def test_absorption_spectra(self):
f, X = absorption_spectra(self.dyn, 10000)
self.assertAlmostEqual(f[np.argmax(X)], 12500)
self.assertTrue(is_constant(np.diff(f)))
self.assertTrue(np.all(np.diff(X)[:int(len(X) / 2.0 - 1)] > 0))
self.assertTrue(np.all(np.diff(X)[-int(len(X) / 2.0 - 1):] < 0))
dyn2 = RedfieldModel(self.ham, rw_freq=12400,
discard_imag_corr=True, unit_convert=CM_FS)
f2, X2 = absorption_spectra(dyn2, 10000)
self.assertAlmostEqual(f2[np.argmax(X2)], 12500, 0)
def test_evolve_basis_sparse_matrix(self):
linear_responses = []
def sparse_func(mat):
return True
for basis, sp in itertools.product(['site', 'eigen'],
[False, True, sparse_func]):
model = self.get_model(basis, sp)
f, X = absorption_spectra(model, 10000)
linear_responses.append(X)
test_response = linear_responses.pop()
for resp in linear_responses:
np.allclose(test_response, resp)
