Statys

Statys provides descriptive measures, pairwise non-parametric tests, Friedman and Iman-Davenport statistics, Nemenyi critical differences, and comparison plots.

Statys requires Python 3.11 or newer.

Installation

pip install statys

Repeated comparisons

import numpy as np

from statys import friedman, nemenyi, plot_critical_difference

scores = np.array(
    [
        [0.82, 0.79, 0.75],
        [0.80, 0.77, 0.78],
        [0.84, 0.81, 0.76],
        [0.79, 0.75, 0.74],
    ]
)

print(friedman(scores))
ranks, critical_difference = nemenyi(scores)
plot_critical_difference(
    ranks,
    critical_difference,
    labels=["Model A", "Model B", "Model C"],
    output="critical-difference.pdf",
)

Rows are experimental blocks and columns are the treatments being compared.

Measures and pairwise tests

from statys import measures, pairwise, significance

control = [0.82, 0.80, 0.84, 0.79]
model_a = [0.79, 0.77, 0.81, 0.75]
model_b = [0.75, 0.78, 0.76, 0.74]

print(measures.mean(control, model_a, model_b))

results = pairwise.signed_rank(control, model_a, model_b)
significance.plot_p_value(
    results,
    labels=["Control", "Model A", "Model B"],
    output="p-values.pdf",
)

The measures module also provides kurtosis, max, median, min, rank, skewness, std, and var. The pairwise module provides u_test, signed_rank, and rank_sum.

Development

uv sync
uv run pytest
uv run pre-commit run --all-files
uv build

Documentation is available at statys.readthedocs.io.