更新代码

X1.py

@@ -23,6 +23,7 @@ def compute_curveData(num, step, coefficient):	# coefficient代表二次函数
     y_values = quadratic_function(x_values)		  # 调用quadratic_function(x)函数得到y值
     curve_data = np.column_stack((x_values, y_values))  # 将两个一维数组堆叠成二维数组，形成(x,y)的形式
     return curve_data
+
 if __name__ == '__main__':
     coefficient = [1, 2, 3]
     ans = compute_curveData(1000, 250, coefficient)

X5.py

@@ -3,7 +3,7 @@
 # Author : lirunsheng
 # User : l'r's
 # Software: PyCharm
-# File : X4.py
+# File : X5.py
 
 # -*- encoding: utf-8 -*-
 """
@@ -12,88 +12,192 @@
  @DateTime: 2023/5/30 15:29
  @SoftWare: PyCharm
 """
+import random
+import re
+from tkinter import messagebox
+
+import pandas as pd
+from sympy import sympify, SympifyError
 import sys
 from fitting import *
 import numpy as np
 import data as gl_data
 import input
 import tkinter as tk
+from tkinter import ttk
 from tkinter import *
+from screeninfo import get_monitors
+import os
+from PIL import ImageTk, Image
 import tkinter.filedialog  # 注意次数要将文件对话框导入
 # from demo1 import Addfunc
+from newly_added.formula import *
+from scipy.optimize import leastsq
 
 global Q_root,F_root
 global root_window
 global label1,label2,label3
 
-class Addfunc():
-    def __init__(self):
-        self.r = 7.5 # 设置按钮大小
-        self.rr = 2.5# 设置按钮大小
-        self.window = tk.Tk() # 新建函数增加窗口
-        self.window.title("新增函数曲线")#设置窗口标题
-        self.window.geometry('400x300')#设置窗口大小
-        self.show()#显示按钮
-        self.window.mainloop()#运行UI界面
-
-    def show(self):
-        for widget in self.window.winfo_children():
-            widget.destroy()#清空已有组件
-        self.add_cv = tk.Canvas(self.window, width=400, height=300)  # 新建画布
-        self.add_cv.place(x=0, y=0)  # 放置画布
-        cur = 0#记录已有按钮个数
-        for f in function.Fun:#遍历已有函数
-            self.add_cv.create_oval(20 - self.r, 20 + 15 + cur * 30 - self.r, 20 + self.r, 20 + 15 + cur * 30 + self.r
-                               , fill="white", width=1, outline="black")# 绘制圆圈
-            if f.show == 1:#若为当前选中函数，则标记
-                self.add_cv.create_oval(20 - self.rr, 20 + 15 + cur * 30 - self.rr, 20 + self.rr, 20 + 15 + cur * 30 + self.rr
-                                   , fill="black", width=1, outline="black")
-            button = tk.Button(self.window, text=f.name + f.demo, bd=0, font=("微软雅黑", 12)
-                               , command=lambda x=f.no: self.change(x), anchor=W)#设置选择按钮
-            button.place(x=40, y=20 + cur * 30, width=300, height=30)#放置选择按钮
-            cur += 1#计数加一
 
-    def change(self, no):#切换函数显示情况
-        function.Show[no] = not function.Show[no]
-        function.Fun[no].show = not function.Fun[no].show
-        self.show()#更新函数选择面板
-        f_button()#更新函数显示界面
-# class AddFunc(Addfunc):
-#     def change(self, no):
-#         # super().change(no)
-#         function.Show[no] = not function.Show[no]
-#         function.Fun[no].show = not function.Fun[no].show
-#         self.show()  # 更新函数选择面板
-#         f_button()
+# 创建弹出窗口
+def creat_window(title):
+    top = tk.Toplevel(root_window)
+    top.geometry("300x350")
+    top.title(title)
+    return top
+
+# 输入框
+def create_input_box(top, text, value):
+    box_label = tk.Label(top, text=text)
+    box_label.pack(padx=10, pady=10)
+    box_size = tk.IntVar(top, value=value)  # 创建一个IntVar对象，并设置默认值为3
+    box_size_entry = tk.Entry(top, textvariable=box_size)  # 关联IntVar对象
+    box_size_entry.pack(padx=20, pady=20)
+    return box_size_entry
+
+def check_formula_syntax(formula):
+    try:
+        sympify(formula)
+        return True
+    except SympifyError:
+        return False
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
+
+def fitting(letters,result):
+    code_str = '''
+def func({}):
+    return {}
+    '''.format(letters,result)
+    return code_str
+
+def save(result1, letters, result , result2):
+    gl_data.INDEX = len(gl_data.FITT_SAVE['no'])
+    gl_data.FITT_SAVE['no'][gl_data.INDEX] = gl_data.INDEX
+    gl_data.FITT_SAVE['name'][gl_data.INDEX] = result1
+    gl_data.FITT_SAVE['variable'][gl_data.INDEX] = letters
+    gl_data.FITT_SAVE['function'][gl_data.INDEX] = result
+    gl_data.FITT_SAVE['demo'][gl_data.INDEX] = result2
+    file_path = 'functions_new.xlsx'#设置路径
+    # 将字典转换为DataFrame
+    df = pd.DataFrame(gl_data.FITT_SAVE)
+    # 将DataFrame保存为Excel文件
+    df.to_excel(file_path, index=False)
+
+def read_fitting():
+    file_path = 'functions_new.xlsx'  # 设置路径
+    df = pd.read_excel(io=file_path, header=0)  # 设置表格
+    gl_data.FITT_SAVE = df.to_dict()
+
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
 
 def addfunc():
-    Addfunc()
-    # AddFunc()
+    top = creat_window('新增拟合函数')  # 创建弹出窗口
+    function_entry = create_input_box(top, "拟合函数名称：", '')  # 创建一个输入框，获取拟合函数名称
+    math_entry = create_input_box(top, "数学式：", '')  # 创建一个输入框，获取数学式
+    def get_input():  # 创建
+        # 获取输入框的内容
+        result1 = function_entry.get()
+        result2 = math_entry.get()
+        if result1 and result2:
+            if check_formula_syntax(result2):
+                top.destroy()  # 关闭窗口
+                letters, result = expression_output(result2)
+                save(result1, letters, result, result2)
+                gl_data.Xian_index = gl_data.INDEX
+                f_button()
+            else:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+        else:
+            messagebox.showinfo('提示','你未输入的完成！')
+    button = tk.Button(top, text="确定", command=get_input)
+    button.pack()
+
+def jis():
+    global screen_size
+    # 获取当前屏幕的宽度和高度
+    monitors = get_monitors()
+    screen_width = monitors[0].width
+    # 计算按钮的宽度和高度
+    button_width = int(screen_width * 0.85)
+    # 打印按钮的宽度和高度
+    screen_size = round(button_width*0.9/900, 1)
+    gl_data.MAGNIDICATION = screen_size
+    read_fitting()
+
+def element1(path):
+    # print(path)
+    # 加载图像并创建一个 PhotoImage 对象
+    image = tk.PhotoImage(file=path)
+    # 保存图片的引用，防止被垃圾回收
+    root_window.image = image
+    return image
+
+def element(path, width, height):
+    # 加载图元对应的图片文件
+    img = Image.open(path)
+    # # 使用resize方法调整图片
+    img = img.resize((width, height))
+    # 把Image对象转换成PhotoImage对象
+    img = ImageTk.PhotoImage(img)
+    # 保存图片的引用，防止被垃圾回收
+    root_window.img = img
+    return img
+
 def window():
     global root_window
     global label1, label2, label3
     root_window = Tk()
     root_window.title('函数拟合')
-    root_window.geometry('900x600')  # 设置窗口大小:宽x高,注,此处不能为 "*",必须使用 "x"
+    width, height = int(900*screen_size), int(560*screen_size)
+    root_window.geometry(str(width)+'x'+str(height))  # 设置窗口大小:宽x高,注,此处不能为 "*",必须使用 "x"
     # 设置主窗口的背景颜色,颜色值可以是英文单词，或者颜色值的16进制数,除此之外还可以使用Tk内置的颜色常量
-    root_window["background"] = "white"
+    img_path = ["background/add.png", "background/下方输入框.png", "background/右侧未选中.png", "background/右侧背景.png",
+                "background/右侧选中.png","background/大背景.png", "background/导航拦.png", "background/导航输入框.png",
+                "background/小直线.png", "background/手动输入数据集.png", "background/拟合.png", "background/新增拟合曲线类型.png",
+                "background/显示数据集与曲线.png", "background/未选中.png", "background/生成数据集.png", "background/矩形.png",
+                "background/背景图片.png", "background/装载.png", "background/选中.png", "background/显示数据集.png",
+                "background/img.png"
+                ]
+    global list_image
+    list_image = []
+    for i in range(len(img_path)):
+        if i in [17, 14, 19, 10, 12]:
+            list_image.append(element(img_path[i], 110, 80))
+        elif i == 16:
+            list_image.append(element(img_path[i], width, height))
+        elif i in [11, 9]:
+            list_image.append(element(img_path[i], 240, 80))
+        else:
+            list_image.append(element1(img_path[i]))
+    # root_window["background"] = "#87ceeb"
+    canvas = tk.Canvas(root_window, width=width-10, height=int(560*screen_size)-10)
+    canvas.place(x=0, y=0)
+    canvas.create_image(0, 0, image=list_image[16], anchor=tk.NW)
     root_window.resizable(0, 0)  # 防止用户调整尺寸
-    label1 = tk.Label(root_window, text="样本数据\n集文件", font=('Times', 8), bg="white",
-                      width=13, height=3,  # 设置标签内容区大小
-                      padx=0, pady=0, borderwidth=0, )
-    label1.place(x=10, y=4)  # 设置填充区距离、边框宽度和其样式（凹陷式）
-    label3 = tk.Label(root_window, text="", font=('Times', 8), bg="white", fg="black",
-                      width=39, height=2, padx=0, pady=0, borderwidth=0, relief="ridge", highlightcolor="blue")
-    label3.place(x=122, y=10)
+    canvas.create_text(int(40*screen_size), int(26*screen_size), text='样本数据\n集文件', font='Arial 14', fill='black')
+    label3 = tk.Label(root_window, text="", font=('Times', 12), bg="#ADD8E6", fg="black",
+                      width=50, height=3, padx=0, pady=0, borderwidth=0, relief="ridge", highlightcolor="blue")
+    label3.place(x=int(122*screen_size), y=int(10*screen_size))
     # 使用按钮控件调用函数
-    tk.Button(root_window, text="装载", relief=RAISED, command=lambda: askfile()).place(x=370, y=12)
-    label2 = tk.Label(root_window, text="拟合曲线类型", font=('Times', 12), bg="white",
-                      width=20, height=3, # 设置标签内容区大小
-                      padx=0, pady=0, borderwidth=0, )
-    # 设置填充区距离、边框宽度和其样式（凹陷式）
-    label2.place(x=450, y=4)
-    gl_data.Canvas2 = tk.Canvas(root_window, bg='white', width=450, height=330)
-    gl_data.Canvas2.place(x=4, y=60)
+    tk.Button(root_window, image=list_image[17], relief=tk.FLAT, bd=0, command=lambda: askfile()).place(x=int(490*screen_size), y=int(12*screen_size))
+    canvas.create_text(int(610*screen_size), int(40 * screen_size), text='拟合曲线类型', font='Arial 14', fill='black')
+    gl_data.Canvas2 = tk.Canvas(root_window, bg='white', width=int(550*screen_size), height=int(330*screen_size))
+    gl_data.Canvas2.place( x=int(4*screen_size), y=int(60*screen_size))
+
+    canvas.create_text(int(60*screen_size), int(490*screen_size),text="结果输出：", font='Arial 16', fill='black')
+
 # 定义一个处理文件的相关函数
 def askfile():
     # 从本地选择一个文件，并返回文件的路径
@@ -125,51 +229,56 @@ def read_sample_data(file_path):
 
 def buttons():
     # 随机生成样本点并显示
-    b_dot = tk.Button(root_window, text="生成\n数据集", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
-                   command=lambda: generate_and_plot_sample_data(gl_data.LOW, gl_data.HIGH))
-    b_dot.place(x=455, y=410)
+    b_dot = tk.Button(root_window, image=list_image[14], relief=tk.FLAT, bd=0, command=lambda: generate_and_plot_sample_data(gl_data.LOW, gl_data.HIGH))
+    b_dot.place(x=int(435*screen_size), y=int(410*screen_size))
     # 显示当前样本点
-    b_show = tk.Button(root_window, text="显示\n数据集", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
-              command=lambda: selfdata_show(gl_data.X, gl_data.Y, gl_data.LOW, gl_data.HIGH))
-    b_show.place(x=510, y=410)
+    b_show = tk.Button(root_window, image=list_image[19], relief=tk.FLAT, bd=0, command=lambda: selfdata_show(gl_data.X, gl_data.Y, gl_data.LOW, gl_data.HIGH))
+    b_show.place(x=int(515*screen_size), y=int(410*screen_size))
     # 显示数据集与曲线
-    b_line = tk.Button(root_window, text="显示数据\n集与曲线", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
-                   command=lambda: draw_dots_and_line(gl_data.Xian_index, gl_data.LOW, gl_data.HIGH, gl_data.X, gl_data.Y))
-    b_line.place(x=565, y=410)
+    b_line = tk.Button(root_window, image=list_image[12], relief=tk.FLAT, bd=0, command=lambda: draw_dots_and_line(gl_data.Xian_index, gl_data.LOW, gl_data.HIGH,
+                                                      gl_data.X, gl_data.Y))
+    b_line.place(x=int(595*screen_size), y=int(410*screen_size))
     # 手动输入数据集
-    b_input = tk.Button(root_window, text="手动输入数据集", relief=RAISED, bd=4, bg="white", pady=7, font=("微软雅黑", 13),
-                        command=lambda: input.input_num(root_window))
-    b_input.place(x=633, y=410)
+    b_input = tk.Button(root_window, image=list_image[9], relief=tk.FLAT, bd=0, command=lambda: input.input_num(root_window))
+    b_input.place(x=int(675*screen_size), y=int(410*screen_size))
     # 拟合并输出拟合结果
-    b_fit = tk.Button(root_window, text="拟合", relief=RAISED, bd=4, bg="white", pady=7, font=("微软雅黑", 13),
-                   command=lambda: fit_data(gl_data.Xian_index, gl_data.X, gl_data.Y))
-    b_fit.place(x=771, y=410)
+    b_fit = tk.Button(root_window, image=list_image[10], relief=tk.FLAT, bd=0, command=lambda: fit_data(gl_data.Xian_index, gl_data.X, gl_data.Y))
+    b_fit.place(x=int(821*screen_size), y=int(410*screen_size))
+
 def show_fit():
-    L = tk.Label(root_window, text='结果输出：', bg='white', font=("微软雅黑", 16)
-                                   , anchor=W)
-    L.place(x=20, y=480, width=100, height=30)
     sout = str(gl_data.Out)
     ans = tk.Label(root_window, text=sout, font=("微软雅黑", 14)
                                    , anchor=W, justify='left')
-    ans.place(x=120, y=480, width=760, height=100)
+    ans.place(x=int(120*screen_size), y=int(480*screen_size), width=int(760*screen_size), height=100)
     print(sout)
+
 def fit_data(xian_index, sx, sy):
-    # gl_data.yvals_pow = []
-    cur = function.Fun[xian_index]  # 装载正在选择的函数
-    func = cur.get_fun()#获取当前函数func
+    if gl_data.Quadrant:
+        x = sx.tolist()
+        y = sy.tolist()
+        negative_x = [i for i, num in enumerate(x) if num < 0]
+        negative_y = [i for i, num in enumerate(y) if num < 0]
+        negative = list(set(negative_x + negative_y))
+        for index in range(len(negative)):
+            # print(negative[-index-1])
+            x.pop(negative[-index-1])
+            y.pop(negative[-index-1])
+        sx = np.array(x)
+        sy = np.array(y)
+    letters, result = gl_data.FITT_SAVE['variable'][xian_index], gl_data.FITT_SAVE['function'][xian_index]
+    code_str = fitting(letters, result)
+    func = create_func(code_str)  # 获取当前函数func
     popt, pcov = curve_fit(func, sx, sy) # 用curve_fit来对点进行拟合
     yvals_pow = func(gl_data.X, *popt)
     rr = gl_data.goodness_of_fit(yvals_pow, gl_data.Y)# 计算本次拟合的R*R值，用于表示拟合优度
     # 输出拟合后的各个参数值
-    ans = '\n函数系数：'
-    for i in range(cur.variable):
-        if i == 4:
-            ans += '\n'
-        if i != 0:
-            ans += ', '
-        ans += chr(ord('a') + i) + '=' + '{:.2e}'.format(popt[i])  # str(round(gl_data.popt[i], 3))
-    gl_data.Out = '函数形式：' + cur.name + '  '
-    gl_data.Out += cur.demo
+    ans = '\n函数系数：F(x) = '
+    letter = str(letters[2:]).split(',')
+    pattern = re.compile('|'.join(letter))
+    s = pattern.sub('{:.2f}', gl_data.FITT_SAVE['demo'][xian_index])
+    ans += str(s.format(*popt))
+    gl_data.Out = '函数形式：' + gl_data.FITT_SAVE['name'][xian_index] + '  '
+    gl_data.Out += gl_data.FITT_SAVE['demo'][xian_index]
     gl_data.Out += ans
     gl_data.Out += '\n拟合优度(R\u00b2)：' + str(round(rr, 5))
     show_fit()# 显示函数信息到输出框
@@ -187,31 +296,31 @@ def q_button():
     rr = 2.5
     for widget in Q_root.winfo_children():
         widget.destroy()
-    q_cv = tk.Canvas(Q_root, width=400, height=50)
+    q_cv = tk.Canvas(Q_root, width=int(400*screen_size), height=int(50*screen_size))
     q_cv.place(x=0, y=0)
-    l = tk.Label(Q_root, text='坐标轴', bd=0, font=("微软雅黑", 16)
-                               , anchor=W)
-    l.place(x=20, y=0, width=80, height=50,)
+    # q_cv.create_image(0, 0, image=list_image[20], anchor=tk.NW)
+    l = tk.Label(Q_root, text='坐标轴', bd=0, font=("微软雅黑", 16), anchor=W)
+    l.place(x=20, y=0, width=int(80*screen_size), height=int(50*screen_size),)
     # 四象限按钮
     b1 = tk.Button(Q_root, text='四象限', bd=0,  font=("微软雅黑", 16)
                                , command=lambda: change_Q(0), anchor=W)
-    b1.place(x=170, y=0, width=80, height=50,)
+    b1.place(x=int(170*screen_size), y=0, width=int(80*screen_size), height=int(50*screen_size),)
     # 一象限按钮
     b2 = tk.Button(Q_root, text='一象限', bd=0, font=("微软雅黑", 16)
                    , command=lambda: change_Q(1), anchor=W)
-    b2.place(x=320, y=0, width=80, height=50,)
-    # 绘制标记框
-    q_cv.create_oval(140 - r, 25 - r, 140 + r, 25 + r
-                     , fill="white", width=1, outline="black")
-    q_cv.create_oval(290 - r, 25 - r, 290 + r, 25 + r
-                     , fill="white", width=1, outline="black")
+    b2.place(x=int(320*screen_size), y=0, width=int(80*screen_size), height=int(50*screen_size),)
+    # # 绘制标记框
+    q_cv.create_image(int((145 - r)*screen_size), int((35 - r)*screen_size),
+                      image=list_image[2])
+    q_cv.create_image(int((295 - r)*screen_size), int((35 - r)*screen_size),
+                      image=list_image[2])
     # 根据当前的象限选择值来填充标记框
     if gl_data.Quadrant == 0:
-        q_cv.create_oval(140 - rr, 25 - rr, 140 + rr, 25 + rr
-                     , fill="black", width=1, outline="black")
+        q_cv.create_image(int((140 - rr)*screen_size), int((30 - rr)*screen_size),
+                            image=list_image[18])
     else:
-        q_cv.create_oval(290 - rr, 25 - rr, 290 + rr, 25 + rr
-                     , fill="black", width=1, outline="black")
+        q_cv.create_image(int((290 - rr)*screen_size), int((30 - rr)*screen_size),
+                          image=list_image[18])
 def change_f(no):
     gl_data.Xian_index = no#设置全局函数编号为该函数
     f_button()#重新绘制函数显示界面
@@ -221,45 +330,219 @@ def f_button():
     rr = 2.5  # 设置按钮大小
     for widget in F_root.winfo_children():
         widget.destroy()  # 清空原有按钮
-    f_cv = tk.Canvas(F_root, width=400, height=330)#新建画布
-    f_cv.place(x=0, y=0)#放置画布
-    f_cv.create_rectangle(2, 2, 398, 328, fill='white', outline="#0099ff")#设置画布边框及底色
+    gl_data.INDEX = len(gl_data.FITT_SAVE['no'])
+    canvas = Canvas(F_root, width=int(320 * screen_size), height=int(270 * screen_size))
+    # # 将图像添加到 Canvas 组件中
+    canvas.pack(side="left", fill="both", expand=True)
+    scrollbar = Scrollbar(F_root, orient="vertical", command=canvas.yview)
+    scrollbar.pack(fill="y", side="right")
+    canvas.configure(yscrollcommand=scrollbar.set)
+    canvas.bind('<Configure>', lambda e: canvas.configure(scrollregion=canvas.bbox("all")))
+    if gl_data.INDEX - 10 <= 0:
+        result = 0
+    else:
+        result = gl_data.INDEX - 10
+    canvas_height = int(328 * screen_size) + result*50  # 或根据需要调整适当的高度增加值
+    # # 绘制矩形边框及底色
+    canvas.create_rectangle(2, 2, int(398 * screen_size), canvas_height, fill='#ADD8E6', outline="#0099ff")
+    # canvas.create_image(4, 4, image=list_image[3], anchor=tk.NW)
     cur = 0  # 函数计数
-    for fun in function.Fit_type_library:#遍历函数库
-        f = function.Fit_type_library.get(fun)#获取函数具体信息
-        if function.Show[f[0]] == 1:# 如果show为1则显示
-            f_cv.create_oval(20 - r, 20 + 15 + cur * 30 - r, 20 + r, 20 + 15 + cur * 30 + r
-                             , fill="white", width=1, outline="black")# 绘制标记框
-            if f[0] == gl_data.Xian_index:# 若选择为当前函数则标记
-                f_cv.create_oval(20 - rr, 20 + 15 + cur * 30 - rr, 20 + rr, 20 + 15 + cur * 30 + rr
-                                 , fill="black", width=1, outline="black")
+    for i in range(gl_data.INDEX):  # 遍历函数库
+        if gl_data.FITT_SAVE['no'][i] == gl_data.Xian_index:  # 若选择为当前函数则标记
+            # 在指定位置绘制图片
+            canvas.create_image(int((20 - rr) * screen_size), int((20 + 15 + cur * 30 - rr) * screen_size), image=list_image[4])
+        else:
+            # 在指定位置绘制图片
+            canvas.create_image(int((20 - rr) * screen_size), int((20 + 15 + cur * 30 - rr) * screen_size),
+                                image=list_image[2])
         # 绘制切换按钮,单击则将当前使用函数切换为该函数
-            button = tk.Button(F_root, text=f[2] + ' ' + f[1], bd=0, bg="white", font=("微软雅黑", 12)
-                               , command=lambda x=f[0]: change_f(x), anchor=W)
-            button.place(x=40, y=20 + cur * 30, width=300, height=30)
+        button = tk.Button(F_root, text=gl_data.FITT_SAVE['name'][i] + ' ' + gl_data.FITT_SAVE['demo'][i], bd=0,
+                           bg="#ADD8E6",  font=("微软雅黑", 10),
+                           command=lambda x=gl_data.FITT_SAVE['no'][i]: change_f(x), anchor=W)
+        # 将按钮放置在Canvas中
+        canvas.create_window(int(40 * screen_size), int((30 + cur * 30) * screen_size), window=button, anchor="w")
         cur += 1  # 计数加一
+    canvas.configure(scrollregion=canvas.bbox("all"))
+
 
 def close_window():
     sys.exit()
+
+def functional_formula(letter,result,decimals):
+    # 使用 zip() 函数将两个列表组合成元组的迭代器
+    pairs = zip(letter, decimals)
+    # 使用字典推导式构建字典
+    target = {key: str(value) for key, value in pairs}
+    # print(target)
+    # # 依次替换字符串中的元素
+    for key, value in target.items():
+        indices = [i for i, c in enumerate(result) if c == key]
+        for i in indices:
+            if (i + 1) == len(result) or result[i + 1] in ['*', '+', '-', '/', ')', '']:
+                result = result[0:i] + value + result[i + 1:]
+    return result
+
+
+def make_func(letters,result):
+    # print(letters,result)
+    letter = str(letters).split(',')
+    n = len(letter)-1
+    decimals = [round(random.uniform(-10, 10), 1) for _ in range(n)]
+    target_result = functional_formula(letter[1:], result, decimals)
+    # 清除以前的值
+    entry3.delete(0, tk.END)
+    # 填入函数
+    entry3.insert(0, target_result)
+    code_str = fitting('x', target_result)
+    target_func = create_func(code_str)  # 获取当前函数func
+    curve_func(target_func)
+
+def curve_func(func):
+    # 绘制拟合结果
+    draw_axis(-100, 100, 20)
+    x_fit = np.linspace(-100, 100, 100)
+    y_fit = func(x_fit)
+
+    plt.plot(x_fit, y_fit, 'r-', label='拟合曲线')
+    plt.legend()
+    plt.xlabel('x')
+    plt.ylabel('y')
+    # plt.show()
+    plt.savefig('new_line.png')
+    # 清除当前图形状态
+    plt.clf()
+    show_image()
+
+def show_image():
+    # 加载图像
+    image = Image.open("new_line.png")
+    image = image.resize((500, 500))
+    # 在画布上显示图像
+    image_tk = ImageTk.PhotoImage(image)
+    root_window.image_tk = image_tk
+    show_canvas.create_image(0, 0, anchor="nw", image=image_tk)
+
+
+def add_func():
+    result1 = entry1.get()
+    result2 = entry2.get()
+    if result1 and result2:
+        if check_formula_syntax(result2):
+            letters, result = expression_output(result2)
+            if result == None:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+            else:
+                make_func(letters,result)
+        else:
+            messagebox.showinfo('提示', '你输入的数学公式错误！')
+    else:
+        messagebox.showinfo('提示','你未输入的完成！')
+
+def customized_curve():
+    result1 = entry2.get()
+    result2 = entry3.get()
+    if result1 and result2:
+        if check_formula_syntax(result1):
+            letters, result = expression_output(result1)
+            if result == None:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+            else:
+                # 删除空格
+                result2 = result2.replace(' ', '')
+                # 使用正则表达式替换数字为空字符串
+                result3 = re.sub(r'[-]?\d+(\.\d+)?', '', result2)
+                letter = str(letters).split(',')
+                decimals = [1 for _ in range(len(letter)-1)]
+                result4 = functional_formula(letter[1:], result, decimals)
+                result4 = result4.replace('1', '')
+                result4 = re.sub(r'[-]?\d+(\.\d+)?', '', result4)
+                result4 = result4.replace(' ', '')
+                # print(result3,result4)
+                if result3 == result4:
+                    code_str = fitting('x', result2)
+                    func = create_func(code_str)  # 获取当前函数func
+                    curve_func(func)
+                else:
+                    messagebox.showinfo('提示', '请检查你修改的函数是否与函数式相对应！')
+def func_save():
+    result1 = entry1.get()
+    result2 = entry2.get()
+    if result1 and result2:
+        if check_formula_syntax(result2):
+            letters, result = expression_output(result2)
+            if result== None:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+            else:
+                save(result1, letters, result, result2)
+                subwindow.destroy()  # 关闭子页面
+                gl_data.Xian_index = gl_data.INDEX
+                f_button()
+        else:
+            messagebox.showinfo('提示', '你输入的数学公式错误！')
+    else:
+        messagebox.showinfo('提示', '你未输入的完成！')
+
+
+def show_subwindow():
+    global subwindow
+    subwindow = tk.Toplevel(root_window)
+    subwindow.geometry('1000x500')
+    subwindow.title('新增拟合函数')
+    # 创建画布
+    global show_canvas
+    canvas_width = 1000
+    canvas_height = 500
+    canvas = Canvas(subwindow, width=canvas_width, height=canvas_height, bg="#ADD8E6")
+    canvas.pack()
+    show_canvas = Canvas(canvas, width=600, height=500, bg="white")
+    show_canvas.place(x=0, y=0)
+    global entry1, entry2, entry3
+    # 创建输入框
+    label1 = tk.Label(canvas, text="函数名:")
+    label1.place(x=650, y=50)
+    entry1 = tk.Entry(canvas)
+    entry1.place(x=650, y=100, width=300, height=40)
+    label2 = tk.Label(canvas, text="函数式:")
+    label2.place(x=650, y=150)
+    entry2 = tk.Entry(canvas)
+    entry2.place(x=650, y=200, width=300, height=40)
+    label3 = tk.Label(canvas, text="测试函数式:")
+    label3.place(x=650, y=250)
+    entry3 = tk.Entry(canvas)
+    entry3.place(x=650, y=300, width=300, height=40)
+    button1 = tk.Button(canvas, text="生成函数", command=add_func)
+    button1.place(x=650, y=400)
+    button2 = tk.Button(canvas, text="函数曲线", command=customized_curve)
+    button2.place(x=750, y=400)
+    button3 = tk.Button(canvas, text="函数确认", command=func_save)
+    button3.place(x=850, y=400)
+    # subwindow.mainloop()
+
+
 def main():
     global Q_root, F_root,root_window
+    jis()
+    # gl_data.LOW, gl_data.HIGH = int(gl_data.LOW*screen_size), int(gl_data.HIGH*screen_size)
     gl_data.X = []
     gl_data.X = []
     window()
     # 函数选择相关界面
-    F_root = tk.Frame(root_window, width=400, height=330, bg='white', )
-    F_root.place(x=490, y=60)
+    F_root = tk.Canvas(root_window, width=int(310*screen_size), height=int(290*screen_size))
+    F_root.place(x=int(560*screen_size), y=int(60*screen_size))
+
     # 象限选择相关界面
-    Q_root = tk.Frame(root_window, width=400, height=50, bg='white', )
-    Q_root.place(x=20, y=410)
-    function.f_read()
+    Q_root = tk.Canvas(root_window, width=int(400*screen_size), height=int(50*screen_size))
+    Q_root.place(x=int(20*screen_size), y=int(410*screen_size))
+
     buttons()
     f_button()
     q_button()
     show_fit()
-    tk.Button(root_window, text="新增拟合曲线类型", bd=4, command=addfunc).place(x=740, y=12)
+    tk.Button(root_window, image=list_image[11], command=show_subwindow, relief=tk.FLAT, highlightthickness=0).place(x=int(640*screen_size), y=int(350)*screen_size)
+    # 设置Grid布局的列和行权重
     root_window.protocol("WM_DELETE_WINDOW", close_window)
     root_window.mainloop()
+
 if __name__ == '__main__':
     main()
     pass

data.py

@@ -9,7 +9,8 @@ import tkinter as tk
 from tkinter import *
 import random
 import numpy as np
-
+FITT_SAVE = {}
+FITT_LIST = []
 X = []                  # 等待拟合的x值
 Y = []                  # 等待拟合的y值
 global Canvas2          # 用于显示函数的画布
@@ -18,10 +19,11 @@ Img2 = None             # 绘制的line.png图像
 Xian_index = 0          # 当前选择的函数编号
 Quadrant = 0            # 当前选择的象限信息0为四象限，1为一象限
 MAXV = 1000             # 最大值
+INDEX = 5               # 拟合函数索引
 Out = ''                # 拟合输出信息
 LOW = -MAXV             # 坐标轴显示上界
 HIGH = MAXV             # 坐标轴显示下界
-
+MAGNIDICATION = 1.0       # 放大倍数
 
 def random_points():
     x=[]

demo.py

@@ -0,0 +1,10 @@
+def func_save():
+    ···与add_func相似
+    else:
+        save(result1, letters, result, result2)
+        subwindow.destroy()  # 关闭子页面
+        gl_data.Xian_index = gl_data.INDEX
+        f_button()
+    tk.Button(root_window, text="新增拟合曲线类型",
+        bd=4, command=show_subwindow).place(
+        x=int(740*screen_size), y=int(12)*screen_size)

fitting.py

@@ -13,7 +13,7 @@ import pylab as mpl
 from tkinter import *
 import mpl_toolkits.axisartist as axisartist
 import data as gl_data
-import function
+# import function
 
 mpl.rcParams['font.sans-serif'] = ['SimHei']  # 解决中文不显示问题
 plt.rcParams['axes.unicode_minus'] = False       #解决负数坐标显示问题
@@ -54,12 +54,30 @@ def selfdata_show(x, y, low, high):# 显示数据集
     plt.clf()
     set_phtot(1)
 
+def fitting(letters,result):
+    code_str = '''
+def func({}):
+    return {}
+    '''.format(letters,result)
+    return code_str
+
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
+
 def draw_line(xian_index, low, high, sx, sy):
     draw_axis(low, high)#绘制坐标轴
     popt = []#初始化curve_fit
     pcov = []#初始化curve_fit
-    cur = function.Fun[xian_index]  # 装载正在选择的函数
-    func = cur.get_fun()#获取当前函数func
+    letters, result = gl_data.FITT_SAVE['variable'][xian_index], gl_data.FITT_SAVE['function'][xian_index]
+    code_str = fitting(letters, result)
+    func = create_func(code_str)  # 获取当前函数func
+    # cur = function.Fun[xian_index]  # 装载正在选择的函数
+    # func = cur.get_fun()#获取当前函数func
     popt, pcov = curve_fit(func, sx, sy)# 用curve_fit来对点进行拟合
     curve_x = np.arange(low, high)#按照步长生成的一串数字
     curve_y = [func(i, *popt) for i in curve_x]# 根据x0(按照步长生成的一串数字)来计算y1值
@@ -71,20 +89,37 @@ def draw_line(xian_index, low, high, sx, sy):
     set_phtot(2)#将图片显示到程序中
 
 def draw_dots_and_line(xian_index, low, high, sx, sy):
+    if gl_data.Quadrant:
+        x = sx.tolist()
+        y = sy.tolist()
+        negative_x = [i for i, num in enumerate(x) if num < 0]
+        negative_y = [i for i, num in enumerate(y) if num < 0]
+        negative = list(set(negative_x + negative_y))
+        for index in range(len(negative)):
+            # print(negative[-index-1])
+            x.pop(negative[-index - 1])
+            y.pop(negative[-index - 1])
+        sx = np.array(x)
+        sy = np.array(y)
+    print(sx)
     ############## begin #####################
     draw_axis(low, high)
     popt = []
     pcov = []
-    cur = function.Fun[xian_index]  # 装载正在选择的函数
-    func = cur.get_fun()#获取当前函数func
+    letters, result = gl_data.FITT_SAVE['variable'][xian_index], gl_data.FITT_SAVE['function'][xian_index]
+    code_str = fitting(letters, result)
+    func = create_func(code_str)  # 获取当前函数func
+    print(code_str)
+    # cur = function.Fun[xian_index]  # 装载正在选择的函数
+    # func = cur.get_fun()#获取当前函数func
     popt, pcov = curve_fit(func, sx, sy)# 用curve_fit来对点进行拟合
     positive_mask = sy >= 0.0#给样本点分类
     negative_mask = sy < 0.0#给样本点分类
-    positive_colors = ['red' if x >= 0.0 else 'blue' for x in sx]#给样本点分类
-    negative_colors = ['green' if x >= 0.0 else 'purple' for x in sx]#给样本点分类
+    positive_colors = ['red' if x >= 0.0 else 'red' for x in sx]#给样本点分类
+    negative_colors = ['red' if x >= 0.0 else 'red' for x in sx]#给样本点分类
     #根据样本点类型决定样本点颜色
-    plt.scatter(gl_data.X[positive_mask], gl_data.Y[positive_mask], color=np.array(positive_colors)[positive_mask], lw=1)
-    plt.scatter(gl_data.X[negative_mask], gl_data.Y[negative_mask], color=np.array(negative_colors)[negative_mask], lw=1)
+    plt.scatter(sx[positive_mask], sy[positive_mask], color=np.array(positive_colors)[positive_mask], lw=1)
+    plt.scatter(sx[negative_mask], sy[negative_mask], color=np.array(negative_colors)[negative_mask], lw=1)
     curve_x = np.arange(low, high)#按照步长生成的一串数字
     curve_y = [func(i, *popt) for i in curve_x]# 根据x0(按照步长生成的一串数字)来计算y1值
     ############## end #######################
@@ -102,13 +137,17 @@ def set_phtot(index1):
     if index1 == 1:
         gl_data.Img1=PhotoImage(file=r"dot.png")
         # print(gl_data.Img1)
+        gl_data.Img1 = gl_data.Img1.zoom(2, 2)
         set_img1=Canvas2.create_image(2, 10, image=gl_data.Img1, anchor=NW)
+        # Canvas2.itemconfigure(set_img1,int(420 * gl_data.MAGNIDICATION), int(300 * gl_data.MAGNIDICATION))
         Canvas2.update()
         print("已输出数据点")
     elif index1 == 2:
         gl_data.Img2=PhotoImage(file=r"line.png")
         # print(gl_data.Img2)
+        gl_data.Img2 = gl_data.Img2.zoom(2, 2)
         set_img2=Canvas2.create_image(2, 10, image=gl_data.Img2, anchor=NW)
+        # Canvas2.itemconfigure(set_img2, 0,0,int(420*gl_data.MAGNIDICATION), int(300*gl_data.MAGNIDICATION))
         Canvas2.update()
         print("已输出数据点和曲线")
 if __name__ == '__main__':

input.py

@@ -6,11 +6,12 @@
  @SoftWare: PyCharm
 """
 import tkinter as tk
-
+from tkinter import *
 import numpy as np
 
 import data as gl_data
-from tkinter import *
+from fitting import selfdata_show
+
 global top
 def input_num(root_tk):
     global top
@@ -31,6 +32,7 @@ def input_data(root_tk, num):
     sample_data = []
     top.destroy()
     top = tk.Toplevel(root_tk)
+
     def add_sample_data():
         try:
             x = float(entry_x.get())
@@ -40,7 +42,7 @@ def input_data(root_tk, num):
             return
         entry_x.delete(0, tk.END)
         entry_y.delete(0, tk.END)
-        if min(x, y) < gl_data.low or max(x, y) > gl_data.high:
+        if min(x, y) < gl_data.LOW or max(x, y) > gl_data.HIGH:
             label_status.config(text="输入超过范围")
             return
         elif len(sample_data) < num:
@@ -53,10 +55,11 @@ def input_data(root_tk, num):
     def check_sample_data():
         if len(sample_data) == num:
             label_status.config(text="已达到最大数量")
-            gl_data.x = np.array(sample_x)
-            gl_data.y = np.array(sample_y)
+            gl_data.X = np.array(sample_x)
+            gl_data.Y = np.array(sample_y)
             print('已添加', sample_data)
             top.destroy()
+            selfdata_show(gl_data.X, gl_data.Y, gl_data.LOW, gl_data.HIGH)
         else:
             label_status.config(text="还需输入{}个点对".format(num - len(sample_data)))
             print(sample_data)
@@ -77,7 +80,6 @@ def input_data(root_tk, num):
     label_status.pack()
     top.mainloop()
 
-
 if __name__ == '__main__':
     root = tk.Tk()
     input_num(root)

new_x5.py

@@ -0,0 +1,23 @@
+import tkinter as tk
+from screeninfo import get_monitors
+
+# 创建Tkinter窗口
+window = tk.Tk()
+window.title("设置按钮尺寸为当前屏幕的百分之85")
+window.geometry('190x160')
+def jis():
+    # 获取当前屏幕的宽度和高度
+    monitors = get_monitors()
+    screen_width = monitors[0].width
+    screen_height = monitors[0].height
+
+    # 计算按钮的宽度和高度
+    button_width = int(screen_width * 0.85)
+    button_height = int(screen_height * 0.85)
+    # 打印按钮的宽度和高度
+    print(f"按钮的尺寸：{button_width}x{button_height}")
+# 创建一个按钮，并设置尺寸
+button = tk.Button(window, text="按钮", command=jis)
+button.pack()
+# 运行Tkinter事件循环
+window.mainloop()

newly_added/X5.py

@@ -0,0 +1,364 @@
+# -*- coding: utf-8 -*-
+# Time : 2023/8/9 10:20
+# Author : lirunsheng
+# User : l'r's
+# Software: PyCharm
+# File : X5.py
+
+# -*- encoding: utf-8 -*-
+"""
+ @Author: packy945
+ @FileName: main.py
+ @DateTime: 2023/5/30 15:29
+ @SoftWare: PyCharm
+"""
+import re
+from tkinter import messagebox
+
+from PIL import ImageTk, Image
+from pandas import DataFrame
+import pandas as pd
+from sympy import sympify, SympifyError
+import sys
+from fitting import *
+import numpy as np
+import data as gl_data
+import input
+import tkinter as tk
+from tkinter import *
+import tkinter.filedialog  # 注意次数要将文件对话框导入
+# from demo1 import Addfunc
+from newly_added.formula import expression_output
+
+global Q_root,F_root
+global root_window
+global label1,label2,label3
+from screeninfo import get_monitors
+import os
+
+# 创建弹出窗口
+def creat_window(title):
+    top = tk.Toplevel(root_window)
+    top.geometry("300x350")
+    top.title(title)
+    return top
+
+# 输入框
+def create_input_box(top, text, value):
+    box_label = tk.Label(top, text=text)
+    box_label.pack(padx=10, pady=10)
+    box_size = tk.IntVar(top, value=value)  # 创建一个IntVar对象，并设置默认值为3
+    box_size_entry = tk.Entry(top, textvariable=box_size)  # 关联IntVar对象
+    box_size_entry.pack(padx=20, pady=20)
+    return box_size_entry
+
+def check_formula_syntax(formula):
+    try:
+        sympify(formula)
+        return True
+    except SympifyError:
+        return False
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
+
+def fitting(letters,result):
+    code_str = '''
+def func({}):
+    return {}
+    '''.format(letters,result)
+    return code_str
+
+def save(result1, letters, result , result2):
+    gl_data.INDEX = len(gl_data.FITT_SAVE['no'])
+    gl_data.FITT_SAVE['no'][gl_data.INDEX] = gl_data.INDEX
+    gl_data.FITT_SAVE['name'][gl_data.INDEX] = result1
+    gl_data.FITT_SAVE['variable'][gl_data.INDEX] = letters
+    gl_data.FITT_SAVE['function'][gl_data.INDEX] = result
+    gl_data.FITT_SAVE['demo'][gl_data.INDEX] = result2
+    file_path = 'functions_new.xlsx'#设置路径
+    df = pd.DataFrame(gl_data.FITT_SAVE)  # 将字典转换为DataFrame
+    df.to_excel(file_path, index=False)  # 将DataFrame保存为Excel文件
+
+def read_fitting():
+    file_path = 'functions_new.xlsx'  # 设置路径
+    df = pd.read_excel(io=file_path, header=0)  # 设置表格
+    gl_data.FITT_SAVE = df.to_dict()
+
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
+
+def addfunc():
+    top = creat_window('新增拟合函数')  # 创建弹出窗口
+    function_entry = create_input_box(top, "拟合函数名称：", '')  # 创建一个输入框，获取拟合函数名称
+    math_entry = create_input_box(top, "数学式：", '')  # 创建一个输入框，获取数学式
+    def get_input():  # 创建
+        # 获取输入框的内容
+        result1 = function_entry.get()
+        result2 = math_entry.get()
+        if result1 and result2:
+            if check_formula_syntax(result2):
+                top.destroy()  # 关闭窗口
+                letters, result = expression_output(result2)
+                save(result1, letters, result, result2)
+                gl_data.Xian_index = gl_data.INDEX
+                f_button()
+            else:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+        else:
+            messagebox.showinfo('提示','你未输入的完成！')
+    button = tk.Button(top, text="确定", command=get_input)
+    button.pack()
+
+def jis():
+    global screen_size
+    # 获取当前屏幕的宽度和高度
+    monitors = get_monitors()
+    screen_width = monitors[0].width
+    # 计算按钮的宽度和高度
+    button_width = int(screen_width * 0.85)
+    # 打印按钮的宽度和高度
+    screen_size = round(button_width*0.9/900, 1)
+    gl_data.MAGNIDICATION = screen_size
+    read_fitting()
+
+def element(path):
+    # print(path)
+    # 加载图像并创建一个 PhotoImage 对象
+    image = tk.PhotoImage(file=path)
+    # 保存图片的引用，防止被垃圾回收
+    root_window.image = image
+    return image
+
+def window():
+    global root_window
+    global label1, label2, label3
+    root_window = Tk()
+    root_window.title('函数拟合')
+    width, height= int(900*screen_size),int(560*screen_size)
+    root_window.geometry(str(width)+'x'+str(height))  # 设置窗口大小:宽x高,注,此处不能为 "*",必须使用 "x"
+    # 设置主窗口的背景颜色,颜色值可以是英文单词，或者颜色值的16进制数,除此之外还可以使用Tk内置的颜色常量
+    img_path = ["background/add.png", "background/下方输入框.png", "background/右侧未选中.png", "background/右侧背景.png",
+                "background/右侧选中.png","background/大背景.png", "background/导航拦.png", "background/导航输入框.png",
+                "background/小直线.png", "background/手动输入数据集.png", "background/拟合.png", "background/新增拟合曲线类型.png",
+                "background/显示数据集与曲线.png", "background/未选中.png", "background/生成数据集.png", "background/矩形.png",
+                "background/背景图片.png", "background/装载.png", "background/选中.png"
+                ]
+    global list_image
+    list_image = []
+    for path in img_path:
+        list_image.append(element(path))
+    root_window["background"] = "white"
+    root_window.resizable(0, 0)  # 防止用户调整尺寸
+    label1 = tk.Label(root_window, text="样本数据\n集文件", font=('Times', 8), bg="white",
+                      width=13, height=3,  # 设置标签内容区大小
+                      padx=0, pady=0, borderwidth=0, )
+    label1.place(x=int(10*screen_size), y=int(4*screen_size))  # 设置填充区距离、边框宽度和其样式（凹陷式）
+    label3 = tk.Label(root_window, text="", font=('Times', 8), bg="white", fg="black",
+                      width=39, height=2, padx=0, pady=0, borderwidth=0, relief="ridge", highlightcolor="blue")
+    label3.place(x=int(122*screen_size), y=int(10*screen_size))
+    # 使用按钮控件调用函数
+    tk.Button(root_window, image=list_image[17], relief=RAISED, command=lambda: askfile()).place(x=int(370*screen_size), y=int(12*screen_size))
+    label2 = tk.Label(root_window, text="拟合曲线类型", font=('Times', 12), bg="white",
+                      width=20, height=3, # 设置标签内容区大小
+                      padx=0, pady=0, borderwidth=0, )
+    # 设置填充区距离、边框宽度和其样式（凹陷式）
+    label2.place(x=int(450*screen_size), y=int(4*screen_size))
+    gl_data.Canvas2 = tk.Canvas(root_window, bg='white', width=int(450*screen_size), height=int(330*screen_size))
+    gl_data.Canvas2.place(x=int(4*screen_size), y=int(60*screen_size))
+# 定义一个处理文件的相关函数
+def askfile():
+    # 从本地选择一个文件，并返回文件的路径
+    filename = tkinter.filedialog.askopenfilename()
+    if filename != '':#若选中了一个文件，则对文件进行读取
+        label3.config(text=filename)#显示文件路径
+        read_sample_data(filename)#将文件读取并存到sampleData中
+        # print_sample_data(filename)#将文件读取并逐行输出
+        selfdata_show(gl_data.X, gl_data.Y, gl_data.LOW, gl_data.HIGH)
+    else:#若未选择文件，则显示为空
+        label3.config(text='')
+
+def print_sample_data(file_path):#打开对应文件
+    with open(file_path, 'r') as file:
+        for line in file:#逐行读取文件
+            line = line.strip('\n')#移除换行符
+            sx, sy = line.split(' ')#以空格分割x，y
+            print(f'sx: {float(sx)}, sy: {float(sy)}')#将sx、sy转换为浮点数并打印
+
+def read_sample_data(file_path):
+    x, y = [], []#初始化x，y
+    with open(file_path, 'r') as file:
+        for line in file:#逐行读文件
+            line = line.strip('\n')#移除换行符
+            sx, sy = line.split(' ')#以空格分割x，y
+            x.append(float(sx))#将sx转换为浮点数并加入数组
+            y.append(float(sy))#将sy转换为浮点数并加入数组
+    gl_data.X, gl_data.Y = np.array(x), np.array(y)#x，y数组转为array并赋值给全局变量
+
+def buttons():
+    # 随机生成样本点并显示
+    b_dot = tk.Button(root_window, text="生成\n数据集", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
+                   command=lambda: generate_and_plot_sample_data(gl_data.LOW, gl_data.HIGH))
+    b_dot.place(x=int(455*screen_size), y=int(410*screen_size))
+    # 显示当前样本点
+    b_show = tk.Button(root_window, text="显示\n数据集", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
+              command=lambda: selfdata_show(gl_data.X, gl_data.Y, gl_data.LOW, gl_data.HIGH))
+    b_show.place(x=int(510*screen_size), y=int(410*screen_size))
+    # 显示数据集与曲线
+    b_line = tk.Button(root_window, text="显示数据\n集与曲线", relief=RAISED, bd=4, bg="white", font=("微软雅黑", 10),
+                   command=lambda: draw_dots_and_line(gl_data.Xian_index, gl_data.LOW, gl_data.HIGH, gl_data.X, gl_data.Y))
+    b_line.place(x=int(565*screen_size), y=int(410*screen_size))
+    # 手动输入数据集
+    b_input = tk.Button(root_window, text="手动输入数据集", relief=RAISED, bd=4, bg="white", pady=7, font=("微软雅黑", 13),
+                        command=lambda: input.input_num(root_window))
+    b_input.place(x=int(633*screen_size), y=int(410*screen_size))
+    # 拟合并输出拟合结果
+    b_fit = tk.Button(root_window, text="拟合", relief=RAISED, bd=4, bg="white", pady=7, font=("微软雅黑", 13),
+                   command=lambda: fit_data(gl_data.Xian_index, gl_data.X, gl_data.Y))
+    b_fit.place(x=int(771*screen_size), y=int(410*screen_size))
+def show_fit():
+    L = tk.Label(root_window, text='结果输出：', bg='white', font=("微软雅黑", 16)
+                                   , anchor=W)
+    L.place(x=20, y=int(480*screen_size), width=int(100*screen_size), height=int(30*screen_size))
+    sout = str(gl_data.Out)
+    ans = tk.Label(root_window, text=sout, font=("微软雅黑", 14)
+                                   , anchor=W, justify='left')
+    ans.place(x=int(120*screen_size), y=int(480*screen_size), width=int(760*screen_size), height=100)
+    print(sout)
+def fit_data(xian_index, sx, sy):
+    letters, result = gl_data.FITT_SAVE['variable'][xian_index], gl_data.FITT_SAVE['function'][xian_index]
+    code_str = fitting(letters, result)
+    func = create_func(code_str) # 获取当前函数func
+    popt, pcov = curve_fit(func, sx, sy) # 用curve_fit来对点进行拟合
+    yvals_pow = func(gl_data.X, *popt)
+    rr = gl_data.goodness_of_fit(yvals_pow, gl_data.Y)# 计算本次拟合的R*R值，用于表示拟合优度
+    # 输出拟合后的各个参数值
+    ans = '\n函数系数：F(x) = '
+    letter = str(letters[2:]).split(',')
+    pattern = re.compile('|'.join(letter))
+    s = pattern.sub('{:.2f}', gl_data.FITT_SAVE['demo'][xian_index])
+    ans += str(s.format(*popt))
+    gl_data.Out = '函数形式：' + gl_data.FITT_SAVE['name'][xian_index] + '  '
+    gl_data.Out += gl_data.FITT_SAVE['demo'][xian_index]
+    gl_data.Out += ans
+    gl_data.Out += '\n拟合优度(R\u00b2)：' + str(round(rr, 5))
+    show_fit()# 显示函数信息到输出框
+
+def change_Q(no):
+    gl_data.Quadrant = no #更改全局变量的象限显示
+    if no:#若为一象限，则修改显示下限为0
+        gl_data.LOW = 0
+    else:#若为四象限，则修改显示下限为-gl_data.maxV
+        gl_data.LOW = -gl_data.MAXV
+    q_button()#更新象限显示面板
+
+def q_button():
+    r = 7.5
+    rr = 2.5
+    for widget in Q_root.winfo_children():
+        widget.destroy()
+    q_cv = tk.Canvas(Q_root, width=int(400*screen_size), height=int(50*screen_size))
+    q_cv.place(x=0, y=0)
+    l = tk.Label(Q_root, text='坐标轴', bd=0, font=("微软雅黑", 16)
+                               , anchor=W)
+    l.place(x=20, y=0, width=int(80*screen_size), height=int(50*screen_size),)
+    # 四象限按钮
+    b1 = tk.Button(Q_root, text='四象限', bd=0,  font=("微软雅黑", 16)
+                               , command=lambda: change_Q(0), anchor=W)
+    b1.place(x=int(170*screen_size), y=0, width=int(80*screen_size), height=int(50*screen_size),)
+    # 一象限按钮
+    b2 = tk.Button(Q_root, text='一象限', bd=0, font=("微软雅黑", 16)
+                   , command=lambda: change_Q(1), anchor=W)
+    b2.place(x=int(320*screen_size), y=0, width=int(80*screen_size), height=int(50*screen_size),)
+    # 绘制标记框
+    q_cv.create_oval(int((140 - r)*screen_size), int((25 - r)*screen_size), int((140 + r)*screen_size), int((25 + r)*screen_size)
+                     , fill="white", width=1, outline="black")
+    q_cv.create_oval(int((290 - r)*screen_size), int((25 - r)*screen_size), int((290 + r)*screen_size), int((25 + r)*screen_size)
+                     , fill="white", width=1, outline="black")
+    # 根据当前的象限选择值来填充标记框
+    if gl_data.Quadrant == 0:
+        q_cv.create_oval(int((140 - rr)*screen_size), int((25 - rr)*screen_size), int((140 + rr)*screen_size), int((25 + rr)*screen_size)
+                     , fill="black", width=1, outline="black")
+    else:
+        q_cv.create_oval(int((290 - rr)*screen_size), int((25 - rr)*screen_size), int((290 + rr)*screen_size), int((25 + rr)*screen_size)
+                     , fill="black", width=1, outline="black")
+def change_f(no):
+    gl_data.Xian_index = no#设置全局函数编号为该函数
+    f_button()#重新绘制函数显示界面
+
+def f_button():
+    r = 7.5  # 设置按钮大小
+    rr = 2.5  # 设置按钮大小
+
+    for widget in F_root.winfo_children():
+        widget.destroy()  # 清空原有按钮
+    gl_data.INDEX = len(gl_data.FITT_SAVE['no'])
+    # 创建滚动条
+    scrollbar = tk.Scrollbar(F_root)
+    scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
+    # 创建Canvas对象
+    f_cv = tk.Canvas(F_root, width=int(370 * screen_size), height=int(310 * screen_size), yscrollcommand=scrollbar.set)
+    f_cv.pack(side=tk.LEFT)
+    # 设置滚动条与Canvas的关联
+    scrollbar.config(command=f_cv.yview)
+    # # 绘制矩形边框及底色
+    # f_cv.create_rectangle(2, 2, int(398 * screen_size), int(328 * screen_size), fill='white',
+    #                       outline="#0099ff")
+    cur = 0  # 函数计数
+    for i in range(gl_data.INDEX):  # 遍历函数库
+        f_cv.create_oval(int((20 - r) * screen_size), int((20 + 15 + cur * 30 - r) * screen_size),
+                         int((20 + r) * screen_size), int((20 + 15 + cur * 30 + r) * screen_size)
+                         , fill="white", width=1, outline="black")  # 绘制标记框
+        if gl_data.FITT_SAVE['no'][i] == gl_data.Xian_index:  # 若选择为当前函数则标记
+            f_cv.create_oval(int((20 - rr) * screen_size), int((20 + 15 + cur * 30 - rr) * screen_size),
+                             int((20 + rr) * screen_size), int((20 + 15 + cur * 30 + rr) * screen_size)
+                             , fill="black", width=int(screen_size), outline="black")
+        # 绘制切换按钮,单击则将当前使用函数切换为该函数
+        button = tk.Button(F_root, text=gl_data.FITT_SAVE['name'][i] + ' ' + gl_data.FITT_SAVE['demo'][i], bd=0,
+                           bg="white", font=("微软雅黑", 12),
+                           command=lambda x=gl_data.FITT_SAVE['no'][i]: change_f(x), anchor=W)
+
+        # 将按钮放置在Canvas中
+        f_cv.create_window(int(40 * screen_size), int((35 + cur * 30) * screen_size), window=button, anchor="w")
+        cur += 1  # 计数加一
+
+    f_cv.configure(scrollregion=f_cv.bbox("all"))
+
+def close_window():
+    sys.exit()
+
+
+def main():
+    global Q_root, F_root,root_window
+    jis()
+    # gl_data.LOW, gl_data.HIGH = int(gl_data.LOW*screen_size), int(gl_data.HIGH*screen_size)
+    gl_data.X = []
+    gl_data.X = []
+    window()
+    # 函数选择相关界面
+    F_root = tk.Frame(root_window, width=int(400*screen_size), height=int(330*screen_size), bg='white', )
+    F_root.place(x=int(490*screen_size), y=int(60*screen_size))
+    # 象限选择相关界面
+    Q_root = tk.Frame(root_window, width=int(400*screen_size), height=int(50*screen_size), bg='white', )
+    Q_root.place(x=int(20*screen_size), y=int(410*screen_size))
+    buttons()
+    f_button()
+    q_button()
+    show_fit()
+    tk.Button(root_window, text="新增拟合曲线类型", bd=4, command=addfunc).place(x=int(740*screen_size), y=int(12)*screen_size)
+    # 设置Grid布局的列和行权重
+    root_window.protocol("WM_DELETE_WINDOW", close_window)
+    root_window.mainloop()
+
+if __name__ == '__main__':
+    main()
+    pass

newly_added/demo.py

@@ -0,0 +1,70 @@
+# import re
+#
+# def add_spaces(expression):
+#     # 匹配运算符的正则表达式
+#     pattern = r'([+\-*/])'
+#     # 替换匹配到的运算符
+#     new_expression = re.sub(pattern, r' \1 ', expression)
+#     return new_expression
+#
+# # 示例用法
+# expression = 'a+b^c-c*d/e'
+# new_expression = add_spaces(expression)
+# print(new_expression)
+
+import re
+from formula import *
+
+def remove_inner_spaces(expression):
+    # 匹配括号内的空格的正则表达式
+    pattern = r'\((.*?)\)'
+    # 替换匹配到的括号内的空格
+    new_expression = re.sub(pattern, lambda match: '(' + match.group(1).replace(' ', '') + ')', expression)
+    return new_expression
+
+def add_spaces(expression):
+    # 匹配运算符的正则表达式
+    pattern = r'([+\-*/])'
+    # 替换匹配到的运算符
+    new_expression = re.sub(pattern, r' \1 ', expression)
+    return new_expression
+# 示例用法
+expression = 'a+b^c-c*d/e+sin(x+y)+e^(0.2*x)'
+expression = add_spaces(expression)
+new_expression = remove_inner_spaces(expression)
+list_expression = new_expression.split(' ')
+conforms = ['e^', 'log', 'sin', 'cos', 'tan', '^']
+new_list = []
+# result2 = ' '.join([word for word in expression.split() if not any(word.startswith(s) for s in conforms)])
+# print(result2)
+# letters = [char for char in result2 if char.isalpha()]
+# print(letters)
+for expres in list_expression:
+    new_list.append(expres)
+    for i in range(6):
+        if conforms[i] in expres:
+            index = list_expression.index(expres)
+            if i == 0:
+                list_expression[index] = convert_e(expres)
+            elif i==1:
+                list_expression[index] = convert_log(expres)
+            elif i==5:
+                list_expression[index] = convert_x(expres)
+            else:
+                list_expression[index] = convert_trigonometric(expres)
+            new_list[-1] = new_list[-1].replace(conforms[i], "")
+            break
+new_list = [char for item in new_list for char in item if char.isalpha()]
+parameter =''
+for item in new_list:
+    if item not in parameter:
+        parameter = parameter+item+','
+print(parameter[:-1])
+for item in new_list:
+    if item not in parameter:
+        parameter = parameter+item+','
+str_expression = ''
+for item in list_expression:
+    str_expression = str_expression + item
+print(str_expression[:-1])
+print(list_expression)

newly_added/demo1.py

@@ -0,0 +1,44 @@
+import mpl_toolkits.axisartist as axisartist
+from scipy.optimize import curve_fit
+from pandas import DataFrame
+import matplotlib.pyplot as plt
+import numpy as np
+import pylab as mpl
+from tkinter import *
+import data as gl_data
+import pandas as pd
+import tkinter
+import sys
+import tkinter as tk
+from tkinter import filedialog
+
+mpl.rcParams['font.sans-serif'] = ['SimHei']  		# 解决matplotlib中文不显示问题
+plt.rcParams['axes.unicode_minus'] = False # 解决matplotlib负数坐标显示问题
+
+# 创建一个二维数组sampleData，用于存储样本数据
+sampleData = []
+
+def askfile():# 从本地选择一个文件，并返回文件的路径
+    global sampleData
+    # 弹出文件选择对话框，选择要打开的文本文件
+    file_path = filedialog.askopenfilename(filetypes=[('Text Files', '*.txt')])
+
+    # 如果没有选择文件，直接返回
+    if not file_path:
+        return
+    # 步骤1：打开样本数据集文件并读取每行数据
+    with open(file_path, 'r') as file:
+        lines = file.readlines()
+
+    # 步骤2：遍历所有行，将每行数据解析为sx和sy值，转换为浮点数并存储到sampleData中
+    for line in lines:
+        sx, sy = line.strip().split(' ')
+        sx = float(sx)
+        sy = float(sy)
+        sampleData.append([sx, sy])
+
+    # # 步骤3：使用循环遍历样本数据并打印出来
+    # for data in sampleData:
+    #     print(data)
+if __name__ == '__main__':
+    askfile()

newly_added/demo2.py

@@ -0,0 +1,19 @@
+import re
+
+
+def find_letter_index(string):
+    pattern = r'([a-zA-Z])x\b'
+    matches = re.findall(pattern, string)
+
+    letter_indices = []
+    for match in matches:
+        letter_index = string.index(match)
+        letter_indices.append(letter_index)
+
+    return letter_indices
+
+
+# 示例使用
+string = "ax+b + cx - dx + e^x"
+indices = find_letter_index(string)
+print(indices)

newly_added/demo3.py

@@ -0,0 +1,4 @@
+screen_size = 1.8
+r = 7.5
+rr = 2.5
+print(int((20 - rr) * screen_size))

newly_added/demo5.py

@@ -0,0 +1,41 @@
+import numpy as np
+from scipy.optimize import leastsq
+import matplotlib.pyplot as plt
+
+# 定义待拟合的函数形式
+def func(x, coeffs):
+    return coeffs[0] * np.sin(coeffs[1] * x) + coeffs[2]
+
+# 定义目标函数，即待拟合数据
+def target_func(x):
+    return 2.5 * np.sin(0.7 * x) + 1.2
+
+# 生成带噪声的待拟合数据
+np.random.seed(0)
+x_data = np.linspace(-10, 10, 100)
+y_data = target_func(x_data) + np.random.normal(0, 0.5, 100)
+
+# 定义误差函数，即最小二乘法的目标函数
+def residuals(coeffs, y, x):
+    return y - func(x, coeffs)
+
+# 初始参数的估计值
+initial_coeffs = [1, 1, 1]
+
+# 使用最小二乘法拟合函数
+result = leastsq(residuals, initial_coeffs, args=(y_data, x_data))
+best_coeffs = result[0]
+
+# 打印拟合得到的系数
+print("拟合得到的系数：", best_coeffs)
+
+# 绘制拟合结果
+x_fit = np.linspace(-10, 10, 100)
+y_fit = func(x_fit, best_coeffs)
+
+plt.plot(x_data, y_data, 'bo', label='原始数据')
+plt.plot(x_fit, y_fit, 'r-', label='拟合曲线')
+plt.legend()
+plt.xlabel('x')
+plt.ylabel('y')
+plt.show()

newly_added/demo6.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+# 定义待拟合的函数形式
+def func(x, coeffs):
+    return coeffs[0] * x + coeffs[1]
+
+# 定义目标函数，即待拟合数据
+def target_func(x):
+    return 2.5 * x + 1.2
+
+# 生成带噪声的待拟合数据
+np.random.seed(0)
+x_data = np.linspace(0, 10, 100)
+y_data = target_func(x_data) + np.random.normal(0, 0.5, 100)
+
+# 定义损失函数，即拟合函数与目标函数之间的差距
+def loss_func(coeffs, x, y):
+    return np.mean((y - func(x, coeffs))**2)
+
+# 定义梯度计算函数，即损失函数对于系数的偏导数
+def gradient_func(coeffs, x, y):
+    gradient = np.zeros_like(coeffs)
+    gradient[0] = -2 * np.mean((y - func(x, coeffs)) * x)
+    gradient[1] = -2 * np.mean(y - func(x, coeffs))
+    return gradient
+
+# 初始化参数
+learning_rate = 0.01
+num_iterations = 1000
+initial_coeffs = np.array([1.0, 1.0], dtype=float)
+
+# 使用梯度下降法拟合函数
+coeffs = initial_coeffs
+for i in range(num_iterations):
+    gradient = gradient_func(coeffs, x_data, y_data)
+    coeffs -= learning_rate * gradient
+
+# 打印拟合得到的系数
+print("拟合得到的系数：", coeffs)
+
+# 绘制拟合结果
+x_fit = np.linspace(0, 10, 100)
+y_fit = func(x_fit, coeffs)
+
+plt.plot(x_data, y_data, 'bo', label='原始数据')
+plt.plot(x_fit, y_fit, 'r-', label='拟合曲线')
+plt.legend()
+plt.xlabel('x')
+plt.ylabel('y')
+plt.show()

newly_added/demo7.py

@@ -0,0 +1,51 @@
+# def make_func(letters,result):
+#     global func_x
+#     # print(letters,result)
+#     draw_axis(-100, 100, 20)
+#     letter = str(letters).split(',')
+#     n = len(letter)-1
+#     decimals = [round(random.uniform(-10, 10), 1) for _ in range(n)]
+#     target_result = functional_formula(letter[1:],result,decimals)
+#     # output.configure(state="normal")
+#     # output.delete("1.0", tk.END)  # 删除当前输出框中的所有文本
+#     # output.insert(tk.END, target_result)
+#     # output.configure(state="disabled")
+#     code_str = fitting('x', target_result)
+#     # print(code_str)
+#     target_func = create_func(code_str)  # 获取当前函数func
+#     # # print(target_result)
+#     # # 生成带噪声的待拟合数据
+#     # np.random.seed(0)
+#     # x_data = np.linspace(-100, 100, 50)
+#     # y_data = target_func(x_data) + np.random.normal(0, 0.5, 50)
+#     # # print(y_data)
+#     # code_str = fitting(letters, result)
+#     # print(code_str)
+#     # func_x = create_func(code_str)  # 获取当前函数func
+#     #
+#     # # 初始参数的估计值
+#     # initial_coeffs = [1.0 for _ in range(n)]
+#     # # 使用最小二乘法拟合函数
+#     # result = leastsq(residuals, initial_coeffs, args=(y_data, x_data))
+#     # best_coeffs = result[0]
+#     # # 打印拟合得到的系数
+#     # print("拟合得到的系数：", best_coeffs)
+#
+#     # 绘制拟合结果
+#     x_fit = np.linspace(-100, 100, 50)
+#     y_fit = target_func(x_fit)
+#
+#     # plt.plot(x_data, y_data, 'bo', label='原始数据')
+#     plt.plot(x_fit, y_fit, 'r-', label='拟合曲线')
+#     plt.legend()
+#     plt.xlabel('x')
+#     plt.ylabel('y')
+#     # plt.show()
+#     plt.savefig('new_line.png')
+#     # 清除当前图形状态
+#     plt.clf()
+#     show_image()
+#
+# # 定义误差函数，即最小二乘法的目标函数
+# def residuals(coeffs, y, x):
+#     return y - func_x(x, *coeffs)

newly_added/demo8.py

@@ -0,0 +1,17 @@
+from sympy import symbols, Eq, simplify
+
+x = symbols('x')
+a = symbols('a')
+b = symbols('b')
+
+expr1 = a*x + b
+expr2 = 12*x + 1.3
+
+eq = Eq(expr1, expr2)  # 创建一个等式表达式
+
+simplified_eq = simplify(eq)  # 化简等式
+
+if simplified_eq == True:
+    print("两个表达式相等")
+else:
+    print("两个表达式不相等")

newly_added/formula.py

@@ -0,0 +1,103 @@
+import re
+def convert_log(expression):
+    # 匹配log(x,b)的正则表达式
+    pattern = r'log\((\w+),(\w+)\)'
+    match = re.match(pattern, expression)
+    if match:
+        x = match.group(1)
+        b = match.group(2)
+        # 构造新表达式
+        new_expression = f'(np.log({x}) + 1e-5) / (np.log({b}) + 1e-5)'
+        return new_expression
+    else:
+        return None
+
+def convert_e(expression):
+    new_expression = 'np.exp'+expression[2:]
+    return new_expression
+
+def convert_trigonometric(expression):
+    # 构造新表达式
+    new_expression = 'np.'+expression
+    return new_expression
+
+def convert_x(expression):
+    # 匹配log(x,b)的正则表达式
+    pattern = r'(\w+)\^(\w+)'
+    match = re.match(pattern, expression)
+    if match:
+        base = match.group(1)
+        exponent = match.group(2)
+        # 构造新表达式
+        new_expression = f'np.power({base}, {exponent})'
+        return new_expression
+    else:
+        return None
+def remove_inner_spaces(expression):
+    # 匹配括号内的空格的正则表达式
+    pattern = r'\((.*?)\)'
+    # 替换匹配到的括号内的空格
+    new_expression = re.sub(pattern, lambda match: '(' + match.group(1).replace(' ', '') + ')', expression)
+    return new_expression
+
+def add_spaces(expression):
+    # 匹配运算符的正则表达式
+    pattern = r'([+\-*/])'
+    # 替换匹配到的运算符
+    new_expression = re.sub(pattern, r' \1 ', expression)
+    return new_expression
+
+def find_letter_index(string):
+    pattern = r'([a-zA-Z])x\b'
+    matches = re.findall(pattern, string)
+    # print(matches)
+    letter_indices = []
+    for i in range(len(string)):
+        if string[i] in matches:
+            if string[i+1]=='x':
+                letter_indices.append(i)
+    return letter_indices
+
+def expression_output(expression):
+    # 示例使用
+    modified_list = find_letter_index(expression)  # 将x前没有*的加上
+    index = 1
+    for i in modified_list:
+        expression = expression[0:index+i]+'*'+expression[index+i:]
+        index += 1
+    # print(expression)
+    expression = add_spaces(expression)
+    new_expression = remove_inner_spaces(expression)
+    list_expression = new_expression.split(' ')
+    conforms = ['e^', 'log', 'sin', 'cos', 'tan', '^']
+    new_list = []
+    for expres in list_expression:
+        new_list.append(expres)
+        for i in range(6):
+            if conforms[i] in expres:
+                index = list_expression.index(expres)
+                if i == 0:
+                    list_expression[index] = convert_e(expres)
+                elif i == 1:
+                    list_expression[index] = convert_log(expres)
+                elif i == 5:
+                    list_expression[index] = convert_x(expres)
+                else:
+                    list_expression[index] = convert_trigonometric(expres)
+                new_list[-1] = new_list[-1].replace(conforms[i], "")
+                break
+    new_list = [char for item in new_list for char in item if char.isalpha()]
+    parameter ='x,'
+    for item in new_list:
+        if item not in parameter and item != 'x':
+            parameter = parameter+item+','
+    for item in new_list:
+        if item not in parameter:
+            parameter = parameter+item+','
+    str_expression = ''
+    for item in list_expression:
+        str_expression = str_expression + item
+    if len(parameter[:-1]) > 1:
+        return parameter[:-1], str_expression
+    else:
+        return None, None

newly_added/functions.py

@@ -0,0 +1,144 @@
+import tkinter as tk
+from tkinter import messagebox
+from collections import OrderedDict
+from mpl_toolkits import axisartist
+from sympy import sympify, SympifyError
+from scipy.optimize import curve_fit
+from tkinter import filedialog
+import numpy as np
+import matplotlib.pyplot as plt
+
+from formula import expression_output
+
+index = 1
+
+def check_formula_syntax(formula):
+    try:
+        sympify(formula)
+        return True
+    except SympifyError:
+        return False
+# 创建弹出窗口
+def creat_window(title):
+    top = tk.Toplevel(Root)
+    top.geometry("300x350")
+    top.title(title)
+    return top
+
+
+# 输入框
+def create_input_box(top, text, value):
+    box_label = tk.Label(top, text=text)
+    box_label.pack(padx=10, pady=10)
+    box_size = tk.IntVar(top, value=value)  # 创建一个IntVar对象，并设置默认值为3
+    box_size_entry = tk.Entry(top, textvariable=box_size)  # 关联IntVar对象
+    box_size_entry.pack(padx=20, pady=20)
+    return box_size_entry
+
+
+def askfile():# 从本地选择一个文件，并返回文件的路径
+    global sampleData
+    # 弹出文件选择对话框，选择要打开的文本文件
+    file_path = filedialog.askopenfilename(filetypes=[('Text Files', '*.txt')])
+
+    # 如果没有选择文件，直接返回
+    if not file_path:
+        return
+    x, y = [], []#初始化x，y
+    with open(file_path, 'r') as file:
+        for line in file:#逐行读文件
+            line = line.strip('\n')#移除换行符
+            sx, sy = line.split(' ')#以空格分割x，y
+            x.append(float(sx))#将sx转换为浮点数并加入数组
+            y.append(float(sy))#将sy转换为浮点数并加入数组
+    X, Y = np.array(x), np.array(y)#x，y数组转为array并赋值给全局变量
+    sampleData.append(X)
+    sampleData.append(Y)
+    print(sampleData)
+
+
+def create_func(code_str):
+    # 创建一个空的命名空间
+    namespace = {}
+    # 使用exec函数执行字符串代码，并指定命名空间为locals
+    exec(code_str, globals(), namespace)
+    # 返回命名空间中的函数对象
+    return namespace['func']
+def draw_axis(low, high, step=250):
+    fig = plt.figure(figsize=(4.4, 3.2))
+    ax = axisartist.Subplot(fig, 111)# 使用axisartist.Subplot方法创建一个绘图区对象ax
+    fig.add_axes(ax)# 将绘图区对象添加到画布中
+    ax.axis[:].set_visible(False)# 通过set_visible方法设置绘图区所有坐标轴隐藏
+    ax.axis["x"] = ax.new_floating_axis(0, 0)# 添加新的x坐标轴
+    ax.axis["x"].set_axisline_style("-|>", size=1.0)# 给x坐标轴加上箭头
+    ax.axis["y"] = ax.new_floating_axis(1, 0)# 添加新的y坐标轴
+    ax.axis["y"].set_axisline_style("-|>", size=1.0)# y坐标轴加上箭头
+    ax.axis["x"].set_axis_direction("bottom")# 设置x、y轴上刻度显示方向
+    ax.axis["y"].set_axis_direction("left")# 设置x、y轴上刻度显示方向
+    plt.xlim(low, high)  # 把x轴的刻度范围设置
+    plt.ylim(low, high) # 把y轴的刻度范围设置
+    ax.set_xticks(np.arange(low, high + 5, step))# 把x轴的刻度间隔设置
+    ax.set_yticks(np.arange(low, high + 5, step))# 把y轴的刻度间隔设置
+def fitting():
+    global letters
+    askfile()
+    letters, result=expression_output(result2)
+    # print(letters,result)
+    # 定义要转换的字符串
+    code_str = '''
+def func({}):
+    return {}
+    '''.format(letters,result)
+    # print(code_str)
+    my_func = create_func(code_str)
+    popt, pcov = curve_fit(my_func, sampleData[0], sampleData[1])# 用curve_fit来对点进行拟合
+    draw_axis(-1000, 1000)  # 绘制坐标轴
+    positive_mask = sampleData[0] >= 0.0#给样本点分类
+    negative_mask = sampleData[1] < 0.0#给样本点分类
+    positive_colors = ['red' if x >= 0.0 else 'blue' for x in sampleData[0]]#给样本点分类
+    negative_colors = ['green' if x >= 0.0 else 'purple' for x in sampleData[0]]#给样本点分类
+    #根据样本点类型决定样本点颜色
+    plt.scatter(sampleData[0][positive_mask], sampleData[1][positive_mask], color=np.array(positive_colors)[positive_mask], lw=1)
+    plt.scatter(sampleData[0][negative_mask], sampleData[1][negative_mask], color=np.array(negative_colors)[negative_mask], lw=1)
+    curve_x = np.arange(-1000, 1000)#按照步长生成的一串数字
+    curve_y = [my_func(i, * popt) for i in curve_x]# 根据x来计算y1值
+    plt.plot(curve_x, curve_y, color='blue', label='Fitted Curve')#绘制拟合曲线
+    plt.savefig(r"dot5.png", facecolor='w')  # 保存到本地
+    plt.legend()
+    plt.show()
+
+def add():
+    top = creat_window('新增拟合函数')  # 创建弹出窗口
+    function_entry = create_input_box(top, "拟合函数名称：", '')  # 创建一个输入框，获取拟合函数名称
+    math_entry = create_input_box(top, "数学式：", '')  # 创建一个输入框，获取数学式
+    def get_input():  # 创建
+        # 获取输入框的内容
+        global result1, result2
+        result1 = function_entry.get()
+        result2 = math_entry.get()
+        if result1 and result2:
+            if check_formula_syntax(result2):
+                top.destroy()  # 关闭窗口
+                # fitting()
+                letters, result = expression_output(result2)
+                print(letters)
+                print(result)
+            else:
+                messagebox.showinfo('提示', '你输入的数学公式错误！')
+        else:
+            messagebox.showinfo('提示','你未输入的完成！')
+
+    button = tk.Button(top, text="确定", command=get_input)
+    button.pack()
+
+if __name__ == '__main__':
+    # 创建一个二维数组sampleData，用于存储样本数据
+    sampleData = []
+    Root = tk.Tk()
+    window_width = 400  # 窗口的宽度
+    window_height = 350  # 窗口的高度
+    Root.title("函数拟合")
+    Root.geometry("400x350")  # 设置窗口的大小和位置
+    button = tk.Button(Root,text='新增拟合函数',bg='blue',command=add)
+    button.place(x=250,y=10)
+    Root.mainloop()