Fix tests

tests/calculations/test_spectra.py

@@ -67,7 +67,14 @@ def _generate_third_rank_tensors():
 
 
 def test_compute_raman_susceptibility_tensors(generate_phonopy_instance, generate_third_rank_tensors):
-    """Test the `compute_raman_susceptibility_tensors` function."""
+    """Test the `compute_raman_susceptibility_tensors` function.
+
+    For cubic semiconductors AB, the Raman susceptibility for phonons polarized along the `l`
+    direction can be written as sqrt(mu*Omega)*alpha_{12} = Omega dChi_{12}/dtau_{A,3},
+    where A is the atom located at the origin, and the atom B in (1/4,1/4,1/4).
+
+    As a consequence, we can test the implementation when specifying a q-direction (Cartesian).
+    """
     from aiida_vibroscopy.calculations.spectra_utils import compute_raman_susceptibility_tensors
     from aiida_vibroscopy.common.constants import DEFAULT
 
@@ -83,10 +90,10 @@ def test_compute_raman_susceptibility_tensors(generate_phonopy_instance, generat
         phonopy_instance=ph,
         raman_tensors=raman,
         nlo_susceptibility=chi2,
-        nac_direction=[0, 1, 0],
+        nac_direction=[1, 0, 0],
     )
 
-    alpha_comp = prefactor * alpha[0, 1, 2]
+    alpha_comp = prefactor * alpha[2, 1, 2]
     alpha_theo = vol * raman[0, 0, 1, 2]
     if DEBUG:
         print('\n', '================================', '\n')
@@ -95,7 +102,7 @@ def test_compute_raman_susceptibility_tensors(generate_phonopy_instance, generat
         print(alpha_comp, alpha_theo)
         print('\n', '================================', '\n')
 
-    assert np.abs(alpha_comp - alpha_theo) < 1e-5
+    assert np.abs(abs(alpha_comp) - abs(alpha_theo)) < 1e-5
 
     alpha, _, _ = compute_raman_susceptibility_tensors(
         phonopy_instance=ph,
@@ -106,8 +113,8 @@ def test_compute_raman_susceptibility_tensors(generate_phonopy_instance, generat
     diel = ph.nac_params['dielectric']
     borns = ph.nac_params['born']
 
-    nlocorr = DEFAULT.nlo_conversion * borns[0, 2, 2] * chi2[0, 1, 2] / diel[2, 2]
-    alpha_theo = vol * raman[0, 0, 1, 2] - nlocorr
+    nlocorr = DEFAULT.nlo_conversion * borns[1, 2, 2] * chi2[0, 1, 2] / diel[2, 2]
+    alpha_theo = vol * raman[1, 0, 1, 2] - nlocorr
 
     # we take the last, cause it is associated to the LO mode
     alpha_comp = prefactor * alpha[2, 0, 1]
@@ -118,8 +125,7 @@ def test_compute_raman_susceptibility_tensors(generate_phonopy_instance, generat
         print('NLO corr. expected: ', nlocorr)
         print('Born corr. expected: ', -borns[1, 0, 0] / np.sqrt(reduced_mass))
         print('Conversion factor nlo: ', DEFAULT.nlo_conversion)
-        # print(prefactor * alpha)
         print(alpha_comp, alpha_theo)
         print('\n', '================================', '\n')
 
-    assert np.abs(alpha_comp - alpha_theo) < 1e-3
+    assert np.abs(abs(alpha_comp) - abs(alpha_theo)) < 1e-4