From e279ca32ceb3c3dab43b1985976b2e574d2f18fd Mon Sep 17 00:00:00 2001
From: Johanna <johanna@zijderveld.de>
Date: Thu, 11 Apr 2024 22:31:08 +0200
Subject: [PATCH] change test temporarily to kvector one
---
codes/test_graphene.py | 20 ++++++++++++++------
1 file changed, 14 insertions(+), 6 deletions(-)
diff --git a/codes/test_graphene.py b/codes/test_graphene.py
index 37681d1..dc6da60 100644
--- a/codes/test_graphene.py
+++ b/codes/test_graphene.py
@@ -1,16 +1,19 @@
# %%
import numpy as np
from codes.model import Model
-from codes.solvers import solver
+from codes.solvers import solverkvector
from codes import kwant_examples
from codes.kwant_helper import utils
from codes.tb.utils import compute_gap
from codes.tb.tb import addTb
import pytest
+
repeatNumber = 10
# %%
graphene_builder, int_builder = kwant_examples.graphene_extended_hubbard()
h_0 = utils.builder2h_0(graphene_builder)
+
+
# %%
def gap_prediction(U, V):
"""
@@ -28,8 +31,8 @@ def gap_prediction(U, V):
params = {"U": U, "V": V}
# Compare to phase diagram in https://arxiv.org/pdf/1204.4531.pdf
- upperPhaseLine = 0.181*U + 0.416
- lowerPhaseLine = 1.707*U - 3.823
+ upperPhaseLine = 0.181 * U + 0.416
+ lowerPhaseLine = 1.707 * U - 3.823
triplePoint = (2.78, 0.92)
gapped = False
@@ -46,7 +49,9 @@ def gap_prediction(U, V):
guess = utils.generate_guess(frozenset(h_int), len(list(h_0.values())[0]))
model = Model(h_0, h_int, filling)
- mf_sol = solver(model, guess, nK=nK, optimizer_kwargs={'verbose' : True, 'M' : 0})
+ mf_sol = solverkvector(
+ model, guess, nK=nK, optimizer_kwargs={"verbose": True, "M": 0}
+ )
gap = compute_gap(addTb(h_0, mf_sol), n=100)
# Check if the gap is predicted correctly
@@ -54,11 +59,14 @@ def gap_prediction(U, V):
gappedPredicted = True
else:
gappedPredicted = False
- assert gapped == gappedPredicted, f"Mean-field theory failed to predict the gap for U = {U}, V = {V}"
+ assert (
+ gapped == gappedPredicted
+ ), f"Mean-field theory failed to predict the gap for U = {U}, V = {V}"
+
# %%
@pytest.mark.repeat(repeatNumber)
def test_gap():
U = np.random.uniform(0, 2)
V = np.random.uniform(0, 1)
- gap_prediction(U, V)
\ No newline at end of file
+ gap_prediction(U, V)
--
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