pyqtgraph Scrolling Plots 曲线的滚动播放;
曲线的滚动播放;
pyqtgraph Scrolling Plots
# -*- coding: utf-8 -*-
"""
Various methods of drawing scrolling plots.
"""
import initExample ## Add path to library (just for examples; you do not need this)
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np
win = pg.GraphicsLayoutWidget(show=True)
win.setWindowTitle('pyqtgraph example: Scrolling Plots')
# 1) Simplest approach -- update data in the array such that plot appears to scroll
# In these examples, the array size is fixed.
p1 = win.addPlot()
p2 = win.addPlot()
data1 = np.random.normal(size=300)
curve1 = p1.plot(data1)
curve2 = p2.plot(data1)
ptr1 = 0
def update1():
global data1, ptr1
data1[:-1] = data1[1:] # shift data in the array one sample left
# (see also: np.roll)
data1[-1] = np.random.normal()
curve1.setData(data1)
ptr1 += 1
curve2.setData(data1)
curve2.setPos(ptr1, 0)
# 2) Allow data to accumulate. In these examples, the array doubles in length
# whenever it is full.
win.nextRow()
p3 = win.addPlot()
p4 = win.addPlot()
# Use automatic downsampling and clipping to reduce the drawing load
p3.setDownsampling(mode='peak')
p4.setDownsampling(mode='peak')
p3.setClipToView(True)
p4.setClipToView(True)
p3.setRange(xRange=[-100, 0])
p3.setLimits(xMax=0)
curve3 = p3.plot()
curve4 = p4.plot()
data3 = np.empty(100)
ptr3 = 0
def update2():
global data3, ptr3
data3[ptr3] = np.random.normal()
ptr3 += 1
if ptr3 >= data3.shape[0]:
tmp = data3
data3 = np.empty(data3.shape[0] * 2)
data3[:tmp.shape[0]] = tmp
curve3.setData(data3[:ptr3])
curve3.setPos(-ptr3, 0)
curve4.setData(data3[:ptr3])
# 3) Plot in chunks, adding one new plot curve for every 100 samples
chunkSize = 100
# Remove chunks after we have 10
maxChunks = 10
startTime = pg.ptime.time()
win.nextRow()
p5 = win.addPlot(colspan=2)
p5.setLabel('bottom', 'Time', 's')
p5.setXRange(-10, 0)
curves = []
data5 = np.empty((chunkSize+1,2))
ptr5 = 0
def update3():
global p5, data5, ptr5, curves
now = pg.ptime.time()
for c in curves:
c.setPos(-(now-startTime), 0)
i = ptr5 % chunkSize
if i == 0:
curve = p5.plot()
curves.append(curve)
last = data5[-1]
data5 = np.empty((chunkSize+1,2))
data5[0] = last
while len(curves) > maxChunks:
c = curves.pop(0)
p5.removeItem(c)
else:
curve = curves[-1]
data5[i+1,0] = now - startTime
data5[i+1,1] = np.random.normal()
curve.setData(x=data5[:i+2, 0], y=data5[:i+2, 1])
ptr5 += 1
# update all plots
def update():
update1()
update2()
update3()
timer = pg.QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)
## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
【推荐】国内首个AI IDE,深度理解中文开发场景,立即下载体验Trae
【推荐】编程新体验,更懂你的AI,立即体验豆包MarsCode编程助手
【推荐】抖音旗下AI助手豆包,你的智能百科全书,全免费不限次数
【推荐】轻量又高性能的 SSH 工具 IShell:AI 加持,快人一步
· .NET Core 中如何实现缓存的预热?
· 从 HTTP 原因短语缺失研究 HTTP/2 和 HTTP/3 的设计差异
· AI与.NET技术实操系列:向量存储与相似性搜索在 .NET 中的实现
· 基于Microsoft.Extensions.AI核心库实现RAG应用
· Linux系列:如何用heaptrack跟踪.NET程序的非托管内存泄露
· TypeScript + Deepseek 打造卜卦网站:技术与玄学的结合
· Manus的开源复刻OpenManus初探
· AI 智能体引爆开源社区「GitHub 热点速览」
· 三行代码完成国际化适配,妙~啊~
· .NET Core 中如何实现缓存的预热?