class Input:
def __init__(self):
self.control = LammpsControl()
self.potential = LammpsPotential()
def to_hdf(self, hdf5):
"""
Args:
hdf5:
Returns:
"""
with hdf5.open("input") as hdf5_input:
self.control.to_hdf(hdf5_input)
self.potential.to_hdf(hdf5_input)
def from_hdf(self, hdf5):
"""
Args:
hdf5:
Returns:
"""
with hdf5.open("input") as hdf5_input:
self.control.from_hdf(hdf5_input)
self.potential.from_hdf(hdf5_input)
class Input:
def __init__(self):
self.control = LammpsControl()
self.potential = LammpsPotential()
self.bond_dict = dict()
# Set default bond parameters
self._load_default_bond_params()
def _load_default_bond_params(self):
"""
Function to automatically load a few default bond params (wont automatically write them)
"""
# Default bond properties of a water molecule
self.bond_dict["O"] = dict()
self.bond_dict["O"]["element_list"] = ["H"]
self.bond_dict["O"]["cutoff_list"] = [2.0]
self.bond_dict["O"]["max_bond_list"] = [2]
self.bond_dict["O"]["bond_type_list"] = [1]
self.bond_dict["O"]["angle_type_list"] = [1]
def to_hdf(self, hdf5):
"""
Args:
hdf5:
Returns:
"""
with hdf5.open("input") as hdf5_input:
self.control.to_hdf(hdf5_input)
self.potential.to_hdf(hdf5_input)
def from_hdf(self, hdf5):
"""
Args:
hdf5:
Returns:
"""
with hdf5.open("input") as hdf5_input:
self.control.from_hdf(hdf5_input)
self.potential.from_hdf(hdf5_input)
if "bond_dict" in hdf5_input.list_nodes():
self.bond_dict = hdf5_input["bond_dict"]
def test_generate_seed_from_job(self):
lc = LammpsControl()
job_hash_dict = {
"job_0_0": lc.generate_seed_from_job(job_name="job_0", seed=0),
"job_0_1": lc.generate_seed_from_job(job_name="job_0", seed=1),
"job_0_2": lc.generate_seed_from_job(job_name="job_0", seed=2),
"job_1_0": lc.generate_seed_from_job(job_name="job_1", seed=0),
"job_1_1": lc.generate_seed_from_job(job_name="job_1", seed=1),
"job_1_2": lc.generate_seed_from_job(job_name="job_1", seed=2),
}
self.assertEqual(job_hash_dict["job_0_0"], 94639)
self.assertEqual(job_hash_dict["job_0_1"], 84051)
self.assertEqual(job_hash_dict["job_0_2"], 50062)
self.assertEqual(job_hash_dict["job_1_0"], 84649)
self.assertEqual(job_hash_dict["job_1_1"], 99268)
self.assertEqual(job_hash_dict["job_1_2"], 45752)
def test_generate_seed_from_job(self):
lc = LammpsControl()
job_hash_dict = {
'job_0_0': lc.generate_seed_from_job(job_name='job_0', seed=0),
'job_0_1': lc.generate_seed_from_job(job_name='job_0', seed=1),
'job_0_2': lc.generate_seed_from_job(job_name='job_0', seed=2),
'job_1_0': lc.generate_seed_from_job(job_name='job_1', seed=0),
'job_1_1': lc.generate_seed_from_job(job_name='job_1', seed=1),
'job_1_2': lc.generate_seed_from_job(job_name='job_1', seed=2)
}
self.assertEqual(job_hash_dict['job_0_0'], 94639)
self.assertEqual(job_hash_dict['job_0_1'], 84051)
self.assertEqual(job_hash_dict['job_0_2'], 50062)
self.assertEqual(job_hash_dict['job_1_0'], 84649)
self.assertEqual(job_hash_dict['job_1_1'], 99268)
self.assertEqual(job_hash_dict['job_1_2'], 45752)
def __init__(self):
self.control = LammpsControl()
self.potential = LammpsPotential()
self.bond_dict = dict()
# Set default bond parameters
self._load_default_bond_params()
def __init__(self):
self.control = LammpsControl()
self.potential = LammpsPotential()
def test_pressure_to_lammps(self):
lc = LammpsControl()
# Correct normalization without rotation. Note that we convert from GPa to bar for LAMMPS.
no_rot = np.identity(3)
cnv = LAMMPS_UNIT_CONVERSIONS[lc["units"]]["pressure"]
self.assertTrue(np.isclose(lc.pressure_to_lammps(0.0, no_rot), 0.0))
self.assertTrue(
np.isclose(lc.pressure_to_lammps(1.0, no_rot), 1.0 * cnv))
for input_pressure in ([1.0, 2.0,
3.0], [1.0, 2.0, 3.0, None, None, None],
[None, None, None, None, None,
2.0], [1.0, 2.0, 3.0, 4.0, 5.0,
6.0], np.random.uniform(-1, 1, 6),
np.random.uniform(-1, 1, 6)):
output_pressure = [
p * cnv if p is not None else None for p in input_pressure
]
out = lc.pressure_to_lammps(input_pressure, no_rot)
for out_i, ref_i in zip(out, output_pressure):
self.assertTrue((out_i is None and ref_i is None)
or np.isclose(out_i, ref_i))
# Check if invalid input raises exceptions.
with self.assertRaises(ValueError):
lc.pressure_to_lammps("foo", no_rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([], no_rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([1, 2, 3, 4, 5, 6, 7], no_rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([None, None, None, None, None, None], no_rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps(["foo", "bar"], no_rot)
# With rotation.
rot = Rotation.random().as_matrix()
self.assertTrue(np.isclose(lc.pressure_to_lammps(0.0, rot), 0.0))
self.assertTrue(np.isclose(lc.pressure_to_lammps(1.0, rot), 1.0 * cnv))
tmp = lc.pressure_to_lammps([1.0, 1.0, 1.0], rot)
self.assertTrue(
np.all(np.isclose(tmp[:3], [1.0 * cnv, 1.0 * cnv, 1.0 * cnv]))
and tmp[3] == tmp[4] == tmp[5] == None)
tmp = lc.pressure_to_lammps([1.0, 1.0, 1.0, None, None, None], rot)
self.assertTrue(
np.all(np.isclose(tmp[:3], [1.0 * cnv, 1.0 * cnv, 1.0 * cnv]))
and tmp[3] == tmp[4] == tmp[5] == None)
del tmp
for input_pressure in ([1.0, 1.0, 1.0, 0.0, 0.0,
0.0], [1.0, 2.0, 3.0, 0.0, 0.0,
0.0], [1.0, 2.0, 3.0, 4.0, 5.0, 6.0],
[1.0, -2.0, 3.0, -4.0, -5.0,
6.0], np.random.uniform(-1, 1, 6),
np.random.uniform(-1, 1, 6)):
output_pressure = np.array(
[[input_pressure[0], input_pressure[3], input_pressure[4]],
[input_pressure[3], input_pressure[1], input_pressure[5]],
[input_pressure[4], input_pressure[5], input_pressure[2]]])
output_pressure = rot.T @ output_pressure @ rot
output_pressure = output_pressure[[0, 1, 2, 0, 0, 1],
[0, 1, 2, 1, 2, 2]] * cnv
out = lc.pressure_to_lammps(input_pressure, rot)
self.assertTrue(np.all(np.isclose(out, output_pressure)))
# Check if invalid input raises exceptions.
with self.assertRaises(ValueError):
lc.pressure_to_lammps([1.0], rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([1.0, None, None], rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([1.0, None, None, None, None, None], rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([1.0, 2.0, 3.0, None, None, None], rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([None, 1.0, 1.0, 0.0, 0.0, 0.0], rot)
with self.assertRaises(ValueError):
lc.pressure_to_lammps([None, 1.0, 1.0, 1.0, 2.0, 3.0], rot)
def test_mean(self):
lc = LammpsControl()
lc.measure_mean_value('energy_pot')
self.assertEqual(
lc['fix___mean_energy_pot'],
'all ave/time 1 ${mean_repeat_times} ${thermotime} v_energy_pot')
lc.measure_mean_value('pressures')
self.assertEqual(lc['variable___pressure_1'], 'equal pyy')
lc.measure_mean_value('energy_tot', 2)
self.assertEqual(
lc['fix___mean_energy_tot'],
'all ave/time 2 ${mean_repeat_times} ${thermotime} v_energy_tot')
lc.measure_mean_value('volume')
lc.measure_mean_value('temperature')
lc.measure_mean_value('positions')
self.assertEqual(lc['compute___unwrap'], 'all property/atom xu yu zu')
lc.measure_mean_value('forces')
self.assertEqual(lc['variable___forces_0'], 'atom fx')
lc.measure_mean_value('velocities')
self.assertEqual(lc['variable___velocities_0'], 'atom vx')
with self.assertWarns(Warning):
lc.measure_mean_value('pe**2', name='pepe')
with self.assertRaises(NotImplementedError):
lc.measure_mean_value('something')
