mol.spin = 0
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 2, 4), (4, 2, 4))
las.state_average_(weights=weights, **states)
las.mo_coeff = las.localize_init_guess(
(list(range(3)), list(range(3, 7)), list(range(7, 10))), mf.mo_coeff)
las.ci = get_init_guess_ci(las, las.mo_coeff, las.get_h2eff(las.mo_coeff))
np.random.seed(1)
for c in las.ci:
for iroot in range(len(c)):
c[iroot] = np.random.rand(*c[iroot].shape)
c[iroot] /= linalg.norm(c[iroot])
orbsym = getattr(las.mo_coeff, 'orbsym', None)
if orbsym is None and callable(getattr(las, 'label_symmetry_', None)):
orbsym = las.label_symmetry_(las.mo_coeff).orbsym
if orbsym is not None:
orbsym = orbsym[las.ncore:las.ncore + las.ncas]
wfnsym = 0
idx_all = np.ones(nroots, dtype=np.bool_)
rand_mat = np.random.rand(57, 57)
rand_mat += rand_mat.T
e, si = linalg.eigh(rand_mat)
def tearDownModule():
global mol, mf, las
mol.stdout.close()
del mol, mf, las
mol.build()
mf = scf.RHF(mol).run()
las = LASSCF(mf, (4, 4), (4, 4), spin_sub=(1, 1))
las.state_average_(weights=[
1.0 / 7.0,
] * 7,
spins=[[0, 0], [0, 0], [2, -2], [-2, 2], [0, 0], [0, 0],
[2, 2]],
smults=[[1, 1], [3, 3], [3, 3], [3, 3], [1, 1], [1, 1],
[3, 3]],
wfnsyms=[
['A\'', 'A\''],
] * 4 + [['A"', 'A\''], ['A\'', 'A"'], ['A\'', 'A\'']])
las.frozen = list(range(las.mo_coeff.shape[-1]))
ugg = las.get_ugg()
las.mo_coeff = las.label_symmetry_(np.loadtxt('test_lassi_symm_mo.dat'))
las.ci = ugg.unpack(np.loadtxt('test_lassi_symm_ci.dat'))[1]
#las.set (conv_tol_grad=1e-8).run ()
las.e_states = las.energy_nuc() + las.states_energy_elec()
e_roots, si = las.lassi()
rdm1s, rdm2s = roots_make_rdm12s(las, las.ci, si)
def tearDownModule():
global mol, mf, las
mol.stdout.close()
del mol, mf, las
class KnownValues(unittest.TestCase):
def test_evals(self):