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version 0.0.21

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guanjihuan 2021-09-25 17:14:59 +08:00
parent cc1f75895c
commit 9efb7b1daf
13 changed files with 229 additions and 254 deletions
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16
API_reference.py
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@ -1,9 +1,7 @@
import guan
# test # Source code: https://py.guanjihuan.com/test
guan.test()
# basic functions # Source code: https://py.guanjihuan.com/basic_functions
guan.test()
sigma_0 = guan.sigma_0()
sigma_x = guan.sigma_x()
sigma_y = guan.sigma_y()
@ -24,8 +22,6 @@ sigma_z0 = guan.sigma_z0()
sigma_zx = guan.sigma_zx()
sigma_zy = guan.sigma_zy()
sigma_zz = guan.sigma_zz()
# calculate reciprocal lattice vectors # Source code: https://py.guanjihuan.com/calculate_reciprocal_lattice_vectors
b1 = guan.calculate_one_dimensional_reciprocal_lattice_vector(a1)
b1, b2 = guan.calculate_two_dimensional_reciprocal_lattice_vectors(a1, a2)
b1, b2, b3 = guan.calculate_three_dimensional_reciprocal_lattice_vectors(a1, a2, a3)
@ -56,15 +52,11 @@ hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k,
hamiltonian = guan.hamiltonian_of_haldane_model(k1, k2, M=2/3, t1=1, t2=1/3, phi=pi/4, a=1/sqrt(3))
hamiltonian = guan.hamiltonian_of_haldane_model_in_quasi_one_dimension(k, N=10, M=2/3, t1=1, t2=1/3, phi=pi/4)
# calculate band structures # Source code: https://py.guanjihuan.com/calculate_band_structures
# calculate band structures # Source code: https://py.guanjihuan.com/source-code/calculate_band_structures_and_wave_functions
eigenvalue = guan.calculate_eigenvalue(hamiltonian)
eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function)
eigenvalue_array = guan.calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function)
# calculate wave functions # Source code: https://py.guanjihuan.com/calculate_wave_functions
eigenvector = guan.calculate_eigenvector(hamiltonian)
# find vector with the same gauge # Source code: https://py.guanjihuan.com/find_vector_with_the_same_gauge
vector_target = guan.find_vector_with_the_same_gauge_with_binary_search(vector_target, vector_ref, show_error=1, show_times=0, show_phase=0, n_test=10001, precision=1e-6)
vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None)
@ -114,10 +106,8 @@ guan.plot(x_array, y_array, xlabel='x', ylabel='y', title='', filename='a', show
guan.plot_3d_surface(x_array, y_array, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0, z_min=None, z_max=None)
guan.plot_contour(x_array, y_array, matrix, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0)
# download # Source code: https://py.guanjihuan.com/download
# download # Source code: https://py.guanjihuan.com/source-code/others
guan.download_with_scihub(address=None, num=1)
# audio # Source code: https://py.guanjihuan.com/audio
guan.str_to_audio(str='hello world', rate=125, voice=1, read=1, save=0, print_text=0)
guan.txt_to_audio(txt_path, rate=125, voice=1, read=1, save=0, print_text=0)
content = guan.pdf_to_text(pdf_path)

3
PyPI/README.md
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@ -1,2 +1 @@
Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.

2
PyPI/setup.cfg
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@ -1,7 +1,7 @@
[metadata]
# replace with your username:
name = guan
version = 0.0.19
version = 0.0.21
author = guanjihuan
author_email = guanjihuan@163.com
description = An open source python package

9
PyPI/src/guan/__init__.py
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@ -2,15 +2,11 @@
# import modules
from .test import *
from .basic_functions import *
from .calculate_reciprocal_lattice_vectors import *
from .Fourier_transform import *
from .Hamiltonian_of_finite_size import *
from .Hamiltonian_of_models_in_the_reciprocal_space import *
from .calculate_band_structures import *
from .calculate_wave_functions import *
from .find_vector_with_the_same_gauge import *
from .calculate_band_structures_and_wave_functions import *
from .calculate_Green_functions import *
from .calculate_density_of_states import *
from .calculate_conductance import *
@ -19,5 +15,4 @@ from .calculate_Chern_number import *
from .calculate_Wilson_loop import *
from .read_and_write import *
from .plot_figures import *
from .download import *
from .audio import *
from .others import *

62
PyPI/src/guan/basic_functions.py
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@ -4,6 +4,11 @@
import numpy as np
## test
def test():
print('\nSuccess in the installation of Guan package!\n')
## Pauli matrices
def sigma_0():
@ -66,4 +71,59 @@ def sigma_zy():
return np.kron(sigma_z(), sigma_y())
def sigma_zz():
return np.kron(sigma_z(), sigma_z())
return np.kron(sigma_z(), sigma_z())
## calculate reciprocal lattice vectors
def calculate_one_dimensional_reciprocal_lattice_vector(a1):
b1 = 2*np.pi/a1
return b1
def calculate_two_dimensional_reciprocal_lattice_vectors(a1, a2):
a1 = np.array(a1)
a2 = np.array(a2)
a1 = np.append(a1, 0)
a2 = np.append(a2, 0)
a3 = np.array([0, 0, 1])
b1 = 2*np.pi*np.cross(a2, a3)/np.dot(a1, np.cross(a2, a3))
b2 = 2*np.pi*np.cross(a3, a1)/np.dot(a1, np.cross(a2, a3))
b1 = np.delete(b1, 2)
b2 = np.delete(b2, 2)
return b1, b2
def calculate_three_dimensional_reciprocal_lattice_vectors(a1, a2, a3):
a1 = np.array(a1)
a2 = np.array(a2)
a3 = np.array(a3)
b1 = 2*np.pi*np.cross(a2, a3)/np.dot(a1, np.cross(a2, a3))
b2 = 2*np.pi*np.cross(a3, a1)/np.dot(a1, np.cross(a2, a3))
b3 = 2*np.pi*np.cross(a1, a2)/np.dot(a1, np.cross(a2, a3))
return b1, b2, b3
def calculate_one_dimensional_reciprocal_lattice_vector_with_sympy(a1):
import sympy
b1 = 2*sympy.pi/a1
return b1
def calculate_two_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2):
import sympy
a1 = sympy.Matrix(1, 3, [a1[0], a1[1], 0])
a2 = sympy.Matrix(1, 3, [a2[0], a2[1], 0])
a3 = sympy.Matrix(1, 3, [0, 0, 1])
cross_a2_a3 = a2.cross(a3)
cross_a3_a1 = a3.cross(a1)
b1 = 2*sympy.pi*cross_a2_a3/a1.dot(cross_a2_a3)
b2 = 2*sympy.pi*cross_a3_a1/a1.dot(cross_a2_a3)
b1 = sympy.Matrix(1, 2, [b1[0], b1[1]])
b2 = sympy.Matrix(1, 2, [b2[0], b2[1]])
return b1, b2
def calculate_three_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2, a3):
import sympy
cross_a2_a3 = a2.cross(a3)
cross_a3_a1 = a3.cross(a1)
cross_a1_a2 = a1.cross(a2)
b1 = 2*sympy.pi*cross_a2_a3/a1.dot(cross_a2_a3)
b2 = 2*sympy.pi*cross_a3_a1/a1.dot(cross_a2_a3)
b3 = 2*sympy.pi*cross_a1_a2/a1.dot(cross_a2_a3)
return b1, b2, b3

59
PyPI/src/guan/calculate_band_structures.py
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@ -1,59 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# calculate band structures
import numpy as np
def calculate_eigenvalue(hamiltonian):
if np.array(hamiltonian).shape==():
eigenvalue = np.real(hamiltonian)
else:
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue = np.sort(np.real(eigenvalue))
return eigenvalue
def calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function):
dim_x = np.array(x_array).shape[0]
i0 = 0
if np.array(hamiltonian_function(0)).shape==():
eigenvalue_array = np.zeros((dim_x, 1))
for x0 in x_array:
hamiltonian = hamiltonian_function(x0)
eigenvalue_array[i0, 0] = np.real(hamiltonian)
i0 += 1
else:
dim = np.array(hamiltonian_function(0)).shape[0]
eigenvalue_array = np.zeros((dim_x, dim))
for x0 in x_array:
hamiltonian = hamiltonian_function(x0)
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue_array[i0, :] = np.sort(np.real(eigenvalue[:]))
i0 += 1
return eigenvalue_array
def calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function):
dim_x = np.array(x_array).shape[0]
dim_y = np.array(y_array).shape[0]
if np.array(hamiltonian_function(0,0)).shape==():
eigenvalue_array = np.zeros((dim_y, dim_x, 1))
i0 = 0
for y0 in y_array:
j0 = 0
for x0 in x_array:
hamiltonian = hamiltonian_function(x0, y0)
eigenvalue_array[i0, j0, 0] = np.real(hamiltonian)
j0 += 1
i0 += 1
else:
dim = np.array(hamiltonian_function(0, 0)).shape[0]
eigenvalue_array = np.zeros((dim_y, dim_x, dim))
i0 = 0
for y0 in y_array:
j0 = 0
for x0 in x_array:
hamiltonian = hamiltonian_function(x0, y0)
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue_array[i0, j0, :] = np.sort(np.real(eigenvalue[:]))
j0 += 1
i0 += 1
return eigenvalue_array

121
PyPI/src/guan/calculate_band_structures_and_wave_functions.py Normal file
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@ -0,0 +1,121 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# calculate_band_structures_and_wave_functions
## calculate band structures
import numpy as np
import cmath
def calculate_eigenvalue(hamiltonian):
if np.array(hamiltonian).shape==():
eigenvalue = np.real(hamiltonian)
else:
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue = np.sort(np.real(eigenvalue))
return eigenvalue
def calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function):
dim_x = np.array(x_array).shape[0]
i0 = 0
if np.array(hamiltonian_function(0)).shape==():
eigenvalue_array = np.zeros((dim_x, 1))
for x0 in x_array:
hamiltonian = hamiltonian_function(x0)
eigenvalue_array[i0, 0] = np.real(hamiltonian)
i0 += 1
else:
dim = np.array(hamiltonian_function(0)).shape[0]
eigenvalue_array = np.zeros((dim_x, dim))
for x0 in x_array:
hamiltonian = hamiltonian_function(x0)
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue_array[i0, :] = np.sort(np.real(eigenvalue[:]))
i0 += 1
return eigenvalue_array
def calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function):
dim_x = np.array(x_array).shape[0]
dim_y = np.array(y_array).shape[0]
if np.array(hamiltonian_function(0,0)).shape==():
eigenvalue_array = np.zeros((dim_y, dim_x, 1))
i0 = 0
for y0 in y_array:
j0 = 0
for x0 in x_array:
hamiltonian = hamiltonian_function(x0, y0)
eigenvalue_array[i0, j0, 0] = np.real(hamiltonian)
j0 += 1
i0 += 1
else:
dim = np.array(hamiltonian_function(0, 0)).shape[0]
eigenvalue_array = np.zeros((dim_y, dim_x, dim))
i0 = 0
for y0 in y_array:
j0 = 0
for x0 in x_array:
hamiltonian = hamiltonian_function(x0, y0)
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvalue_array[i0, j0, :] = np.sort(np.real(eigenvalue[:]))
j0 += 1
i0 += 1
return eigenvalue_array
## calculate wave functions
def calculate_eigenvector(hamiltonian):
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvector = eigenvector[:, np.argsort(np.real(eigenvalue))]
return eigenvector
## find vector with the same gauge
def find_vector_with_the_same_gauge_with_binary_search(vector_target, vector_ref, show_error=1, show_times=0, show_phase=0, n_test=10001, precision=1e-6):
phase_1_pre = 0
phase_2_pre = np.pi
for i0 in range(n_test):
test_1 = np.sum(np.abs(vector_target*cmath.exp(1j*phase_1_pre) - vector_ref))
test_2 = np.sum(np.abs(vector_target*cmath.exp(1j*phase_2_pre) - vector_ref))
if test_1 < precision:
phase = phase_1_pre
if show_times==1:
print('Binary search times=', i0)
break
if i0 == n_test-1:
phase = phase_1_pre
if show_error==1:
print('Gauge not found with binary search times=', i0)
if test_1 < test_2:
if i0 == 0:
phase_1 = phase_1_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_1_pre+(phase_2_pre-phase_1_pre)/2
else:
phase_1 = phase_1_pre
phase_2 = phase_1_pre+(phase_2_pre-phase_1_pre)/2
else:
if i0 == 0:
phase_1 = phase_2_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_2_pre+(phase_2_pre-phase_1_pre)/2
else:
phase_1 = phase_2_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_2_pre
phase_1_pre = phase_1
phase_2_pre = phase_2
vector_target = vector_target*cmath.exp(1j*phase)
if show_phase==1:
print('Phase=', phase)
return vector_target
def find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None):
if index == None:
index = np.argmax(np.abs(vector))
sign_pre = np.sign(np.imag(vector[index]))
for phase in np.arange(0, 2*np.pi, precision):
sign = np.sign(np.imag(vector[index]*cmath.exp(1j*phase)))
if np.abs(np.imag(vector[index]*cmath.exp(1j*phase))) < 1e-9 or sign == -sign_pre:
break
sign_pre = sign
vector = vector*cmath.exp(1j*phase)
if np.real(vector[index]) < 0:
vector = -vector
return vector

59
PyPI/src/guan/calculate_reciprocal_lattice_vectors.py
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@ -1,59 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# calculate reciprocal lattice vectors
import numpy as np
from math import *
def calculate_one_dimensional_reciprocal_lattice_vector(a1):
b1 = 2*pi/a1
return b1
def calculate_two_dimensional_reciprocal_lattice_vectors(a1, a2):
a1 = np.array(a1)
a2 = np.array(a2)
a1 = np.append(a1, 0)
a2 = np.append(a2, 0)
a3 = np.array([0, 0, 1])
b1 = 2*pi*np.cross(a2, a3)/np.dot(a1, np.cross(a2, a3))
b2 = 2*pi*np.cross(a3, a1)/np.dot(a1, np.cross(a2, a3))
b1 = np.delete(b1, 2)
b2 = np.delete(b2, 2)
return b1, b2
def calculate_three_dimensional_reciprocal_lattice_vectors(a1, a2, a3):
a1 = np.array(a1)
a2 = np.array(a2)
a3 = np.array(a3)
b1 = 2*pi*np.cross(a2, a3)/np.dot(a1, np.cross(a2, a3))
b2 = 2*pi*np.cross(a3, a1)/np.dot(a1, np.cross(a2, a3))
b3 = 2*pi*np.cross(a1, a2)/np.dot(a1, np.cross(a2, a3))
return b1, b2, b3
def calculate_one_dimensional_reciprocal_lattice_vector_with_sympy(a1):
import sympy
b1 = 2*sympy.pi/a1
return b1
def calculate_two_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2):
import sympy
a1 = sympy.Matrix(1, 3, [a1[0], a1[1], 0])
a2 = sympy.Matrix(1, 3, [a2[0], a2[1], 0])
a3 = sympy.Matrix(1, 3, [0, 0, 1])
cross_a2_a3 = a2.cross(a3)
cross_a3_a1 = a3.cross(a1)
b1 = 2*sympy.pi*cross_a2_a3/a1.dot(cross_a2_a3)
b2 = 2*sympy.pi*cross_a3_a1/a1.dot(cross_a2_a3)
b1 = sympy.Matrix(1, 2, [b1[0], b1[1]])
b2 = sympy.Matrix(1, 2, [b2[0], b2[1]])
return b1, b2
def calculate_three_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2, a3):
import sympy
cross_a2_a3 = a2.cross(a3)
cross_a3_a1 = a3.cross(a1)
cross_a1_a2 = a1.cross(a2)
b1 = 2*sympy.pi*cross_a2_a3/a1.dot(cross_a2_a3)
b2 = 2*sympy.pi*cross_a3_a1/a1.dot(cross_a2_a3)
b3 = 2*sympy.pi*cross_a1_a2/a1.dot(cross_a2_a3)
return b1, b2, b3

10
PyPI/src/guan/calculate_wave_functions.py
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@ -1,10 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# calculate wave functions
import numpy as np
def calculate_eigenvector(hamiltonian):
eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
eigenvector = eigenvector[:, np.argsort(np.real(eigenvalue))]
return eigenvector

38
PyPI/src/guan/download.py
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@ -1,38 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# download
def download_with_scihub(address=None, num=1):
from bs4 import BeautifulSoup
import re
import requests
import os
if num==1 and address!=None:
address_array = [address]
else:
address_array = []
for i in range(num):
address = input('\nInput：')
address_array.append(address)
for address in address_array:
r = requests.post('https://sci-hub.st/', data={'request': address})
print('\nResponse：', r)
print('Address：', r.url)
soup = BeautifulSoup(r.text, features='lxml')
pdf_URL = soup.iframe['src']
if re.search(re.compile('^https:'), pdf_URL):
pass
else:
pdf_URL = 'https:'+pdf_URL
print('PDF address：', pdf_URL)
name = re.search(re.compile('fdp.*?/'),pdf_URL[::-1]).group()[::-1][1::]
print('PDF name：', name)
print('Directory：', os.getcwd())
print('\nDownloading...')
r = requests.get(pdf_URL, stream=True)
with open(name, 'wb') as f:
for chunk in r.iter_content(chunk_size=32):
f.write(chunk)
print('Completed!\n')
if num != 1:
print('All completed!\n')

57
PyPI/src/guan/find_vector_with_the_same_gauge.py
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@ -1,57 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# find vector with the same gauge
import numpy as np
import cmath
from math import *
def find_vector_with_the_same_gauge_with_binary_search(vector_target, vector_ref, show_error=1, show_times=0, show_phase=0, n_test=10001, precision=1e-6):
phase_1_pre = 0
phase_2_pre = pi
for i0 in range(n_test):
test_1 = np.sum(np.abs(vector_target*cmath.exp(1j*phase_1_pre) - vector_ref))
test_2 = np.sum(np.abs(vector_target*cmath.exp(1j*phase_2_pre) - vector_ref))
if test_1 < precision:
phase = phase_1_pre
if show_times==1:
print('Binary search times=', i0)
break
if i0 == n_test-1:
phase = phase_1_pre
if show_error==1:
print('Gauge not found with binary search times=', i0)
if test_1 < test_2:
if i0 == 0:
phase_1 = phase_1_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_1_pre+(phase_2_pre-phase_1_pre)/2
else:
phase_1 = phase_1_pre
phase_2 = phase_1_pre+(phase_2_pre-phase_1_pre)/2
else:
if i0 == 0:
phase_1 = phase_2_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_2_pre+(phase_2_pre-phase_1_pre)/2
else:
phase_1 = phase_2_pre-(phase_2_pre-phase_1_pre)/2
phase_2 = phase_2_pre
phase_1_pre = phase_1
phase_2_pre = phase_2
vector_target = vector_target*cmath.exp(1j*phase)
if show_phase==1:
print('Phase=', phase)
return vector_target
def find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None):
if index == None:
index = np.argmax(np.abs(vector))
sign_pre = np.sign(np.imag(vector[index]))
for phase in np.arange(0, 2*pi, precision):
sign = np.sign(np.imag(vector[index]*cmath.exp(1j*phase)))
if np.abs(np.imag(vector[index]*cmath.exp(1j*phase))) < 1e-9 or sign == -sign_pre:
break
sign_pre = sign
vector = vector*cmath.exp(1j*phase)
if np.real(vector[index]) < 0:
vector = -vector
return vector

41
PyPI/src/guan/audio.py → PyPI/src/guan/others.py
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@ -1,6 +1,45 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# audio
# others
## download
def download_with_scihub(address=None, num=1):
from bs4 import BeautifulSoup
import re
import requests
import os
if num==1 and address!=None:
address_array = [address]
else:
address_array = []
for i in range(num):
address = input('\nInput：')
address_array.append(address)
for address in address_array:
r = requests.post('https://sci-hub.st/', data={'request': address})
print('\nResponse：', r)
print('Address：', r.url)
soup = BeautifulSoup(r.text, features='lxml')
pdf_URL = soup.iframe['src']
if re.search(re.compile('^https:'), pdf_URL):
pass
else:
pdf_URL = 'https:'+pdf_URL
print('PDF address：', pdf_URL)
name = re.search(re.compile('fdp.*?/'),pdf_URL[::-1]).group()[::-1][1::]
print('PDF name：', name)
print('Directory：', os.getcwd())
print('\nDownloading...')
r = requests.get(pdf_URL, stream=True)
with open(name, 'wb') as f:
for chunk in r.iter_content(chunk_size=32):
f.write(chunk)
print('Completed!\n')
if num != 1:
print('All completed!\n')
## audio
def str_to_audio(str='hello world', rate=125, voice=1, read=1, save=0, print_text=0):
import pyttsx3

6
PyPI/src/guan/test.py
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@ -1,6 +0,0 @@
# Guan is an open-source python package developed and maintained by https://www.guanjihuan.com. The primary location of this package is on website https://py.guanjihuan.com.
# test
def test():
print('\nSuccess in the installation of Guan package!\n')