使用matplotlib或pyqtgraph绘制实时数据图 [英] using matplotlib or pyqtgraph to graph real time data

问题描述

我有连接到串行端口的设备，我需要轮询它们，然后在绘图中显示该数据.我目前正在使用matplotlib进行此工作(缓慢).我最多可以连接64个设备，每个设备可以更新20个数据.我进行了设置，以便可以创建一个新窗口，并可以添加一段数据以进行绘制.随着其他每个打开的绘图窗口的打开，我的更新速度会大大降低.
我已经尝试在matplotlib中使用blit动画，但是它并不是真正的平滑，我可以在更新中看到异常情况.我已经尝试过PyQtGraph，但是找不到有关如何使用此软件包的任何文档，现在我正在尝试PyQwt，但是无法安装它(主要是因为我的公司不允许我们安装将处理.gz文件). 任何想法或建议，将不胜感激.

I have devices connected to my serial port and I need to poll them and then display that data in a plot. I currently have this working (slowly) using matplotlib. I could have up to 64 devices connected and each device could have 20 pieces of data to update. I've set it up so that a new window can be created and a piece of data can be added to be plotted. With each additional plotting window that is opened my update rate slows considerably.
I've tried using blit animation in matplotlib, but it's not real smooth and I can see anomolies in the update. I've tried PyQtGraph, but can't find any documentation on how to use this package, and now I'm trying PyQwt, but can't get it installed (mostly because my company won't let us install a package that will handle a .gz file). Any ideas or suggestions would be greatly appreciated.

import sys
from PyQt4.QtCore import (Qt, QModelIndex, QObject, SIGNAL, SLOT, QTimer, QThread,  QSize, QString, QVariant)
from PyQt4 import QtGui

from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from plot_toolbar import NavigationToolbar2QT as NavigationToolbar
import matplotlib.dates as md
import psutil as p
import time
import datetime as dt
import string
import ui_plotting
import pickle

try:
  _fromUtf8 = QString.fromUtf8
except AttributeError:
  _fromUtf8 = lambda s: s

class Monitor(FigureCanvas):
"""Plot widget to display real time graphs"""
  def __init__(self, timenum):
    self.timenum=timenum
    self.main_frame = QtGui.QWidget()
    self.timeTemp1 = 0
    self.timeTemp2 = 0
    self.temp = 1
    self.placeHolder = []
    self.y_max = 0
    self.y_min = 100

# initialization of the canvas
#        self.dpi = 100
#        self.fig = Figure((5.0, 4.0), dpi=self.dpi)
    self.fig = Figure()
    FigureCanvas.__init__(self, self.fig)
#        self.canvas = FigureCanvas(self.fig)
#        self.canvas.setParent(self.main_frame)
# first image setup
#        self.fig = Figure()
#        self.fig.subplots_adjust(bottom=0.5)
    self.ax = self.fig.add_subplot(111)
    self.mpl_toolbar = NavigationToolbar(self.fig.canvas, self.main_frame,False)
    self.mpl_toolbar.setFixedHeight(24)

# set specific limits for X and Y axes
#        now=dt.datetime.fromtimestamp(time.mktime(time.localtime()))       
#        self.timenum = now.strftime("%H:%M:%S.%f")
    self.timeSec = 0      
    self.x_lim = 100
    self.ax.set_xlim(0, self.x_lim)
    self.ax.set_ylim(0, 100)
    self.ax.get_xaxis().grid(True)
    self.ax.get_yaxis().grid(True)
# and disable figure-wide autoscale
    self.ax.set_autoscale_on(False)
    self.ax.set_xlabel('Time in Seconds')
# generates first "empty" plots
    self.timeb = []
    self.user = []
    self.l_user = []
    self.l_user = [[] for x in xrange(50)]
    for i in range(50):
        self.l_user[i], = self.ax.plot(0,0)


# add legend to plot
#        self.ax.legend()


def addTime(self,t1,t2):
    timeStamp = t1+"000"
#   print "timeStamp",timeStamp
    timeStamp2 = t2+"000"
    test = string.split(timeStamp,":")
    test2 = string.split(test[2],".")        
    testa = string.split(timeStamp2,":")
    testa2 = string.split(testa[2],".")

    sub1 = int(testa[0])-int(test[0])
    sub2 = int(testa[1])-int(test[1])
    sub3 = int(testa2[0])-int(test2[0])
    sub4 = int(testa2[1])-int(test2[1])

    testing = dt.timedelta(hours=sub1,minutes=sub2,seconds=sub3,microseconds=sub4)

    self.timeSec = testing.total_seconds()

def timerEvent(self, evt, timeStamp, val, lines):
    temp_min = 0
    temp_max = 0
# Add user arrays for each user_l array used, don't reuse user arrays
    if self.y_max<max(map(float, val)):
        self.y_max = max(map(float, val))
    if self.y_min>min(map(float, val)):
        self.y_min = min(map(float, val))            
#       print "val: ",val
    if lines[len(lines)-1]+1 > len(self.user):
        for k in range((lines[len(lines)-1]+1)-len(self.user)):
            self.user.append([])


# append new data to the datasets
#        print "timenum=",self.timenum
    self.addTime(self.timenum, timeStamp)
    self.timeb.append(self.timeSec)
    for j in range((lines[len(lines)-1]+1)):
        if j >49:
            break
        if j not in lines:
            del self.user[j][:]
            self.user[j].extend(self.placeHolder)
            self.user[j].append(0)
        else:
            if len(self.timeb) > (len(self.user[j])+1):
                self.user[j].extend(self.placeHolder)
            self.user[j].append(str(val[lines.index(j)])) 

    for i in range(len(lines)):
        if i>49:
            break
        self.l_user[lines[i]].set_data(self.timeb, self.user[lines[i]])
# force a redraw of the Figure

#        if self.y_max < 2:
#            self.y_max = 2
#        if self.y_min < 2:
#            self.y_min = 0 
    if self.y_min > -.1 and self.y_max < .1:            
        temp_min = -1
        temp_max = 1
    else:
        temp_min = self.y_min-(self.y_min/10)
        temp_max = self.y_max+(self.y_max/10)


    self.ax.set_ylim(temp_min, temp_max)
    if self.timeSec >= self.x_lim:
        if str(self.x_lim)[0]=='2':
            self.x_lim = self.x_lim * 2.5
        else:
            self.x_lim = self.x_lim * 2
        self.ax.set_xlim(0, self.x_lim)
#        self.fig.canvas.restore_region(self.fig.canvas)
#        self.ax.draw_artist(self.l_user[lines[0]])
#        self.fig.canvas.blit(self.ax.bbox)
    self.fig.canvas.draw()

#        self.draw()

    self.placeHolder.append(None)

class List(QtGui.QListWidget):

  def __init__(self, parent):
    super(List, self).__init__(parent)

    font = QtGui.QFont()
    font.setFamily(_fromUtf8("Century Gothic"))
    font.setPointSize(7)
    self.setFont(font)
    self.setDragDropMode(4)
    self.setAcceptDrops(True)
    self.row = []
    self.col = []
    self.disName = []
    self.lines = []
    self.counter = 0
    self.setStyleSheet("background-color:#DDDDDD")
    self.colors = ["blue", "green", "red", "deeppink", "black", "slategray", "sienna", "goldenrod", "teal", "orange", "orchid", "lightskyblue", "navy", "darkgreen", "indigo", "firebrick", "deepskyblue", "lightskyblue", "darkseagreen", "gold"]

def dragEnterEvent(self, e):
    if e.mimeData().hasFormat("application/x-qabstractitemmodeldatalist"):
#            print "currentRow : ", self.currentRow()
#            print "self.col: ", self.col
#            print "self.row: ", self.row
#            print "self.col[]: ", self.col.pop(self.currentRow())
#            print "self.row[]: ", self.row.pop(self.currentRow())

        self.col.pop(self.currentRow())
        self.row.pop(self.currentRow())
        self.disName.pop(self.currentRow())
        self.lines.pop(self.currentRow())
        self.takeItem(self.currentRow())
    if e.mimeData().hasFormat("application/pubmedrecord"):
        e.accept()
    else:
        e.ignore() 


def dropEvent(self, e):

    items = 0
    data = e.mimeData()
    bstream = data.retrieveData("application/pubmedrecord", QVariant.ByteArray)
    selected = pickle.loads(bstream.toByteArray())
    e.accept()
#        print selected
#        if self.count() != 0:
#            j = (self.lines[self.count()-1]%len(self.colors))+1

#        else:
#            j=0
    while items < len(selected):
        j=self.counter
        if j >= len(self.colors)-1:
            j = self.counter%len(self.colors)
        m = len(self.lines)
        self.lines.append(self.counter)
#            if m != 0:
#                n = self.lines[m-1]
#                self.lines.append(n+1)
#            else:
#                self.lines.append(0)
        self.col.append(str(selected[items]))
        items = items+1
        self.row.append(str(selected[items]))
        items = items+1
        self.disName.append(str(selected[items]))
        listItem = QtGui.QListWidgetItem()
        listItem.setText(str(selected[items]))

        listItem.setTextColor(QtGui.QColor(self.colors[j]))
        self.addItem(listItem)            
        items = items+1

        self.counter += 1
def dragLeaveEvent(self, event):
    event.accept()  


class PlotDlg(QtGui.QDialog):
  NextID = 0
  filename = 'Plot'
  def __init__(self,time, callback, parent=None):
    super(PlotDlg, self).__init__(parent)
    self.id = PlotDlg.NextID
    PlotDlg.NextID += 1
    self.callback = callback
    self.setWindowFlags(Qt.Window | Qt.WindowMinimizeButtonHint | Qt.WindowMaximizeButtonHint)
    self.setAttribute(Qt.WA_DeleteOnClose,True)
    self.value = []
    print "time=",time
    self.time = time
    self.dc = Monitor(self.time)
#        self.threadPool = []

    self.listWidget = List(self)
    sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.MinimumExpanding)
    sizePolicy.setHorizontalStretch(0)
    self.listWidget.setSizePolicy(sizePolicy)
    self.listWidget.setMaximumSize(QSize(150, 16777215))

    grid = QtGui.QGridLayout()
    grid.setSpacing(0)
    grid.setContentsMargins(0, 0, 0, 0)
    grid.addWidget(self.dc.mpl_toolbar,0,0,1,12)
    grid.addWidget(self.listWidget,1,1)
    grid.addWidget(self.dc,1,0)
    grid.setColumnMinimumWidth(1,110)

    self.setLayout(grid)

def update(self, clear=0):
    if clear == 1:
 now=dt.datetime.fromtimestamp(time.mktime(time.localtime()))                         
        self.dc.timenum = now.strftime("%H:%M:%S.%f") 

        self.dc.timeSec = 0
        self.dc.x_lim = 100
        self.dc.y_max = 0
        self.dc.y_min = 100            
        del self.dc.timeb[:]
        del self.dc.user[:]
        del self.dc.placeHolder[:]

#            del self.dc.l_user[:]
#            self.dc.l_user = [[] for x in xrange(50)]
#            for i in range(50):
#                self.dc.l_user[i], = self.dc.ax.plot(0,0)
        for i in range(50):
            self.dc.l_user[i].set_data(0, 0)

#            print self.dc.l_user
#            print self.dc.user

        self.dc.ax.set_xlim(0, self.dc.x_lim)
        self.dc.fig.canvas.draw()
#        print self.value
#        print str(self.time)
#        print "time:",str(self.time)
#        self.threadPool.append( GenericThread(self.dc.timerEvent,None, str(self.time), self.value, self.listWidget.lines) )
#        self.threadPool[len(self.threadPool)-1].start()

    self.dc.timerEvent(None, str(self.time), self.value, self.listWidget.lines) 

def closeEvent(self, event):
#        self.update(1)
    self.callback(self.id)
    PlotDlg.NextID -= 1

class GenericThread(QThread):
  def __init__(self, function, *args, **kwargs):
    QThread.__init__(self)
    self.function = function
    self.args = args
    self.kwargs = kwargs

  def __del__(self):
    self.wait()

  def run(self):
    self.function(*self.args,**self.kwargs)
    return 

推荐答案

我建议查科"...用于构建交互式和自定义二维图和可视化的程序包."它可以集成到Qt应用程序中，尽管您可能可以从PyQwt获得更高的帧速率.

I would suggest Chaco "... a package for building interactive and custom 2-D plots and visualizations." It can be integrated in Qt apps, though you can probably get higher frame rates from PyQwt.

我实际上已经用它编写了一个应用程序"(这个词太大了:它不太花哨，并且都适合〜200 LOC)，它可以从串行端口获取数据并绘制数据(超过20行) 20 fps，50 fps(15 fps)，笔记本电脑全屏显示).

I've actually used it to write an "app" (that's too big a word: it's not very fancy and it all fits in ~200 LOC) that gets data from a serial port and draws it (20 lines at over 20 fps, 50 at 15 fps, at full screen in my laptop).

Chaco文档或在线帮助不如matplotlib全面，但我想它会有所改进，无论如何对我来说已经足够了.

Chaco documentation or online help weren't as comprehensive as matplotlib's, but I guess it will have improved and at any rate it was enough for me.

作为一般建议，避免在每一帧绘制所有内容，即，在matplotlib和chaco中都使用.set_data方法.另外，在stackoverflow中，还有一些关于使matplotlib更快的问题.

As a general advice, avoid drawing everything at every frame, ie., use the .set_data methods in both matplotlib and chaco. Also, here in stackoverflow there are some questions about making matplotlib faster.

这篇关于使用matplotlib或pyqtgraph绘制实时数据图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！