def xyz_rdf(name):
os.chdir(
'/home/jinho93/oxides/cluster/zno/cp2k/1.aimd/3.16A/30/3.fix/2.again')
mole = IMolecule.from_file('tail.xyz')
# mole = IMolecule.from_str(out, fmt='xyz')
s = mole.get_boxed_structure(1.6027345000000000E+01,
1.6671211000000000E+01,
6.0678892000000005E+01)
structures = [s]
ind = []
ref = []
print(name)
for i, sp in enumerate(s.sites):
print(sp.z)
up = .7
down = .66
if sp.species_string == name and up > sp.c > down:
ind.append(i)
elif sp.species_string == 'O' and up + 0.05 > sp.c > down - 0.05:
ref.append(i)
r = RadialDistributionFunction(structures,
ind,
reference_indices=ref,
ngrid=301,
sigma=.1)
print(r.peak_r[0])
r.get_rdf_plot(plt=plt, ylim=[-0.005, max(r.rdf)], label=f'{name}-ref')
r.export_rdf('rdf.dat')
plt.show()
def xdat_rdf_speices(name):
import matplotlib.pyplot as plt
from pymatgen_diffusion.aimd.van_hove import RadialDistributionFunction
s = Xdatcar('XDATCAR').structures[-1:]
ind = []
ref = []
for i, sp in enumerate(s[0].species):
if sp.name == name:
ind.append(i)
elif sp.name == 'O':
ref.append(i)
r = RadialDistributionFunction(s, ind, reference_indices=ref, ngrid=501, sigma=.1)
print(r.peak_r[0])
r.get_rdf_plot(plt=plt, ylim=[-0.005, max(r.rdf)], label=f'{name}-ref')
r.export_rdf('/home/jinho93/rdf.dat')
plt.show()
import os
import numpy as np
from pymatgen.io.vasp import Xdatcar
from pymatgen_diffusion.aimd.van_hove import RadialDistributionFunction, plt
from pymatgen import Structure
if __name__ == '__main__':
structure = Structure.from_file('POSCAR')
num = 4
fig = plt.figure(0)
output = np.zeros((201, num))
output[:, 0] = np.linspace(0.0, 10, 201)
for c in range(num - 1):
oxy = []
for i, j in enumerate(structure.sites):
if j.species_string == "O" and c / num < j.c < (c + 1) / num:
oxy.append(i)
zn = []
for i, j in enumerate(structure.sites):
if j.species_string == "Zn":
zn.append(i)
ax = fig.add_subplot(221 + c)
rdf = RadialDistributionFunction([structure], oxy, zn, ngrid=201)
rdf.get_rdf_plot(ylim=(0, max(rdf.rdf)))
output[:, c + 1] = rdf.rdf
np.savetxt('output.dat', output)
plt.show()