Metrics: Default to numpy scalars for computation #163
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External testing found that attempting to compute categorical metrics using contingency tables with zero-valued components resulted in a
ZeroDivision
error. This behavior was undesirable for downstream users and inconsistent with the behavior of other packages used byhydrotools
. This update introduces conversion of contingency table components tonumpy.float64
scalars. This has the advantage of inheriting all of thenumpy
built-in value checking, including raising aRuntimeWarning
in the event of division by zero, instead of raising an error.Additions
convert_mapping_values
is a new method used to convert dict-like objects to numpyDTypeLike
values.Removals
Changes
convert_mapping_values
on the input contingency table.Testing
convert_mapping_values
is specifically tested using apandas.Series
Notes
Todos
Checklist