本文主要介绍了Pyqt+matplotlib 实现实时画图案例,具有很好的参考价值,希望对大家有所帮助。
需求分析:
项目中根据测得的数据在界面上实时绘制
运行环境:
Python 3.7 + Matplotlib 3.0.2 + PyQt 5
matplot官网给的相应的例子:
import sys
import time
import numpy as np
from matplotlib.backends.qt_compat import QtCore, QtWidgets, is_pyqt5
if is_pyqt5():
from matplotlib.backends.backend_qt5agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
else:
from matplotlib.backends.backend_qt4agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
from matplotlib.figure import Figure
class ApplicationWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
self._main = QtWidgets.QWidget()
self.setCentralWidget(self._main)
layout = QtWidgets.QVBoxLayout(self._main)
static_canvas = FigureCanvas(Figure(figsize=(5, 3)))
layout.addWidget(static_canvas)
self.addToolBar(NavigationToolbar(static_canvas, self))
dynamic_canvas = FigureCanvas(Figure(figsize=(5, 3)))
layout.addWidget(dynamic_canvas)
self.addToolBar(QtCore.Qt.BottomToolBarArea,
NavigationToolbar(dynamic_canvas, self))
self._static_ax = static_canvas.figure.subplots()
t = np.linspace(0, 10, 501)
self._static_ax.plot(t, np.tan(t), ".")
self._dynamic_ax = dynamic_canvas.figure.subplots()
self._timer = dynamic_canvas.new_timer(
100, [(self._update_canvas, (), {})])
self._timer.start()
def _update_canvas(self):
self._dynamic_ax.clear()
t = np.linspace(0, 10, 101)
# Shift the sinusoid as a function of time.
self._dynamic_ax.plot(t, np.sin(t + time.time()))
self._dynamic_ax.figure.canvas.draw()
if __name__ == "__main__":
qapp = QtWidgets.QApplication(sys.argv)
app = ApplicationWindow()
app.show()
qapp.exec_()
上图中的散点为静止的,下面的图为动态的,类似行波,一直在行走,是应为用了self._dynamic_ax.plot(t, np.sin(t + time.time()))
函数,但是这个和我想得实时画图不太一样,在项目中要根据生成的数据实时绘图,因此x轴的元素和y轴的元素个数是逐渐增加的。
通过阅读上述 _update_canvas 函数代码以及 dynamic_canvas.new_timer 可以使得每次调用_update_canvas是的相应的x的元素和y轴的元素增加更改后的代码如下:
import sys
import time
import numpy as np
from matplotlib.backends.qt_compat import QtCore, QtWidgets, is_pyqt5
if is_pyqt5():
from matplotlib.backends.backend_qt5agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
else:
from matplotlib.backends.backend_qt4agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
from matplotlib.figure import Figure
class ApplicationWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
self._main = QtWidgets.QWidget()
self.setCentralWidget(self._main)
layout = QtWidgets.QVBoxLayout(self._main)
static_canvas = FigureCanvas(Figure(figsize=(5, 3)))
layout.addWidget(static_canvas)
self.addToolBar(NavigationToolbar(static_canvas, self))
dynamic_canvas = FigureCanvas(Figure(figsize=(5, 3)))
layout.addWidget(dynamic_canvas)
self.addToolBar(QtCore.Qt.BottomToolBarArea,
NavigationToolbar(dynamic_canvas, self))
self._static_ax = static_canvas.figure.subplots()
t = np.linspace(0, 10, 501)
self._static_ax.plot(t, np.tan(t), ".")
self.x = [] #建立空的x轴数组和y轴数组
self.y = []
self.n = 0
self._dynamic_ax = dynamic_canvas.figure.subplots()
self._timer = dynamic_canvas.new_timer(
100, [(self._update_canvas, (), {})])
self._timer.start()
def _update_canvas(self):
self.n += 1
if self.n == 200: #画200个点就停止,根据实际情况确定终止条件
self._timer.stop()
self._dynamic_ax.clear()
self.x.append(np.pi/100*self.n) #x加入一个值,后一个值比前一个大pi/100
xx = np.array(self.x)
# t = np.linspace(0, 10, 101)
# Shift the sinusoid as a function of time.
self._dynamic_ax.plot(xx, np.sin(xx))
self._dynamic_ax.set_xlim(0,7)
self._dynamic_ax.set_ylim(-1,1)
self._dynamic_ax.figure.canvas.draw()
if __name__ == "__main__":
qapp = QtWidgets.QApplication(sys.argv)
app = ApplicationWindow()
app.show()
qapp.exec_()
上面的图仍然静止,下面的可以实时显示
pyqtgraph实时绘图时,会概率出现无法实时刷新绘制图,原因是
while True:
......
update() # 通过 plotitem.setData()更新数据
......
这里使用的是while循环,不断的更新数据概率出现绘图不刷新和操作不响应(最小化操作会高概率出现该问题)
解决方法1:
我使用的是PlotWidget,remove后再addwidget,然后再重新绘制
解决方法2:
不使用while循环,使用QTime定时器
t = QTimer()
t.timeout.connect(self.update)
t.start(10)
两种方法都可以解决这个问题,推荐方法2
据说使用while循环,需要在更新数据之后调用pg.QtGui.QApplication.processEvents()才能确保正常,这个本人试了不行,可能是我这边的原因吧
以上为个人经验,希望能给大家一个参考,也希望大家多多支持脚本之家。如有错误或未考虑完全的地方,望不吝赐教。