import numpy as np
import scipy.stats
import itertools
from pprint import pprint

n_treat_hyper, n_treat_non = 11, 39
n_control_hyper, n_control_non = 15, 11


icu_treat_total = 1
icu_control_total = 13


corrected_pvals = {}
for icu_treat_hyper, icu_control_hyper in\
        itertools.product(range(1+icu_treat_total), range(1+icu_control_total)):
    icu_treat_non = icu_treat_total - icu_treat_hyper
    icu_control_non = icu_control_total - icu_control_hyper

    if n_control_hyper - icu_control_hyper < 0 or n_control_non - icu_control_non < 0:
        continue

    pval_hyper = scipy.stats.fisher_exact(
            [[icu_treat_hyper, n_treat_hyper - icu_treat_hyper],
             [icu_control_hyper, n_control_hyper - icu_control_hyper]])[1]
    pval_non = scipy.stats.fisher_exact(
            [[icu_treat_non, n_treat_non - icu_treat_non],
             [icu_control_non, n_control_non - icu_control_non]])[1]

    corrected_pvals[icu_treat_hyper, icu_control_hyper] = [2*pval_hyper, 2*pval_non]

#print(corrected_pvals)
print(max(corrected_pvals.items(), key=lambda tup: min(tup[1])))