# Read in wannier90 output file hr.dat to construct real space Hamiltonian to calculate Fermi surface

``````def get_uniformity_kpoint(n):
kPoints = []
for i in range(n):
for j in range(n):
kPoints.append(i/n * rec[0] + j/n * rec[1])
np.save("kPoints.npy", np.array(kPoints))
return kPoints``````

Take points evenly along the inverted parallelogram. Carry out the previous calculation.

The whole Brillouin zone is restored by translation.

``````import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.axes3d import Axes3D
from matplotlib.ticker import LinearLocator, FormatStrFormatter

basis_vector = [[1.37287871,1.37287871,-2.74575742],[-2.74575742,1.37287871,1.37287871],[13.36629497,13.36629497,13.36629497]]
V = np.dot(basis_vector[0], np.cross(basis_vector[1], basis_vector[2]) )
rec = [np.cross(basis_vector[1], basis_vector[2]) * 2 * np.pi/V,
np.cross(basis_vector[2], basis_vector[0]) * 2 * np.pi/V,
np.cross(basis_vector[0], basis_vector[1]) * 2 * np.pi/V]

print(rec)
nk = 200
Ek = Ek.reshape(nk, nk)
print(Ek.shape)

print(kPoints.shape)
kx = kPoints[:,0]
ky = kPoints[:,1]
print(kx.shape)
kx = kx.reshape(nk, nk)
ky = ky.reshape(nk, nk)

plt.contour(kx, ky, Ek, [0.0])
plt.contour(kx + rec[0][0] -rec[1][0] , ky + rec[0][1] -rec[1][1] , Ek, [0.0])
plt.contour(kx - rec[0][0], ky - rec[0][1] , Ek, [0.0])
plt.contour(kx - rec[1][0], ky - rec[1][1] , Ek, [0.0])
plt.contour(kx  +rec[0][0], ky + rec[0][1] , Ek, [0.0])
plt.show()
``````