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0.0.106

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guanjihuan 2022-07-12 21:32:10 +08:00
parent f5f3f2d2f5
commit 35f2d18463
3 changed files with 8 additions and 4 deletions
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2
API_Reference.py
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@ -145,7 +145,7 @@ vector = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector,
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, vector2 = guan.rotation_of_degenerate_vectors(vector1, vector2, index1=None, index2=None, 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)

2
PyPI/setup.cfg
View File

@ -1,7 +1,7 @@
[metadata]
# replace with your username:
name = guan
version = 0.0.105
version = 0.0.106
author = guanjihuan
author_email = guanjihuan@163.com
description = An open source python package

8
PyPI/src/guan/__init__.py
View File

@ -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-0.0.105, updated on July 12, 2022.
# The current version is guan-0.0.106, updated on July 12, 2022.
# Installation: pip install --upgrade guan
@ -751,9 +751,13 @@ def find_vector_array_with_fixed_gauge_by_making_one_component_real(vector_array
vector_array[i0] = guan.find_vector_with_fixed_gauge_by_making_one_component_real(vector_array[i0], precision=precision, index=index)
return vector_array
def rotation_of_degenerate_vectors(vector1, vector2, index1, index2, precision=0.01, criterion=0.01, show_theta=0):
def rotation_of_degenerate_vectors(vector1, vector2, index1=None, index2=None, precision=0.01, criterion=0.01, show_theta=0):
vector1 = np.array(vector1)
vector2 = np.array(vector2)
if index1 == None:
index1 = np.argmax(np.abs(vector1))
if index2 == None:
index2 = np.argmax(np.abs(vector2))
if np.abs(vector1[index2])>criterion or np.abs(vector2[index1])>criterion:
for theta in np.arange(0, 2*math.pi, precision):
if show_theta==1: