From 8497151477b32c4d8885793426e728bb931f81d2 Mon Sep 17 00:00:00 2001
From: Kostas Vilkelis <kostasvilkelis@gmail.com>
Date: Tue, 7 May 2024 00:33:02 +0200
Subject: [PATCH] rm unused ks argument
---
pymf/tb/transforms.py | 10 +++-------
pymf/tb/utils.py | 2 +-
pymf/tests/test_graphene.py | 2 +-
3 files changed, 5 insertions(+), 9 deletions(-)
diff --git a/pymf/tb/transforms.py b/pymf/tb/transforms.py
index 3a0e990..374526d 100644
--- a/pymf/tb/transforms.py
+++ b/pymf/tb/transforms.py
@@ -6,7 +6,7 @@ from pymf.tb.tb import tb_type
ks_type = Optional[np.ndarray]
-def tb_to_khamvector(tb: tb_type, nk: int, ks: ks_type = None) -> np.ndarray:
+def tb_to_khamvector(tb: tb_type, nk: int) -> np.ndarray:
"""Evaluate a tight-binding dictionary on a k-space grid.
Parameters
@@ -16,9 +16,6 @@ def tb_to_khamvector(tb: tb_type, nk: int, ks: ks_type = None) -> np.ndarray:
nk :
Number of k-points in a grid to sample the Brillouin zone along each dimension.
If the system is 0-dimensional (finite), this parameter is ignored.
- ks :
- Set of points along which to evalaute the k-point grid. Repeated for all dimensions.
- If not provided, a linear grid is used based on nk.
Returns
-------
@@ -27,9 +24,8 @@ def tb_to_khamvector(tb: tb_type, nk: int, ks: ks_type = None) -> np.ndarray:
Has shape (nk, nk, ..., ndof, ndof), where ndof is number of internal degrees of freedom.
"""
ndim = len(list(tb)[0])
- if ks is None:
- ks = np.linspace(-np.pi, np.pi, nk, endpoint=False)
- ks = np.concatenate((ks[nk // 2 :], ks[: nk // 2]), axis=0) # shift for ifft
+ ks = np.linspace(-np.pi, np.pi, nk, endpoint=False)
+ ks = np.concatenate((ks[nk // 2 :], ks[: nk // 2]), axis=0) # shift for ifft
kgrid = np.meshgrid(*([ks] * ndim), indexing="ij")
num_keys = len(list(tb.keys()))
diff --git a/pymf/tb/utils.py b/pymf/tb/utils.py
index a8d22dd..e8e80b8 100644
--- a/pymf/tb/utils.py
+++ b/pymf/tb/utils.py
@@ -78,6 +78,6 @@ def calculate_fermi_energy(tb: tb_type, filling: float, nk: int = 100):
:
Fermi energy.
"""
- kham = tb_to_khamvector(tb, nk, ks=None)
+ kham = tb_to_khamvector(tb, nk)
vals = np.linalg.eigvalsh(kham)
return fermi_on_grid(vals, filling)
diff --git a/pymf/tests/test_graphene.py b/pymf/tests/test_graphene.py
index 8657f7d..e28f30f 100644
--- a/pymf/tests/test_graphene.py
+++ b/pymf/tests/test_graphene.py
@@ -27,7 +27,7 @@ def compute_gap(tb, fermi_energy=0, nk=100):
gap : float
Indirect gap.
"""
- kham = tb_to_khamvector(tb, nk, ks=None)
+ kham = tb_to_khamvector(tb, nk)
vals = np.linalg.eigvalsh(kham)
emax = np.max(vals[vals <= fermi_energy])
--
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