From 4d5cfe29141111be7d4cd185fc7dadb83fe0e61e Mon Sep 17 00:00:00 2001 From: guanjihuan Date: Fri, 12 Aug 2022 19:21:58 +0800 Subject: [PATCH] 0.0.121 --- API_Reference.py | 2 +- PyPI/setup.cfg | 2 +- PyPI/src/guan.egg-info/PKG-INFO | 2 +- PyPI/src/guan/__init__.py | 14 +++++++------- 4 files changed, 10 insertions(+), 10 deletions(-) diff --git a/API_Reference.py b/API_Reference.py index 08b7598..99079f6 100644 --- a/API_Reference.py +++ b/API_Reference.py @@ -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_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) diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg index a99c33d..e7b5d64 100644 --- a/PyPI/setup.cfg +++ b/PyPI/setup.cfg @@ -1,7 +1,7 @@ [metadata] # replace with your username: name = guan -version = 0.0.120 +version = 0.0.121 author = guanjihuan author_email = guanjihuan@163.com description = An open source python package diff --git a/PyPI/src/guan.egg-info/PKG-INFO b/PyPI/src/guan.egg-info/PKG-INFO index 89af6bf..fa3cdbe 100644 --- a/PyPI/src/guan.egg-info/PKG-INFO +++ b/PyPI/src/guan.egg-info/PKG-INFO @@ -1,6 +1,6 @@ Metadata-Version: 2.1 Name: guan -Version: 0.0.120 +Version: 0.0.121 Summary: An open source python package Home-page: https://py.guanjihuan.com Author: guanjihuan diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py index 6637f5b..289689f 100644 --- a/PyPI/src/guan/__init__.py +++ b/PyPI/src/guan/__init__.py @@ -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. -# 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 @@ -1592,7 +1592,7 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_funct chern_number = chern_number/(2*math.pi) 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 chern_number = 0 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_array.append(vector_delta) Wilson_loop = 1 - dim = len(num_of_bands) + dim = len(index_of_bands) for i0 in range(len(vector_array)-1): dot_matrix = np.zeros((dim , dim), dtype=complex) i01 = 0 - for dim1 in num_of_bands: + for dim1 in index_of_bands: 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]) i02 += 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 dot_matrix_plus = np.zeros((dim , dim), dtype=complex) i01 = 0 - for dim1 in num_of_bands: + for dim1 in index_of_bands: 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]) i02 += 1 i01 += 1