def tmp(geom, mode_ind, nu_thresh=-5.):
org_coords = geom.coords.copy()
hessian = geom.hessian
mw_hess = geom.mw_hessian
start_result = do_analysis(geom, nu_thresh)
print(f"Distorting along mode #{mode_ind}")
mode = start_result.v[:, mode_ind]
# lengths = np.linspace(-2, 2, 41)
lengths = np.linspace(-1.5, 1.5, 31)
print(lengths)
coords_list = list()
M = np.sqrt(geom.masses_rep)
results = list()
mw_coords = geom.mw_coords.copy()
for l in lengths:
print(f"l={l:02f}")
new_coords = (mw_coords + l * mode) / M
geom.coords = new_coords
# res = do_analysis(geom)
# sys.stdout.flush()
# results.append(res)
coords_list.append(new_coords)
coords_to_trj("displaced.trj", geom.atoms, coords_list)
# with open("res", "wb") as handle: cloudpickle.dump(results, handle)
with open("res", "rb") as handle:
results = cloudpickle.load(handle)
energies = np.array([r.energy for r in results])
energies -= energies.min()
energies *= 2625.50
grad_norms = [np.linalg.norm(r.gradient) for r in results]
neg_nus = np.array([r.nus[:2] for r in results])
fig, (ax, ax2, ax3) = plt.subplots(nrows=3, sharex=True)
ax.plot(lengths, energies, "o--")
ax.set_title("Energies")
ax.set_ylabel("$\Delta$E / kJ mol⁻¹")
ax2.plot(lengths, grad_norms, "o--")
ax2.set_ylabel("Hartree Bohr⁻¹")
ax2.set_title("norm(gradient)")
width = .025
for i, modes in enumerate(neg_nus.T):
ax3.bar(lengths + i * width, modes, width=width)
ax3.set_xlabel("l")
ax3.set_ylabel(r"$\nu$ / cm⁻¹")
plt.tight_layout()
plt.show()
fig.savefig("imgkill.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 test_freq_distort():
geom = geom_from_xyz_file("final_geometry.xyz")
print(geom)
# calc = ORCA("")
# print(calc)
# cwd = Path(".")
# results = calc.parse_hessian(cwd)
# print(results)
# hess = results["hessian"]
# np.save("hess", hess)
# hess = np.load("hess.npy")
hess = np.loadtxt("calculated_final_cart_hessian")
# print("Non-mass-weighted")
# w, v = np.linalg.eigh(hess)
# nus = eigval_to_wavenumber(w)
# neg_inds = w < 0
# print(w[neg_inds])
# print(nus[neg_inds])
# print("Mass-weighted")
mw_hess = geom.mass_weigh_hessian(hess)
# w, v = np.linalg.eigh(mw_hess)
# nus = eigval_to_wavenumber(w)
# neg_inds = w < 0
# print(w[neg_inds])
# print(nus[neg_inds])
# shaked = geom.copy()
# shaked.coords = shake_coords(shaked.coords, scale=0.05, seed=25032018)
# shaked.set_calculator(XTB(pal=4, base_name="shake"))
# shess = shaked.hessian
# sw, sv = np.linalg.eigh(shess)
# with open("shaked.xyz", "w") as handle:
# handle.write(shaked.as_xyz())
print("Eckart projected")
proj_hess = geom.eckart_projection(mw_hess)
w, v = np.linalg.eigh(proj_hess)
nus = eigval_to_wavenumber(w)
neg_inds = w < 0
print(w[neg_inds])
print(nus[neg_inds])
imag_mode = v[:, 0]
print(imag_mode)
lengths = np.linspace(-1, 1, 21)
print(lengths)
coords_list = list()
M = np.sqrt(geom.masses_rep)
for l in lengths:
new_coords = (geom.mw_coords + l * imag_mode) / M
coords_list.append(new_coords)
coords_to_trj("displaced.trj", geom.atoms, coords_list)
# calc = XTB(pal=4)
# geom.set_calculator(calc)
# energies = list()
# for cs in coords_list:
# geom.coords = cs
# energy = geom.energy
# energies.append(energy)
# pass
# print(energies)
# energies = np.array(energies)
# np.save("energies", energies)
energies = np.load("energies.npy")
energies -= energies.min()
energies *= 2625.25
def func_harmonic(x, a, b, c):
return a + b * (x + c)**2
fromto = 4
slice_ = slice(fromto, -fromto + 1)
ydata = energies[slice_]
xdata = np.arange(energies.size)[slice_]
popt, pcov = curve_fit(func_harmonic, xdata, ydata)
print("popt")
print(popt)
print("pcov")
print(pcov)
fig, ax = plt.subplots()
ax.plot(energies, "o-", label="True")
ax.plot(xdata, func_harmonic(xdata, *popt), "--", label="Harmonic")
ax.legend()
plt.show()
pass
def freq_distort(geom, mode_ind):
print(geom)
hess = geom.hessian
mw_hess = geom.mass_weigh_hessian(hess)
# w, v = np.linalg.eigh(mw_hess)
# nus = eigval_to_wavenumber(w)
# neg_inds = w < 0
# print(w[neg_inds])
# print(nus[neg_inds])
# shaked = geom.copy()
# shaked.coords = shake_coords(shaked.coords, scale=0.05, seed=25032018)
# shaked.set_calculator(XTB(pal=4, base_name="shake"))
# shess = shaked.hessian
# sw, sv = np.linalg.eigh(shess)
# with open("shaked.xyz", "w") as handle:
# handle.write(shaked.as_xyz())
print("Eckart projected")
proj_hess = geom.eckart_projection(mw_hess)
w, v = np.linalg.eigh(proj_hess)
nus = eigval_to_wavenumber(w)
neg_inds = w < 0
print(w[neg_inds])
print(nus[neg_inds])
imag_mode = v[:, mode_ind]
print(imag_mode)
lengths = np.linspace(-1, 1, 21)
print(lengths)
coords_list = list()
M = np.sqrt(geom.masses_rep)
for l in lengths:
new_coords = (geom.mw_coords + l * imag_mode) / M
coords_list.append(new_coords)
coords_to_trj("displaced.trj", geom.atoms, coords_list)
energies = list()
for cs in coords_list:
geom.coords = cs
energy = geom.energy
energies.append(energy)
pass
print(energies)
energies = np.array(energies)
np.save("energies", energies)
# energies -= energies.min()
# energies *= 2625.25
def func_harmonic(x, a, b, c):
return a + b * (x + c)**2
fromto = 4
slice_ = slice(fromto, -fromto + 1)
ydata = energies[slice_]
xdata = np.arange(energies.size)[slice_]
popt, pcov = curve_fit(func_harmonic, xdata, ydata)
print("popt")
print(popt)
print("pcov")
print(pcov)
fig, ax = plt.subplots()
ax.plot(energies, "o-", label="True")
ax.plot(xdata, func_harmonic(xdata, *popt), "--", label="Harmonic")
ax.legend()
plt.show()
pass