def test_ener_shift(self):
dp_random.seed(0)
data = DeepmdDataSystem(['system_0', 'system_1'], 5, 10, 1.0)
data.add('energy', 1, must=True)
ener_shift0 = data.compute_energy_shift(rcond=1)
all_stat = make_stat_input(data, 4, merge_sys=False)
ener_shift1 = EnerFitting._compute_output_stats(all_stat, rcond=1)
np.testing.assert_almost_equal(ener_shift0, ener_shift1)
def test_ener_shift(self):
dp_random.seed(0)
data = DeepmdDataSystem(['system_0', 'system_1'], 5, 10, 1.0)
data.add('energy', 1, must=True)
ener_shift0 = data.compute_energy_shift(rcond=1)
all_stat = make_stat_input(data, 4, merge_sys=False)
descrpt = DescrptSeA(6.0,
5.8, [46, 92],
neuron=[25, 50, 100],
axis_neuron=16)
fitting = EnerFitting(descrpt, neuron=[240, 240, 240], resnet_dt=True)
ener_shift1 = fitting._compute_output_stats(all_stat, rcond=1)
np.testing.assert_almost_equal(ener_shift0, ener_shift1)
def test_merge_all_stat(self):
dp_random.seed(0)
data0 = DeepmdDataSystem(['system_0', 'system_1'], 5, 10, 1.0)
data0.add('energy', 1, must=True)
dp_random.seed(0)
data1 = DeepmdDataSystem(['system_0', 'system_1'], 5, 10, 1.0)
data1.add('energy', 1, must=True)
dp_random.seed(0)
data2 = DeepmdDataSystem(['system_0', 'system_1'], 5, 10, 1.0)
data2.add('energy', 1, must=True)
dp_random.seed(0)
all_stat_0 = make_stat_input(data0, 10, merge_sys=False)
dp_random.seed(0)
all_stat_1 = make_stat_input(data1, 10, merge_sys=True)
all_stat_2 = merge_sys_stat(all_stat_0)
dp_random.seed(0)
all_stat_3 = _make_all_stat_ref(data2, 10)
####################################
# only check if the energy is concatenated correctly
####################################
dd = 'energy'
# if 'find_' in dd: continue
# if 'natoms_vec' in dd: continue
# if 'default_mesh' in dd: continue
# print(all_stat_2[dd])
# print(dd, all_stat_1[dd])
d1 = np.array(all_stat_1[dd])
d2 = np.array(all_stat_2[dd])
d3 = np.array(all_stat_3[dd])
# print(dd)
# print(d1.shape)
# print(d2.shape)
# self.assertEqual(all_stat_2[dd], all_stat_1[dd])
self._comp_data(d1, d2)
self._comp_data(d1, d3)
def test_ener_shift_assigned(self):
dp_random.seed(0)
ae0 = dp_random.random()
data = DeepmdDataSystem(['system_0'], 5, 10, 1.0)
data.add('energy', 1, must=True)
all_stat = make_stat_input(data, 4, merge_sys=False)
descrpt = DescrptSeA(6.0,
5.8, [46, 92],
neuron=[25, 50, 100],
axis_neuron=16)
fitting = EnerFitting(descrpt,
neuron=[240, 240, 240],
resnet_dt=True,
atom_ener=[ae0, None, None])
ener_shift1 = fitting._compute_output_stats(all_stat, rcond=1)
# check assigned energy
np.testing.assert_almost_equal(ae0, ener_shift1[0])
# check if total energy are the same
natoms = data.natoms_vec[0][2:]
tot0 = np.dot(data.compute_energy_shift(rcond=1), natoms)
tot1 = np.dot(ener_shift1, natoms)
np.testing.assert_almost_equal(tot0, tot1)