def test_extend(self):
traj = self.traj.copy()
# Case of compatible trajectories
compatible_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_1"))
traj.extend(compatible_traj)
full_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_Full"))
compatible_success = self._check_traj_equality(self.traj, full_traj)
# Case of incompatible trajectories
traj = self.traj.copy()
incompatible_traj = Trajectory.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR,
"Traj_Combine_Test_XDATCAR_2"))
incompatible_test_success = False
try:
traj.extend(incompatible_traj)
except Exception:
incompatible_test_success = True
self.assertTrue(compatible_success and incompatible_test_success)
def test_variable_lattice(self):
structure = self.structures[0]
# Generate structures with different lattices
structures = []
for i in range(10):
new_lattice = np.dot(structure.lattice.matrix,
np.diag(1 + np.random.random_sample(3) / 20))
temp_struct = structure.copy()
temp_struct.lattice = Lattice(new_lattice)
structures.append(temp_struct)
traj = Trajectory.from_structures(structures, constant_lattice=False)
# Check if lattices were properly stored
self.assertTrue(
all(
np.allclose(struct.lattice.matrix,
structures[i].lattice.matrix)
for i, struct in enumerate(traj)))
# Check if the file is written correctly when lattice is not constant.
traj.write_Xdatcar(filename="traj_test_XDATCAR")
# Load trajectory from written xdatcar and compare to original
written_traj = Trajectory.from_file("traj_test_XDATCAR",
constant_lattice=False)
self._check_traj_equality(traj, written_traj)
os.remove("traj_test_XDATCAR")
def test_xdatcar_write(self):
self.traj.write_Xdatcar(filename="traj_test_XDATCAR")
# Load trajectory from written xdatcar and compare to original
written_traj = Trajectory.from_file(os.path.join("./", "traj_test_XDATCAR"))
self._check_traj_equality(self.traj, written_traj)
def test_extend(self):
traj = self.traj.copy()
# Case of compatible trajectories
compatible_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_1"))
traj.extend(compatible_traj)
full_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_Full"))
compatible_success = self._check_traj_equality(self.traj, full_traj)
# Case of incompatible trajectories
traj = self.traj.copy()
incompatible_traj = Trajectory.from_file(os.path.join(test_dir, "Traj_Combine_Test_XDATCAR_2"))
incompatible_test_success=False
try:
traj.extend(incompatible_traj)
except:
incompatible_test_success=True
self.assertTrue(compatible_success and incompatible_test_success)
'''
分析AIMD结果，计算MSD 和 conductivity
'''
import os
from pymatgen.core.trajectory import Trajectory
from pymatgen.io.vasp.outputs import Xdatcar
from pymatgen import Structure
from pymatgen.analysis.diffusion_analyzer import DiffusionAnalyzer
import numpy as np
import pickle
# 这一步是读取 XDATCAR，得到一系列结构信息
traj = Trajectory.from_file('XDATCAR')
# 这一步是实例化 DiffusionAnalyzer 的类
# 并用 from_structures 方法初始化这个类； 900 是温度，2 是POTIM 的值，1是间隔步数
# 间隔步数（step_skip）不太容易理解，但是根据官方教程:
# dt = timesteps * self.time_step * self.step_skip
diff = DiffusionAnalyzer.from_structures(traj,'Li',900,2,1)
# 可以用内置的 plot_msd 方法画出 MSD 图像
# 有些终端不能显示图像，这时候可以调用 export_msdt() 方法，得到数据后再自己作图
diff.plot_msd()
# 接下来直接得到 离子迁移率， 单位是 mS/cm
C = diff.conductivity
with open('result.dat','w') as f:
f.write('# AIMD result for Li-ion\n')
f.write('temp\tconductivity\n')
def setUp(self):
xdatcar = Xdatcar(os.path.join(test_dir, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(test_dir,
"Traj_XDATCAR"))
self.structures = xdatcar.structures
def setUp(self):
xdatcar = Xdatcar(os.path.join(PymatgenTest.TEST_FILES_DIR, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(PymatgenTest.TEST_FILES_DIR, "Traj_XDATCAR"))
self.structures = xdatcar.structures
def setUp(self):
xdatcar = Xdatcar(os.path.join(test_dir, "Traj_XDATCAR"))
self.traj = Trajectory.from_file(os.path.join(test_dir, "Traj_XDATCAR"))
self.structures = xdatcar.structures
rc('text', usetex=True)
import matplotlib.pylab as pylab
params = {
'legend.fontsize': '15',
'figure.figsize': (7, 6),
'axes.labelsize': 20,
'axes.titlesize': 20,
'xtick.labelsize': 16,
'ytick.labelsize': 16
}
pylab.rcParams.update(params)
trajectory = Trajectory.from_file("./vasprun_md.xml")
trajectory.write_Xdatcar(filename='XDATCAR_temp')
images = read_vasp_xdatcar('XDATCAR_temp', index=None)
print("total number of frames: " + str(len(images)))
os.remove('./XDATCAR_temp')
reference_frame = read_vasp('./SPOSCAR')
desc = SOAP(species=[55, 51, 53],
rcut=6.0,
nmax=9,
lmax=9,
sigma=0.3,
periodic=True,
crossover=True,
sparse=False)
ref_features = desc.create(reference_frame)