def test_adc2_shift_invert_triplets(self):
refdata = cache.reference_data["h2o_sto3g"]
matrix = adcc.AdcMatrix("adc2", LazyMp(cache.refstate["h2o_sto3g"]))
conv_tol = 1e-5
shift = -0.5
# Construct shift and inverted matrix:
shinv = IterativeInverse(AdcMatrixShifted(matrix, shift),
conv_tol=conv_tol / 10,
Pinv=JacobiPreconditioner,
callback=cg_print)
# Solve for triplets
guesses = adcc.guesses_triplet(matrix, n_guesses=5, block="ph")
symm = IndexSpinSymmetrisation(matrix, enforce_spin_kind="triplet")
res = lanczos(shinv,
guesses,
n_ep=5,
callback=la_print,
explicit_symmetrisation=symm)
assert res.converged
# Undo spectral transformation and compare
eigenvalues = sorted(1 / res.eigenvalues - shift)
ref_triplets = refdata["adc2"]["triplet"]["eigenvalues"][:5]
assert eigenvalues == approx(ref_triplets)
def test_adc2_triplets(self):
refdata = cache.reference_data["h2o_sto3g"]
matrix = adcc.AdcMatrix("adc2", LazyMp(cache.refstate["h2o_sto3g"]))
# Solve for triplets
guesses = adcc.guesses_triplet(matrix, n_guesses=10, block="s")
res = jacobi_davidson(matrix, guesses, n_ep=10)
ref_triplets = refdata["adc2"]["triplet"]["eigenvalues"]
assert res.converged
assert res.eigenvalues == approx(ref_triplets)
def test_adc2_triplets(self):
refdata = cache.reference_data["h2o_sto3g"]
matrix = adcc.AdcMatrix("adc2", LazyMp(cache.refstate["h2o_sto3g"]))
# Solve for triplets
guesses = adcc.guesses_triplet(matrix, n_guesses=6, block="ph")
res = lanczos(matrix, guesses, n_ep=6, which="SM")
ref_triplets = refdata["adc2"]["triplet"]["eigenvalues"][:6]
assert res.converged
assert res.eigenvalues == approx(ref_triplets)
def make_mock_adc_state(refstate, matmethod, kind, reference):
ground_state = LazyMp(refstate, CacheAllPolicy())
matrix = AdcMatrix(matmethod, ground_state)
# Number of full state results
n_full = len(reference[kind]["eigenvectors_singles"])
state = AdcMockState(matrix)
state.method = matrix.method
state.ground_state = ground_state
state.reference_state = refstate
state.kind = kind
state.eigenvalues = reference[kind]["eigenvalues"][:n_full]
spin_change = 0
if refstate.restricted and kind == "singlet":
symm = "symmetric"
elif refstate.restricted and kind == "triplet":
symm = "antisymmetric"
elif kind in ["state", "spin_flip"]:
symm = "none"
else:
raise ValueError("Unknown kind: {}".format(kind))
state.eigenvectors = [
guess_zero(matrix,
irrep="A",
spin_change=spin_change,
spin_block_symmetrisation=symm) for i in range(n_full)
]
has_doubles = "eigenvectors_doubles" in reference[kind]
vec_singles = reference[kind]["eigenvectors_singles"]
vec_doubles = reference[kind].get("eigenvectors_doubles", None)
for i, evec in enumerate(state.eigenvectors):
evec["s"].set_from_ndarray(vec_singles[i])
if has_doubles:
evec["d"].set_from_ndarray(vec_doubles[i], 1e-14)
return ExcitedStates(state)