single-band in a 3-D FCC lattice

Given the nearest neighbor sites Rm of FCC crystal, please modify the Hamiltonian to plot the band structure

import matplotlib.pyplot as plt import numpy as np from numpy import pi from toolbox import solve_bands, kpoints_to_xaxis plt.rcParams.update('font.size:14) HO Your code here! sk- (pl.pl.pl]). (10,01). ("X". 10.2 p.) ('0', ipi/2,2"pi,pi/2)), (W. (pl.pl .01). (K) 13*1/2, 3pi/2.0]). ('. 10,01), Karenplinspace(p.pl.pl], [ ... 20) LG Kennplinspace(I ... 10,2pi.o). 20) + GX plinspace([0,2*pl.). (pi/7,2 pl.pl/2), nun-20) XV korrnp. 1inspace([pf/2.2,pi/21. [pl.pl,01. num.20) 0 karr- np. linspace([pi, 2 pio), 13pi/2.3"p1/ 20], nu-20). koreninspace([*p1/2, 1/2,0). [..). nus 20) #6 kernp.r_karr, Karr, karr, kter, karr, Arr] In [10]: solve bands bands - solve_bands (H, kare) print(f'Shape of bands: (bands.shape}") print (f Number of calculated K-points: (bands.shape[o]}') print("Number of bands: bands.shape[1])") print) moke x-axis for plotting xArr-kpoints_to_xaxis (kArr) k_labels = [ S[@] for sin sk] hk_points - [for sin sk i hk_xaxis - kpoints_to_xaxis (hk_points) #plot bonds for band in bands.T: plt.plot(xArr, band, -0) for i. in enumerate(hk labels): plt.axvline(hk_xaxis[1]) plt.ylabel("Energy (ev) plt.xtickschk_xaxis, hk_labels) pit.show() Shape of bands: (120, 1) Number of calculated k-points: 120 Number of bands: 1 8 -10