Struct TDataAssociationResults
Defined in File data_association.h
Struct Documentation
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struct TDataAssociationResults
The results from mrpt::slam::data_association_independent_predictions()
Public Members
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std::map<observation_index_t, prediction_index_t> associations
For each observation (with row index IDX_obs in the input “Z_observations”), its association in the predictions, as the row index in the “Y_predictions_mean” input (or it’s mapping to a custom ID, if it was provided). Note that not all observations may have an associated prediction. An observation with index “IDX_obs” corresponds to the prediction number “associations[IDX_obs]”, or it may not correspond to anyone if it’s not present in the std::map (Tip: Use associations.find(IDX_obs)!=associations.end() )
Note
The types observation_index_t and prediction_index_t are just used for clarity, use normal size_t’s.
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double distance = {0}
The Joint Mahalanobis distance or matching likelihood of the best associations found.
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mrpt::math::CMatrixDouble indiv_distances
Individual mahalanobis distances (or matching likelihood, depending on the selected metric) between predictions (row indices) & observations (column indices). Indices are for the appearing order in the arguments “Y_predictions_mean” & “Z_observations”, they are NOT landmark IDs.
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mrpt::math::CMatrixBool indiv_compatibility
The result of a chi2 test for compatibility using mahalanobis distance - Indices are like in “indiv_distances”.
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std::vector<uint32_t> indiv_compatibility_counts
The sum of each column of indiv_compatibility, that is, the number of compatible pairings for each observation.
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size_t nNodesExploredInJCBB = {0}
Only for the JCBB method,the number of recursive calls expent in the algorithm.
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std::map<observation_index_t, prediction_index_t> associations