diff --git a/PyPI/dist/guan-0.0.118-py3-none-any.whl b/PyPI/dist/guan-0.0.118-py3-none-any.whl
new file mode 100644
index 0000000..0d32f0a
Binary files /dev/null and b/PyPI/dist/guan-0.0.118-py3-none-any.whl differ
diff --git a/PyPI/dist/guan-0.0.118.tar.gz b/PyPI/dist/guan-0.0.118.tar.gz
new file mode 100644
index 0000000..f314b8e
Binary files /dev/null and b/PyPI/dist/guan-0.0.118.tar.gz differ
diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg
index 191843a..c236179 100644
--- a/PyPI/setup.cfg
+++ b/PyPI/setup.cfg
@@ -1,7 +1,7 @@
 [metadata]
 # replace with your username:
 name = guan
-version = 0.0.117
+version = 0.0.118
 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
new file mode 100644
index 0000000..af34f6c
--- /dev/null
+++ b/PyPI/src/guan.egg-info/PKG-INFO
@@ -0,0 +1,16 @@
+Metadata-Version: 2.1
+Name: guan
+Version: 0.0.118
+Summary: An open source python package
+Home-page: https://py.guanjihuan.com
+Author: guanjihuan
+Author-email: guanjihuan@163.com
+Project-URL: Bug Tracker, https://py.guanjihuan.com
+Classifier: Programming Language :: Python :: 3
+Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
+Classifier: Operating System :: OS Independent
+Requires-Python: >=3.6
+Description-Content-Type: text/markdown
+License-File: LICENSE
+
+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.
diff --git a/PyPI/src/guan.egg-info/SOURCES.txt b/PyPI/src/guan.egg-info/SOURCES.txt
new file mode 100644
index 0000000..d26d474
--- /dev/null
+++ b/PyPI/src/guan.egg-info/SOURCES.txt
@@ -0,0 +1,9 @@
+LICENSE
+README.md
+pyproject.toml
+setup.cfg
+src/guan/__init__.py
+src/guan.egg-info/PKG-INFO
+src/guan.egg-info/SOURCES.txt
+src/guan.egg-info/dependency_links.txt
+src/guan.egg-info/top_level.txt
\ No newline at end of file
diff --git a/PyPI/src/guan.egg-info/dependency_links.txt b/PyPI/src/guan.egg-info/dependency_links.txt
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/PyPI/src/guan.egg-info/dependency_links.txt
@@ -0,0 +1 @@
+
diff --git a/PyPI/src/guan.egg-info/top_level.txt b/PyPI/src/guan.egg-info/top_level.txt
new file mode 100644
index 0000000..ff25243
--- /dev/null
+++ b/PyPI/src/guan.egg-info/top_level.txt
@@ -0,0 +1 @@
+guan
diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py
index e766e6e..b9913a0 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-0.0.117, updated on July 21, 2022.
+# The current version is guan-0.0.118, updated on August 10, 2022.
 
 # Installation: pip install --upgrade guan
 
@@ -1560,26 +1560,26 @@ def calculate_chern_number_for_square_lattice_with_Wilson_loop(hamiltonian_funct
         for ky in np.arange(-math.pi, math.pi, delta):
             vector_array = []
             # line_1
-            for i0 in range(precision_of_Wilson_loop+1):
+            for i0 in range(precision_of_Wilson_loop):
                 H_delta = hamiltonian_function(kx+delta/precision_of_Wilson_loop*i0, ky) 
                 eigenvalue, eigenvector = np.linalg.eig(H_delta)
                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))]
                 vector_array.append(vector_delta)
             # line_2
             for i0 in range(precision_of_Wilson_loop):
-                H_delta = hamiltonian_function(kx+delta, ky+delta/precision_of_Wilson_loop*(i0+1))  
+                H_delta = hamiltonian_function(kx+delta, ky+delta/precision_of_Wilson_loop*i0)  
                 eigenvalue, eigenvector = np.linalg.eig(H_delta)
                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))]
                 vector_array.append(vector_delta)
             # line_3
             for i0 in range(precision_of_Wilson_loop):
-                H_delta = hamiltonian_function(kx+delta-delta/precision_of_Wilson_loop*(i0+1), ky+delta)  
+                H_delta = hamiltonian_function(kx+delta-delta/precision_of_Wilson_loop*i0, ky+delta)  
                 eigenvalue, eigenvector = np.linalg.eig(H_delta)
                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))]
                 vector_array.append(vector_delta)
             # line_4
-            for i0 in range(precision_of_Wilson_loop-1):
-                H_delta = hamiltonian_function(kx, ky+delta-delta/precision_of_Wilson_loop*(i0+1))  
+            for i0 in range(precision_of_Wilson_loop):
+                H_delta = hamiltonian_function(kx, ky+delta-delta/precision_of_Wilson_loop*i0)  
                 eigenvalue, eigenvector = np.linalg.eig(H_delta)
                 vector_delta = eigenvector[:, np.argsort(np.real(eigenvalue))]
                 vector_array.append(vector_delta)