Create wrapper types for arrays output by localization models with the following properties:
Associates a real-world unit (arb., mm, cm, m) and interpretation (Mean, covariance, cholesky) with the array data
Contains convenience functions for unit conversions
This change aims to resolve the following problems:
Evaluation and assessment scripts contain many lines of ambiguous shape-checking code to determine what kind of model output was presented (as models can choose to output parametrized densities, mass functions, or point estimates)
As Numpy arrays and Torch tensors carry no information about units, it is easy to erroneously attempt a unit conversion where none is needed
Create wrapper types for arrays output by localization models with the following properties:
This change aims to resolve the following problems:
Merge deadline: Fri 2023-06-16