`culebra.tools.ResultsComparison` class¶

class ResultsComparison(normality: TestOutcome, homoscedasticity: TestOutcome | None, global_comparison: TestOutcome, pairwise_comparison: TestOutcome | None)¶

Bases: NamedTuple

Create new instance of ResultsComparison(normality, homoscedasticity, global_comparison, pairwise_comparison)

Attributes¶

ResultsComparison.global_comparison: TestOutcome¶: Outcome of the global comparison of all the results

ResultsComparison.homoscedasticity: TestOutcome | None¶: Outcome of the homoscedasticity test. None if the compared results did not follow a normal distribution

ResultsComparison.normality: TestOutcome¶: Outcome of the normality test

ResultsComparison.pairwise_comparison: TestOutcome | None¶: Outcome of the pairwise comparison of the results. Only performed if more than two results are analyzed and not all the analyzed results follow the same distribution

Dunder methods¶

ResultsComparison.__repr__() → str¶: Print all the input parameters and outputs returned by a test.

ResultsComparison.__str__() → str¶: Pretty print of the success and p-values returned by a test.

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 Ministerio de Ciencia, Innovación y Universidades, and by the European Regional Development Fund (ERDF).