def _get_potential_data(pkey):
"""return data to create a potential,
and accompanying structure data and expected output data to test it with
"""
if pkey == "eam":
pair_style = "eam"
with io.open(os.path.join(TEST_DIR, "input_files",
"Fe_mm.eam.fs")) as handle:
potential_dict = {
"type": "fs",
"file_contents": handle.readlines(),
"element_names": ["Fe"],
}
structure = get_structure_data("Fe")
output_dict = {"initial_energy": -8.2441284, "energy": -8.2448702}
elif pkey == "lennard-jones":
structure = get_structure_data("Ar")
# Example LJ parameters for Argon. These may not be accurate at all
pair_style = "lennard_jones"
potential_dict = {
"1 1": "0.01029 3.4 3.5",
# '2 2': '1.0 1.0 2.5',
# '1 2': '1.0 1.0 2.5'
}
output_dict = {
"initial_energy": 0.0,
"energy": 0.0, # TODO should LJ energy be 0?
}
elif pkey == "tersoff":
structure = get_structure_data("GaN")
potential_dict = {
"Ga Ga Ga":
"1.0 0.007874 1.846 1.918000 0.75000 -0.301300 1.0 1.0 1.44970 410.132 2.87 0.15 1.60916 535.199",
"N N N":
"1.0 0.766120 0.000 0.178493 0.20172 -0.045238 1.0 1.0 2.38426 423.769 2.20 0.20 3.55779 1044.77",
"Ga Ga N":
"1.0 0.001632 0.000 65.20700 2.82100 -0.518000 1.0 0.0 0.00000 0.00000 2.90 0.20 0.00000 0.00000",
"Ga N N":
"1.0 0.001632 0.000 65.20700 2.82100 -0.518000 1.0 1.0 2.63906 3864.27 2.90 0.20 2.93516 6136.44",
"N Ga Ga":
"1.0 0.001632 0.000 65.20700 2.82100 -0.518000 1.0 1.0 2.63906 3864.27 2.90 0.20 2.93516 6136.44",
"N Ga N ":
"1.0 0.766120 0.000 0.178493 0.20172 -0.045238 1.0 0.0 0.00000 0.00000 2.20 0.20 0.00000 0.00000",
"N N Ga":
"1.0 0.001632 0.000 65.20700 2.82100 -0.518000 1.0 0.0 0.00000 0.00000 2.90 0.20 0.00000 0.00000",
"Ga N Ga":
"1.0 0.007874 1.846 1.918000 0.75000 -0.301300 1.0 0.0 0.00000 0.00000 2.87 0.15 0.00000 0.00000",
}
pair_style = "tersoff"
output_dict = {"initial_energy": -18.109886, "energy": -18.110852}
elif pkey == "reaxff":
from aiida_lammps.common.reaxff_convert import (
filter_by_species,
read_lammps_format,
)
pair_style = "reaxff"
with io.open(
os.path.join(TEST_DIR, "input_files",
"FeCrOSCH.reaxff")) as handle:
potential_dict = read_lammps_format(
handle.read().splitlines(), tolerances={"hbonddist": 7.0})
potential_dict = filter_by_species(potential_dict,
["Fe core", "S core"])
for n in ["anglemin", "angleprod", "hbondmin", "torsionprod"]:
potential_dict["global"].pop(n)
potential_dict["control"] = {"safezone": 1.6}
# potential_dict = {
# "file_contents": handle.readlines(),
# "control": {"safezone": 1.6},
# "global": {"hbonddist": 7.0},
# }
structure = get_structure_data("pyrite")
output_dict = {
"initial_energy": -1027.9739,
"energy": -1030.3543,
"units": "real",
}
else:
raise ValueError("Unknown potential key: {}".format(pkey))
return potential_data(pair_style, potential_dict, structure,
output_dict)
def _get_potential_data(pkey):
"""return data to create a potential,
and accompanying structure data and expected output data to test it with
"""
if pkey == 'eam':
pair_style = 'eam'
filename = os.path.join(
TEST_DIR,
'input_files',
'potentials',
'Fe_mm.eam.fs',
)
with io.open(filename) as handle:
potential_dict = {
'type': 'fs',
'file_contents': handle.readlines(),
'element_names': ['Fe'],
}
structure = get_structure_data('Fe')
output_dict = {'initial_energy': -8.2441284, 'energy': -8.2448702}
elif pkey == 'lennard-jones':
structure = get_structure_data('Ar')
# Example LJ parameters for Argon. These may not be accurate at all
pair_style = 'lennard_jones'
potential_dict = {
'1 1': '0.01029 3.4 3.5',
}
output_dict = {
'initial_energy': 0.0,
'energy': 0.0, # TODO should LJ energy be 0?
}
elif pkey == 'tersoff':
structure = get_structure_data('GaN')
potential_dict = {
'Ga Ga Ga':
'1.0 0.007874 1.846 1.918000 0.75000 -0.301300 '+\
'1.0 1.0 1.44970 410.132 2.87 0.15 1.60916 535.199',
'N N N':
'1.0 0.766120 0.000 0.178493 0.20172 -0.045238 '+\
'1.0 1.0 2.38426 423.769 2.20 0.20 3.55779 1044.77',
'Ga Ga N':
'1.0 0.001632 0.000 65.20700 2.82100 -0.518000 '+\
'1.0 0.0 0.00000 0.00000 2.90 0.20 0.00000 0.00000',
'Ga N N':
'1.0 0.001632 0.000 65.20700 2.82100 -0.518000 '+\
'1.0 1.0 2.63906 3864.27 2.90 0.20 2.93516 6136.44',
'N Ga Ga':
'1.0 0.001632 0.000 65.20700 2.82100 -0.518000 '+\
'1.0 1.0 2.63906 3864.27 2.90 0.20 2.93516 6136.44',
'N Ga N ':
'1.0 0.766120 0.000 0.178493 0.20172 -0.045238 '+\
'1.0 0.0 0.00000 0.00000 2.20 0.20 0.00000 0.00000',
'N N Ga':
'1.0 0.001632 0.000 65.20700 2.82100 -0.518000 '+\
'1.0 0.0 0.00000 0.00000 2.90 0.20 0.00000 0.00000',
'Ga N Ga':
'1.0 0.007874 1.846 1.918000 0.75000 -0.301300 '+\
'1.0 0.0 0.00000 0.00000 2.87 0.15 0.00000 0.00000',
}
pair_style = 'tersoff'
output_dict = {'initial_energy': -18.109886, 'energy': -18.110852}
elif pkey == 'reaxff':
pair_style = 'reaxff'
filename = os.path.join(
TEST_DIR,
'input_files',
'potentials',
'FeCrOSCH.reaxff',
)
with io.open(filename) as handle:
potential_dict = read_lammps_format(
handle.read().splitlines(),
tolerances={'hbonddist': 7.0},
)
potential_dict = filter_by_species(
potential_dict,
['Fe core', 'S core'],
)
for name in [
'anglemin', 'angleprod', 'hbondmin', 'torsionprod'
]:
potential_dict['global'].pop(name)
potential_dict['control'] = {'safezone': 1.6}
structure = get_structure_data('pyrite')
output_dict = {
'initial_energy': -1027.9739,
'energy': -1030.3543,
'units': 'real',
}
else:
raise ValueError(f'Unknown potential key: {pkey}')
return PotentialData(
pair_style,
potential_dict,
structure,
output_dict,
)
def test_round_trip_lammps_format2(file_regression):
"""Check that one can write the reaxff potential in the second format"""
data = read_lammps_format(lammps_file2.splitlines())
output = write_lammps_format(data)
file_regression.check(output)
def test_read_lammps_format2(data_regression):
"""Check that the reaxff potential is compatible with the second lammps format"""
output = read_lammps_format(lammps_file2.splitlines())
data_regression.check(output)
def test_round_trip_lammps_format2(file_regression):
data = read_lammps_format(lammps_file2.splitlines())
output = write_lammps_format(data)
file_regression.check(output)
def test_read_lammps_format2(data_regression):
output = read_lammps_format(lammps_file2.splitlines())
data_regression.check(output)