def test_vampola_singleval(self):
"""sin^n model should have d_flux that integrates to input omniflux"""
omniflux = 3000
dnflux, alphas = em.vampolaPA(omniflux, order=2, alpha=self.PA)
d_sum = em.omniFromDirectionalFlux(dnflux, alphas, norm=False)
np.testing.assert_almost_equal(d_sum, omniflux, decimal=3)
dnflux, alphas = em.vampolaPA(omniflux, order=4, alpha=self.PA)
d_sum = em.omniFromDirectionalFlux(dnflux, alphas, norm=False)
np.testing.assert_almost_equal(d_sum, omniflux, decimal=3)
def test_vampola_singleval(self):
"""sin^n model should have d_flux that integrates to input omniflux"""
omniflux = 3000
dnflux, alphas = em.vampolaPA(omniflux, order=2, alpha=self.PA)
d_sum = em.omniFromDirectionalFlux(dnflux, alphas, norm=False)
np.testing.assert_almost_equal(d_sum, omniflux, decimal=3)
dnflux, alphas = em.vampolaPA(omniflux, order=4, alpha=self.PA)
d_sum = em.omniFromDirectionalFlux(dnflux, alphas, norm=False)
np.testing.assert_almost_equal(d_sum, omniflux, decimal=3)
def test_vampola_multi_n(self):
"""sin^n model should have d_flux that integrates to input omniflux"""
omniflux = [3000, 6000]
dnflux, alphas = em.vampolaPA(omniflux, order=[2,4], alpha=self.PA)
for i in range(len(omniflux)):
d_sum = em.omniFromDirectionalFlux(dnflux[:,i], alphas, norm=False)
np.testing.assert_almost_equal(d_sum, omniflux[i])
def test_vampola_multi_n(self):
"""sin^n model should have d_flux that integrates to input omniflux"""
omniflux = [3000, 6000]
dnflux, alphas = em.vampolaPA(omniflux, order=[2, 4], alpha=self.PA)
for i in range(len(omniflux)):
d_sum = em.omniFromDirectionalFlux(dnflux[:, i],
alphas,
norm=False)
np.testing.assert_almost_equal(d_sum, omniflux[i])
