使用PyQt5和pyhton，从类MonitoringCPUResources接收参数x和y的列表，要求绘制实时更新的曲线

可以使用PyQtGraph库来实现实时更新的曲线绘制。具体实现步骤如下：

1. 安装PyQtGraph库

可以使用pip安装：

pip install pyqtgraph

2. 导入库

import pyqtgraph as pg
from pyqtgraph.Qt import QtGui, QtCore

3. 创建应用程序对象和主窗口

app = QtGui.QApplication([])
win = pg.GraphicsWindow(title="Real-time plot")
win.resize(800, 600)
win.setWindowTitle('Real-time plot')

4. 创建图形对象和曲线对象

p = win.addPlot(title="Real-time plot")
curve = p.plot(pen='y')

5. 定义更新曲线的函数

def update():
    global curve, data, ptr
    curve.setData(data)
    ptr += 1

6. 创建定时器并启动

timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)

7. 在类MonitoringCPUResources中接收参数x和y的列表，并更新data变量

class MonitoringCPUResources:
    def __init__(self):
        self.x = []
        self.y = []
        self.data = []
    
    def receive_data(self, x, y):
        self.x.append(x)
        self.y.append(y)
        self.data = np.column_stack((self.x, self.y))

完整代码如下：

import pyqtgraph as pg
from pyqtgraph.Qt import QtGui, QtCore
import numpy as np

class MonitoringCPUResources:
    def __init__(self):
        self.x = []
        self.y = []
        self.data = []
    
    def receive_data(self, x, y):
        self.x.append(x)
        self.y.append(y)
        self.data = np.column_stack((self.x, self.y))

def start_gui():
    app = QtGui.QApplication([])
    win = pg.GraphicsWindow(title="Real-time plot")
    win.resize(800, 600)
    win.setWindowTitle('Real-time plot')
    
    p = win.addPlot(title="Real-time plot")
    curve = p.plot(pen='y')
    
    def update():
        global curve, data, ptr
        curve.setData(data)
        ptr += 1
    
    timer = QtCore.QTimer()
    timer.timeout.connect(update)
    timer.start(50)
    
    monitor = MonitoringCPUResources()
    
    def receive_data(x, y):
        monitor.receive_data(x, y)
    
    return app, win, monitor, receive_data

if __name__ == '__main__':
    app, win, monitor, receive_data = start_gui()
    
    # 模拟数据
    ptr = 0
    data = np.random.normal(size=(10,2))
    
    # 模拟更新数据
    for i in range(1000):
        x = i
        y = np.random.normal()
        receive_data(x, y)
        app.processEvents()
        data = monitor.data