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
# Find continuous segments in KPOINTS
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()
from pymatgen import MPRester
from pymatgen.electronic_structure.plotter import DosPlotter
mpr = MPRester('DhmFQPuibZo8JtXn')
dsp = DosPlotter()
cdos = mpr.get_dos_by_material_id('mp-352')
dsp.add_dos_dict(cdos.get_element_dos())
dsp.show()
