From 6a056b04c28cf01092a8155778562d4d69399580 Mon Sep 17 00:00:00 2001 From: guanjihuan Date: Mon, 16 May 2022 14:39:56 +0800 Subject: [PATCH] guan-0.0.85 --- API_Reference/API_Reference.py | 286 ------------------------------ PyPI/setup.cfg | 4 +- PyPI/src/guan/__init__.py | 307 ++++++++++++++++++++++++++++++++- 3 files changed, 308 insertions(+), 289 deletions(-) delete mode 100644 API_Reference/API_Reference.py diff --git a/API_Reference/API_Reference.py b/API_Reference/API_Reference.py deleted file mode 100644 index cbe9c91..0000000 --- a/API_Reference/API_Reference.py +++ /dev/null @@ -1,286 +0,0 @@ -import guan -import math - -# basic functions - -guan.test() - -sigma_0 = guan.sigma_0() - -sigma_x = guan.sigma_x() - -sigma_y = guan.sigma_y() - -sigma_z = guan.sigma_z() - -sigma_00 = guan.sigma_00() - -sigma_0x = guan.sigma_0x() - -sigma_0y = guan.sigma_0y() - -sigma_0z = guan.sigma_0z() - -sigma_x0 = guan.sigma_x0() - -sigma_xx = guan.sigma_xx() - -sigma_xy = guan.sigma_xy() - -sigma_xz = guan.sigma_xz() - -sigma_y0 = guan.sigma_y0() - -sigma_yx = guan.sigma_yx() - -sigma_yy = guan.sigma_yy() - -sigma_yz = guan.sigma_yz() - -sigma_z0 = guan.sigma_z0() - -sigma_zx = guan.sigma_zx() - -sigma_zy = guan.sigma_zy() - -sigma_zz = guan.sigma_zz() - - - -# Fourier transform - -hamiltonian = guan.one_dimensional_fourier_transform(k, unit_cell, hopping) - -hamiltonian = guan.two_dimensional_fourier_transform_for_square_lattice(k1, k2, unit_cell, hopping_1, hopping_2) - -hamiltonian = guan.three_dimensional_fourier_transform_for_cubic_lattice(k1, k2, k3, unit_cell, hopping_1, hopping_2, hopping_3) - -hamiltonian_function = guan.one_dimensional_fourier_transform_with_k(unit_cell, hopping) - -hamiltonian_function = guan.two_dimensional_fourier_transform_for_square_lattice_with_k1_k2(unit_cell, hopping_1, hopping_2) - -hamiltonian_function = guan.three_dimensional_fourier_transform_for_cubic_lattice_with_k1_k2_k3(unit_cell, hopping_1, hopping_2, hopping_3) - -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) - -b1 = guan.calculate_one_dimensional_reciprocal_lattice_vector_with_sympy(a1) - -b1, b2 = guan.calculate_two_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2) - -b1, b2, b3 = guan.calculate_three_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2, a3) - - - -# Hamiltonian of finite size systems - -hamiltonian = guan.hamiltonian_of_finite_size_system_along_one_direction(N, on_site=0, hopping=1, period=0) - -hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(N1, N2, on_site=0, hopping_1=1, hopping_2=1, period_1=0, period_2=0) - -hamiltonian = guan.hamiltonian_of_finite_size_system_along_three_directions_for_cubic_lattice(N1, N2, N3, on_site=0, hopping_1=1, hopping_2=1, hopping_3=1, period_1=0, period_2=0, period_3=0) - -hopping = guan.hopping_matrix_along_zigzag_direction_for_graphene_ribbon(N) - -hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_graphene(N1, N2, period_1=0, period_2=0) - - - -# Hamiltonian of models in the reciprocal space - -hamiltonian = guan.hamiltonian_of_simple_chain(k) - -hamiltonian = guan.hamiltonian_of_square_lattice(k1, k2) - -hamiltonian = guan.hamiltonian_of_square_lattice_in_quasi_one_dimension(k, N=10) - -hamiltonian = guan.hamiltonian_of_cubic_lattice(k1, k2, k3) - -hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1) - -hamiltonian = guan.hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3)) - -hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1) - -hamiltonian = guan.hamiltonian_of_haldane_model(k1, k2, M=2/3, t1=1, t2=1/3, phi=math.pi/4, a=1/math.sqrt(3)) - -hamiltonian = guan.hamiltonian_of_haldane_model_in_quasi_one_dimension(k, N=10, M=2/3, t1=1, t2=1/3, phi=math.pi/4) - -hamiltonian = guan.hamiltonian_of_one_QAH_model(k1, k2, t1=1, t2=1, t3=0.5, m=-1) - -hamiltonian = guan.hamiltonian_of_BBH_model(kx, ky, gamma_x=0.5, gamma_y=0.5, lambda_x=1, lambda_y=1) - - - -# band structures and wave functions - -eigenvalue = guan.calculate_eigenvalue(hamiltonian) - -eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function, print_show=0) - -eigenvalue_array = guan.calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function, print_show=0, print_show_more=0) - -eigenvector = guan.calculate_eigenvector(hamiltonian) - -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=1000, precision=1e-6) - -vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None) - -vector_array = guan.find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array, precision=0.005) - -vector1, vector2 = guan.rotation_of_degenerate_vectors(vector1, vector2, index1, index2, precision=0.01, criterion=0.01, show_theta=0) - -vector1_array, vector2_array = guan.rotation_of_degenerate_vectors_array(vector1_array, vector2_array, precision=0.01, criterion=0.01, show_theta=0) - - - -# Green functions - -green = guan.green_function(fermi_energy, hamiltonian, broadening, self_energy=0) - -green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening, self_energy=0) - -green_in_n = guan.green_function_in_n(green_in_n_minus, h01, green_nn_n) - -green_ni_n = guan.green_function_ni_n(green_nn_n, h01, green_ni_n_minus) - -green_ii_n = guan.green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus) - -transfer = guan.transfer_matrix(fermi_energy, h00, h01) - -right_lead_surface, left_lead_surface = guan.surface_green_function_of_lead(fermi_energy, h00, h01) - -right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01) - -right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead_with_h_LC_and_h_CR(fermi_energy, h00, h01, h_LC, h_CR) - -self_energy, gamma = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00, h01, h_lead_to_center) - -green, gamma_right, gamma_left = guan.green_function_with_leads(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian) - -G_n = guan.electron_correlation_function_green_n_for_local_current(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian) - - - -# density of states - -total_dos = guan.total_density_of_states(fermi_energy, hamiltonian, broadening=0.01) - -total_dos_array = guan.total_density_of_states_with_fermi_energy_array(fermi_energy_array, hamiltonian, broadening=0.01, print_show=0) - -local_dos = guan.local_density_of_states_for_square_lattice(fermi_energy, hamiltonian, N1, N2, internal_degree=1, broadening=0.01) - -local_dos = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, N3, internal_degree=1, broadening=0.01) - -local_dos = guan.local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01) - -local_dos = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01) - -local_dos = guan.local_density_of_states_for_square_lattice_with_self_energy_using_dyson_equation(fermi_energy, h00, h01, N2, N1, right_self_energy, left_self_energy, internal_degree=1, broadening=0.01) - - - -# quantum transport - -conductance = guan.calculate_conductance(fermi_energy, h00, h01, length=100) - -conductance_array = guan.calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01, length=100, print_show=0) - -conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100) - -conductance_array = guan.calculate_conductance_with_disorder_intensity_array(fermi_energy, h00, h01, disorder_intensity_array, disorder_concentration=1.0, length=100, calculation_times=1, print_show=0) - -conductance_array = guan.calculate_conductance_with_disorder_concentration_array(fermi_energy, h00, h01, disorder_concentration_array, disorder_intensity=2.0, length=100, calculation_times=1, print_show=0) - -conductance_array = guan.calculate_conductance_with_scattering_length_array(fermi_energy, h00, h01, length_array, disorder_intensity=2.0, disorder_concentration=1.0, calculation_times=1, print_show=0) - -gamma_array, green = guan.get_gamma_array_and_green_for_six_terminal_transmission(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) - -transmission_matrix = guan.calculate_six_terminal_transmission_matrix(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) - -transmission_12, transmission_13, transmission_14, transmission_15, transmission_16 = guan.calculate_six_terminal_transmissions_from_lead_1(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) - -if_active = guan.if_active_channel(k_of_channel) - -k_of_channel, velocity_of_channel, eigenvalue, eigenvector = guan.get_k_and_velocity_of_channel(fermi_energy, h00, h01) - -k_right, k_left, velocity_right, velocity_left, f_right, f_left, u_right, u_left, ind_right_active = guan.get_classified_k_velocity_u_and_f(fermi_energy, h00, h01) - -transmission_matrix, reflection_matrix, k_right, k_left, velocity_right, velocity_left, ind_right_active = guan.calculate_scattering_matrix(fermi_energy, h00, h01, length=100) - -guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_show=1, write_file=0, filename='a', format='txt') - - - -# topological invariant - -chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_function, precision=100, print_show=0) - -chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=10, precision_of_Wilson_loop=100, print_show=0) - -chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) - -wilson_loop_array = guan.calculate_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0) - - - -# read and write - -x_array, y_array = guan.read_one_dimensional_data(filename='a', format='txt') - -x_array, y_array, matrix = guan.read_two_dimensional_data(filename='a', format='txt') - -guan.write_one_dimensional_data(x_array, y_array, filename='a', format='txt') - -guan.write_two_dimensional_data(x_array, y_array, matrix, filename='a', format='txt') - - - -# plot figures - -guan.plot(x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', format='jpg', dpi=300, style='', y_min=None, y_max=None, linewidth=None, markersize=None, adjust_bottom=0.2, adjust_left=0.2) - -guan.plot_3d_surface(x_array, y_array, matrix, xlabel='x', ylabel='y', zlabel='z', title='', fontsize=20, labelsize=15, show=1, save=0, filename='a', format='jpg', dpi=300, z_min=None, z_max=None, rcount=100, ccount=100) - -guan.plot_contour(x_array, y_array, matrix, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=15, show=1, save=0, filename='a', format='jpg', dpi=300) - -guan.draw_dots_and_lines(coordinate_array, draw_dots=1, draw_lines=1, max_distance=1.1, line_style='-k', linewidth=1, dot_style='ro', markersize=3, show=1, save=0, filename='a', format='eps', dpi=300) - -guan.combine_two_images(image_path_array, figsize=(16,8), show=0, save=1, filename='a', format='jpg', dpi=300) - -guan.combine_three_images(image_path_array, figsize=(16,5), show=0, save=1, filename='a', format='jpg', dpi=300) - -guan.combine_four_images(image_path_array, figsize=(16,16), show=0, save=1, filename='a', format='jpg', dpi=300) - -guan.make_gif(image_path_array, filename='a', duration=0.1) - - - -# data processing - -parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, cpus=1, task_index=0) - -guan.change_directory_by_replacement(current_key_word='codes', new_key_word='data') - -guan.batch_reading_and_plotting(directory, xlabel='x', ylabel='y') - - - -# others - -guan.download_with_scihub(address=None, num=1) - -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) - -guan.pdf_to_audio(pdf_path, rate=125, voice=1, read=1, save=0, print_text=0) - -guan.play_academic_words(bre_or_ame='ame', random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1) - -guan.play_element_words(random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1) \ No newline at end of file diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg index 3d26a40..e9c0d31 100644 --- a/PyPI/setup.cfg +++ b/PyPI/setup.cfg @@ -1,10 +1,10 @@ [metadata] # replace with your username: name = guan -version = 0.0.84 +version = 0.0.85 author = guanjihuan author_email = guanjihuan@163.com -description = An open source python package +description = Guan is an open-source python package developed and maintained by https://www.guanjihuan.com/about. The primary location of this package is on website https://py.guanjihuan.com. 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. long_description = file: README.md long_description_content_type = text/markdown url = https://py.guanjihuan.com diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py index da5fda2..683f9c6 100644 --- a/PyPI/src/guan/__init__.py +++ b/PyPI/src/guan/__init__.py @@ -1,7 +1,10 @@ # Guan is an open-source python package developed and maintained by https://www.guanjihuan.com/about. The primary location of this package is on website https://py.guanjihuan.com. -# Modules +# 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. +# Installation: pip install --upgrade guan + +# Modules: # # Module 1: basic functions # # Module 2: Fourier transform # # Module 3: Hamiltonian of finite size systems @@ -16,6 +19,308 @@ # # Module 12: data processing # # Module 13: others + + + +''' +API Reference + + + +# Module 1: basic functions + +guan.test() + +sigma_0 = guan.sigma_0() + +sigma_x = guan.sigma_x() + +sigma_y = guan.sigma_y() + +sigma_z = guan.sigma_z() + +sigma_00 = guan.sigma_00() + +sigma_0x = guan.sigma_0x() + +sigma_0y = guan.sigma_0y() + +sigma_0z = guan.sigma_0z() + +sigma_x0 = guan.sigma_x0() + +sigma_xx = guan.sigma_xx() + +sigma_xy = guan.sigma_xy() + +sigma_xz = guan.sigma_xz() + +sigma_y0 = guan.sigma_y0() + +sigma_yx = guan.sigma_yx() + +sigma_yy = guan.sigma_yy() + +sigma_yz = guan.sigma_yz() + +sigma_z0 = guan.sigma_z0() + +sigma_zx = guan.sigma_zx() + +sigma_zy = guan.sigma_zy() + +sigma_zz = guan.sigma_zz() + + + +# Module 2: Fourier transform + +hamiltonian = guan.one_dimensional_fourier_transform(k, unit_cell, hopping) + +hamiltonian = guan.two_dimensional_fourier_transform_for_square_lattice(k1, k2, unit_cell, hopping_1, hopping_2) + +hamiltonian = guan.three_dimensional_fourier_transform_for_cubic_lattice(k1, k2, k3, unit_cell, hopping_1, hopping_2, hopping_3) + +hamiltonian_function = guan.one_dimensional_fourier_transform_with_k(unit_cell, hopping) + +hamiltonian_function = guan.two_dimensional_fourier_transform_for_square_lattice_with_k1_k2(unit_cell, hopping_1, hopping_2) + +hamiltonian_function = guan.three_dimensional_fourier_transform_for_cubic_lattice_with_k1_k2_k3(unit_cell, hopping_1, hopping_2, hopping_3) + +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) + +b1 = guan.calculate_one_dimensional_reciprocal_lattice_vector_with_sympy(a1) + +b1, b2 = guan.calculate_two_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2) + +b1, b2, b3 = guan.calculate_three_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2, a3) + + + +# Module 3: Hamiltonian of finite size systems + +hamiltonian = guan.hamiltonian_of_finite_size_system_along_one_direction(N, on_site=0, hopping=1, period=0) + +hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_square_lattice(N1, N2, on_site=0, hopping_1=1, hopping_2=1, period_1=0, period_2=0) + +hamiltonian = guan.hamiltonian_of_finite_size_system_along_three_directions_for_cubic_lattice(N1, N2, N3, on_site=0, hopping_1=1, hopping_2=1, hopping_3=1, period_1=0, period_2=0, period_3=0) + +hopping = guan.hopping_matrix_along_zigzag_direction_for_graphene_ribbon(N) + +hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_graphene(N1, N2, period_1=0, period_2=0) + + + +# Module 4: Hamiltonian of models in the reciprocal space + +hamiltonian = guan.hamiltonian_of_simple_chain(k) + +hamiltonian = guan.hamiltonian_of_square_lattice(k1, k2) + +hamiltonian = guan.hamiltonian_of_square_lattice_in_quasi_one_dimension(k, N=10) + +hamiltonian = guan.hamiltonian_of_cubic_lattice(k1, k2, k3) + +hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1) + +hamiltonian = guan.hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3)) + +hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1) + +hamiltonian = guan.hamiltonian_of_haldane_model(k1, k2, M=2/3, t1=1, t2=1/3, phi=math.pi/4, a=1/math.sqrt(3)) + +hamiltonian = guan.hamiltonian_of_haldane_model_in_quasi_one_dimension(k, N=10, M=2/3, t1=1, t2=1/3, phi=math.pi/4) + +hamiltonian = guan.hamiltonian_of_one_QAH_model(k1, k2, t1=1, t2=1, t3=0.5, m=-1) + +hamiltonian = guan.hamiltonian_of_BBH_model(kx, ky, gamma_x=0.5, gamma_y=0.5, lambda_x=1, lambda_y=1) + + + +# Module 5: band structures and wave functions + +eigenvalue = guan.calculate_eigenvalue(hamiltonian) + +eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function, print_show=0) + +eigenvalue_array = guan.calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function, print_show=0, print_show_more=0) + +eigenvector = guan.calculate_eigenvector(hamiltonian) + +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=1000, precision=1e-6) + +vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None) + +vector_array = guan.find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array, precision=0.005) + +vector1, vector2 = guan.rotation_of_degenerate_vectors(vector1, vector2, index1, index2, precision=0.01, criterion=0.01, show_theta=0) + +vector1_array, vector2_array = guan.rotation_of_degenerate_vectors_array(vector1_array, vector2_array, precision=0.01, criterion=0.01, show_theta=0) + + + +# Module 6: Green functions + +green = guan.green_function(fermi_energy, hamiltonian, broadening, self_energy=0) + +green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening, self_energy=0) + +green_in_n = guan.green_function_in_n(green_in_n_minus, h01, green_nn_n) + +green_ni_n = guan.green_function_ni_n(green_nn_n, h01, green_ni_n_minus) + +green_ii_n = guan.green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus) + +transfer = guan.transfer_matrix(fermi_energy, h00, h01) + +right_lead_surface, left_lead_surface = guan.surface_green_function_of_lead(fermi_energy, h00, h01) + +right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01) + +right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead_with_h_LC_and_h_CR(fermi_energy, h00, h01, h_LC, h_CR) + +self_energy, gamma = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00, h01, h_lead_to_center) + +green, gamma_right, gamma_left = guan.green_function_with_leads(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian) + +G_n = guan.electron_correlation_function_green_n_for_local_current(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian) + + + +# Module 7: density of states + +total_dos = guan.total_density_of_states(fermi_energy, hamiltonian, broadening=0.01) + +total_dos_array = guan.total_density_of_states_with_fermi_energy_array(fermi_energy_array, hamiltonian, broadening=0.01, print_show=0) + +local_dos = guan.local_density_of_states_for_square_lattice(fermi_energy, hamiltonian, N1, N2, internal_degree=1, broadening=0.01) + +local_dos = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, N3, internal_degree=1, broadening=0.01) + +local_dos = guan.local_density_of_states_for_square_lattice_using_dyson_equation(fermi_energy, h00, h01, N2, N1, internal_degree=1, broadening=0.01) + +local_dos = guan.local_density_of_states_for_cubic_lattice_using_dyson_equation(fermi_energy, h00, h01, N3, N2, N1, internal_degree=1, broadening=0.01) + +local_dos = guan.local_density_of_states_for_square_lattice_with_self_energy_using_dyson_equation(fermi_energy, h00, h01, N2, N1, right_self_energy, left_self_energy, internal_degree=1, broadening=0.01) + + + +# Module 8: quantum transport + +conductance = guan.calculate_conductance(fermi_energy, h00, h01, length=100) + +conductance_array = guan.calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01, length=100, print_show=0) + +conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100) + +conductance_array = guan.calculate_conductance_with_disorder_intensity_array(fermi_energy, h00, h01, disorder_intensity_array, disorder_concentration=1.0, length=100, calculation_times=1, print_show=0) + +conductance_array = guan.calculate_conductance_with_disorder_concentration_array(fermi_energy, h00, h01, disorder_concentration_array, disorder_intensity=2.0, length=100, calculation_times=1, print_show=0) + +conductance_array = guan.calculate_conductance_with_scattering_length_array(fermi_energy, h00, h01, length_array, disorder_intensity=2.0, disorder_concentration=1.0, calculation_times=1, print_show=0) + +gamma_array, green = guan.get_gamma_array_and_green_for_six_terminal_transmission(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) + +transmission_matrix = guan.calculate_six_terminal_transmission_matrix(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) + +transmission_12, transmission_13, transmission_14, transmission_15, transmission_16 = guan.calculate_six_terminal_transmissions_from_lead_1(fermi_energy, h00_for_lead_4, h01_for_lead_4, h00_for_lead_2, h01_for_lead_2, center_hamiltonian, width=10, length=50, internal_degree=1, moving_step_of_leads=10) + +if_active = guan.if_active_channel(k_of_channel) + +k_of_channel, velocity_of_channel, eigenvalue, eigenvector = guan.get_k_and_velocity_of_channel(fermi_energy, h00, h01) + +k_right, k_left, velocity_right, velocity_left, f_right, f_left, u_right, u_left, ind_right_active = guan.get_classified_k_velocity_u_and_f(fermi_energy, h00, h01) + +transmission_matrix, reflection_matrix, k_right, k_left, velocity_right, velocity_left, ind_right_active = guan.calculate_scattering_matrix(fermi_energy, h00, h01, length=100) + +guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_show=1, write_file=0, filename='a', format='txt') + + + +# Module 9: topological invariant + +chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_function, precision=100, print_show=0) + +chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_function, precision_of_plaquettes=10, precision_of_Wilson_loop=100, print_show=0) + +chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) + +wilson_loop_array = guan.calculate_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0) + + + +# Module 10: read and write + +x_array, y_array = guan.read_one_dimensional_data(filename='a', format='txt') + +x_array, y_array, matrix = guan.read_two_dimensional_data(filename='a', format='txt') + +guan.write_one_dimensional_data(x_array, y_array, filename='a', format='txt') + +guan.write_two_dimensional_data(x_array, y_array, matrix, filename='a', format='txt') + + + +# Module 11: plot figures + +guan.plot(x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', format='jpg', dpi=300, style='', y_min=None, y_max=None, linewidth=None, markersize=None, adjust_bottom=0.2, adjust_left=0.2) + +guan.plot_3d_surface(x_array, y_array, matrix, xlabel='x', ylabel='y', zlabel='z', title='', fontsize=20, labelsize=15, show=1, save=0, filename='a', format='jpg', dpi=300, z_min=None, z_max=None, rcount=100, ccount=100) + +guan.plot_contour(x_array, y_array, matrix, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=15, show=1, save=0, filename='a', format='jpg', dpi=300) + +guan.draw_dots_and_lines(coordinate_array, draw_dots=1, draw_lines=1, max_distance=1.1, line_style='-k', linewidth=1, dot_style='ro', markersize=3, show=1, save=0, filename='a', format='eps', dpi=300) + +guan.combine_two_images(image_path_array, figsize=(16,8), show=0, save=1, filename='a', format='jpg', dpi=300) + +guan.combine_three_images(image_path_array, figsize=(16,5), show=0, save=1, filename='a', format='jpg', dpi=300) + +guan.combine_four_images(image_path_array, figsize=(16,16), show=0, save=1, filename='a', format='jpg', dpi=300) + +guan.make_gif(image_path_array, filename='a', duration=0.1) + + + +# Module 12: data processing + +parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, cpus=1, task_index=0) + +guan.change_directory_by_replacement(current_key_word='codes', new_key_word='data') + +guan.batch_reading_and_plotting(directory, xlabel='x', ylabel='y') + + + +# Module 13: others + +guan.download_with_scihub(address=None, num=1) + +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) + +guan.pdf_to_audio(pdf_path, rate=125, voice=1, read=1, save=0, print_text=0) + +guan.play_academic_words(bre_or_ame='ame', random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1) + +guan.play_element_words(random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1) + +''' + + + + + + + + + # import packages import numpy as np