:22 -04:00
f88c928ca0
refactor QPSolver into its own class
2014-08-06 10:55:22 -04:00
c0e201f06c
Detailed comments for choosing the step size
2014-08-06 10:55:22 -04:00
f00d673646
Detailed comments about the lambda<0 condition for good ineq <=0 constraints, wrt the Lagrangian L = f(x) - lambda*c(x)
2014-08-06 10:55:21 -04:00
9fd78faf4b
first ineq QP test passed!
2014-08-06 10:55:21 -04:00
cb02a95f94
fix bug in weightedPseudoInverse dealing with negative weights of ineq constraints
2014-08-06 10:55:21 -04:00
cb37b025e9
small improvement on negative weights
2014-08-06 10:55:20 -04:00
ba1273ae6b
fix bug in NoiseModel signs for ineq weights. Unittest dual graph
2014-08-06 10:55:20 -04:00
a31e9568a1
QPSolver in progress. Finish building dual graph, but not tested.
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Use mixed constrained noise with sigma < 0 to denote inequalities.
Working set implements the active set method, turning inactive inequalities
to active one as equality constraints by setting their corresponding sigmas to 0
and vice versa. Dual graph now has to deal with mixed sigmas.
2014-08-06 10:55:20 -04:00
thduynguyen