import numpy as np
import pytest

import pyewjn.dielectric
import pyewjn.noise.chi
from pyewjn.baskets import CalculationParams


cutoff_to_use = 5.4596e9

TOO_SLOW_REASON = "These tests are too slow and pretty unhelpful"


@pytest.mark.skip(reason=TOO_SLOW_REASON)
@pytest.fixture
def chi_zz_e_nam_unapproximated():
	params = CalculationParams(
		omega=1e9, v_f=2e6, omega_p=3.544907701811032e15, tau=1e-14, t_rel=0.99999
	)
	eps_l = pyewjn.dielectric.get_unapproximated_nam_dielectric(cutoff_to_use, params)
	return pyewjn.noise.chi.get_chi_zz_e(eps_l)


@pytest.mark.skip(reason=TOO_SLOW_REASON)
@pytest.mark.parametrize(
	"test_input,expected",
	[
		# z   chi_zz_e_nam_unapproximated(z)
		(1e-5, 4.07695673649665e6),
		(1e-6, 4.095895777068543e9),
		# (1e-7, 5.012885033150058e12), commenting this one out because it seems numerically too unstable
		# (1e-8, 1.441261982619894e16), commenting this one out because it seems numerically too unstable
	],
)
def test_chi_zz_e_nam_unapproximated(chi_zz_e_nam_unapproximated, test_input, expected):
	actual = chi_zz_e_nam_unapproximated(test_input)

	np.testing.assert_allclose(
		actual,
		expected,
		rtol=0.05,
		err_msg="chi_zz_e is inaccurate for nam_unapproximated case",
		verbose=True,
	)


@pytest.mark.skip(reason=TOO_SLOW_REASON)
@pytest.mark.parametrize(
	"test_input,expected",
	[
		# z   chi_zz_e_nam_unapproximated(z)
		(1e-6, 4.095895777068543e9),
	],
)
def test_chi_zz_e_nam_unapproximated_benchmark(
	benchmark, chi_zz_e_nam_unapproximated, test_input, expected
):
	actual = benchmark(chi_zz_e_nam_unapproximated, test_input)
	np.testing.assert_allclose(
		actual,
		expected,
		rtol=0.05,
		err_msg="chi_zz_e is inaccurate for nam_unapproximated case",
		verbose=True,
	)