def test_binom_tost(): # consistency check with two different implementation, # proportion_confint is tested against R # no reference case from other package available ci = smprop.proportion_confint(10, 20, method='beta', alpha=0.1) bt = smprop.binom_tost(10, 20, *ci) assert_almost_equal(bt, [0.05] * 3, decimal=12) ci = smprop.proportion_confint(5, 20, method='beta', alpha=0.1) bt = smprop.binom_tost(5, 20, *ci) assert_almost_equal(bt, [0.05] * 3, decimal=12) # vectorized, TODO: observed proportion = 0 returns nan ci = smprop.proportion_confint(np.arange(1, 20), 20, method='beta', alpha=0.05) bt = smprop.binom_tost(np.arange(1, 20), 20, *ci) bt = np.asarray(bt) assert_almost_equal(bt, 0.025 * np.ones(bt.shape), decimal=12)
def test_binom_tost(): # consistency check with two different implementation, # proportion_confint is tested against R # no reference case from other package available ci = smprop.proportion_confint(10, 20, method='beta', alpha=0.1) bt = smprop.binom_tost(10, 20, *ci) assert_almost_equal(bt, [0.05] * 3, decimal=12) ci = smprop.proportion_confint(5, 20, method='beta', alpha=0.1) bt = smprop.binom_tost(5, 20, *ci) assert_almost_equal(bt, [0.05] * 3, decimal=12) # vectorized, TODO: observed proportion = 0 returns nan ci = smprop.proportion_confint(np.arange(1, 20), 20, method='beta', alpha=0.05) bt = smprop.binom_tost(np.arange(1, 20), 20, *ci) bt = np.asarray(bt) assert_almost_equal(bt, 0.025 * np.ones(bt.shape), decimal=12)