Guan软件包官网：https://py.guanjihuan.com。安装或更新命令：pip install --upgrade guan。如果无法获取最新版本，可以指定默认源安装，安装命令为：pip install --upgrade guan -i https://pypi.python.org/simple。使用方法：import guan。个人常用的函数会不定期添加进去。
这是之前的一篇：Python开源项目Guan。本篇给出一些的学习示例，如果你需要实现相同的功能，那么可以安装软件包后进行调用或者直接复制函数源码到你自身的项目中。
测试代码：
# GUAN软件包官网: https://py.guanjihuan.com
import guan
guan.test()一、日常场景
1. 运行时间日志
# 运行时间日志
import guan
import time
guan.logging_with_day_and_time(content='start')
for i in range(3):
time.sleep(5)
guan.logging_with_day_and_time(f'end_of_{i}')2. 函数计时器
# 函数计时器
import guan
@guan.timer_decorator
def test1(a, b):
import time
print(a)
time.sleep(1)
print(b)
print('Run finished.')
for _ in range(2):
test1(10, b=20)
print()
def test2(a, b):
import time
print(a)
time.sleep(1)
print(b)
print('Run finished.')
for _ in range(2):
guan.timer(test2, 100, b=200)3. try except 简写
import guan
def test1(a, b):
print(a)
bug_code
print(b)
return 'return_message1'
result1 = guan.try_except(test1, 10, b=20)
print(result1)
print()
@guan.try_decorator
def test2(a, b):
print(a)
bug_code
print(b)
return 'return_message2'
result2 = test2(100, b=200)
print(result2)4. 变量写入文件
# 变量写入文件
import guan
import numpy as np
data = np.array([1, 2, 3])
guan.dump_data(data, filename='a')
loaded_data = guan.load_data(filename='a')
print(loaded_data)5. 打印数组
# 打印数组
import guan
a = [1, 2, 3, 'a', 'b', 'c']
guan.print_array(a)6. 矩阵写入文件后查看
# 矩阵写入文件后查看
import guan
import numpy as np
matrix = np.random.rand(5, 5)
guan.write_matrix_in_markdown_format(matrix=matrix, filename='markdown_matrix')
guan.write_matrix_in_latex_format(matrix=matrix, filename='latex_matrix')7. 检查是否为厄米矩阵
# 检查是否为厄米矩阵（相对误差为1e-5)
import guan
matrix1 = [
[2, 1.00001-1j],
[1+1j, 1]
]
print(guan.is_hermitian(matrix1))
matrix2 = [
[2, 1.00002-1j],
[1+1j, 1]
]
print(guan.is_hermitian(matrix2))8. 数组分割
# 数组分割
import numpy as np
import guan
task_num = 4
parameter_array_all = np.arange(0, 17, 1)
for task_index in range(task_num):
parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, task_num, task_index)
print(parameter_array)
print()二、物理场景
1. 泡利矩阵
# 泡利矩阵
import guan
sigma_x = guan.sigma_x()
print(sigma_x)2. 实空间哈密顿量
# 实空间哈密顿量
import guan
print('\n', guan.hamiltonian_of_finite_size_system_along_one_direction(3), '\n')
print(guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(2, 2), '\n')
print(guan.hamiltonian_of_finite_size_system_along_three_directions_for_cubic_lattice(2, 2, 2), '\n')3. 能带图计算
# 能带图计算
import guan
import numpy as np
k_array = np.linspace(-np.pi, np.pi, 100)
# one dimensional chain
hamiltonian_function = guan.one_dimensional_fourier_transform_with_k(unit_cell=0, hopping=1)
eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(k_array, hamiltonian_function)
guan.plot(k_array, eigenvalue_array, xlabel='k', ylabel='E', style='-k', fontfamily=None)
# square lattice ribbon
eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(k_array, guan.hamiltonian_of_square_lattice_in_quasi_one_dimension)
guan.plot(k_array, eigenvalue_array, xlabel='k', ylabel='E', style='-k', fontfamily=None)
# graphene ribbon
eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(k_array, guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension)
guan.plot(k_array, eigenvalue_array, xlabel='k', ylabel='E', style='-k', fontfamily=None)4. 陈数和Wilson loop计算
# 陈数和Wilson loop计算
import guan
import numpy as np
chern_number = guan.calculate_chern_number_for_square_lattice_with_efficient_method(guan.hamiltonian_of_one_QAH_model, precision=100)
print('\nChern number=', chern_number, '\n')
wilson_loop_array = guan.calculate_wilson_loop(guan.hamiltonian_of_ssh_model)
print('Wilson loop =', wilson_loop_array)
p = np.log(wilson_loop_array)/2/np.pi/1j
print('\np =', p, '\n')5. 使用格林函数计算态密度
# 使用格林函数计算态密度
import guan
import numpy as np
hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(2,2)
fermi_energy_array = np.linspace(-4, 4, 400)
total_dos_array = guan.total_density_of_states_with_fermi_energy_array(fermi_energy_array, hamiltonian, broadening=0.1)
guan.plot(fermi_energy_array, total_dos_array, xlabel='E', ylabel='Total DOS', style='-', fontfamily=None)
fermi_energy = 0
N1 = 3
N2 = 4
hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(N1,N2)
LDOS = guan.local_density_of_states_for_square_lattice(fermi_energy, hamiltonian, N1=N1, N2=N2)
print('square lattice:\n', LDOS, '\n')
h00 = guan.hamiltonian_of_finite_size_system_along_one_direction(N2)
h01 = np.identity(N2)
LDOS = guan.local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00=h00, h01=h01, N2=N2, N1=N1)
print(LDOS, '\n\n')
LDOS2 = guan.local_density_of_states_for_square_lattice_using_dyson_equation_with_second_method(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01)
print(LDOS2, '\n\n')
guan.plot_contour(range(N1), range(N2), LDOS, fontfamily=None)
guan.plot_contour(range(N1), range(N2), LDOS2, fontfamily=None)
N1 = 3
N2 = 4
N3 = 5
hamiltonian = guan.hamiltonian_of_finite_size_system_along_three_directions_for_cubic_lattice(N1, N2, N3)
LDOS = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1=N1, N2=N2, N3=N3)
print('cubic lattice:\n', LDOS, '\n')
h00 = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(N2, N3)
h01 = np.identity(N2*N3)
LDOS = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3=N3, N2=N2, N1=N1)
print(LDOS)6. 电导和散射矩阵的计算
# 电导和散射矩阵的计算
import guan
import numpy as np
fermi_energy_array = np.linspace(-4, 4, 400)
h00 = guan.hamiltonian_of_finite_size_system_along_one_direction(4)
h01 = np.identity(4)
conductance_array = guan.calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01)
guan.plot(fermi_energy_array, conductance_array, xlabel='E', ylabel='Conductance', style='-', fontfamily=None)
fermi_energy = 0
guan.print_or_write_scattering_matrix(fermi_energy, h00, h01)7. 波函数规范的选取
# 波函数规范的选取
import numpy as np
import cmath
import guan
# Fixed gauge example 1
vector = np.array([np.sqrt(0.5), np.sqrt(0.5)])*cmath.exp(np.random.uniform(0, 1)*1j)
print('\nExample 1\n', vector)
print(np.dot(vector.transpose().conj(), vector), '\n')
vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector)
print(vector)
print(np.dot(vector.transpose().conj(), vector), '\n')
# Fixed gauge example 2
vector = np.array([1, 0])*cmath.exp(np.random.uniform(0, 1)*1j)
print('\nExample 2\n', vector)
print(np.dot(vector.transpose().conj(), vector), '\n')
vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector)
print(vector)
print(np.dot(vector.transpose().conj(), vector), '\n')【说明：本站主要是个人的一些笔记和代码分享，内容可能会不定期修改。为了使全网显示的始终是最新版本，这里的文章未经同意请勿转载。引用请注明出处：https://www.guanjihuan.com】
