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0.0.155

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guanjihuan
2022-11-24 17:11:20 +08:00
parent 61c91480ab
commit 2f8fdae7db
3 changed files with 11 additions and 11 deletions
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2
PyPI/setup.cfg
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@@ -1,7 +1,7 @@
[metadata] [metadata]
# replace with your username: # replace with your username:
name = guan name = guan
version = 0.0.154 version = 0.0.155
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

2
PyPI/src/guan.egg-info/PKG-INFO
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@@ -1,6 +1,6 @@
Metadata-Version: 2.1 Metadata-Version: 2.1
Name: guan Name: guan
Version: 0.0.154 Version: 0.0.155
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

18
PyPI/src/guan/__init__.py
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@@ -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-0.0.154, updated on November 24, 2022. # The current version is guan-0.0.155, updated on November 24, 2022.
# Installation: pip install --upgrade guan # Installation: pip install --upgrade guan
@@ -1187,10 +1187,10 @@ def calculate_conductance_with_disorder(fermi_energy, h00, h01, disorder_intensi
green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy) green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy)
green_0n_n = copy.deepcopy(green_nn_n) green_0n_n = copy.deepcopy(green_nn_n)
elif ix != length+1: elif ix != length+1:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0) green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
return conductance return conductance
@@ -1206,10 +1206,10 @@ def calculate_conductance_with_slice_disorder(fermi_energy, h00, h01, disorder_i
green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy) green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy)
green_0n_n = copy.deepcopy(green_nn_n) green_0n_n = copy.deepcopy(green_nn_n)
elif ix != length+1: elif ix != length+1:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0) green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
return conductance return conductance
@@ -1226,10 +1226,10 @@ def calculate_conductance_with_disorder_inside_unit_cell_which_keeps_translation
green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy) green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy)
green_0n_n = copy.deepcopy(green_nn_n) green_0n_n = copy.deepcopy(green_nn_n)
elif ix != length+1: elif ix != length+1:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0) green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00+disorder, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
return conductance return conductance
@@ -1246,10 +1246,10 @@ def calculate_conductance_with_random_vacancy(fermi_energy, h00, h01, vacancy_co
green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy) green_nn_n = guan.green_function(fermi_energy, h00, broadening=0, self_energy=left_self_energy)
green_0n_n = copy.deepcopy(green_nn_n) green_0n_n = copy.deepcopy(green_nn_n)
elif ix != length+1: elif ix != length+1:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0) green_nn_n = guan.green_function_nn_n(fermi_energy, h00+random_vacancy, h01, green_nn_n, broadening=0)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
else: else:
green_nn_n = guan.green_function_nn_n(fermi_energy, h00+random_vacancy, h01, green_nn_n, broadening=0, self_energy=right_self_energy) green_nn_n = guan.green_function_nn_n(fermi_energy, h00, h01, green_nn_n, broadening=0, self_energy=right_self_energy)
green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n) green_0n_n = guan.green_function_in_n(green_0n_n, h01, green_nn_n)
conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj())) conductance = np.trace(np.dot(np.dot(np.dot(gamma_left, green_0n_n), gamma_right), green_0n_n.transpose().conj()))
return conductance return conductance