changed order of output parameters from surface_greens_function

examples/si_nw_transmission.py

@@ -45,7 +45,7 @@ def main():
         logging.info("{0} Energy: {1:.4f} eV".format(j, E))
 
         # compute self-energies describing boundary conditions at the leads contacts
-        R, L = negf.surface_greens_function(E, hl, h0, hr, iterate=True, damp=damp)
+        L, R = negf.surface_greens_function(E, hl, h0, hr, iterate=True, damp=damp)
 
         # compute Green's functions using the recursive Green's function algorithm
         # g_trans, grd, grl, gru, gr_left = negf.recursive_gf(E, [hl, hl], [h0 + L, h0, h0 + R], [hr, hr], damp=damp)

examples/si_nw_transmission_blocks.py

@@ -52,7 +52,7 @@ def main():
         logging.info("{0} Energy: {1:.4f} eV".format(j, E))
 
         # compute self-energies describing boundary conditions at the leads contacts
-        R, L = negf.surface_greens_function(E, hl_bd, h0_bd, hr_bd, iterate=True, damp=damp)
+        L, R = negf.surface_greens_function(E, hl_bd, h0_bd, hr_bd, iterate=True, damp=damp)
 
         # compute Green's functions using the recursive Green's function algorithm
         g_trans, grd, grl, gru, gr_left = negf.recursive_gf(E,

nanonet/negf/greens_functions.py

@@ -256,4 +256,4 @@ def surface_greens_function(E, h_l, h_0, h_r, iterate=False, damp=0.0001j):
     sgf_l = sgf_l[-s11:, -s12:]
     sgf_r = sgf_r[:s01, :s02]
 
-    return sgf_l, sgf_r
+    return sgf_r, sgf_l

nanonet/negf/hamiltonian_chain.py

@@ -57,9 +57,9 @@ def sgf(self):
 
         for jjj in range(len(self.h_0)):
             if jjj == 0:
-                sgf[jjj] = -2.0 * np.imag(self.sgf_r) * fd(self.energy, self.ef1, self.tempr)
+                sgf[jjj] = -2.0 * np.imag(self.sgf_l) * fd(self.energy, self.ef1, self.tempr)
             elif jjj == len(self.h_0) - 1:
-                sgf[jjj] = -2.0 * np.imag(self.sgf_l) * fd(self.energy, self.ef2, self.tempr)
+                sgf[jjj] = -2.0 * np.imag(self.sgf_r) * fd(self.energy, self.ef2, self.tempr)
             else:
                 sgf[jjj] = np.zeros(self.h_0[jjj].shape)
 
@@ -172,14 +172,14 @@ def add_self_energies(self, sgf_l, sgf_r, energy=0, tempr=0, ef1=0, ef2=0):
         self.sgf_l = sgf_l
         self.sgf_r = sgf_r
 
-        self.h_0[-1] = self.h_0[-1] + sgf_l
-        self.h_0[0] = self.h_0[0] + sgf_r
+        self.h_0[-1] = self.h_0[-1] + sgf_r
+        self.h_0[0] = self.h_0[0] + sgf_l
 
     def remove_self_energies(self):
         """ """
 
-        self.h_0[-1] = self.h_0[-1] - self.sgf_l
-        self.h_0[0] = self.h_0[0] - self.sgf_r
+        self.h_0[-1] = self.h_0[-1] - self.sgf_r
+        self.h_0[0] = self.h_0[0] - self.sgf_l
 
         self.sgf_l = None
         self.sgf_r = None

setup.py

@@ -7,7 +7,7 @@
     install_requires = fp.read().splitlines()
 
 setup(name='nano-net',
-      version='1.2.1',
+      version='1.3.0',
       description='Python framework for tight-binding computations',
       long_description=long_description,
       long_description_content_type="text/markdown",

test/test_greens_functions.py

@@ -811,13 +811,14 @@ def z_dependence(coord):
                                                                                h_chain.h_l,
                                                                                h_chain.h_0,
                                                                                h_chain.h_r,
-                                                                               s_in=h_chain.sgf)
+                                                                               s_in=h_chain.sgf,
+                                                                               damp=0.0000001j)
         h_chain.remove_self_energies()
 
         gamma_l = 1j * (sgf_l[j, :, :] - sgf_l[j, :, :].conj().T)
         gamma_r = 1j * (sgf_r[j, :, :] - sgf_r[j, :, :].conj().T)
 
-        tr[j] = np.real(np.trace(gamma_l.dot(g_trans).dot(gamma_r).dot(g_trans.conj().T)))
+        tr[j] = np.real(np.trace(gamma_r.dot(g_trans).dot(gamma_l).dot(g_trans.conj().T)))
 
         for jj in range(num_periods):
             dos1[j] = dos1[j] + np.real(np.trace(1j * (grd[jj] - grd[jj].conj().T))) / num_periods
@@ -830,7 +831,7 @@ def z_dependence(coord):
     # test_double_barrier_density_recursive()
     # test_gf_complex_chain_several_periods()
     # test_gf_single_atom_chain_several_periods()
-    # test_double_barrier_density_recursive(complex_chain, 20)
+    test_double_barrier_density_recursive(complex_chain, 20)
     # test_complex_chain()
-    test_gf_complex_chain_several_periods_recursive()
+    # test_gf_complex_chain_several_periods_recursive()
     # test_single_atom_chain()