def test_oniom_md():
calc_dict = {
"high": {
"type": "pypsi4",
"method": "scf",
"basis": "sto-3g",
},
"low": {
"type": "pyxtb",
},
}
high_inds = (4, 5, 6)
from pysisyphus.calculators.ONIOM import ONIOM
oniom = ONIOM(calc_dict, high_inds)
geom = geom_loader("lib:acetaldehyd_oniom.xyz")
geom.set_calculator(oniom)
v0 = .005 * np.random.rand(*geom.coords.shape)
md_kwargs = {
"v0": v0,
"t": 40,
"dt": 0.5,
}
md_result = md(geom, **md_kwargs)
from pysisyphus.xyzloader import make_trj_str
coords = md_result.coords.reshape(-1, len(geom.atoms), 3) * BOHR2ANG
trj_str = make_trj_str(geom.atoms, coords)
with open("md.trj", "w") as handle:
handle.write(trj_str)
def test_thermostat():
geom = geom_loader("lib:dynamics/10_water.xyz")
from pysisyphus.calculators.XTB import XTB
geom.set_calculator(XTB(pal=2))
opt = RFOptimizer(geom, thresh="gau_loose", max_cycles=25)
opt.run()
T = 298.15
seed = 20182503
v0 = get_mb_velocities_for_geom(geom, T, seed=seed).flatten()
# steps = 6000
steps = 250
dt = 0.5
md_kwargs = {
"v0": v0,
"steps": steps,
"dt": dt,
"remove_com_v": True,
"thermostat": "csvr",
"timecon": 25,
}
res = md(geom, **md_kwargs)
# assert dt * steps / 1000 == pytest.approx(res.t)
import matplotlib.pyplot as plt
E_tot = res.E_tot
E_tot -= E_tot.mean()
from pysisyphus.constants import AU2KJPERMOL
E_tot *= AU2KJPERMOL
T = res.T
fig, (ax0, ax1) = plt.subplots(nrows=2)
ax0.plot(E_tot)
ax0.axhline(E_tot.mean())
ax0.set_title("$\Delta$E$_{tot}$ / kJ mol⁻¹")
ax1.plot(T)
T_mean = T.mean()
print("T_mean", T_mean, "K")
ax1.axhline(T_mean)
ax1.set_title(f"T / K, avg. = {T_mean:.2f} K")
plt.tight_layout()
plt.show()
fig.savefig("md.pdf")
def test_rattle_tip3p(this_dir):
geom = geom_loader(this_dir / "output_10.xyz")
# geom = geom_loader(this_dir / "output_2.xyz")
# geom.jmol()
T = 298.15
calc = TIP3P()
potentials = [
{
"type": "logfermi",
"beta": 6,
"T": T,
"radius": 10,
},
]
ext_calc = ExternalPotential(calc, potentials=potentials)
geom.set_calculator(ext_calc)
constraints = list(
it.chain(
*[get_water_constraints(i) for i in range(len(geom.atoms) // 3)]))
seed = 20200626
v0 = get_mb_velocities_for_geom(geom, T, seed=seed).flatten()
md_kwargs = {
"v0": v0,
# "steps": 100,
# "dt": 1,
"steps": 250,
"dt": 1.5,
# "steps": 500,
# "dt": 0.25,
"constraints": constraints,
"constraint_kwargs": {
# "remove_com_v": False,
},
# "thermostat": "csvr",
}
# import pdb; pdb.set_trace()
md_result = md(geom, **md_kwargs)
from pysisyphus.xyzloader import coords_to_trj
coords = md_result.coords
trj_fn = "md.trj"
atoms = geom.atoms
coords_to_trj(trj_fn, atoms, coords)
def test_mb_velocities():
geom = geom_loader("lib:h2o.xyz")
geom.set_calculator(PySCF(basis="sto3g"))
# Preoptimization
opt = RFOptimizer(geom, thresh="gau_tight")
opt.run()
print()
T = 298.15
seed = 20182503
v0 = get_mb_velocities_for_geom(geom, T, seed=seed).flatten()
steps = 100
dt = 0.5
res = md(geom, v0, steps, dt)
assert dt * steps / 1000 == pytest.approx(res.t)
# import pdb; pdb.set_trace()
from pysisyphus.xyzloader import coords_to_trj
coords = res.coords
trj_fn = "md.trj"
atoms = geom.atoms
coords_to_trj(trj_fn, atoms, coords)
def run_md(geom, dt, steps, v0=None, term_funcs=None, external=False):
if external and hasattr(geom.calculator, "run_md"):
t = dt * steps
t_ps = t * 1e-3
md_kwargs = {
"atoms": geom.atoms,
"coords": geom.coords,
"t": t,
"dt": dt,
"velocities": v0,
"dump": dt,
}
print("Running MD with external calculator implementation.")
if term_funcs is not None:
print("Termination functions are not supported in external MD!")
geoms = geom.calculator.run_md(**md_kwargs)
md_result = MDResult(
coords=[geom.coords for geom in geoms],
t_ps=t_ps,
step=int(t / dt - 1),
terminated=None,
T=None,
E_tot=None,
)
else:
md_kwargs = {
"v0": v0,
"steps": steps,
"dt": dt,
"term_funcs": term_funcs,
"verbose": False,
"remove_com_v": False,
}
print("Running MD with internal implementation.")
md_result = md(geom, **md_kwargs)
return md_result
def test_velocity_verlet():
geom = AnaPot.get_geom((0.52, 1.80, 0))
x0 = geom.coords.copy()
v0 = .1 * np.random.rand(*geom.coords.shape)
t = 3
dts = (.005, .01, .02, .04, .08)
all_xs = list()
for dt in dts:
geom.coords = x0.copy()
md_kwargs = {
"v0": v0.copy(),
"t": t,
"dt": dt,
}
md_result = md(geom, **md_kwargs)
all_xs.append(md_result.coords)
calc = geom.calculator
calc.plot()
ax = calc.ax
for dt, xs in zip(dts, all_xs):
ax.plot(*xs.T[:2], "o-", label=f"dt={dt:.3f}")
# ax.plot(*xs.T[:2], "-", label=f"dt={dt:.3f}")
ax.legend()
plt.show()
