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509f68cfe3fd13b794c4e67ff38c761407c858cf
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8 Commits

Author SHA1 Message Date
Sameer Agarwal 509f68cfe3 Problem::Evaluate implementation. 
1. Add Problem::Evaluate and tests.
2. Remove Solver::Summary::initial/final_*
3. Remove Solver::Options::return_* members.
4. Various cpplint cleanups.

Change-Id: I4266de53489896f72d9c6798c5efde6748d68a47
 2013-02-24 19:04:21 +00:00
Sameer Agarwal 42a84b87fa Expand reporting of timing information. 
1. Add an ExecutionSummary object to record execution
   information about Ceres objects.
2. Add an EventLogger object to log events in a function call.
3. Add a ScopedExecutionTimer object to log times in ExecutionSummary.
4. Instrument ProgramEvaluator and all the linear solvers
   to report their timing statistics.
5. Connect the timing statistics to Summary::FullReport.
6. Add high precision timer on unix systems using
   gettimeofday() call.
7. Various minor clean ups all around.

Change-Id: I5e09804b730b09535484124be7dbc1c58eccd1d4
 2013-02-06 01:00:38 -08:00
Sameer Agarwal 31432aeec4 Fix an initialization bug in ProgramEvaluator. 
The buffers used to store the per thread value of the gradient
were not set to zero at the beginning of each call to evaluate.

Change-Id: I9c8afea54a4e2e0b805164025da3023166a309af
 2012-11-25 18:36:04 -08:00
Sameer Agarwal 9123e2f624 An implementation of Ruhe & Wedin's Algorithm II. 
A non-linear generalization of Ruhe & Wedin's algorithm
for separable non-linear least squares problem. It is implemented
as coordinate descent on an independent subset of the parameter
blocks at the end of every successful Newton step. The resulting
algorithm has much improved convergence at the cost of some
execution time.

Change-Id: I8fdc5edbd0ba1e702c9658b98041b2c2ae705402
 2012-09-25 11:13:39 -07:00
Keir Mierle f44907f702 Compute the gradient if requested in the evaluator 
This extends the Evaluator interface to support evaluating the
gradient in addition to the residuals and jacobian, if requested.

   bool Evaluate(const double* state,
                 double* cost,
                 double* residuals,
                 double* gradient,  <----------- NEW
                 SparseMatrix* jacobian) = 0;

The ProgramEvaluator is extended to support the new gradient
evaluation. This required some gymnastics around the block
evaluate preparer, which now contains a scratch evaluate preparer
for the case that no jacobian is requested but the gradient is.

Gradient evaluation is a prerequisite for the planned suite of
first order methods, including nonlinear conjugate gradient,
CG_DESCENT, L-BFGS, trust region with line search, and more.

This also considerably refactors the evaluator_test to make it
shorter and check the results for all combinations of the optional
parameters [residuals, gradient, jacobian].

Change-Id: Ic7d0fec028dc5ffebc08ee079ad04eeaf6e02582
 2012-07-11 09:44:45 -07:00
Sameer Agarwal 319ef465e2 1. Zero out the residuals vector before it is used. 
2. explicit comparison with NULL for jacobian and residuals pointers.
 2012-05-22 20:44:52 -07:00
Keir Mierle cc38774d74 Clarify ProgramEvaluator comments. 2012-05-03 01:27:50 -07:00
Keir Mierle 8ebb073038 Initial commit of Ceres Solver. 2012-04-30 23:09:08 -07:00