unified docstrings and made additional tb_params module

examples/si_nw_transmission.py

@@ -6,7 +6,7 @@
 import numpy as np
 import nanonet.negf as negf
 import matplotlib.pyplot as plt
-from nanonet.tb import Hamiltonian
+from nanonet.tb import Hamiltonian, HamiltonianSp
 from nanonet.tb import Orbitals
 from nanonet.tb.sorting_algorithms import sort_projection
 
@@ -40,7 +40,7 @@ def main():
     hl1, h01, hr1, subblocks = hamiltonian.get_hamiltonians_block_tridiagonal()
 
     # specify energy array
-    energy = np.linspace(2.0, 2.45, 50)
+    energy = np.linspace(2.1, 2.2, 50)
 
     # specify dephasing constant
     damp = 0.001j
@@ -56,6 +56,8 @@ def main():
 
         # compute self-energies describing boundary conditions at the leads contacts
         R, L = negf.surface_greens_function(E, hl, h0, hr, iterate=False, damp=damp)
+        # R, L = surface_greens_function_poles_Shur(E, hl, h0, hr)
+        # R, L = surface_greens_function(E, hl, h0, hr, iterate=False, damp=damp)
 
         s01, s02 = h01[0].shape
         s11, s12 = h01[-1].shape
@@ -92,6 +94,9 @@ def main():
     plt.plot(energy, dos)
     plt.show()
 
+    plt.plot(dos)
+    plt.show()
+
     plt.plot(energy, tr)
     plt.show()
 

nanonet/negf/cfr.py

@@ -3,6 +3,7 @@
 
 
 class CFR(object):
+    """ """
 
     val_inf = 1.0e4
 
@@ -16,6 +17,17 @@ def __init__(self, cutoff=0):
             self.gen_poles_and_residues(self.cutoff)
 
     def fd_approximant(self, energy):
+        """
+
+        Parameters
+        ----------
+        energy :
+            
+
+        Returns
+        -------
+
+        """
         arg = np.array(energy)
         ans = np.zeros(arg.shape) + 0.5
 
@@ -27,6 +39,17 @@ def fd_approximant(self, energy):
         return ans
 
     def fd_approximant_diff(self, energy):
+        """
+
+        Parameters
+        ----------
+        energy :
+            
+
+        Returns
+        -------
+
+        """
 
         arg = np.array(energy)
         ans = np.zeros(arg.shape) + 0.5 * 0
@@ -39,11 +62,16 @@ def fd_approximant_diff(self, energy):
         return ans
 
     def gen_poles_and_residues(self, cutoff=50):
-        """
-        Compute positions of poles and their residuals for the Fermi-Dirac function
+        """Compute positions of poles and their residuals for the Fermi-Dirac function
+
+        Parameters
+        ----------
+        cutoff :
+            cutoff energy (Default value = 50)
+
+        Returns
+        -------
 
-        :param cutoff:   cutoff energy
-        :return:
         """
 
         self.cutoff = cutoff
@@ -60,16 +88,26 @@ def gen_poles_and_residues(self, cutoff=50):
         self.num_poles = len(self.fd_poles_coords)
 
     def get_poles_and_residues(self):
+        """ """
         return self.fd_poles_coords, self.fd_poles
 
     def integrate(self, gf, ef=0, tempr=300, zero_moment=-1):
         """
 
-        :param gf:
-        :param ef:
-        :param tempr:
-        :param zero_moment:
-        :return:
+        Parameters
+        ----------
+        gf :
+            param ef:
+        tempr :
+            param zero_moment: (Default value = 300)
+        ef :
+             (Default value = 0)
+        zero_moment :
+             (Default value = -1)
+
+        Returns
+        -------
+
         """
 
         if zero_moment == -1:
@@ -86,6 +124,19 @@ def integrate(self, gf, ef=0, tempr=300, zero_moment=-1):
         return np.real(zero_moment + np.imag(ans))
 
     def genetate_integration_points(self, ef, tempr):
+        """
+
+        Parameters
+        ----------
+        ef :
+            
+        tempr :
+            
+
+        Returns
+        -------
+
+        """
         ans = []
         betha = 1.0 / (8.617333262145e-5 * tempr)
 
@@ -97,10 +148,18 @@ def genetate_integration_points(self, ef, tempr):
     def integrate1(self, gf_vals, tempr, zero_moment=0):
         """
 
-        :param gf_vals:
-        :param tempr:
-        :param zero_moment:
-        :return:
+        Parameters
+        ----------
+        gf_vals :
+            param tempr:
+        zero_moment :
+            return: (Default value = 0)
+        tempr :
+            
+
+        Returns
+        -------
+
         """
 
         assert len(gf_vals) == len(self.fd_poles_coords)

nanonet/negf/continued_fraction_representation.py

@@ -4,10 +4,36 @@
 
 
 def t_order_frac(x):
+    """
+
+    Parameters
+    ----------
+    x :
+        
+
+    Returns
+    -------
+
+    """
     return 0.5 * (np.sign(x) + 1.0) / x
 
 
 def approximant(energy, poles, residues):
+    """
+
+    Parameters
+    ----------
+    energy :
+        
+    poles :
+        
+    residues :
+        
+
+    Returns
+    -------
+
+    """
 
     arg = np.array(energy)
     ans = np.zeros(arg.shape) + 0.5
@@ -20,6 +46,21 @@ def approximant(energy, poles, residues):
 
 
 def approximant_diff(energy, poles, residues):
+    """
+
+    Parameters
+    ----------
+    energy :
+        
+    poles :
+        
+    residues :
+        
+
+    Returns
+    -------
+
+    """
 
     arg = np.array(energy)
     ans = np.zeros(arg.shape) + 0.5 * 0
@@ -32,6 +73,17 @@ def approximant_diff(energy, poles, residues):
 
 
 def poles_and_residues(cutoff=2):
+    """
+
+    Parameters
+    ----------
+    cutoff :
+         (Default value = 2)
+
+    Returns
+    -------
+
+    """
 
     b_mat = [1 / (2.0 * np.sqrt((2*(j+1) - 1)*(2*(j+1) + 1))) for j in range(0, cutoff-1)]
     b_mat = np.diag(b_mat, -1) + np.diag(b_mat, 1)
@@ -46,20 +98,59 @@ def poles_and_residues(cutoff=2):
 
 
 def test_gf1(z):
+    """
+
+    Parameters
+    ----------
+    z :
+        
+
+    Returns
+    -------
+
+    """
     return t_order_frac(z + 10.0) + \
            t_order_frac(z + 5.0) + \
            t_order_frac(z + 2.0) + \
            t_order_frac(z - 5.0)
 
 
 def test_gf(z):
+    """
+
+    Parameters
+    ----------
+    z :
+        
+
+    Returns
+    -------
+
+    """
     return 1.0 / (z + 10.0) + \
            1.0 / (z + 5.0) + \
            1.0 / (z + 2.0) + \
            1.0 / (z - 5.0)
 
 
 def test_integration(Ef, tempr, cutoff=70, gf=test_gf):
+    """
+
+    Parameters
+    ----------
+    Ef :
+        
+    tempr :
+        
+    cutoff :
+         (Default value = 70)
+    gf :
+         (Default value = test_gf)
+
+    Returns
+    -------
+
+    """
 
     R = 1.0e10
 
@@ -81,6 +172,21 @@ def test_integration(Ef, tempr, cutoff=70, gf=test_gf):
 
 
 def bf_integration(Ef, tempr, gf=test_gf):
+    """
+
+    Parameters
+    ----------
+    Ef :
+        
+    tempr :
+        
+    gf :
+         (Default value = test_gf)
+
+    Returns
+    -------
+
+    """
 
     # temp = 100
     R = 2e2