def test(self, structure):
failures = []
if self.is_valid:
if not structure.is_valid():
failures.append("IS_VALID=False")
if self.potcar_exists:
elements = structure.composition.elements
if set(elements).intersection(set(self.NO_POTCARS)):
failures.append("POTCAR_EXISTS=False")
if self.max_natoms:
if structure.num_sites > self.max_natoms:
failures.append("MAX_NATOMS=Exceeded")
if self.is_ordered:
if not structure.is_ordered:
failures.append("IS_ORDERED=False")
if self.not_in_MP:
mpr = MPRester(self.MAPI_KEY)
mpids = mpr.find_structure(structure)
if mpids:
if self.require_bandstructure:
for mpid in mpids:
try:
bs = mpr.get_bandstructure_by_material_id(mpid)
if bs:
failures.append("NOT_IN_MP=False ({})".format(mpid))
except:
pass
else:
failures.append("NOT_IN_MP=False ({})".format(mpids[0]))
return True if not failures else False
def test(self, structure):
failures = []
if self.is_valid:
if not structure.is_valid():
failures.append("IS_VALID=False")
if self.potcar_exists:
elements = structure.composition.elements
if set(elements).intersection(set(self.NO_POTCARS)):
failures.append("POTCAR_EXISTS=False")
if self.max_natoms:
if structure.num_sites > self.max_natoms:
failures.append("MAX_NATOMS=Exceeded")
if self.is_ordered:
if not structure.is_ordered:
failures.append("IS_ORDERED=False")
if self.not_in_MP:
mpr = MPRester(self.MAPI_KEY)
mpids = mpr.find_structure(structure)
if mpids:
if self.require_bandstructure:
for mpid in mpids:
try:
bs = mpr.get_bandstructure_by_material_id(mpid)
if bs:
failures.append("NOT_IN_MP=False ({})".format(mpid))
except:
pass
else:
failures.append("NOT_IN_MP=False ({})".format(mpids[0]))
return True if not failures else False
import json
from pymatgen import MPRester
mpr = MPRester('fn8WQGgT9rvZAh6H')
bs=mpr.get_bandstructure_by_material_id('mp-3315').as_dict() #,line_mode=True)
with open("test.json", "w") as outfile:
json.dump(bs, outfile, indent=4)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import math
from pymatgen import MPRester
from pymatgen.electronic_structure.plotter import BSPlotter
a = MPRester("wuoepAHZnBtMv4gC")
bs = a.get_bandstructure_by_material_id("mp-3748")
print(bs.is_metal())
print(bs.get_band_gap())
print(bs.get_direct_band_gap())
plotter = BSPlotter(bs)
plotter.get_plot().show()
def plot_band_structure(mpid, band_index, width, k_highlight, pattern):
"""
- Plots two bands (which one is indicated by band_index)
- Highlights a window of width `width` at k `k_highlight`
"""
mpr = MPRester('4JzM8sNnMkyVJceK')
bs = mpr.get_bandstructure_by_material_id(mpid)
dos = mpr.get_dos_by_material_id(mpid)
kpoints = pymatgen.Kpoints(bs)
doscar = pymatgen.Doscar(dos)
fermi_energy = doscar.fermi_energy
eigenval = pymatgen.Eigenval(bs, fermi_energy)
bands = eigenval.spin_up
lower_fermi_band_index = np.argmax(np.nanmax(bands, axis=1) > 0) - 1
"""
segment_sizes = kpoints.segment_sizes
segmented_lower_band = np.split(bands[lower_fermi_band_index+band_index], np.cumsum(segment_sizes))[:-1]
segmented_upper_band = np.split(bands[lower_fermi_band_index+band_index+1], np.cumsum(segment_sizes))[:-1]
segmented_kpoints = np.split(eigenval.k_points, np.cumsum(segment_sizes))[:-1]
last_k = 0
"""
k = eigenval.k_points
band_l = bands[lower_fermi_band_index + band_index]
band_u = bands[lower_fermi_band_index + band_index + 1]
#for k, band_l, band_u in zip(segmented_kpoints, segmented_lower_band, segmented_upper_band):
#k_1D = np.array(path_1D(k)) + last_k
k_1D = np.array(path_1D(k))
plt.plot(k_1D, band_l, 'k')
plt.plot(k_1D, band_u, 'k')
#last_k = np.max(k_1D)
plt.axvspan(float(k_highlight),
float(k_highlight) + width,
color='red',
alpha=0.5)
# Collect axis ticks (high symmetry points) from KPOINTS.gz
last_k = 0
label_k = []
label_names = []
#NOTE: Labels for none are question marks
for left_k, right_k in pymatgen.chunks(kpoints.k_points, 2):
if len(label_names) == 0:
label_k.append(last_k)
#label_names.append(left_k[0])
#elif label_names[-1] != left_k[0]:
#label_names[-1] += (';' + left_k[0])
last_k += np.linalg.norm(right_k[1] - left_k[1])
label_k.append(last_k)
#label_names.append(right_k[0])
#plt.xticks(label_k, label_names)
#plt.xticks(label_k)
plt.ylabel('Energy')
plt.xlabel('k')
plt.grid(True)
plt.title('material ' + mpid)
plt.savefig('misc/' + pattern + '_search_result.png')
plt.show()
default=10,
help='number of trees in annoy index')
opt = parser.parse_args()
print(opt)
# Annoy index stores the electronic band structure with each vector corresponding to a sliding window.
annoyindex = AnnoyIndex(int(2 * opt.dimensions), metric='angular')
# A lookuptable is necessary to link annoy vectors to their correct material and k-space position.
lookuptable = []
for mpid in ["mp-2090"]:
mpr = MPRester('4JzM8sNnMkyVJceK')
bs = mpr.get_bandstructure_by_material_id(mpid)
dos = mpr.get_dos_by_material_id(mpid)
kpoints = pymatgen.Kpoints(bs)
doscar = pymatgen.Doscar(dos)
if doscar.converged == False:
continue # skip calculations that did not converge
fermi_energy = doscar.fermi_energy
eigenval = pymatgen.Eigenval(bs, fermi_energy)
bands = eigenval.spin_up
# lower_fermi_band_index indicates the band just below Fermi level
lower_fermi_band_index = np.argmax(np.nanmax(bands, axis=1) > 0) - 1
# plot(np.array(bs.bands[sp])[iband-1,:].T-bs.efermi) # from MP
# plot(np.array(bs.bands[sp])[iband-2,:].T-bs.efermi) # from MP
# plot(np.array(bs.bands[sp])[iband-3,:].T-bs.efermi) # from MP
plot(en, color='b') # interpolated by BoltzTraP
show()
if __name__ == "__main__":
# user inputs
PbTe_id = 'mp-19717' # valence_idx = 9
Si_id = 'mp-149' # valence_idx = 4
GaAs_id = 'mp-2534' # valence_idx = ?
SnSe2_id = "mp-665"
Si_bs = api.get_bandstructure_by_material_id(Si_id)
bs = Vasprun('GaAs_28electron_ncsf_line_vasprun.xml').get_band_structure(
kpoints_filename='GaAs_28electron_KPOINTS', line_mode=True)
GaAs_st = api.get_structure_by_material_id(GaAs_id)
bs.structure = GaAs_st
# Si_bs.structure = api.get_structure_by_material_id(Si_id)
Si_bs.structure = Vasprun("../test_files/Si/vasprun.xml").final_structure
print(bs.get_sym_eq_kpoints([0.5, 0.5, 0.5]))
print(bs.get_sym_eq_kpoints([0.5, 0., 0.5]))
# vbm_idx = bs.get_vbm()['band_index'][Spin.up][0]
vbm_idx, _ = get_bindex_bspin(Si_bs.get_vbm(), is_cbm=False)
print('vbm band index (vbm_idx): {}'.format(vbm_idx))
ibands = [1, 2] # in this notation, 1 is the last valence band
ibands = [i + vbm_idx for i in ibands]
comp = Composition("Fe2O3") # 获得带有材料标识的结构， 假设你想找到所有与fe2o3类似的化学计量结构
anon_formula = comp.anonymized_formula
# We need to convert the formula to the dict form used in the database.
anon_formula = {
m.group(1): int(m.group(2))
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
import numpy as np
import matplotlib.pyplot as plt
import pymatgen
from pymatgen import MPRester
import sys
sys.path.append('/home/will/Research/model_fitting/si_model_fitting')
import chkinfo
hf2ev = 27.2114
if __name__=='__main__':
mpr = MPRester(api_key='D9uwc2I45fGbd8FU')
bs = mpr.get_bandstructure_by_material_id('mp-149', line_mode=False)
mproj_kpts = np.array([k._ccoords for k in bs.kpoints])
xinds = np.nonzero(np.dot(mproj_kpts,[1,0,0])/np.linalg.norm(mproj_kpts, axis=1)==-1)[0]
key = list(bs.bands.keys())[0]
mproj_bands = bs.bands[key]
vbm = 3
cbm = 4
print(mproj_bands.shape)
print(np.round(mproj_kpts[[0,10,90]], 3))
xkpts = np.abs(mproj_kpts[xinds,0])
print(xinds)
print(np.round(xkpts,3))
print(bs.kpoints[0].__dict__.keys())
plt.plot(xkpts, mproj_bands[:6,xinds].T)
plt.axhline(y=mproj_bands[vbm,0], ls=':')
plt.axhline(y=mproj_bands[cbm,90], ls=':')
