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0.0.124

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guanjihuan 2022-08-13 07:16:12 +08:00
parent e4ad66e9f4
commit f2650131a8
4 changed files with 5 additions and 5 deletions
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2
API_Reference.py
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@ -244,7 +244,7 @@ guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_
# Module 9: topological invariant
chern_number = guan.calculate_chern_number_for_square_lattice_efficient_method(hamiltonian_function, precision=100, print_show=0)
chern_number = guan.calculate_chern_number_for_square_lattice_with_efficient_method(hamiltonian_function, precision=100, print_show=0)
chern_number = guan.calculate_chern_number_for_square_lattice_with_wilson_loop(hamiltonian_function, precision_of_plaquettes=20, precision_of_wilson_loop=5, print_show=0)

2
PyPI/setup.cfg
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@ -1,7 +1,7 @@
[metadata]
# replace with your username:
name = guan
version = 0.0.123
version = 0.0.124
author = guanjihuan
author_email = guanjihuan@163.com
description = An open source python package

2
PyPI/src/guan.egg-info/PKG-INFO
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@ -1,6 +1,6 @@
Metadata-Version: 2.1
Name: guan
Version: 0.0.123
Version: 0.0.124
Summary: An open source python package
Home-page: https://py.guanjihuan.com
Author: guanjihuan

4
PyPI/src/guan/__init__.py
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@ -2,7 +2,7 @@
# With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated in this package, such as file reading/writing, figure plotting, data processing.
# The current version is guan-0.0.123, updated on August 13, 2022.
# The current version is guan-0.0.124, updated on August 13, 2022.
# Installation: pip install --upgrade guan
@ -1518,7 +1518,7 @@ def print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_s
# Module 9: topological invariant
def calculate_chern_number_for_square_lattice_efficient_method(hamiltonian_function, precision=100, print_show=0):
def calculate_chern_number_for_square_lattice_with_efficient_method(hamiltonian_function, precision=100, print_show=0):
if np.array(hamiltonian_function(0, 0)).shape==():
dim = 1
else: