0.0.121
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		| @@ -248,7 +248,7 @@ chern_number = guan.calculate_chern_number_for_square_lattice(hamiltonian_functi | |||||||
|  |  | ||||||
| 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) | 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) | ||||||
|  |  | ||||||
| chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_case(hamiltonian_function, num_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0) | chern_number = guan.calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0) | ||||||
|  |  | ||||||
| chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) | chern_number = guan.calculate_chern_number_for_honeycomb_lattice(hamiltonian_function, a=1, precision=300, print_show=0) | ||||||
|  |  | ||||||
|   | |||||||
| @@ -1,7 +1,7 @@ | |||||||
| [metadata] | [metadata] | ||||||
| # replace with your username: | # replace with your username: | ||||||
| name = guan | name = guan | ||||||
| version = 0.0.120 | version = 0.0.121 | ||||||
| author = guanjihuan | author = guanjihuan | ||||||
| author_email = guanjihuan@163.com | author_email = guanjihuan@163.com | ||||||
| description = An open source python package | description = An open source python package | ||||||
|   | |||||||
| @@ -1,6 +1,6 @@ | |||||||
| Metadata-Version: 2.1 | Metadata-Version: 2.1 | ||||||
| Name: guan | Name: guan | ||||||
| Version: 0.0.120 | Version: 0.0.121 | ||||||
| Summary: An open source python package | Summary: An open source python package | ||||||
| Home-page: https://py.guanjihuan.com | Home-page: https://py.guanjihuan.com | ||||||
| Author: guanjihuan | Author: guanjihuan | ||||||
|   | |||||||
| @@ -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. | # 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-0.0.120, updated on August 12, 2022. | # The current version is guan-0.0.121, updated on August 12, 2022. | ||||||
|  |  | ||||||
| # Installation: pip install --upgrade guan | # Installation: pip install --upgrade guan | ||||||
|  |  | ||||||
| @@ -1592,7 +1592,7 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_funct | |||||||
|     chern_number = chern_number/(2*math.pi) |     chern_number = chern_number/(2*math.pi) | ||||||
|     return chern_number |     return chern_number | ||||||
|  |  | ||||||
| def calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_case(hamiltonian_function, num_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0): | def calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_case(hamiltonian_function, index_of_bands=[0, 1], precision_of_plaquettes=20, precision_of_Wilson_loop=5, print_show=0): | ||||||
|     delta = 2*math.pi/precision_of_plaquettes |     delta = 2*math.pi/precision_of_plaquettes | ||||||
|     chern_number = 0 |     chern_number = 0 | ||||||
|     for kx in np.arange(-math.pi, math.pi, delta): |     for kx in np.arange(-math.pi, math.pi, delta): | ||||||
| @@ -1625,13 +1625,13 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_ca | |||||||
|                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] |                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))] | ||||||
|                 vector_array.append(vector_delta)            |                 vector_array.append(vector_delta)            | ||||||
|             Wilson_loop = 1 |             Wilson_loop = 1 | ||||||
|             dim = len(num_of_bands) |             dim = len(index_of_bands) | ||||||
|             for i0 in range(len(vector_array)-1): |             for i0 in range(len(vector_array)-1): | ||||||
|                 dot_matrix = np.zeros((dim , dim), dtype=complex) |                 dot_matrix = np.zeros((dim , dim), dtype=complex) | ||||||
|                 i01 = 0 |                 i01 = 0 | ||||||
|                 for dim1 in num_of_bands: |                 for dim1 in index_of_bands: | ||||||
|                     i02 = 0 |                     i02 = 0 | ||||||
|                     for dim2 in num_of_bands: |                     for dim2 in index_of_bands: | ||||||
|                         dot_matrix[i01, i02] = np.dot(vector_array[i0][:, dim1].transpose().conj(), vector_array[i0+1][:, dim2]) |                         dot_matrix[i01, i02] = np.dot(vector_array[i0][:, dim1].transpose().conj(), vector_array[i0+1][:, dim2]) | ||||||
|                         i02 += 1 |                         i02 += 1 | ||||||
|                     i01 += 1 |                     i01 += 1 | ||||||
| @@ -1639,9 +1639,9 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop_for_degenerate_ca | |||||||
|                 Wilson_loop = Wilson_loop*det_value |                 Wilson_loop = Wilson_loop*det_value | ||||||
|             dot_matrix_plus = np.zeros((dim , dim), dtype=complex) |             dot_matrix_plus = np.zeros((dim , dim), dtype=complex) | ||||||
|             i01 = 0 |             i01 = 0 | ||||||
|             for dim1 in num_of_bands: |             for dim1 in index_of_bands: | ||||||
|                 i02 = 0 |                 i02 = 0 | ||||||
|                 for dim2 in num_of_bands: |                 for dim2 in index_of_bands: | ||||||
|                     dot_matrix_plus[i01, i02] = np.dot(vector_array[len(vector_array)-1][:, dim1].transpose().conj(), vector_array[0][:, dim2]) |                     dot_matrix_plus[i01, i02] = np.dot(vector_array[len(vector_array)-1][:, dim1].transpose().conj(), vector_array[0][:, dim2]) | ||||||
|                     i02 += 1 |                     i02 += 1 | ||||||
|                 i01 += 1 |                 i01 += 1 | ||||||
|   | |||||||
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