Todo List

Member DataTree.INode.get_active_leaf (IModel model, id)

rename this method to get_leaf

Member DataTree.INode.get_active_leaf_index (IModel model, id)

rename this method to get_leaf_index

Member DataTree.INode.get_index ( id, mu, nt)

add get_indices method returning indices in a range

Member DataTree.TpartNode.get_indices_in_region ( ids, mu_geo, tslice)

implement

Member doxygen ( param1, param2)

There needs to be done something in this file

Member Greedy.Checkpoint.data_index

: Why do I not store a single vector

Class Greedy.DataTree.Detailed.InfoNode

Do I need it? If yes, document it.

Member Greedy.DataTree.Detailed.INode.format_snapshot ( id, indices)

: rewrite

Member Greedy.DataTree.Detailed.INode.get_rb ()

is this correct or should it be in a specialization?

Member Greedy.DataTree.Detailed.INode.set_rb ( RB)

is this correct or should it be in a specialization?

Class Greedy.DataTree.Reduced.TpartNode

doc me

Class Greedy.TrainingSetAdaptation

add reference to adaptive paper.

Member gridbase.check_consistency ()

: perhaps later further extensions

Member gridbase.plot_polygon_grid ( params)

For large grids, the routine can be slow. In these cases interestingly, the grid plotting should be implemented with patches, as that seems to be faster...

Member IModel.num_cpus

: This flag should move to the FakeMPI sigleton control structure.

Class LinStat.ReducedData

Describe the matrix components, or add a link to a paper...

Member ParameterSampling.IRefineable.cogs ()

Maybe this should be renamed to refinement_candidates, because otherwise it is restricted to grids.

Member Postprocess.StochasticAssessment.Assessment.detailed_data

make this cached...

Member Postprocess.StochasticAssessment.Output.assessment

Maybe we should cache this, too...

Namespace Test

Move to namespace Greedy

Member velocity_parabola ( glob, params)

lambda needs to be set to something more reasonable for reduced simulations.

lambda needs to be set to something more reasonable for reduced simulations.