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# -*- coding: utf-8 -*- |
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import numpy as np |
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import pytest |
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import eppaurora as aur |
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EDISS_FUNCS_EXPECTED = [ |
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(aur.rr1987, 4.51517584e-07), |
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(aur.rr1987_mod, 4.75296602e-07), |
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(aur.fang2008, 4.44256875e-07), |
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(aur.fang2010_mono, 1.96516057e-007), |
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(aur.fang2010_maxw_int, 4.41340659e-07), |
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(aur.fang2013_protons, 4.09444686e-22), |
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(aur.berger1974, 1.18682805e-12), |
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] |
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View Code Duplication |
@pytest.mark.parametrize( |
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"edissfunc, expected", |
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EDISS_FUNCS_EXPECTED, |
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) |
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def test_endiss(edissfunc, expected): |
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energies = np.logspace(-1, 2, 4) |
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fluxes = np.ones_like(energies) |
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# ca. 100, 150, 200 km |
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scale_heights = np.array([6e5, 27e5, 40e5]) |
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rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
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# energy dissipation "profiles" |
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ediss = edissfunc( |
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energies[None, :], fluxes[None, :], |
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scale_heights[:, None], rhos[:, None] |
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) |
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assert ediss.shape == (3, 4) |
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np.testing.assert_allclose(ediss[0, 2], expected) |
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return |
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@pytest.mark.parametrize( |
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"edissfunc, expected", |
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EDISS_FUNCS_EXPECTED, |
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) |
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def test_endiss_scalar(edissfunc, expected): |
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energies = 10. |
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fluxes = 1. |
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# ca. 100, 150, 200 km |
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scale_heights = np.array([6e5, 27e5, 40e5]) |
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rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
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# energy dissipation "profiles" |
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ediss = edissfunc( |
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energies, fluxes, |
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scale_heights[:, None], rhos[:, None] |
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) |
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assert ediss.shape == (3, 1) |
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np.testing.assert_allclose(ediss[0, 0], expected) |
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return |
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View Code Duplication |
@pytest.mark.parametrize( |
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"edissfunc, expected", |
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EDISS_FUNCS_EXPECTED, |
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) |
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def test_endiss_transposed(edissfunc, expected): |
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energies = np.logspace(-1, 2, 4) |
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fluxes = np.ones_like(energies) |
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# ca. 100, 150, 200 km |
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scale_heights = np.array([6e5, 27e5, 40e5]) |
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rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
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ediss = edissfunc( |
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energies[:, None], fluxes[:, None], |
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scale_heights[None, :], rhos[None, :] |
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) |
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assert ediss.shape == (4, 3) |
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np.testing.assert_allclose(ediss[2, 0], expected) |
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return |
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View Code Duplication |
@pytest.mark.parametrize( |
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"edissfunc, expected", |
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EDISS_FUNCS_EXPECTED, |
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) |
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def test_endiss_3d(edissfunc, expected): |
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energies = np.logspace(-1, 2, 4) |
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fluxes = np.ones_like(energies) |
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# ca. 100, 150, 200 km |
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scale_heights = np.array([6e5, 27e5, 40e5]) |
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rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
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ediss = edissfunc( |
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energies[None, None, :], fluxes[None, None, :], |
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scale_heights[:, None, None], rhos[:, None, None] |
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) |
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assert ediss.shape == (3, 1, 4) |
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np.testing.assert_allclose(ediss[0, 0, 2], expected) |
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return |
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View Code Duplication |
@pytest.mark.parametrize( |
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"edissfunc, expected", |
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EDISS_FUNCS_EXPECTED, |
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) |
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def test_endiss_3d_transposed(edissfunc, expected): |
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energies = np.logspace(-1, 2, 4) |
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fluxes = np.ones_like(energies) |
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# ca. 100, 150, 200 km |
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scale_heights = np.array([6e5, 27e5, 40e5]) |
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rhos = np.array([5e-10, 1.7e-12, 2.6e-13]) |
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ediss = edissfunc( |
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energies[None, :, None], fluxes[None, :, None], |
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scale_heights[:, None, None], rhos[:, None, None] |
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) |
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assert ediss.shape == (3, 4, 1) |
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np.testing.assert_allclose(ediss[0, 2, 0], expected) |
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return |
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def test_ssusi_ioniz(): |
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energies = np.logspace(-1, 2, 4) |
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fluxes = np.ones_like(energies) |
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z = np.array([100, 120, 150]) |
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# energy dissipation "profiles" |
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ediss = aur.ssusi_ioniz( |
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z[:, None], |
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energies[None, :], fluxes[None, :], |
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) |
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assert ediss.shape == (3, 4) |
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return |
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st-bender /
pyeppaurora
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