python - 如何使用 tkinter GUI 可视化 matplotlib 预测？

Question

我有一个场景，我对特定数据集进行了预测。现在我想使用 Tkinter 可视化该预测图。

我的机器学习模型如下所示，由图表组成:

# Importing Libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import sys

# Importing the Batsmen Dataset
dataset = pd.read_csv('Batsmen/Batsmen.csv')
X = dataset.iloc[:, [1, 2, 3, 4, 5, 6]].values

# Using Elbow Method to find the optimal number of Clusters
from sklearn.cluster import KMeans
wcss = []
for i in range(1, 11):
    kmeans = KMeans(n_clusters=i, init='k-means++', n_init=10, max_iter=300, random_state=0)
    kmeans.fit(X)
    wcss.append(kmeans.inertia_)
plt.plot(range(1, 11), wcss)
plt.title('The Elbow Method')
plt.xlabel('Number of Clusters')
plt.ylabel('WCSS')
plt.show()

我尝试了如下所示:

from tkinter import *

# these four imports are important
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure

def plot():
    # Importing Libraries
    import numpy as np
    import matplotlib.pyplot as plt
    import pandas as pd
    import sys

    # Importing the Batsmen Dataset
    dataset = pd.read_csv('Batsmen/Batsmen.csv')
    X = dataset.iloc[:, [1, 2, 3, 4, 5, 6]].values

    # Using Elbow Method to find the optimal number of Clusters
    from sklearn.cluster import KMeans
    wcss = []
    for i in range(1, 11):
        kmeans = KMeans(n_clusters=i, init='k-means++', n_init=10, max_iter=300, random_state=0)
        kmeans.fit(X)
        wcss.append(kmeans.inertia_)

root = Tk()

def app():
    # initialise a window.
    root = Tk()
    root.config(background='white')
    root.geometry("1000x700")

    lab = Label(root, text="Live Plotting", bg = 'white').pack()

    fig = Figure()

    ax = fig.add_subplot(111)
    ax.set_title('The Elbow Method')
    ax.set_xlabel('Number of Clusters')
    ax.set_ylabel('WCSS')
    ax.grid()

    graph = FigureCanvasTkAgg(fig, master=root)
    graph.get_tk_widget().pack(side="top",fill='both',expand=True)

def plotter():
    ax.cla()
    ax.grid()
    dpts = plot()
    ax.plot(range(1, 11), wcss, marker='o', color='orange')
    graph.draw()
    time.sleep(1)

def gui_handler():
    threading.Thread(target=plotter).start()

b = Button(root, text="Start/Stop", command=gui_handler, bg="red", fg="white")
b.pack()

root.mainloop()

if __name__ == '__main__':
    app()

但是它不起作用!

我只想在 Tkinter GUI 上显示预测，当我按下 GUI 中的预测按钮时，我希望图形显示在 GUI Canvas 内。那么，有人可以帮我做同样的事情吗？

Answer 1

如果我使用 root.after() 而不是线程，你的代码对我有用。

可能在大多数 GUI 框架中，线程应该(或不能)更改 GUI 中的元素。

在我的计算机上，当我按下运行线程的按钮时，带有线程的代码就会结束工作。

我运行plotter，它不使用while和sleep，而是使用after(1000，plotter)来1000ms(1s)后再次运行

from tkinter import *
from random import randint

# these two imports are important
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure

continuePlotting = False

def change_state():
    global continuePlotting
    if continuePlotting == True:
        continuePlotting = False
    else:
        continuePlotting = True


def data_points():
    f = open("data.txt", "w")
    for i in range(10):
        f.write(str(randint(0, 10))+'\n')
    f.close()

    f = open("data.txt", "r")
    data = f.readlines()
    f.close()

    l = []
    for i in range(len(data)):
        l.append(int(data[i].rstrip("\n")))
    return l

def app():
    # initialise a window.
    root = Tk()
    root.config(background='white')
    root.geometry("1000x700")

    lab = Label(root, text="Live Plotting", bg = 'white').pack()

    fig = Figure()

    ax = fig.add_subplot(111)
    ax.set_xlabel("X axis")
    ax.set_ylabel("Y axis")
    ax.grid()

    graph = FigureCanvasTkAgg(fig, master=root)
    graph.get_tk_widget().pack(side="top",fill='both',expand=True)

    def plotter():
        if continuePlotting:
            ax.cla()
            ax.grid()
            dpts = data_points()
            ax.plot(range(10), dpts, marker='o', color='orange')
            graph.draw()
            root.after(1000, plotter)

    def gui_handler():
        change_state()
        plotter()

    b = Button(root, text="Start/Stop", command=gui_handler, bg="red", fg="white")
    b.pack()

    root.mainloop()

if __name__ == '__main__':
    app()

<小时/>

编辑:在新代码中，您不会运行循环，因此不需要线程或 after()

但是您还有其他基本问题:

您的缩进错误，并且 mainloop() 位于 app() 之外 - 它在 app() 之前执行

在以前的版本中，plotter 位于 app() 内部 - 如果您在外部需要它，那么您就会遇到局部变量的问题 - 例如 ax -并且您必须使用 global 才能在其他函数中访问这些变量。或者你必须使用这个值作为参数来运行函数 - 即。 绘图仪(ax、wcss、图表)

这个版本使用global，它对我有用。我没有您的 CSV，并且不想运行 sklearn，因此我输入了一些虚假数据。

from tkinter import *

# these four imports are important
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure

def plot():
    # Importing Libraries
    import numpy as np
    import matplotlib.pyplot as plt
    import pandas as pd
    import sys

    # Importing the Batsmen Dataset
#    dataset = pd.read_csv('Batsmen/Batsmen.csv')
    dataset = pd.DataFrame({
        'a': range(10),
        'b': range(10),
        'c': range(10),
        'd': range(10),
        'e': range(10),
        'f': range(10),
        'g': range(10),
    })

    X = dataset.iloc[:, [1, 2, 3, 4, 5, 6]].values

    # Using Elbow Method to find the optimal number of Clusters
    from sklearn.cluster import KMeans

    global wcss
    wcss = range(1, 11)
    #wcss = []
#    for i in range(1, 11):
#        kmeans = KMeans(n_clusters=i, init='k-means++', n_init=10, max_iter=300, random_state=0)
#        kmeans.fit(X)
#        wcss.append(kmeans.inertia_)

def plotter():
    global wcss
    global ax
    global graph

    ax.cla()
    ax.grid()
    dpts = plot()
    ax.plot(range(1, 11), wcss, marker='o', color='orange')
    graph.draw()

def gui_handler():
    plotter()

def app():
    global ax
    global graph

    # initialise a window.
    root = Tk()
    root.config(background='white')
    root.geometry("1000x700")

    lab = Label(root, text="Live Plotting", bg = 'white').pack()

    fig = Figure()

    ax = fig.add_subplot(111)
    ax.set_title('The Elbow Method')
    ax.set_xlabel('Number of Clusters')
    ax.set_ylabel('WCSS')
    ax.grid()

    graph = FigureCanvasTkAgg(fig, master=root)
    graph.get_tk_widget().pack(side="top",fill='both',expand=True)

    b = Button(root, text="Start/Stop", command=gui_handler, bg="red", fg="white")
    b.pack()

    root.mainloop()

if __name__ == '__main__':
    app()