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# fmt: off
import numpy as np
import pytest
from ase import units
from ase.build import bulk
from ase.calculators.emt import EMT
from ase.md.bussi import Bussi
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
def test_bussi():
atoms = bulk("Pt")
atoms.calc = EMT()
with pytest.raises(ValueError):
with Bussi(atoms, 0.1 * units.fs, 300, 100 * units.fs) as dyn:
dyn.run(1)
MaxwellBoltzmannDistribution(
atoms, temperature_K=300, rng=np.random.default_rng(seed=42)
)
with Bussi(
atoms,
0.1 * units.fs,
300,
100 * units.fs,
) as dyn:
dyn.run(10)
assert dyn.taut == 100 * units.fs
assert dyn.temp == 300 * units.kB
assert dyn.dt == 0.1 * units.fs
assert dyn.ndof == 3
assert dyn.target_kinetic_energy == 0.5 * dyn.temp * dyn.ndof
assert dyn.transferred_energy != 0.0
def test_bussi_transfered_energy_conservation():
atoms = bulk("Cu") * (4, 4, 4)
atoms.calc = EMT()
MaxwellBoltzmannDistribution(
atoms, temperature_K=300, rng=np.random.default_rng(seed=42)
)
conserved_quantity = []
with Bussi(
atoms,
1.0e-5 * units.fs,
300,
100 * units.fs,
rng=np.random.default_rng(seed=42),
) as dyn:
for _ in dyn.irun(100):
conserved_quantity.append(
dyn.atoms.get_total_energy() - dyn.transferred_energy
)
assert np.unique(np.round(conserved_quantity, 10)).size == 1
def test_bussi_paranoia_check():
"""Test that check if the average temperature
of the system is close to the target temperature.
From Giovanni Bussi:
As a further paranoia check, you can try to run a simulation with:
- tiny timestep (say 1e-100) so that atoms do not move
- tiny tau (say 1e-100) so that kinetic energy equilibrates anyway
The distribution of the kinetic energy should converge
quickly to the correct one."""
atoms = bulk("Cu") * (3, 3, 3)
atoms.calc = EMT()
MaxwellBoltzmannDistribution(
atoms,
temperature_K=300,
rng=np.random.default_rng(seed=10),
force_temp=True,
)
temperatures = []
with Bussi(
atoms,
1.0e-100 * units.fs,
300,
1.0e-100 * units.fs,
rng=np.random.default_rng(seed=10),
) as dyn:
for _ in dyn.irun(1000):
temperatures.append(dyn.atoms.get_temperature())
assert np.mean(temperatures) == pytest.approx(300, abs=5.0)
def test_bussi_paranoia_check2():
"""We test even DOF"""
atoms = bulk("Cu") * (4, 4, 4)
atoms.calc = EMT()
MaxwellBoltzmannDistribution(
atoms,
temperature_K=300,
rng=np.random.default_rng(seed=91),
force_temp=True,
)
temperatures = []
with Bussi(
atoms,
1.0e-100 * units.fs,
300,
1.0e-100 * units.fs,
rng=np.random.default_rng(seed=91),
) as dyn:
for _ in dyn.irun(1000):
temperatures.append(dyn.atoms.get_temperature())
assert np.mean(temperatures) == pytest.approx(300, abs=5.0)
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