Pycharm SciView 截断历史记录

Question

我正在尝试创建一个可以实时可视化投资组合变化的程序。为此，我更新了我的数据并用它创建了一个新图。当我在 PyCharm 中运行下面的代码时，SciView 在 30 次迭代后停止显示绘图。理想情况下，我希望它只显示最近的情节，但如果它只是截断历史，这样我至少总是能看到当前的情节，那也没关系。有没有办法做到这一点？我尝试了不同的方法来关闭数字（例如使用 plt.close()），但没有达到预期的结果。

重现代码：

import matplotlib.pyplot as plt
import numpy as np
import random


class RealTimeVisualizer:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def update_data(self, x_value, y_value):
        """
        Appends values to the data arrays.
        """
        self.x.append(x_value)
        self.y.append(y_value)

    def create_plot(self):
        """
        Takes an x and a y (both 1D arrays and constructs a plot from it)
        :return: a pyplot figure object
        """
        fig = plt.figure()
        ax = fig.add_subplot(1, 1, 1)

        # Draw x and y lists
        ax.clear()
        ax.plot(self.x, self.y)

        # Format plot
        plt.xticks(rotation=90)
        plt.title('Portfolio')
        plt.ylabel('Value')
        plt.show()
        plt.close('all')


if __name__ == '__main__':
    portfolio_cash = 10000
    tick = 0
    real_time_visualizer = RealTimeVisualizer([tick], [portfolio_cash])
    for i in np.arange(50):
        tick += 1
        portfolio_cash += random.randint(-50, 50)
        real_time_visualizer.update_data(tick, portfolio_cash)
        real_time_visualizer.create_plot()

Answer 1

不是每次都创建一个新的绘图和窗口，您还可以在每次迭代中更新当前的 Matplotlib 图形数据。然后您需要在交互式 Matplotlib 环境中查看绘图。

实时更新 Matplotlib 图

您可以使用与此类似的代码来更新图中的数据：

import matplotlib.pyplot as plt
import random

plt.ion()  # Set pyplot to interactive mode
fig = plt.figure()  # Create a figure
ax = fig.add_subplot(111)  # Add a subplot to the figure

# Variables for our updating data
x = []
y = []

for i in range(50):
    # Generate random data
    x.append(i)
    y.append(random.random())

    # Update the plot with the new x, y data
    ax.plot(x, y, 'ro-')
    fig.canvas.draw()
    fig.canvas.flush_events()

在使用 SciView 时允许交互式 Matplotlib 模式

停用 SciView 或手动将后端设置为另一个交互式 GUI 以查看更新图。 这段代码会自动选择正确的后端（与 Matplotlib code 中的列表相同）：

import matplotlib.pyplot as plt

candidates = ["macosx", "qt5agg", "gtk3agg", "tkagg", "wxagg"]
for candidate in candidates:
    try:
        plt.switch_backend(candidate)
        print('Using backend: ' + candidate)
        break
    except (ImportError, ModuleNotFoundError):
        pass

---

应用于您的代码

带有建议修改的代码如下所示：

import matplotlib.pyplot as plt
import numpy as np
import random


class RealTimeVisualizer:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def update_data(self, x_value, y_value):
        """
        Appends values to the data arrays.
        """
        self.x.append(x_value)
        self.y.append(y_value)

    def update_plot(self, fig, ax):
        import _tkinter
        try:
            ax.plot(self.x, self.y, 'ro-')
            fig.canvas.draw()
            fig.canvas.flush_events()
        # Capture an error in case the plotting window is being closed
        except _tkinter.TclError:
            pass


if __name__ == '__main__':
    portfolio_cash = 10000
    tick = 0
    real_time_visualizer = RealTimeVisualizer([tick], [portfolio_cash])

    # Choose the right backend
    candidates = ["macosx", "qt5agg", "gtk3agg", "tkagg", "wxagg"]
    for candidate in candidates:
        try:
            plt.switch_backend(candidate)
            print('Using backend: ' + candidate)
            break
        except (ImportError, ModuleNotFoundError):
            pass

    # Create plot
    plt.ion()  # Set pyplot to interactive mode
    fig = plt.figure()  # Create a figure
    ax = fig.add_subplot(111)  # Add a subplot to the figure

    for i in np.arange(50):
        tick += 1
        portfolio_cash += random.randint(-50, 50)
        real_time_visualizer.update_data(tick, portfolio_cash)
        real_time_visualizer.update_plot(fig, ax)  # Update the plot the new data