0.1.186

PyPI/setup.cfg

@@ -1,7 +1,7 @@
 [metadata]
 # replace with your username:
 name = guan
-version = 0.1.175
+version = 0.1.186
 author = guanjihuan
 author_email = guanjihuan@163.com
 description = An open source python package

PyPI/src/guan.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.4
 Name: guan
-Version: 0.1.175
+Version: 0.1.186
 Summary: An open source python package
 Home-page: https://py.guanjihuan.com
 Author: guanjihuan

PyPI/src/guan.egg-info/SOURCES.txt

@@ -8,14 +8,11 @@ src/guan/Hamiltonian_of_examples.py
 src/guan/__init__.py
 src/guan/band_structures_and_wave_functions.py
 src/guan/basic_functions.py
-src/guan/custom_classes.py
 src/guan/data_processing.py
 src/guan/decorators.py
 src/guan/density_of_states.py
-src/guan/deprecated.py
 src/guan/figure_plotting.py
 src/guan/file_reading_and_writing.py
-src/guan/functions_using_objects_of_custom_classes.py
 src/guan/machine_learning.py
 src/guan/others.py
 src/guan/quantum_transport.py

PyPI/src/guan/__init__.py

@@ -14,7 +14,4 @@ from .figure_plotting import *
 from .data_processing import *
 from .decorators import *
 from .others import *
-from .custom_classes import *
-from .functions_using_objects_of_custom_classes import *
-from .deprecated import *
 statistics_of_guan_package()

PyPI/src/guan/band_structures_and_wave_functions.py

@@ -1,12 +1,15 @@
 # Module: band_structures_and_wave_functions
 
 # 计算哈密顿量的本征值
-def calculate_eigenvalue(hamiltonian):
+def calculate_eigenvalue(hamiltonian, hermitian=True):
     import numpy as np
     if np.array(hamiltonian).shape==():
         eigenvalue = np.real(hamiltonian)
     else:
-        eigenvalue, eigenvector = np.linalg.eigh(hamiltonian)
+        if hermitian:
+            eigenvalue, eigenvector = np.linalg.eigh(hamiltonian)
+        else:
+            eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
     return eigenvalue
 
 # 输入哈密顿量函数（带一组参数），计算一组参数下的本征值，返回本征值向量组
@@ -65,10 +68,13 @@ def calculate_eigenvalue_with_two_parameters(x_array, y_array, hamiltonian_funct
             i0 += 1
     return eigenvalue_array
 
-# 计算哈密顿量的本征矢（厄密矩阵）
+# 计算哈密顿量的本征矢
-def calculate_eigenvector(hamiltonian):
+def calculate_eigenvector(hamiltonian, hermitian=True):
     import numpy as np
-    eigenvalue, eigenvector = np.linalg.eigh(hamiltonian)
+    if hermitian:
+        eigenvalue, eigenvector = np.linalg.eigh(hamiltonian)
+    else:
+        eigenvalue, eigenvector = np.linalg.eig(hamiltonian)
     return eigenvector
 
 # 施密特正交化

PyPI/src/guan/custom_classes.py

@@ -1,11 +0,0 @@
-# Module: custom_classes
-
-# 原子类
-class Atom:
-    def __init__(self, name='atom', index=0, x=0, y=0, z=0, energy=0):
-        self.name = name
-        self.index = index
-        self.x = x
-        self.y = y
-        self.z = z
-        self.energy = energy

PyPI/src/guan/data_processing.py

@@ -9,9 +9,9 @@ def logging_with_day_and_time(content='', filename='time_logging', file_format='
        if content == '':
            f2.write(datetime_today+' '+datetime_time+'\n')
        else:
-           f2.write(datetime_today+' '+datetime_time+' '+content+'\n')
+           f2.write(datetime_today+' '+datetime_time+' '+str(content)+'\n')
 
-# 使用该函数获取函数计算时间（秒）
+# 使用该函数运行某个函数并获取函数计算时间（秒）
 def timer(function_name, *args, **kwargs):
     import time
     start = time.time()
@@ -20,13 +20,66 @@ def timer(function_name, *args, **kwargs):
     print(f"Running time of {function_name.__name__}: {end - start} seconds")
     return result
 
-# 使用该函数实现 try except 结构
+# 使用该函数运行某个函数并实现 try-except-pass 结构
 def try_except(function_name, *args, **kwargs):
     try:
         return function_name(*args, **kwargs)
     except:
         pass
 
+# 使用 multiprocessing.Pool 实现自动分配任务并行
+def parallel_calculation_with_multiprocessing_Pool(func, args_list=[1, 2, 3], show_time=0):
+    import multiprocessing
+    import time
+    start_time = time.time()
+    with multiprocessing.Pool() as pool:
+        result_array = pool.map(func, args_list)
+    end_time = time.time()
+    if show_time:
+        print(end_time - start_time)
+    return result_array
+
+# 循环一个参数计算某个函数，并返回计算结果的数组
+def loop_calculation_with_one_parameter(function_name, parameter_array):
+    import numpy as np
+    result_array = []
+    for parameter in parameter_array:
+        result = function_name(parameter)
+        result_array.append(result)
+    result_array = np.array(result_array)
+    return result_array
+
+# 循环两个参数计算某个函数，并返回计算结果的数组
+def loop_calculation_with_two_parameters(function_name, parameter_array_1, parameter_array_2):
+    import numpy as np
+    result_array = np.zeros((len(parameter_array_2), len(parameter_array_1)))
+    i1 = 0
+    for parameter_1 in parameter_array_1:
+        i2 = 0
+        for parameter_2 in parameter_array_2:
+            result = function_name(parameter_1, parameter_2)
+            result_array[i2, i1] = result
+            i2 += 1
+        i1 += 1
+    return result_array
+
+# 循环三个参数计算某个函数，并返回计算结果的数组
+def loop_calculation_with_three_parameters(function_name, parameter_array_1, parameter_array_2, parameter_array_3):
+    import numpy as np
+    result_array = np.zeros((len(parameter_array_3), len(parameter_array_2), len(parameter_array_1)))
+    i1 = 0
+    for parameter_1 in parameter_array_1:
+        i2 = 0
+        for parameter_2 in parameter_array_2:
+            i3 = 0
+            for parameter_3 in parameter_array_3:
+                result = function_name(parameter_1, parameter_2, parameter_3)
+                result_array[i3, i2, i1] = result
+                i3 += 1
+            i2 += 1
+        i1 += 1
+    return result_array
+
 # 打印数组
 def print_array(array, line_break=0):
     if line_break == 0:
@@ -101,6 +154,20 @@ def generate_random_int_number_for_a_specific_seed(seed=0, x_min=0, x_max=10):
     rand_num = np.random.randint(x_min, x_max) # 左闭右开[x_min, x_max)
     return rand_num
 
+# ​使用Numpy库计算​总体标准差
+def standard_deviation(data_array):
+    import numpy as np
+    std_result = np.std(data_array)
+    return std_result
+
+# ​​使用公式计算总体标准差
+def standard_deviation_with_formula(data_array):
+    import numpy as np
+    averaged_data = sum(data_array)/len(data_array)
+    averaged_squared_data = sum(np.array(data_array)**2)/len(data_array)
+    std_result = np.sqrt(averaged_squared_data-averaged_data**2)
+    return std_result
+
 # 获取两个模式之间的字符串
 def get_string_between_two_patterns(original_string, start, end, include_start_and_end=0):
     import re

PyPI/src/guan/deprecated.py

@@ -1,45 +0,0 @@
-# Module: deprecated
-
-def make_sh_file(sh_filename='a', command_line='python a.py', cpu_num=1, task_name='task', cd_dir=0):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.make_sh_file_for_qsub().')
-    guan.make_sh_file_for_qsub(sh_filename=sh_filename, command_line=command_line, cpu_num=cpu_num, task_name=task_name, cd_dir=cd_dir)
-
-def plot_without_starting_fig(plt, fig, ax, x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, style='', y_min=None, y_max=None, linewidth=None, markersize=None, color=None, fontfamily='Times New Roman'):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.plot_without_starting_fig_ax().')
-    guan.plot_without_starting_fig_ax(plt, fig, ax, x_array, y_array, xlabel=xlabel, ylabel=ylabel, title=title, fontsize=fontsize, style=style, y_min=y_min, y_max=y_max, linewidth=linewidth, markersize=markersize, color=color, fontfamily=fontfamily)
-
-def draw_dots_and_lines_without_starting_fig(plt, fig, ax, coordinate_array, draw_dots=1, draw_lines=1, max_distance=1, line_style='-k', linewidth=1, dot_style='ro', markersize=3):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.draw_dots_and_lines_without_starting_fig_ax().')
-    guan.draw_dots_and_lines_without_starting_fig_ax(plt, fig, ax, coordinate_array, draw_dots=draw_dots, draw_lines=draw_lines, max_distance=max_distance, line_style=line_style, linewidth=linewidth, dot_style=dot_style, markersize=markersize)
-
-def get_days_of_the_current_month(str_or_datetime='str'):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_current_month().')
-    date_array = guan.get_date_array_of_the_current_month(str_or_datetime=str_or_datetime)
-    return date_array
-
-def get_days_of_the_last_month(str_or_datetime='str'):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_last_month().')
-    date_array = guan.get_date_array_of_the_last_month(str_or_datetime=str_or_datetime)
-    return date_array
-
-def get_days_of_the_month_before_last(str_or_datetime='str'):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_month_before_last().')
-    date_array = guan.get_date_array_of_the_month_before_last(str_or_datetime=str_or_datetime)
-    return date_array
-
-def pdf_to_text(pdf_path):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.pdf_to_text_with_pdfminer3k().')
-    content = guan.pdf_to_text_with_pdfminer3k(pdf_path)
-    return content
-
-def statistics_with_day_and_time(content='', filename='time_logging', file_format='.txt'):
-    import guan
-    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.logging_with_day_and_time().')
-    guan.logging_with_day_and_time(content=content, filename=filename, file_format=file_format)

PyPI/src/guan/file_reading_and_writing.py

@@ -1,7 +1,7 @@
 # Module: file_reading_and_writing
 
 # 使用pickle将变量保存到文件（支持几乎所有对象类型）
-def dump_data(data, filename, file_format='.pkl'):
+def dump_data(data, filename='a', file_format='.pkl'):
     import pickle
     with open(filename+file_format, 'wb') as f:
         pickle.dump(data, f)
@@ -14,7 +14,7 @@ def load_data(filename, file_format='.pkl'):
     return data
 
 # 使用NumPy保存数组变量到npy文件（二进制文件）
-def save_npy_data(data, filename):
+def save_npy_data(data, filename='a'):
     import numpy as np
     np.save(filename+'.npy', data)
 
@@ -25,7 +25,7 @@ def load_npy_data(filename):
     return data
 
 # 使用NumPy保存数组变量到TXT文件（文本文件）
-def save_txt_data(data, filename):
+def save_txt_data(data, filename='a'):
     import numpy as np
     np.savetxt(filename+'.txt', data)
 
@@ -421,13 +421,15 @@ def write_matrix_in_markdown_format(matrix, filename='a'):
     dim_0 = matrix.shape[0]
     dim_1 = matrix.shape[1]
     with open(filename+'.md', 'w', encoding='UTF-8') as f:
+        f.write(f'| Row\Column ')
         for i1 in range(dim_1):
             f.write(f'| column {i1+1} ')
         f.write('|\n')
-        for i1 in range(dim_1):
+        for i1 in range(dim_1+1):
             f.write('| :---: ')
         f.write('|\n')
         for i0 in range(dim_0):
+            f.write(f'| row {i0+1} ')
             for i1 in range(dim_1):
                 f.write(f'| {matrix[i0, i1]} ')
             f.write('|\n')

PyPI/src/guan/functions_using_objects_of_custom_classes.py

@@ -1,79 +0,0 @@
-# Module: functions_using_objects_of_custom_classes
-
-# 将原子对象列表转成多个独立列表
-def convert_atom_object_list_to_multiple_lists(atom_object_list):
-    name_list = []
-    index_list = []
-    x_list = []
-    y_list = []
-    z_list = []
-    energy_list = []
-    for atom_object in atom_object_list:
-        name_list.append(atom_object.name)
-        index_list.append(atom_object.index)
-        x_list.append(atom_object.x)
-        y_list.append(atom_object.y)
-        z_list.append(atom_object.z)
-        energy_list.append(atom_object.energy)
-    return name_list, index_list, x_list, y_list, z_list, energy_list
-
-# 将原子对象列表转成原子字典列表
-def convert_atom_object_list_to_atom_dict_list(atom_object_list):
-    atom_dict_list = []
-    for atom_object in atom_object_list:
-        atom_dict = {
-            'name': atom_object.name,
-            'index': atom_object.index, 
-            'x': atom_object.x,
-            'y': atom_object.y,
-            'z': atom_object.z,
-            'energy': atom_object.energy,
-        }
-        atom_dict_list.append(atom_dict)
-    return atom_dict_list
-
-# 从原子对象列表中获取 (x, y) 坐标数组
-def get_coordinate_array_from_atom_object_list(atom_object_list):
-    coordinate_array = []
-    for atom in atom_object_list:
-        x = atom.x
-        y = atom.y
-        coordinate_array.append([x, y])
-    return coordinate_array
-
-# 从原子对象列表中获取 x 和 y 的最大值和最小值
-def get_max_min_x_y_from_atom_object_list(atom_object_list):
-    import guan
-    coordinate_array = guan.get_coordinate_array_from_atom_object_list(atom_object_list)
-    x_array = []
-    for coordinate in coordinate_array:
-        x_array.append(coordinate[0])
-    y_array = []
-    for coordinate in coordinate_array:
-        y_array.append(coordinate[1])
-    max_x = max(x_array)
-    min_x = min(x_array)
-    max_y = max(y_array)
-    min_y = min(y_array)
-    return max_x, min_x, max_y, min_y
-
-# 从原子对象列表中获取满足坐标条件的索引
-def get_index_via_coordinate_from_atom_object_list(atom_object_list, x=0, y=0, z=0, eta=1e-3):
-    for atom in atom_object_list:
-        x_i = atom.x
-        y_i = atom.y
-        z_i = atom.z
-        index = atom.index
-        if abs(x-x_i)<eta and abs(y-y_i)<eta and abs(z-z_i)<eta:
-            return index
-
-# 根据原子对象列表来初始化哈密顿量
-def initialize_hamiltonian_from_atom_object_list(atom_object_list):
-    import numpy as np
-    import guan
-    dim = guan.dimension_of_array(atom_object_list[0].energy)
-    num = len(atom_object_list)
-    hamiltonian = np.zeros((dim*num, dim*num))
-    for i0 in range(num):
-        hamiltonian[i0*dim+0:i0*dim+dim, i0*dim+0:i0*dim+dim] = atom_object_list[i0].energy
-    return hamiltonian

PyPI/src/guan/others.py

@@ -59,33 +59,6 @@ def auto_chat_with_guide(prompt='你好', guide_message='（回答字数少于30
         print('机器人 2: ')
         response0 = guan.chat(prompt=response1+guide_message, model=model, stream=stream)
 
-# 在云端服务器上运行函数（需要函数是独立可运行的代码）
-def run(function_name, *args, **kwargs):
-    import requests
-    import guan
-    url = "http://run.guanjihuan.com/run_function"
-    function_source = guan.get_source(function_name)
-    data = {
-        "function_name": function_name.__name__,
-        "function_source": function_source,
-        'args': str(args),
-        'kwargs': str(kwargs),
-    }
-    return_data = None
-    try:
-        response = requests.post(url, json=data)
-        if response.status_code == 200:
-            result = response.json()
-            print_data = result['print_data']
-            print(print_data, end='')
-            encoded_return_data = result['encoded_return_data']
-            import base64
-            import pickle
-            return_data = pickle.loads(base64.b64decode(encoded_return_data))
-    except:
-        pass
-    return return_data
-
 # CPU性能测试（十亿次循环的浮点加法运算的时间，约30秒左右）
 def cpu_test_with_addition(print_show=1):
     import time
@@ -328,26 +301,86 @@ def get_memory_info():
     used_memory_percent = memory_info.percent
     return total_memory, used_memory, available_memory, used_memory_percent
 
-# 获取CPU的平均使用率
+# 获取CPU使用率（基于性能计数器，适用于Windows系统）
+def get_cpu_usage_for_windows(interval=1.0):
+    import time
+    import ctypes
+    from ctypes import wintypes
+    class FILETIME(ctypes.Structure):
+        _fields_ = [
+            ('dwLowDateTime', wintypes.DWORD),
+            ('dwHighDateTime', wintypes.DWORD)
+        ]
+    kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)
+    # 第一次采样
+    idle1 = FILETIME()
+    kernel1 = FILETIME()
+    user1 = FILETIME()
+    kernel32.GetSystemTimes(ctypes.byref(idle1), ctypes.byref(kernel1), ctypes.byref(user1))
+    time.sleep(interval)
+    # 第二次采样
+    idle2 = FILETIME()
+    kernel2 = FILETIME()
+    user2 = FILETIME()
+    kernel32.GetSystemTimes(ctypes.byref(idle2), ctypes.byref(kernel2), ctypes.byref(user2))
+    # 计算时间差
+    def filetime_to_int(ft):
+        return (ft.dwHighDateTime << 32) + ft.dwLowDateTime
+    idle = filetime_to_int(idle2) - filetime_to_int(idle1)
+    kernel = filetime_to_int(kernel2) - filetime_to_int(kernel1)
+    user = filetime_to_int(user2) - filetime_to_int(user1)
+    total = kernel + user
+    if total == 0:
+        return 0.0
+    return 100.0 * (total - idle) / total
+
+# 获取CPU使用率（基于/proc/stat，适用于Linux系统）
+def get_cpu_usage_for_linux(interval=1.0):
+    import time
+    def read_cpu_stats():
+        with open('/proc/stat') as f:
+            for line in f:
+                if line.startswith('cpu '):
+                    parts = line.split()
+                    return list(map(int, parts[1:]))
+        return None
+    stats1 = read_cpu_stats()
+    if not stats1:
+        return 0.0
+    time.sleep(interval)
+    stats2 = read_cpu_stats()
+    if not stats2:
+        return 0.0
+    idle1 = stats1[3] + stats1[4]
+    total1 = sum(stats1)
+    idle2 = stats2[3] + stats2[4]
+    total2 = sum(stats2)
+    total_delta = total2 - total1
+    idle_delta = idle2 - idle1
+    if total_delta == 0:
+        return 0.0
+    return 100.0 * (total_delta - idle_delta) / total_delta
+
+# 使用psutil获取CPU的平均使用率
 def get_cpu_usage(interval=1):
     import psutil
     cpu_usage = psutil.cpu_percent(interval=interval)
     return cpu_usage
 
-# 获取每个CPU核心的使用率，返回列表
+# 使用psutil获取每个CPU核心的使用率，返回列表
 def get_cpu_usage_array_per_core(interval=1):
     import psutil
     cpu_usage_array_per_core = psutil.cpu_percent(interval=interval, percpu=True)
     return cpu_usage_array_per_core
 
-# 获取使用率最高的CPU核心的使用率
+# 使用psutil获取使用率最高的CPU核心的使用率
 def get_cpu_max_usage_for_all_cores(interval=1):
     import guan
     cpu_usage_array_per_core = guan.get_cpu_usage_array_per_core(interval=interval)
     max_cpu_usage = max(cpu_usage_array_per_core)
     return max_cpu_usage
 
-# 获取非零使用率的CPU核心的平均使用率
+# 使用psutil获取非零使用率的CPU核心的平均使用率
 def get_cpu_averaged_usage_for_non_zero_cores(interval=1):
     import guan
     cpu_usage_array_per_core = guan.get_cpu_usage_array_per_core(interval=interval)
@@ -355,7 +388,7 @@ def get_cpu_averaged_usage_for_non_zero_cores(interval=1):
     averaged_cpu_usage = sum(cpu_usage_array_per_core_new)/len(cpu_usage_array_per_core_new)
     return averaged_cpu_usage
 
-# 在一定数量周期内得到CPU的使用率信息。默认为1秒钟收集一次，(interval+sleep_interval)*times 为收集的时间范围，范围默认为60秒，即1分钟后返回列表，总共得到60组数据。其中，数字第一列和第二列分别是平均值和最大值。
+# 使用psutil在一定数量周期内得到CPU的使用率信息。默认为1秒钟收集一次，(interval+sleep_interval)*times 为收集的时间范围，范围默认为60秒，即1分钟后返回列表，总共得到60组数据。其中，数字第一列和第二列分别是平均值和最大值。
 def get_cpu_information_for_times(interval=1, sleep_interval=0, times=60):
     import guan
     import time
@@ -375,7 +408,7 @@ def get_cpu_information_for_times(interval=1, sleep_interval=0, times=60):
         time.sleep(sleep_interval)
     return cpu_information_array
 
-# 将得到的CPU的使用率信息写入文件。默认为1分钟收集一次，(interval+sleep_interval)*times 为收集的时间范围，范围默认为60分钟，即1小时写入文件一次，总共得到60组数据。其中，数字第一列和第二列分别是平均值和最大值。
+# 使用psutil获取CPU的使用率，将得到的CPU的使用率信息写入文件。默认为1分钟收集一次，(interval+sleep_interval)*times 为收集的时间范围，范围默认为60分钟，即1小时写入文件一次，总共得到60组数据。其中，数字第一列和第二列分别是平均值和最大值。
 def write_cpu_information_to_file(filename='./cpu_usage', interval=1, sleep_interval=59, times=60):
     import guan
     guan.make_file(filename+'.txt')
@@ -393,7 +426,7 @@ def write_cpu_information_to_file(filename='./cpu_usage', interval=1, sleep_inte
             f.write('\n')
         f.close()
 
-# 画CPU的使用率图。默认为画最近的60个数据，以及不画CPU核心的最大使用率。
+# 使用psutil获取CPU的使用率，画CPU的使用率图。默认为画最近的60个数据，以及不画CPU核心的最大使用率。
 def plot_cpu_information(filename='./cpu_usage', recent_num=60, max_cpu=0):
     import guan
     from datetime import datetime
@@ -426,7 +459,7 @@ def plot_cpu_information(filename='./cpu_usage', recent_num=60, max_cpu=0):
     plt.legend(legend_array)
     plt.show()
 
-# 画详细的CPU的使用率图，分CPU核心画图。
+# 使用psutil获取CPU的使用率，画详细的CPU的使用率图，分CPU核心画图。
 def plot_detailed_cpu_information(filename='./cpu_usage', recent_num=60):
     import guan
     from datetime import datetime
@@ -1006,7 +1039,8 @@ def stock_symbols_classification():
     for stock_symbol in stock_symbols:
         find_300 = re.findall(r'^300', stock_symbol)
         find_301 = re.findall(r'^301', stock_symbol)
-        if find_300 != [] or find_301 != []:
+        find_302 = re.findall(r'^302', stock_symbol)
+        if find_300 != [] or find_301 != [] or find_302 != []:
             stock_symbols_30.append(stock_symbol)
     # 科创板
     stock_symbols_68 = []
@@ -1015,24 +1049,23 @@ def stock_symbols_classification():
         find_689 = re.findall(r'^689', stock_symbol)
         if find_688 != [] or find_689 != []:
             stock_symbols_68.append(stock_symbol)
-    # 新三板
+    # 北交所和新三板
-    stock_symbols_8_4 = []
+    stock_symbols_8_4_9 = []
     for stock_symbol in stock_symbols:
-        find_82 = re.findall(r'^82', stock_symbol)
         find_83 = re.findall(r'^83', stock_symbol)
         find_87 = re.findall(r'^87', stock_symbol)
-        find_88 = re.findall(r'^88', stock_symbol)
         find_430 = re.findall(r'^430', stock_symbol)
         find_420 = re.findall(r'^420', stock_symbol)
         find_400 = re.findall(r'^400', stock_symbol)
-        if find_82 != [] or find_83 != [] or find_87 != [] or find_88 != [] or find_430 != [] or find_420 != [] or find_400 != []:
+        find_920 = re.findall(r'^920', stock_symbol)
-            stock_symbols_8_4.append(stock_symbol)
+        if find_83 != [] or find_87 != [] or find_430 != [] or find_420 != [] or find_400 != [] or find_920 != []:
+            stock_symbols_8_4_9.append(stock_symbol)
     # 检查遗漏的股票代码
     stock_symbols_others = []
     for stock_symbol in stock_symbols:
-        if stock_symbol not in stock_symbols_60 and stock_symbol not in stock_symbols_00 and stock_symbol not in stock_symbols_30 and stock_symbol not in stock_symbols_68 and stock_symbol not in stock_symbols_8_4:
+        if stock_symbol not in stock_symbols_60 and stock_symbol not in stock_symbols_00 and stock_symbol not in stock_symbols_30 and stock_symbol not in stock_symbols_68 and stock_symbol not in stock_symbols_8_4_9:
-            stock_symbols_others.others.append(stock_symbol) 
+            stock_symbols_others.append(stock_symbol) 
-    return stock_symbols_60, stock_symbols_00, stock_symbols_30, stock_symbols_68, stock_symbols_8_4, stock_symbols_others
+    return stock_symbols_60, stock_symbols_00, stock_symbols_30, stock_symbols_68, stock_symbols_8_4_9, stock_symbols_others
 
 # 股票代码各个分类的数量
 def statistics_of_stock_symbols_classification():
@@ -1174,7 +1207,7 @@ def statistics_of_guan_package(function_name=None):
     except:
         pass
 
-# Guan软件包升级检查和提示（如果无法连接或者版本为最新，那么均没有提示）
+# Guan软件包升级检查和提示（对于无法连接或者版本为最新的情况，检查结果都没有提示）
 def notification_of_upgrade(timeout=5):
     try:
         import guan
@@ -1185,3 +1218,139 @@ def notification_of_upgrade(timeout=5):
                 print('升级提示：您当前使用的版本是 guan-'+current_version+'，目前已经有最新版本 guan-'+latest_version+'。您可以通过以下命令对软件包进行升级：pip install --upgrade guan -i https://pypi.python.org/simple 或 pip install --upgrade guan')
     except:
         pass
+
+# --- 自定义类和使用自定义类的函数 custom classes and functions using objects of custom classes ---
+
+# 原子类
+class Atom:
+    def __init__(self, name='atom', index=0, x=0, y=0, z=0, energy=0):
+        self.name = name
+        self.index = index
+        self.x = x
+        self.y = y
+        self.z = z
+        self.energy = energy
+
+# 将原子对象列表转成多个独立列表
+def convert_atom_object_list_to_multiple_lists(atom_object_list):
+    name_list = []
+    index_list = []
+    x_list = []
+    y_list = []
+    z_list = []
+    energy_list = []
+    for atom_object in atom_object_list:
+        name_list.append(atom_object.name)
+        index_list.append(atom_object.index)
+        x_list.append(atom_object.x)
+        y_list.append(atom_object.y)
+        z_list.append(atom_object.z)
+        energy_list.append(atom_object.energy)
+    return name_list, index_list, x_list, y_list, z_list, energy_list
+
+# 将原子对象列表转成原子字典列表
+def convert_atom_object_list_to_atom_dict_list(atom_object_list):
+    atom_dict_list = []
+    for atom_object in atom_object_list:
+        atom_dict = {
+            'name': atom_object.name,
+            'index': atom_object.index, 
+            'x': atom_object.x,
+            'y': atom_object.y,
+            'z': atom_object.z,
+            'energy': atom_object.energy,
+        }
+        atom_dict_list.append(atom_dict)
+    return atom_dict_list
+
+# 从原子对象列表中获取 (x, y) 坐标数组
+def get_coordinate_array_from_atom_object_list(atom_object_list):
+    coordinate_array = []
+    for atom in atom_object_list:
+        x = atom.x
+        y = atom.y
+        coordinate_array.append([x, y])
+    return coordinate_array
+
+# 从原子对象列表中获取 x 和 y 的最大值和最小值
+def get_max_min_x_y_from_atom_object_list(atom_object_list):
+    import guan
+    coordinate_array = guan.get_coordinate_array_from_atom_object_list(atom_object_list)
+    x_array = []
+    for coordinate in coordinate_array:
+        x_array.append(coordinate[0])
+    y_array = []
+    for coordinate in coordinate_array:
+        y_array.append(coordinate[1])
+    max_x = max(x_array)
+    min_x = min(x_array)
+    max_y = max(y_array)
+    min_y = min(y_array)
+    return max_x, min_x, max_y, min_y
+
+# 从原子对象列表中获取满足坐标条件的索引
+def get_index_via_coordinate_from_atom_object_list(atom_object_list, x=0, y=0, z=0, eta=1e-3):
+    for atom in atom_object_list:
+        x_i = atom.x
+        y_i = atom.y
+        z_i = atom.z
+        index = atom.index
+        if abs(x-x_i)<eta and abs(y-y_i)<eta and abs(z-z_i)<eta:
+            return index
+
+# 根据原子对象列表来初始化哈密顿量
+def initialize_hamiltonian_from_atom_object_list(atom_object_list):
+    import numpy as np
+    import guan
+    dim = guan.dimension_of_array(atom_object_list[0].energy)
+    num = len(atom_object_list)
+    hamiltonian = np.zeros((dim*num, dim*num))
+    for i0 in range(num):
+        hamiltonian[i0*dim+0:i0*dim+dim, i0*dim+0:i0*dim+dim] = atom_object_list[i0].energy
+    return hamiltonian
+
+# --- 废弃函数/版本兼容（不推荐使用，并可能在未来的版本中被移除）deprecated ---
+
+def make_sh_file(sh_filename='a', command_line='python a.py', cpu_num=1, task_name='task', cd_dir=0):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.make_sh_file_for_qsub().')
+    guan.make_sh_file_for_qsub(sh_filename=sh_filename, command_line=command_line, cpu_num=cpu_num, task_name=task_name, cd_dir=cd_dir)
+
+def plot_without_starting_fig(plt, fig, ax, x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, style='', y_min=None, y_max=None, linewidth=None, markersize=None, color=None, fontfamily='Times New Roman'):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.plot_without_starting_fig_ax().')
+    guan.plot_without_starting_fig_ax(plt, fig, ax, x_array, y_array, xlabel=xlabel, ylabel=ylabel, title=title, fontsize=fontsize, style=style, y_min=y_min, y_max=y_max, linewidth=linewidth, markersize=markersize, color=color, fontfamily=fontfamily)
+
+def draw_dots_and_lines_without_starting_fig(plt, fig, ax, coordinate_array, draw_dots=1, draw_lines=1, max_distance=1, line_style='-k', linewidth=1, dot_style='ro', markersize=3):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.draw_dots_and_lines_without_starting_fig_ax().')
+    guan.draw_dots_and_lines_without_starting_fig_ax(plt, fig, ax, coordinate_array, draw_dots=draw_dots, draw_lines=draw_lines, max_distance=max_distance, line_style=line_style, linewidth=linewidth, dot_style=dot_style, markersize=markersize)
+
+def get_days_of_the_current_month(str_or_datetime='str'):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_current_month().')
+    date_array = guan.get_date_array_of_the_current_month(str_or_datetime=str_or_datetime)
+    return date_array
+
+def get_days_of_the_last_month(str_or_datetime='str'):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_last_month().')
+    date_array = guan.get_date_array_of_the_last_month(str_or_datetime=str_or_datetime)
+    return date_array
+
+def get_days_of_the_month_before_last(str_or_datetime='str'):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.get_date_array_of_the_month_before_last().')
+    date_array = guan.get_date_array_of_the_month_before_last(str_or_datetime=str_or_datetime)
+    return date_array
+
+def pdf_to_text(pdf_path):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.pdf_to_text_with_pdfminer3k().')
+    content = guan.pdf_to_text_with_pdfminer3k(pdf_path)
+    return content
+
+def statistics_with_day_and_time(content='', filename='time_logging', file_format='.txt'):
+    import guan
+    print('Warning: The current function name has been deprecated, which will be deleted in the future version. Please change it into guan.logging_with_day_and_time().')
+    guan.logging_with_day_and_time(content=content, filename=filename, file_format=file_format)

README.md

@@ -28,8 +28,6 @@ import guan
 + data processing
 + decorators
 + others
-+ custom classes
-+ functions using objects of custom classes
 
 ## About this package