guan-0.0.85
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import guan
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import math
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# basic functions
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guan.test()
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sigma_0 = guan.sigma_0()
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sigma_x = guan.sigma_x()
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sigma_y = guan.sigma_y()
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sigma_z = guan.sigma_z()
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sigma_00 = guan.sigma_00()
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sigma_0x = guan.sigma_0x()
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sigma_0y = guan.sigma_0y()
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sigma_0z = guan.sigma_0z()
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sigma_x0 = guan.sigma_x0()
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sigma_xx = guan.sigma_xx()
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sigma_xy = guan.sigma_xy()
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sigma_xz = guan.sigma_xz()
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sigma_y0 = guan.sigma_y0()
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sigma_yx = guan.sigma_yx()
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sigma_yy = guan.sigma_yy()
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sigma_yz = guan.sigma_yz()
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sigma_z0 = guan.sigma_z0()
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sigma_zx = guan.sigma_zx()
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sigma_zy = guan.sigma_zy()
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sigma_zz = guan.sigma_zz()
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# Fourier transform
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hamiltonian = guan.one_dimensional_fourier_transform(k, unit_cell, hopping)
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hamiltonian = guan.two_dimensional_fourier_transform_for_square_lattice(k1, k2, unit_cell, hopping_1, hopping_2)
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hamiltonian = guan.three_dimensional_fourier_transform_for_cubic_lattice(k1, k2, k3, unit_cell, hopping_1, hopping_2, hopping_3)
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hamiltonian_function = guan.one_dimensional_fourier_transform_with_k(unit_cell, hopping)
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hamiltonian_function = guan.two_dimensional_fourier_transform_for_square_lattice_with_k1_k2(unit_cell, hopping_1, hopping_2)
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hamiltonian_function = guan.three_dimensional_fourier_transform_for_cubic_lattice_with_k1_k2_k3(unit_cell, hopping_1, hopping_2, hopping_3)
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b1 = guan.calculate_one_dimensional_reciprocal_lattice_vector(a1)
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b1, b2 = guan.calculate_two_dimensional_reciprocal_lattice_vectors(a1, a2)
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b1, b2, b3 = guan.calculate_three_dimensional_reciprocal_lattice_vectors(a1, a2, a3)
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b1 = guan.calculate_one_dimensional_reciprocal_lattice_vector_with_sympy(a1)
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b1, b2 = guan.calculate_two_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2)
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b1, b2, b3 = guan.calculate_three_dimensional_reciprocal_lattice_vectors_with_sympy(a1, a2, a3)
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# Hamiltonian of finite size systems
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hamiltonian = guan.hamiltonian_of_finite_size_system_along_one_direction(N, on_site=0, hopping=1, period=0)
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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)
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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)
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hopping = guan.hopping_matrix_along_zigzag_direction_for_graphene_ribbon(N)
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hamiltonian = guan.hamiltonian_of_finite_size_system_along_two_directions_for_graphene(N1, N2, period_1=0, period_2=0)
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# Hamiltonian of models in the reciprocal space
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hamiltonian = guan.hamiltonian_of_simple_chain(k)
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hamiltonian = guan.hamiltonian_of_square_lattice(k1, k2)
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hamiltonian = guan.hamiltonian_of_square_lattice_in_quasi_one_dimension(k, N=10)
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hamiltonian = guan.hamiltonian_of_cubic_lattice(k1, k2, k3)
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hamiltonian = guan.hamiltonian_of_ssh_model(k, v=0.6, w=1)
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hamiltonian = guan.hamiltonian_of_graphene(k1, k2, M=0, t=1, a=1/math.sqrt(3))
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hamiltonian = guan.hamiltonian_of_graphene_with_zigzag_in_quasi_one_dimension(k, N=10, M=0, t=1)
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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))
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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)
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hamiltonian = guan.hamiltonian_of_one_QAH_model(k1, k2, t1=1, t2=1, t3=0.5, m=-1)
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hamiltonian = guan.hamiltonian_of_BBH_model(kx, ky, gamma_x=0.5, gamma_y=0.5, lambda_x=1, lambda_y=1)
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# band structures and wave functions
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eigenvalue = guan.calculate_eigenvalue(hamiltonian)
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eigenvalue_array = guan.calculate_eigenvalue_with_one_parameter(x_array, hamiltonian_function, print_show=0)
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eigenvalue_array = guan.calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_function, print_show=0, print_show_more=0)
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eigenvector = guan.calculate_eigenvector(hamiltonian)
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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)
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vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector, precision=0.005, index=None)
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vector_array = guan.find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array, precision=0.005)
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vector1, vector2 = guan.rotation_of_degenerate_vectors(vector1, vector2, index1, index2, precision=0.01, criterion=0.01, show_theta=0)
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vector1_array, vector2_array = guan.rotation_of_degenerate_vectors_array(vector1_array, vector2_array, precision=0.01, criterion=0.01, show_theta=0)
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# Green functions
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green = guan.green_function(fermi_energy, hamiltonian, broadening, self_energy=0)
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green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n_minus, broadening, self_energy=0)
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green_in_n = guan.green_function_in_n(green_in_n_minus, h01, green_nn_n)
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green_ni_n = guan.green_function_ni_n(green_nn_n, h01, green_ni_n_minus)
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green_ii_n = guan.green_function_ii_n(green_ii_n_minus, green_in_n_minus, h01, green_nn_n, green_ni_n_minus)
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transfer = guan.transfer_matrix(fermi_energy, h00, h01)
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right_lead_surface, left_lead_surface = guan.surface_green_function_of_lead(fermi_energy, h00, h01)
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right_self_energy, left_self_energy, gamma_right, gamma_left = guan.self_energy_of_lead(fermi_energy, h00, h01)
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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)
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self_energy, gamma = guan.self_energy_of_lead_with_h_lead_to_center(fermi_energy, h00, h01, h_lead_to_center)
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green, gamma_right, gamma_left = guan.green_function_with_leads(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian)
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G_n = guan.electron_correlation_function_green_n_for_local_current(fermi_energy, h00, h01, h_LC, h_CR, center_hamiltonian)
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# density of states
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total_dos = guan.total_density_of_states(fermi_energy, hamiltonian, broadening=0.01)
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total_dos_array = guan.total_density_of_states_with_fermi_energy_array(fermi_energy_array, hamiltonian, broadening=0.01, print_show=0)
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local_dos = guan.local_density_of_states_for_square_lattice(fermi_energy, hamiltonian, N1, N2, internal_degree=1, broadening=0.01)
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local_dos = guan.local_density_of_states_for_cubic_lattice(fermi_energy, hamiltonian, N1, N2, N3, internal_degree=1, broadening=0.01)
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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)
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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)
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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)
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# quantum transport
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conductance = guan.calculate_conductance(fermi_energy, h00, h01, length=100)
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conductance_array = guan.calculate_conductance_with_fermi_energy_array(fermi_energy_array, h00, h01, length=100, print_show=0)
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conductance = guan.calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensity=2.0, disorder_concentration=1.0, length=100)
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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)
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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)
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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)
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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)
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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)
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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)
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if_active = guan.if_active_channel(k_of_channel)
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k_of_channel, velocity_of_channel, eigenvalue, eigenvector = guan.get_k_and_velocity_of_channel(fermi_energy, h00, h01)
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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)
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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)
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guan.print_or_write_scattering_matrix(fermi_energy, h00, h01, length=100, print_show=1, write_file=0, filename='a', format='txt')
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# topological invariant
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chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_function, precision=100, print_show=0)
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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)
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chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0)
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wilson_loop_array = guan.calculate_wilson_loop(hamiltonian_function, k_min=-math.pi, k_max=math.pi, precision=100, print_show=0)
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# read and write
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x_array, y_array = guan.read_one_dimensional_data(filename='a', format='txt')
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x_array, y_array, matrix = guan.read_two_dimensional_data(filename='a', format='txt')
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guan.write_one_dimensional_data(x_array, y_array, filename='a', format='txt')
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guan.write_two_dimensional_data(x_array, y_array, matrix, filename='a', format='txt')
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# plot figures
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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)
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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)
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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)
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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)
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guan.combine_two_images(image_path_array, figsize=(16,8), show=0, save=1, filename='a', format='jpg', dpi=300)
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guan.combine_three_images(image_path_array, figsize=(16,5), show=0, save=1, filename='a', format='jpg', dpi=300)
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guan.combine_four_images(image_path_array, figsize=(16,16), show=0, save=1, filename='a', format='jpg', dpi=300)
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guan.make_gif(image_path_array, filename='a', duration=0.1)
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# data processing
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parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, cpus=1, task_index=0)
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guan.change_directory_by_replacement(current_key_word='codes', new_key_word='data')
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guan.batch_reading_and_plotting(directory, xlabel='x', ylabel='y')
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# others
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guan.download_with_scihub(address=None, num=1)
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guan.str_to_audio(str='hello world', rate=125, voice=1, read=1, save=0, print_text=0)
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guan.txt_to_audio(txt_path, rate=125, voice=1, read=1, save=0, print_text=0)
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content = guan.pdf_to_text(pdf_path)
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guan.pdf_to_audio(pdf_path, rate=125, voice=1, read=1, save=0, print_text=0)
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guan.play_academic_words(bre_or_ame='ame', random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1)
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guan.play_element_words(random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1)
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@@ -1,10 +1,10 @@
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[metadata]
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# replace with your username:
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name = guan
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version = 0.0.84
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version = 0.0.85
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author = guanjihuan
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author_email = guanjihuan@163.com
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description = An open source python package
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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.
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long_description = file: README.md
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long_description_content_type = text/markdown
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url = https://py.guanjihuan.com
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@@ -1,7 +1,10 @@
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# 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.
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# Modules
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# 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.
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# Installation: pip install --upgrade guan
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# Modules:
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# # Module 1: basic functions
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# # Module 2: Fourier transform
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# # Module 3: Hamiltonian of finite size systems
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@@ -16,6 +19,308 @@
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# # Module 12: data processing
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# # Module 13: others
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'''
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API Reference
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# Module 1: basic functions
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guan.test()
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sigma_0 = guan.sigma_0()
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sigma_x = guan.sigma_x()
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sigma_y = guan.sigma_y()
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sigma_z = guan.sigma_z()
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sigma_00 = guan.sigma_00()
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sigma_0x = guan.sigma_0x()
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sigma_0y = guan.sigma_0y()
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sigma_0z = guan.sigma_0z()
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sigma_x0 = guan.sigma_x0()
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sigma_xx = guan.sigma_xx()
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sigma_xy = guan.sigma_xy()
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sigma_xz = guan.sigma_xz()
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sigma_y0 = guan.sigma_y0()
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sigma_yx = guan.sigma_yx()
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sigma_yy = guan.sigma_yy()
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sigma_yz = guan.sigma_yz()
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sigma_z0 = guan.sigma_z0()
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|
||||
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
|
||||
|
||||
Reference in New Issue
Block a user