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gumbel_gof.py 575 bytes 






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import numpy as np

from extreme_fit.model.result_from_model_fit.abstract_result_from_model_fit import AbstractResultFromModelFit
from extreme_fit.model.utils import r


def cramer_von_mises_and_anderson_darling_tests_pvalues_for_gumbel_distribution(data):
    res = r.gnfit(data, "gum")
    res = AbstractResultFromModelFit.get_python_dictionary(res)
    res = {k: np.array(v)[0] for k, v in res.items()}
    return res['Wpval'], res['Apval']


if __name__ == '__main__':
    cramer_von_mises_and_anderson_darling_tests_pvalues_for_gumbel_distribution(np.array([2.0, 3.0]))