`culebra.tools.EffectSize` class¶

class EffectSize(test: str, data: str, column: str, batches: list, value: np.ndarray)¶

Bases: NamedTuple

Create new instance of EffectSize(test, data, column, batches, value)

Attributes¶

EffectSize.batches: list¶: Labels of all the analyzed batches.

EffectSize.column: str¶: Column key in the dataframe

EffectSize.data: str¶: Key for the dataframe containing the data

EffectSize.test: str¶: Name of the test.

EffectSize.value: ndarray¶: Effect size values.

Properties¶

property EffectSize.series: Series¶

Test outcome as a Series.

Returns:: A series with the test outcome
Return type:: Series

Dunder methods¶

EffectSize.__repr__() → str¶: Print all the input parameters and outputs.

EffectSize.__str__() → str¶: Pretty print of the effect sizes.

This work is supported by projects New Computing Paradigms and Heterogeneous Parallel Architectures for High-Performance and Energy Efficiency of Classification and Optimization Tasks on Biomedical Engineering Applications (HPEE-COBE), with reference PGC2018-098813-B-C31, and Advanced Methods of Biomedical Data Analysis and Brain Modeling Optimized for High-Performance and Energy-Efficient Computing (HPEEC-BIOBRAIN), with reference PID2022-137461NB-C31, both funded by the Spanish State Research Agency MCIN/AEI/10.13039/501100011033, and by the European Regional Development Fund (ERDF).