# Reference MPMATH implementation: # # import mpmath # from mpmath import nsum # # def Wright_Series_MPMATH(a, b, z, dps=50, method='r+s+e', steps=[1000]): # """Compute Wright' generalized Bessel function as Series. # # This uses mpmath for arbitrary precision. # """ # with mpmath.workdps(dps): # res = nsum(lambda k: z**k/mpmath.fac(k) * mpmath.rgamma(a*k+b), # [0, mpmath.inf], # tol=dps, method=method, steps=steps # ) # # return res import pytest import numpy as np from numpy.testing import assert_equal, assert_allclose import scipy.special as sc from scipy.special import rgamma, wright_bessel @pytest.mark.parametrize('a', [0, 1e-6, 0.1, 0.5, 1, 10]) @pytest.mark.parametrize('b', [0, 1e-6, 0.1, 0.5, 1, 10]) def test_wright_bessel_zero(a, b): """Test at x = 0.""" assert_equal(wright_bessel(a, b, 0.), rgamma(b)) @pytest.mark.parametrize('b', [0, 1e-6, 0.1, 0.5, 1, 10]) @pytest.mark.parametrize('x', [0, 1e-6, 0.1, 0.5, 1]) def test_wright_bessel_iv(b, x): """Test relation of wright_bessel and modified bessel function iv. iv(z) = (1/2*z)**v * Phi(1, v+1; 1/4*z**2). See https://dlmf.nist.gov/10.46.E2 """ if x != 0: v = b - 1 wb = wright_bessel(1, v + 1, x**2 / 4.) # Note: iv(v, x) has precision of less than 1e-12 for some cases # e.g v=1-1e-6 and x=1e-06) assert_allclose(np.power(x / 2., v) * wb, sc.iv(v, x), rtol=1e-11, atol=1e-11) @pytest.mark.parametrize('a', [0, 1e-6, 0.1, 0.5, 1, 10]) @pytest.mark.parametrize('b', [1, 1 + 1e-3, 2, 5, 10]) @pytest.mark.parametrize('x', [0, 1e-6, 0.1, 0.5, 1, 5, 10, 100]) def test_wright_functional(a, b, x): """Test functional relation of wright_bessel. Phi(a, b-1, z) = a*z*Phi(a, b+a, z) + (b-1)*Phi(a, b, z) Note that d/dx Phi(a, b, x) = Phi(a, b-1, x) See Eq. (22) of B. Stankovic, On the Function of E. M. Wright, Publ. de l' Institut Mathematique, Beograd, Nouvelle S`er. 10 (1970), 113-124. """ assert_allclose(wright_bessel(a, b - 1, x), a * x * wright_bessel(a, b + a, x) + (b - 1) * wright_bessel(a, b, x), rtol=1e-8, atol=1e-8) # grid of rows [a, b, x, value, accuracy] that do not reach 1e-11 accuracy # see output of: # cd scipy/scipy/_precompute # python wright_bessel_data.py grid_a_b_x_value_acc = np.array([ [0.1, 100.0, 709.7827128933841, 8.026353022981087e+34, 2e-8], [0.5, 10.0, 709.7827128933841, 2.680788404494657e+48, 9e-8], [0.5, 10.0, 1000.0, 2.005901980702872e+64, 1e-8], [0.5, 100.0, 1000.0, 3.4112367580445246e-117, 6e-8], [1.0, 20.0, 100000.0, 1.7717158630699857e+225, 3e-11], [1.0, 100.0, 100000.0, 1.0269334596230763e+22, np.nan], [1.0000000000000222, 20.0, 100000.0, 1.7717158630001672e+225, 3e-11], [1.0000000000000222, 100.0, 100000.0, 1.0269334595866202e+22, np.nan], [1.5, 0.0, 500.0, 15648961196.432373, 3e-11], [1.5, 2.220446049250313e-14, 500.0, 15648961196.431465, 3e-11], [1.5, 1e-10, 500.0, 15648961192.344728, 3e-11], [1.5, 1e-05, 500.0, 15648552437.334162, 3e-11], [1.5, 0.1, 500.0, 12049870581.10317, 2e-11], [1.5, 20.0, 100000.0, 7.81930438331405e+43, 3e-9], [1.5, 100.0, 100000.0, 9.653370857459075e-130, np.nan], ]) @pytest.mark.xfail @pytest.mark.parametrize( 'a, b, x, phi', grid_a_b_x_value_acc[:, :4].tolist()) def test_wright_data_grid_failures(a, b, x, phi): """Test cases of test_data that do not reach relative accuracy of 1e-11""" assert_allclose(wright_bessel(a, b, x), phi, rtol=1e-11) @pytest.mark.parametrize( 'a, b, x, phi, accuracy', grid_a_b_x_value_acc.tolist()) def test_wright_data_grid_less_accurate(a, b, x, phi, accuracy): """Test cases of test_data that do not reach relative accuracy of 1e-11 Here we test for reduced accuracy or even nan. """ if np.isnan(accuracy): assert np.isnan(wright_bessel(a, b, x)) else: assert_allclose(wright_bessel(a, b, x), phi, rtol=accuracy)