Interface refactoring

Find a design which is more intuitive and minimal.

codes/kwant_helper/utils.py

@@ -239,8 +239,6 @@ def build_interacting_syst(builder, lattice, func_onsite, func_hop, max_neighbor
 
 def generate_guess(tb_model, int_model, scale=0.1):
     """
-    nk : int
-        Number of k-points along each direction.
     tb_model : dict
         Tight-binding model of non-interacting systems.
     int_model : dict
@@ -250,22 +248,24 @@ def generate_guess(tb_model, int_model, scale=0.1):
 
     Returns:
     --------
-    guess : nd-array
-        Guess evaluated on a k-point grid.
+    guess : tb dictionary
+        TB guess.
     """
     ndof = tb_model[next(iter(tb_model))].shape[-1]
     guess = {}
-    vectors = [*tb_model.keys(), *int_model.keys()]
+    vectors = frozenset(tb_model) | frozenset(int_model)
     for vector in vectors:
         amplitude = np.random.rand(ndof, ndof)
         phase = 2 * np.pi * np.random.rand(ndof, ndof)
         rand_hermitian = amplitude * np.exp(1j * phase)
-        if np.linalg.norm(np.array(vector)):
-            rand_hermitian += rand_hermitian.T.conj()
-            rand_hermitian /= 2
-        guess[vector] = rand_hermitian*scale
-
-    return guess#kgrid_hamiltonian(nk, guess) * scale
+        guess[vector] = rand_hermitian * scale
+        op_vector = tuple(-np.array(vector))
+        if op_vector==vector:
+            guess[vector] += guess[vector].T.conj()
+            guess[vector] /= 2
+        else:
+            guess[op_vector] = guess[vector].T.conj()
+    return guess
 
 
 def hk2tb_model(hk, tb_model, int_model, ks=None):