diff --git a/codes/kwant_helper/utils.py b/codes/kwant_helper/utils.py
index 41612e8ddabe4c151c0ec3dc134498c632b993fe..e2f35af95e86499af3ae6678846153a1ac377ade 100644
--- a/codes/kwant_helper/utils.py
+++ b/codes/kwant_helper/utils.py
@@ -6,7 +6,7 @@ import inspect
from copy import copy
-def builder2tb(builder, params={}, return_data=False):
+def builder_to_tb(builder, params={}, return_data=False):
"""
Constructs a tight-binding model dictionary from a `kwant.Builder`.
@@ -151,52 +151,3 @@ def build_interacting_syst(builder, lattice, func_onsite, func_hop, max_neighbor
for neighbors in range(max_neighbor):
int_builder[lattice.neighbors(neighbors + 1)] = func_hop
return int_builder
-
-
-def generate_guess(vectors, ndof, scale=1):
- """
- vectors : list
- List of hopping vectors.
- ndof : int
- Number internal degrees of freedom (orbitals),
- scale : float
- The scale of the guess. Maximum absolute value of each element of the guess.
-
- Returns:
- --------
- guess : tb dictionary
- Guess in the form of a tight-binding model.
- """
- guess = {}
- for vector in vectors:
- if vector not in guess.keys():
- amplitude = scale * 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)) == 0:
- rand_hermitian += rand_hermitian.T.conj()
- rand_hermitian /= 2
- guess[vector] = rand_hermitian
- else:
- guess[vector] = rand_hermitian
- guess[tuple(-np.array(vector))] = rand_hermitian.T.conj()
-
- return guess
-
-
-def generate_vectors(cutoff, dim):
- """
- Generates hopping vectors up to a cutoff.
-
- Parameters:
- -----------
- cutoff : int
- Maximum distance along each direction.
- dim : int
- Dimension of the vectors.
-
- Returns:
- --------
- List of hopping vectors.
- """
- return [*product(*([[*range(-cutoff, cutoff + 1)]] * dim))]
diff --git a/codes/tb/utils.py b/codes/tb/utils.py
index 1d00831c97c7cfcaba577e6088144037f97a3b9d..041d372d25f3f6877742029b7322892c7d9a78a4 100644
--- a/codes/tb/utils.py
+++ b/codes/tb/utils.py
@@ -1,6 +1,56 @@
import numpy as np
from codes.tb.transforms import tb_to_kfunc
import itertools as it
+from itertools import product
+
+
+def generate_guess(vectors, ndof, scale=1):
+ """
+ vectors : list
+ List of hopping vectors.
+ ndof : int
+ Number internal degrees of freedom (orbitals),
+ scale : float
+ The scale of the guess. Maximum absolute value of each element of the guess.
+
+ Returns:
+ --------
+ guess : tb dictionary
+ Guess in the form of a tight-binding model.
+ """
+ guess = {}
+ for vector in vectors:
+ if vector not in guess.keys():
+ amplitude = scale * 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)) == 0:
+ rand_hermitian += rand_hermitian.T.conj()
+ rand_hermitian /= 2
+ guess[vector] = rand_hermitian
+ else:
+ guess[vector] = rand_hermitian
+ guess[tuple(-np.array(vector))] = rand_hermitian.T.conj()
+
+ return guess
+
+
+def generate_vectors(cutoff, dim):
+ """
+ Generates hopping vectors up to a cutoff.
+
+ Parameters:
+ -----------
+ cutoff : int
+ Maximum distance along each direction.
+ dim : int
+ Dimension of the vectors.
+
+ Returns:
+ --------
+ List of hopping vectors.
+ """
+ return [*product(*([[*range(-cutoff, cutoff + 1)]] * dim))]
def compute_gap(h, fermi_energy=0, n=100):
diff --git a/codes/test_graphene.py b/codes/test_graphene.py
index 1ebcd41ae1e313e7b120713756ef69e91380cb35..921428ef58b304e21423c1a7fef4361a9b277d3a 100644
--- a/codes/test_graphene.py
+++ b/codes/test_graphene.py
@@ -11,7 +11,7 @@ import pytest
repeat_number = 10
# %%
graphene_builder, int_builder = kwant_examples.graphene_extended_hubbard()
-h_0 = utils.builder2tb(graphene_builder)
+h_0 = utils.builder_to_tb(graphene_builder)
# %%
@@ -45,7 +45,7 @@ def gap_prediction(U, V):
filling = 2
nk = 20
- h_int = utils.builder2tb(int_builder, params)
+ h_int = utils.builder_to_tb(int_builder, params)
guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))
model = Model(h_0, h_int, filling)
diff --git a/examples/graphene_extended_hubbard.ipynb b/examples/graphene_extended_hubbard.ipynb
index 20b9770e677681f124134c24d7f0ba744d4a19bf..12c3bba59b09fd694f62f3af80a9180829fef4a6 100644
--- a/examples/graphene_extended_hubbard.ipynb
+++ b/examples/graphene_extended_hubbard.ipynb
@@ -65,7 +65,7 @@
"source": [
"# Create translationally-invariant `kwant.Builder`\n",
"graphene_builder, int_builder = kwant_examples.graphene_extended_hubbard()\n",
- "h_0 = utils.builder2tb(graphene_builder)"
+ "h_0 = utils.builder_to_tb(graphene_builder)"
]
},
{
@@ -84,7 +84,7 @@
" guess=None\n",
" for V in Vs: \n",
" params = dict(U=U, V=V)\n",
- " h_int = utils.builder2tb(int_builder, params)\n",
+ " h_int = utils.builder_to_tb(int_builder, params)\n",
" if guess==None:\n",
" guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))\n",
" model = Model(h_0, h_int, filling=2)\n",
@@ -225,7 +225,7 @@
"params = dict(U=0, V=1)\n",
"filling = 2 \n",
"\n",
- "h_int = utils.builder2tb(int_builder, params)\n",
+ "h_int = utils.builder_to_tb(int_builder, params)\n",
"model = Model(h_0, h_int, filling)\n",
"mf_guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))\n",
"mf_sol = solver(model, mf_guess, nK=30)\n",
@@ -295,8 +295,8 @@
"filling = 2\n",
"nK = 300\n",
"\n",
- "h_int = utils.builder2tb(int_builder, params)\n",
- "h_0 = utils.builder2tb(graphene_builder)\n",
+ "h_int = utils.builder_to_tb(int_builder, params)\n",
+ "h_0 = utils.builder_to_tb(graphene_builder)\n",
"guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))\n",
"\n",
"model = Model(h_0, h_int, filling)\n",
diff --git a/profiling/graphene.py b/profiling/graphene.py
index 9731d90fb0e984ab34250c976b3971819cbc77f8..5b653bd343a2c1e64be0f2cfaf9b3aec01ebaba1 100644
--- a/profiling/graphene.py
+++ b/profiling/graphene.py
@@ -14,8 +14,8 @@ params = {"U": 0.5, "V": 1.1}
filling = 2
nk = 600
-h_int = utils.builder2tb(int_builder, params)
-h_0 = utils.builder2tb(graphene_builder)
+h_int = utils.builder_to_tb(int_builder, params)
+h_0 = utils.builder_to_tb(graphene_builder)
guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))
model = Model(h_0, h_int, filling)