def phonon_dos(fcp_file):
if 'fcc2x2x2' in fcp_file:
prim = read(ref_fcc_conv2x2x2)
else:
prim = read(ref_fcc)
fcp = ForceConstantPotential.read(fcp_file)
mesh = [33, 33, 33]
atoms_phonopy = PhonopyAtoms(symbols=prim.get_chemical_symbols(),
scaled_positions=prim.get_scaled_positions(),
cell=prim.cell)
phonopy = Phonopy(atoms_phonopy,
supercell_matrix=5 * np.eye(3),
primitive_matrix=None)
supercell = phonopy.get_supercell()
supercell = Atoms(cell=supercell.cell,
numbers=supercell.numbers,
pbc=True,
scaled_positions=supercell.get_scaled_positions())
fcs = fcp.get_force_constants(supercell)
phonopy.set_force_constants(fcs.get_fc_array(order=2))
phonopy.set_mesh(mesh, is_eigenvectors=True, is_mesh_symmetry=False)
phonopy.run_total_dos()
phonopy.plot_total_DOS()
plt.savefig("phononDOS.png", dpi=200)
Nq = 51
G2X = get_band(np.array([0, 0, 0]), np.array([0.5, 0.5, 0]), Nq)
X2K2G = get_band(np.array([0.5, 0.5, 1.0]), np.array([0, 0, 0]), Nq)
G2L = get_band(np.array([0, 0, 0]), np.array([0.5, 0.5, 0.5]), Nq)
bands = [G2X, X2K2G, G2L]
phonopy.set_band_structure(bands)
phonopy.plot_band_structure()
xticks = plt.gca().get_xticks()
xticks = [x * hbar * 1e15 for x in xticks] # Convert THz to meV
# plt.gca().set_xticks(xticks)
plt.gca().set_xlabel("Frequency (THz)")
plt.savefig("phononBand.png", dpi=200)
phonopy.run_thermal_properties(t_step=10, t_max=800, t_min=100)
tp_dict = phonopy.get_thermal_properties_dict()
temperatures = tp_dict['temperatures']
free_energy = tp_dict['free_energy']
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(temperatures, free_energy)
plt.show()
# Integration with phonopy
from phonolammps import Phonolammps
from phonopy import Phonopy
phlammps = Phonolammps('in.lammps',
supercell_matrix=[[3, 0, 0], [0, 3, 0], [0, 0, 3]])
unitcell = phlammps.get_unitcell()
force_constants = phlammps.get_force_constants()
supercell_matrix = phlammps.get_supercell_matrix()
phonon = Phonopy(unitcell, supercell_matrix)
phonon.set_force_constants(force_constants)
phonon.set_mesh([20, 20, 20])
phonon.set_total_DOS()
phonon.plot_total_DOS().show()
phonon.set_thermal_properties()
phonon.plot_thermal_properties().show()
q_points, distances, frequencies, eigvecs = phonon.get_band_structure()
for q, d, freq in zip(q_points, distances, frequencies):
print q, d, freq
phonon.plot_band_structure().show()
# Mesh sampling 20x20x20
phonon.set_mesh([20, 20, 20])
phonon.set_thermal_properties(t_step=10,
t_max=1000,
t_min=0)
# DOS
phonon.set_total_DOS(sigma=0.1)
for omega, dos in np.array(phonon.get_total_DOS()).T:
print "%15.7f%15.7f" % (omega, dos)
phonon.plot_total_DOS().show()
# Thermal properties
for t, free_energy, entropy, cv in np.array(phonon.get_thermal_properties()).T:
print ("%12.3f " + "%15.7f" * 3) % ( t, free_energy, entropy, cv )
phonon.plot_thermal_properties().show()
# PDOS
phonon.set_mesh([10, 10, 10],
is_mesh_symmetry=False,
is_eigenvectors=True)
phonon.set_partial_DOS(tetrahedron_method=True)
omegas, pdos = phonon.get_partial_DOS()
pdos_indices = [[0], [1]]
phonon.plot_partial_DOS(pdos_indices=pdos_indices,
legend=pdos_indices).show()
def MVibrationauto(self, maxx=4500):
import os
import numpy as np
from pymatgen.io.phonopy import get_phonopy_structure
import pymatgen as pmg
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.io.vasp import Poscar
from pymatgen.symmetry.kpath import KPathSeek, KPathBase
from phonopy.phonon.band_structure import get_band_qpoints_and_path_connections
from phonopy import Phonopy
from phonopy.structure.atoms import Atoms as PhonopyAtoms
from pymatgen.phonon.plotter import PhononBSPlotter
from pymatgen.phonon.bandstructure import PhononBandStructureSymmLine
import csv
import pandas as pd
import matplotlib.pyplot as plt
os.chdir(self.dire)
print(os.getcwd())
poscar = Poscar.from_file("POSCAR")
structure = poscar.structure
scell = [[2, 0, 0], [0, 2, 0], [0, 0, 2]]
vrun = Vasprun("vasprun.xml")
phonopyAtoms = get_phonopy_structure(structure)
phonon = Phonopy(phonopyAtoms, scell)
phonon.set_force_constants(-vrun.force_constants)
# labels = ["$\\Gamma$", "X", "U", "K", "L"]
labels = ['K', "$\\Gamma$", 'L', 'W', 'X']
# bands = []
cd = KPathSeek(structure)
cds = cd.kpath
# print(cds)
for k, v in cds.items():
if "kpoints" in k:
dics = v
else:
dicss = v
print(dics)
print(dicss)
# bands=[]
# for k,v in dics.items():
# if k in dicss[0]:
# bands.append(v)
path = []
#
# bandd1=[]
# for k,v in dics.items():
# for i in dicss[0]:
# if k in i:
# bandd1.append(v)
# path.append(bandd1)
bandd1 = []
for i in dicss[1]:
for k, v in dics.items():
if k in i:
bandd1.append(v)
path.append(bandd1)
print(dicss[1])
qpoints, connections = get_band_qpoints_and_path_connections(
path, npoints=51)
phonon.run_band_structure(qpoints,
path_connections=connections,
labels=labels)
print(path)
# kpoints=cd.get_kpoints
# print(kpoints)
# phonon.set_band_structure(bands,labels=labels)
phonon.plot_band_structure().show()
phonon.plot_band_structure().savefig("BAND.png",
bbox_inches='tight',
transparent=True,
dpi=300,
format='png')
# phonon.write_band_structure()
mesh = [31, 31, 31]
phonon.set_mesh(mesh)
phonon.set_total_DOS()
phonon.write_total_DOS()
phonon.plot_total_DOS().show()
phonon.plot_total_DOS().savefig("DOS.png")
# c = np.fromfile('total_dos.dat', dtype=float)
datContent = [
i.strip().split() for i in open("./total_dos.dat").readlines()
]
del datContent[0]
x_ax = []
y_ax = []
for i in datContent:
x_ax.append(1 / ((3 * (10**8) / (float(i[0]) * (10**12))) * 100))
y_ax.append(float(i[1]))
da = {'Density of states': x_ax, 'Frequency': y_ax}
df = pd.DataFrame(da) #构造原始数据文件
df.to_excel("Wave number.xlsx") #生成Excel文件，并存到指定文件路径下
fig, ax = plt.subplots()
line1 = ax.plot(x_ax, y_ax, c='grey')
ax.set_xlim([maxx, 0])
# 以下是XRD图片的格式设置
#设置横纵坐标的名称以及对应字体格式
font2 = {
'family': 'Times New Roman',
'weight': 'bold',
}
plt.xlabel('Wavenumber ($\mathregular{cm^-}$$\mathregular{^1}$)',
font2)
plt.ylabel('Density of states', font2)
#不显示Y轴的刻度
plt.yticks([])
#设置图例对应格式和字体
font1 = {
'family': 'Times New Roman',
'weight': 'bold',
}
# ax.legend(edgecolor='none', prop=font1)
# plt.legend(edgecolor='none', prop=font1)
# plt.set_facecolor('none')
ax.set_facecolor('none')
#存储为
fig.savefig('FTIR.png',
bbox_inches='tight',
transparent=True,
dpi=300,
format='png') #指定分辨率,边界紧，背景透明
plt.show()
def Vibration(self, maxx=4500):
import os
import numpy as np
from pymatgen.io.phonopy import get_phonopy_structure
import pymatgen as pmg
from pymatgen.io.vasp.outputs import Vasprun
from pymatgen.io.vasp import Poscar
from pymatgen.symmetry.kpath import KPathSeek, KPathBase
from phonopy import Phonopy
from phonopy.structure.atoms import Atoms as PhonopyAtoms
from pymatgen.phonon.plotter import PhononBSPlotter
from pymatgen.phonon.bandstructure import PhononBandStructureSymmLine
import csv
import pandas as pd
import matplotlib.pyplot as plt
os.chdir(self.dire)
print(os.getcwd())
poscar = Poscar.from_file("POSCAR")
structure = poscar.structure
scell = [[1, 0, 0], [0, 1, 0], [0, 0, 1]]
vrun = Vasprun("vasprun.xml")
phonopyAtoms = get_phonopy_structure(structure)
phonon = Phonopy(phonopyAtoms, scell)
phonon.set_force_constants(-vrun.force_constants)
labels = ["$\\Gamma$", "X", "U", "K", "$\\Gamma$", "L", "W"]
bands = []
# path 1
q_start = np.array([0.0, 0.0, 0.0])
q_end = np.array([0.5, 0.0, 0.0])
band = []
for i in range(51):
band.append(q_start + (q_end - q_start) / 50 * i)
bands.append(band)
# path 2
q_start = np.array([0.5, 0.0, 0.0])
q_end = np.array([0.5, 0.5, 0.0])
band = []
for i in range(51):
band.append(q_start + (q_end - q_start) / 50 * i)
bands.append(band)
# # path 3
# q_start = np.array([0.5, 0.5, 0.0])
# q_end = np.array([-0.0, -0.0, 0.0])
# band = []
# for i in range(51):
# band.append(q_start + (q_end - q_start) / 50 * i)
# bands.append(band)
# # path 4
# q_start = np.array([0.0, 0.0, 0.0])
# q_end = np.array([0.5, 0.5, 0.5])
# band = []
# for i in range(51):
# band.append(q_start + (q_end - q_start) / 50 * i)
# bands.append(band)
print(bands)
phonon.set_band_structure(bands)
phonon.plot_band_structure().show()
phonon.plot_band_structure().savefig("BAND.png")
mesh = [31, 31, 31]
phonon.set_mesh(mesh)
phonon.set_total_DOS()
phonon.write_total_DOS()
phonon.plot_total_DOS().show()
phonon.plot_total_DOS().savefig("DOS.png")
# c = np.fromfile('total_dos.dat', dtype=float)
datContent = [
i.strip().split() for i in open("./total_dos.dat").readlines()
]
del datContent[0]
x_ax = []
y_ax = []
for i in datContent:
x_ax.append(1 / ((3 * (10**8) / (float(i[0]) * (10**12))) * 100))
y_ax.append(float(i[1]))
da = {'Density of states': x_ax, 'Frequency': y_ax}
df = pd.DataFrame(da) #构造原始数据文件
df.to_excel("Wave number.xlsx") #生成Excel文件，并存到指定文件路径下
fig, ax = plt.subplots()
line1 = ax.plot(x_ax, y_ax, c="grey")
ax.set_xlim([maxx, 0])
# 以下是XRD图片的格式设置
#设置横纵坐标的名称以及对应字体格式
font2 = {
'family': 'Times New Roman',
'weight': 'bold',
}
plt.xlabel('Wavenumber ($\mathregular{cm^-}$$\mathregular{^1}$)',
font2)
plt.ylabel('Density of states', font2)
#不显示Y轴的刻度
plt.yticks([])
#设置图例对应格式和字体
font1 = {
'family': 'Times New Roman',
'weight': 'bold',
}
# ax.legend(edgecolor='none', prop=font1)
# plt.legend(edgecolor='none', prop=font1)
# plt.set_facecolor('none')
ax.set_facecolor('none')
#存储为
fig.savefig('FTIR.png',
bbox_inches='tight',
transparent=True,
dpi=300,
format='png') #指定分辨率,边界紧，背景透明
plt.show()
def test_phonolammps():
os.chdir('data')
with open('data.si', 'w') as f:
f.write('''Generated using dynaphopy
8 atoms
1 atom types
0.0000000000 5.4500000000 xlo xhi
0.0000000000 5.4500000000 ylo yhi
0.0000000000 5.4500000000 zlo zhi
0.0000000000 0.0000000000 0.0000000000 xy xz yz
Masses
1 28.0855000000
Atoms
1 1 4.7687500000 4.7687500000 4.7687500000
2 1 4.7687500000 2.0437500000 2.0437500000
3 1 2.0437500000 4.7687500000 2.0437500000
4 1 2.0437500000 2.0437500000 4.7687500000
5 1 0.6812500000 0.6812500000 0.6812500000
6 1 0.6812500000 3.4062500000 3.4062500000
7 1 3.4062500000 0.6812500000 3.4062500000
8 1 3.4062500000 3.4062500000 0.6812500000
''')
with open('si.in', 'w') as f:
f.write('''
units metal
boundary p p p
box tilt large
atom_style atomic
read_data data.si
pair_style tersoff
pair_coeff * * SiCGe.tersoff Si(C)
neighbor 0.3 bin
''')
supercell = [[2, 0, 0], [0, 2, 0], [0, 0, 2]]
print(supercell)
phlammps = Phonolammps('si.in', supercell_matrix=supercell)
print(phlammps)
unitcell = phlammps.get_unitcell()
force_constants = phlammps.get_force_constants()
supercell_matrix = phlammps.get_supercell_matrix()
print(unitcell)
print(force_constants)
print(supercell_matrix)
os.chdir('..')
return
phonon = Phonopy(unitcell, supercell_matrix)
phonon.set_force_constants(force_constants)
phonon.set_mesh([20, 20, 20])
phonon.set_total_DOS()
phonon.plot_total_DOS().show()
phonon.set_thermal_properties()
phonon.plot_thermal_properties().show()
