def plot_bs(vasprun_path: str):
try:
v = BSVasprun(vasprun_path)
except xml.etree.ElementTree.ParseError:
print("\tskipped due to parse error")
return
bs = v.get_band_structure(kpoints_filename="KPOINTS", line_mode=True)
plt = BSPlotter(bs)
plt.show()
from pymatgen.io.vasp.outputs import BSVasprun
from pymatgen.electronic_structure.plotter import BSPlotter
import os
os.chdir('/home/jinho93/half-metal/1.CrO2/3.band')
vrun = BSVasprun('vasprun.xml')
bs = vrun.get_band_structure('KPOINTS', line_mode=True)
bsp = BSPlotter(bs)
bsp.show()
from pymatgen.electronic_structure.bandstructure import BandStructure
import os
# vaspout = BSVasprun("./hubbard/hub_Mn-5_Fe-5/vasprun.xml")
vaspout = BSVasprun("../calc_seq_test/bands-mag/vasprun.xml")
# 50 k-points = 0.3863000000000012 eV
# 100 k-points = 0.38480000000000114 eV
# 8x8x8 50 k-points = 0.39029999999999987 eV
# 50 k-points with LASPH = 0.3932000000000002 eV
bandstr = vaspout.get_band_structure(line_mode=True)
print(bandstr.get_band_gap())
# print(bandstr.get_direct_band_gap_dict())
plt = BSPlotter(bandstr).get_plot(ylim=[-10, 5])
plt.show()
# get band gap for all directories
def get_band_gap(directory):
vasp_out = BSVasprun(directory + "/vasprun.xml")
band_str = vasp_out.get_band_structure(line_mode=True)
band_gap = band_str.get_band_gap()
print(band_gap)
return band_gap
get_band_gap("../calc_seq_test/bands-mag")
# for directory in os.getcwd():
# get_band_gap(directory)
print("------------------------------------------------------------")
# POSCAR 晶体结构可视化 , 可视化需要软件VTK
input_poscarVis = StructureVis()
input_poscarVis.set_structure(input_structure)
input_poscarVis.show()
# 画能代结构图 ,
from pymatgen.io.vasp import Vasprun, BSVasprun
from pymatgen.electronic_structure.plotter import BSPlotter
vasprun = BSVasprun(vasprun_path)
bankStructure = vasprun.get_band_structure(kpoints_filename=KPOINTS,
line_mode=True)
plt = BSPlotter(bankStructure)
# print(plt.get_ticks()) #Get all ticks and labels for a band structure plot. return A dictionary with ‘distance’
plt.show(ylim=(-36, 5)) # 这一行有问题。就是这个范围参数该如何得到。
# 解析INCAR部分,应该直接打印 INCAR 中所有参数信息也是没问题的。
incar = ParseINCAR(INCAR)
print("------------------------------------------------------------")
print(incar.as_dict())
# 解析KPOINTS 部分， 需要的参数有 kpoints， nkpoints, label,
kpoints = ParseKPOINTS(KPOINTS)
kPoints = kpoints['kpoints']
nkpoints = kpoints['nkpoints']
label = kpoints['label']
# print(kpoints.as_dict())
#解析OSZICAR 部分。
for m in re.finditer(r"([A-Z]+)(\d+)", anon_formula)
}
data = mpr.query({"anonymous_formula": anon_formula},
properties=["task_id", "pretty_formula", "structure"])
print(len(data)) #Should show ~600 data.比较慢，多等一会儿。
# data now contains a list of dict. This shows you what each dict has.
# Note that the mp id is named "task_id" in the database itself.
pprint.pprint(data[0])
# # 得到“能带结构”（Getting band structures）
# 能带结构是相当大的物体。不建议你一次下载大量的绷带结构，而是直接下载你需要的。Band structures are fairly large objects. It is not recommended that you download large quantities of bandstructures in one shot, but rather just download the ones you need.
bs = mpr.get_bandstructure_by_material_id(
"mp-20470") #这个是material上对应的编号，需要自己去查找写自己需要的
from pymatgen.electronic_structure.plotter import BSPlotter
# %matplotlib inline
plotter = BSPlotter(bs)
plotter.show()
elastic_data = mpr.query(
{"elasticity": {
"$exists": True
}},
properties=["task_id", "pretty_formula", "elasticity"])
print(len(elastic_data))
pprint.pprint(elastic_data[0])
# # More resources
# In general, almost any data can be obtained from MP using the MPRester, either via the high-level functions or the very powerful "query" method.
# For more complex queries, you can refer to the documentation for the Materials API at https://github.com/materialsproject/mapidoc.
# # Fitting structures
# Pymatgen has its own structure matching algorithm, which we have used to effectively reduce the 130,000 structures in ICSD to ~60,000 - 70,000 structures. It is fast and accurate. Here's an example of how it works.
from pymatgen.analysis.structure_matcher import StructureMatcher
m = StructureMatcher(
