函数 chart() 中的 result_dict 变量没有被赋值，如何实现

要实现在函数 `chart()` 中使用 `result_dict` 变量，需要在函数 `button_click()` 中生成 `result_dict` 并将其传递给函数 `chart()`。可以将 `result_dict` 定义为全局变量，并在 `button_click()` 函数中赋值，然后在 `chart()` 函数中使用即可。

以下是修改后的代码示例：

import tkinter as tk 
from sklearn.neighbors import KNeighborsClassifier 
from sklearn.model_selection import train_test_split 
import numpy as np 
import pandas as pd 
import matplotlib.pyplot as plt 
from matplotlib.figure import Figure 
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg 

seeds = pd.read_csv("seed2.csv", sep='\t', header=None) 
X = seeds.iloc[:, :7].copy() 
y = seeds.iloc[:, -1].copy() 

global result_dict 

def knn_score(k, X, y): 
    # 构造算法对象 
    knn = KNeighborsClassifier(n_neighbors=k) 
    scores = [] 
    train_scores = [] 
    random = NIrandom_state.get() 
    global test_size 
    for i in range(100): 
        # 拆分 
        if random_state != "": 
            X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test, random_state=random) 
        else: 
            X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test) 
        # 训练 
        knn.fit(X_train, y_train) 
        # 评价模型 
        scores.append(knn.score(X_test, y_test)) 
        # 经验评分 
        train_scores.append(knn.score(X_train, y_train)) 
    return np.array(scores).mean(), np.array(train_scores).mean() 

def root4(): 
    root4 = tk.Toplevel() 
    # 建立顶层控件wind 
    root4.geometry("800x600") 
    # 设置窗口大小 
    root4.title("测试集与训练集划分") 
    # 设置窗口标题 
    label1 = tk.Label(root4, text="测试集与训练集划分", font=("Arial", 16)) 
    label1.pack() 
    global NIrandom_state, NItest_size 
    NIrandom_state = tk.IntVar() 
    tk.Label(root4, text="random_state:").place(x=50, y=50) 
    tk.Entry(root4, textvariable=NIrandom_state).place(x=190, y=50) 
    NItest_size = tk.DoubleVar() 
    tk.Label(root4, text="用于测试的数据集比例:").place(x=50, y=110) 
    tk.Entry(root4, textvariable=NItest_size).place(x=190, y=110) 
    # 添加按钮 
    global button1, button2 
    button1 = tk.Button(root4, text="运算", font=("Arial", 12), command=button_click) 
    button1.place(x=50, y=150) 
    button2 = tk.Button(root4, text="图表展示", font=("Arial", 12), command=chart) 
    button2.place(x=200, y=150) 
    # 添加文本框 
    global text1 
    text1 = tk.Text(root4, width=50, height=10) 
    text1.place(x=50, y=200) 

def button_click(): 
    global test, random, result_dict 
    random = int(NIrandom_state.get()) 
    test = float(NItest_size.get()) 
    result_dict = {} 
    k_list = [1, 3, 5, 7, 9, 11] 
    for k in k_list: 
        score, train_score = knn_score(k, X, y) 
        result_dict[k] = [score, train_score] 
    result = pd.DataFrame(result_dict).T.copy() 
    result.columns = ['Test', 'Train'] 
    text = tk.Text(root4) 
    text.place(x=100, y=220) 
    text.insert("end", str(X_train)) 
    text.insert("end", str(X_test)) 
    text.insert("end", str(y_train)) 
    text.insert("end", str(y_test)) 
    text1.delete(1.0, tk.END) 
    text1.insert(tk.END, str(result)) 

def chart(): 
    root5 = tk.Toplevel() 
    root5.title("结果图形") 
    fig = Figure() 
    ax = fig.add_subplot(111) 
    k_list = [1, 3, 5, 7, 9, 11] 
    global result_dict 
    result = pd.DataFrame(result_dict).T.copy() 
    result.columns = ['Test', 'Train'] 
    result.plot(kind='line', ax=ax) 
    ax.set_xticks(k_list) 
    canvas = FigureCanvasTkAgg(fig, master=root5) 
    canvas.get_tk_widget().pack() 
    canvas.draw() 

root4()

在这个修改后的代码中，`result_dict` 变量定义为全局变量，并在 `button_click()` 函数中生成和赋值，然后在 `chart()` 函数中使用。在 `chart()` 函数中，将 `result_dict` 转换为 `DataFrame` 对象，并通过 `plot` 方法将结果绘制在 `Figure` 对象上。最后，将 `FigureCanvasTkAgg` 对象插入到 `Toplevel` 窗口中，就可以显示结果图形了。