causallib.utils.general_tools module

Copyright 2019 IBM Corp.

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Created on Jun 27, 2018

General (i.e. non-scientific) utils used throughout the package.

causallib.utils.general_tools.check_learner_is_fitted(learner)[source]: Return True if fitted and False otherwise

causallib.utils.general_tools.create_repr_string(o)[source]

Parameters: o (object) – any core object
Returns: repr string based on internal attributes
Return type: str

causallib.utils.general_tools.get_iterable_treatment_values(treatment_values, treatment_assignment, sort=True)[source]

Convert an optionally provided specification of unique treatment values to an iterable of the unique treatment options. Since user can provide treatment values as either an iterable or a single value, this conversion to an iterable allows a generic approach of going over all provided treatment values.

Parameters

treatment_values (None|Any|list[Any]) – Unique values of possible treatment values. Can be either one value (scalar) or list of values (any iterable). Can be None, if None - treatment values are inferred from treatment assignment.
treatment_assignment (Series) – The observed treatment assignment, used to infer a list of unique treatment values in case no treatment values are provided (None is passed to treatment_values).
sort (bool) – Whether to sort the treatment values

Returns

list of unique treatment values.

Return type

list[Any]