ai-content-maker/.venv/Lib/site-packages/scipy/special/tests/test_cdft_asymptotic.py

50 lines
1.4 KiB
Python

# gh-14777 regression tests
# Test stdtr and stdtrit with infinite df and large values of df
import numpy as np
from numpy.testing import assert_allclose, assert_equal
from scipy.special import stdtr, stdtrit, ndtr, ndtri
def test_stdtr_vs_R_large_df():
df = [1e10, 1e12, 1e120, np.inf]
t = 1.
res = stdtr(df, t)
# R Code:
# options(digits=20)
# pt(1., c(1e10, 1e12, 1e120, Inf))
res_R = [0.84134474605644460343,
0.84134474606842180044,
0.84134474606854281475,
0.84134474606854292578]
assert_allclose(res, res_R, rtol=2e-15)
# last value should also agree with ndtr
assert_equal(res[3], ndtr(1.))
def test_stdtrit_vs_R_large_df():
df = [1e10, 1e12, 1e120, np.inf]
p = 0.1
res = stdtrit(df, p)
# R Code:
# options(digits=20)
# qt(0.1, c(1e10, 1e12, 1e120, Inf))
res_R = [-1.2815515656292593150,
-1.2815515655454472466,
-1.2815515655446008125,
-1.2815515655446008125]
assert_allclose(res, res_R, rtol=1e-14, atol=1e-15)
# last value should also agree with ndtri
assert_equal(res[3], ndtri(0.1))
def test_stdtr_stdtri_invalid():
# a mix of large and inf df with t/p equal to nan
df = [1e10, 1e12, 1e120, np.inf]
x = np.nan
res1 = stdtr(df, x)
res2 = stdtrit(df, x)
res_ex = 4*[np.nan]
assert_equal(res1, res_ex)
assert_equal(res2, res_ex)