def test_zero_t_abs(algorithm, compress_method, ph_info, rtol, switch_to_64backend):
np.random.seed(0)
# print "data", value
procedure = [[1, 0], [1, 0], [1, 0]]
optimize_config = OptimizeConfig()
optimize_config.procedure = procedure
mol_list = parameter.custom_mol_list(None, *ph_info)
if algorithm == 1:
SpectraZeroT = SpectraOneWayPropZeroT
else:
SpectraZeroT = SpectraTwoWayPropZeroT
zero_t_corr = SpectraZeroT(
mol_list.switch_scheme(2), "abs", optimize_config, offset=parameter.offset
)
zero_t_corr.info_interval = 30
nsteps = 100
dt = 30.0
zero_t_corr.evolve(dt, nsteps)
with open(
os.path.join(
cur_dir, "ZeroTabs_" + str(algorithm) + str(compress_method) + ".npy"
),
"rb",
) as f:
std = np.load(f)
assert np.allclose(zero_t_corr.autocorr[:nsteps], std[:nsteps], rtol=rtol)
def test_zero_t_abs_mposcheme3(
algorithm, compress_method, ph_info, rtol, switch_to_64backend
):
np.random.seed(0)
# print "data", value
j_matrix = (
np.array([[0.0, -0.1, 0.0], [-0.1, 0.0, -0.3], [0.0, -0.3, 0.0]])
/ constant.au2ev
)
procedure = [[1, 0], [1, 0], [1, 0]]
mol_list = parameter.custom_mol_list(j_matrix, *ph_info)
nsteps = 50
dt = 30.0
if algorithm == 1:
SpectraZeroT = SpectraOneWayPropZeroT
else:
SpectraZeroT = SpectraTwoWayPropZeroT
optimize_config = OptimizeConfig()
optimize_config.procedure = procedure
zero_t_corr2 = SpectraZeroT(
mol_list, "abs", optimize_config, offset=parameter.offset
)
zero_t_corr2.evolve(dt, nsteps)
zero_t_corr3 = SpectraZeroT(
mol_list.switch_scheme(3), "abs", optimize_config, offset=parameter.offset
)
zero_t_corr3.evolve(dt, nsteps)
assert np.allclose(zero_t_corr2.autocorr, zero_t_corr3.autocorr, rtol=rtol)
def test_zero_t_abs(algorithm):
np.random.seed(0)
# print "data", value
procedure = [[1, 0], [1, 0], [1, 0]]
optimize_config = OptimizeConfig()
optimize_config.procedure = procedure
model = parameter.holstein_model
if algorithm == 1:
SpectraZeroT = SpectraOneWayPropZeroT
else:
SpectraZeroT = SpectraTwoWayPropZeroT
zero_t_corr = SpectraZeroT(model.switch_scheme(2),
"abs",
optimize_config,
offset=parameter.offset)
zero_t_corr.info_interval = 30
nsteps = 100
dt = 30.0
zero_t_corr.evolve(dt, nsteps)
with open(
os.path.join(cur_dir, "ZeroTabs_" + str(algorithm) + "svd.npy"),
"rb",
) as f:
std = np.load(f)
assert np.allclose(zero_t_corr.autocorr[:nsteps], std[:nsteps], rtol=1e-2)