How do I plot in real-time in a while loop using matplotlib

Question

I am trying to plot some data from a camera in real time using OpenCV  However  the real-time plotting  using matplotlib  doesn t seem to be working   I ve isolated the problem into this simple example   fig   plt figure   plt axis  0  1000  0  1    i   0 x   list   y   list    while i  lt  1000      temp y   np random random       x append i      y append temp y      plt scatter i  temp y      i    1     plt show     I would expect this example to plot 1000 points individually  What actually happens is that the window pops up with the first point showing  ok with that   then waits for the loop to finish before it populates the rest of the graph   Any thoughts why I am not seeing points populated one at a time

User · Answer

show is probably not the best choice for this   What I would do is use pyplot draw   instead   You also might want to include a small time delay  e g   time sleep 0 05   in the loop so that you can see the plots happening   If I make these changes to your example it works for me and I see each point appearing one at a time

User · Answer

I know I m a bit late to answer this question  Nevertheless  I ve made some code a while ago to plot live graphs  that I would like to share   Code for PyQt4                                                                                                                                                                PLOT A LIVE GRAPH  PyQt4                                          -----------------------------                                 EMBED A MATPLOTLIB ANIMATION INSIDE YOUR                            OWN GUI                                                                                                                                                                                          import sys import os from PyQt4 import QtGui from PyQt4 import QtCore import functools import numpy as np import random as rd import matplotlib matplotlib use  Qt4Agg   from matplotlib figure import Figure from matplotlib animation import TimedAnimation from matplotlib lines import Line2D from matplotlib backends backend qt4agg import FigureCanvasQTAgg as FigureCanvas import time import threading   def setCustomSize x  width  height       sizePolicy   QtGui QSizePolicy QtGui QSizePolicy Fixed  QtGui QSizePolicy Fixed      sizePolicy setHorizontalStretch 0      sizePolicy setVerticalStretch 0      sizePolicy setHeightForWidth x sizePolicy   hasHeightForWidth        x setSizePolicy sizePolicy      x setMinimumSize QtCore QSize width  height       x setMaximumSize QtCore QSize width  height            class CustomMainWindow QtGui QMainWindow        def   init   self            super CustomMainWindow  self    init                Define the geometry of the main window         self setGeometry 300  300  800  400          self setWindowTitle  my first window              Create FRAME A         self FRAME A   QtGui QFrame self          self FRAME A setStyleSheet  QWidget   background-color   s      QtGui QColor 210 210 235 255  name            self LAYOUT A   QtGui QGridLayout           self FRAME A setLayout self LAYOUT A          self setCentralWidget self FRAME A             Place the zoom button         self zoomBtn   QtGui QPushButton text    zoom           setCustomSize self zoomBtn  100  50          self zoomBtn clicked connect self zoomBtnAction          self LAYOUT A addWidget self zoomBtn    0 0              Place the matplotlib figure         self myFig   CustomFigCanvas           self LAYOUT A addWidget self myFig    0 1              Add the callbackfunc to            myDataLoop   threading Thread name    myDataLoop   target   dataSendLoop  daemon   True  args    self addData callbackFunc            myDataLoop start            self show                     def zoomBtnAction self           print  zoom in           self myFig zoomIn 5                   def addData callbackFunc self  value             print  Add data      str value           self myFig addData value         End Class       class CustomFigCanvas FigureCanvas  TimedAnimation        def   init   self            self addedData              print matplotlib   version               The data         self xlim   200         self n   np linspace 0  self xlim - 1  self xlim          a              b              a append 2 0          a append 4 0          a append 2 0          b append 4 0          b append 3 0          b append 4 0          self y    self n   0 0    50            The window         self fig   Figure figsize  5 5   dpi 100          self ax1   self fig add subplot 111              self ax1 settings         self ax1 set xlabel  time           self ax1 set ylabel  raw data           self line1   Line2D         color  blue           self line1 tail   Line2D         color  red   linewidth 2          self line1 head   Line2D         color  red   marker  o   markeredgecolor  r           self ax1 add line self line1          self ax1 add line self line1 tail          self ax1 add line self line1 head          self ax1 set xlim 0  self xlim - 1          self ax1 set ylim 0  100            FigureCanvas   init   self  self fig          TimedAnimation   init   self  self fig  interval   50  blit   True       def new frame seq self           return iter range self n size        def  init draw self           lines    self line1  self line1 tail  self line1 head          for l in lines              l set data              def addData self  value           self addedData append value       def zoomIn self  value           bottom   self ax1 get ylim   0          top   self ax1 get ylim   1          bottom    value         top -  value         self ax1 set ylim bottom top          self draw         def  step self   args             Extends the  step   method for the TimedAnimation class          try              TimedAnimation  step self   args          except Exception as e              self abc    1             print str self abc               TimedAnimation  stop self              pass      def  draw frame self  framedata           margin   2         while len self addedData   gt  0               self y   np roll self y  -1              self y -1    self addedData 0              del self addedData 0             self line1 set data self n  0   self n size - margin    self y  0   self n size - margin            self line1 tail set data np append self n -10 -1 - margin   self n -1 - margin    np append self y -10 -1 - margin   self y -1 - margin            self line1 head set data self n -1 - margin   self y -1 - margin           self  drawn artists    self line1  self line1 tail  self line1 head       End Class        You need to setup a signal slot mechanism  to    send data to your GUI in a thread-safe way    Believe me  if you don t do this right  things   go very very wrong   class Communicate QtCore QObject       data signal   QtCore pyqtSignal float       End Class       def dataSendLoop addData callbackFunc         Setup the signal-slot mechanism      mySrc   Communicate       mySrc data signal connect addData callbackFunc         Simulate some data     n   np linspace 0  499  500      y   50   25  np sin n   8 3     10  np sin n   7 5   - 5  np sin n   1 5       i   0      while True           if i  gt  499               i   0         time sleep 0 1          mySrc data signal emit y i      lt - Here you emit a signal          i    1               if   name        main         app   QtGui QApplication sys argv      QtGui QApplication setStyle QtGui QStyleFactory create  Plastique        myGUI   CustomMainWindow       sys exit app exec                nbsp  I recently rewrote the code for PyQt5  Code for PyQt5                                                                                                                                                                PLOT A LIVE GRAPH  PyQt5                                          -----------------------------                                 EMBED A MATPLOTLIB ANIMATION INSIDE YOUR                            OWN GUI                                                                                                                                                                                         import sys import os from PyQt5 QtWidgets import   from PyQt5 QtCore import   from PyQt5 QtGui import   import functools import numpy as np import random as rd import matplotlib matplotlib use  Qt5Agg   from matplotlib figure import Figure from matplotlib animation import TimedAnimation from matplotlib lines import Line2D from matplotlib backends backend qt5agg import FigureCanvasQTAgg as FigureCanvas import time import threading  class CustomMainWindow QMainWindow       def   init   self           super CustomMainWindow  self    init               Define the geometry of the main window         self setGeometry 300  300  800  400          self setWindowTitle  my first window             Create FRAME A         self FRAME A   QFrame self          self FRAME A setStyleSheet  QWidget   background-color   s      QColor 210 210 235 255  name            self LAYOUT A   QGridLayout           self FRAME A setLayout self LAYOUT A          self setCentralWidget self FRAME A            Place the zoom button         self zoomBtn   QPushButton text    zoom           self zoomBtn setFixedSize 100  50          self zoomBtn clicked connect self zoomBtnAction          self LAYOUT A addWidget self zoomBtn    0 0             Place the matplotlib figure         self myFig   CustomFigCanvas           self LAYOUT A addWidget self myFig    0 1             Add the callbackfunc to            myDataLoop   threading Thread name    myDataLoop   target   dataSendLoop  daemon   True  args    self addData callbackFunc            myDataLoop start           self show           return      def zoomBtnAction self           print  zoom in           self myFig zoomIn 5          return      def addData callbackFunc self  value             print  Add data      str value           self myFig addData value          return      End Class       class CustomFigCanvas FigureCanvas  TimedAnimation       def   init   self           self addedData              print matplotlib   version              The data         self xlim   200         self n   np linspace 0  self xlim - 1  self xlim          a              b              a append 2 0          a append 4 0          a append 2 0          b append 4 0          b append 3 0          b append 4 0          self y    self n   0 0    50           The window         self fig   Figure figsize  5 5   dpi 100          self ax1   self fig add subplot 111            self ax1 settings         self ax1 set xlabel  time           self ax1 set ylabel  raw data           self line1   Line2D         color  blue           self line1 tail   Line2D         color  red   linewidth 2          self line1 head   Line2D         color  red   marker  o   markeredgecolor  r           self ax1 add line self line1          self ax1 add line self line1 tail          self ax1 add line self line1 head          self ax1 set xlim 0  self xlim - 1          self ax1 set ylim 0  100          FigureCanvas   init   self  self fig          TimedAnimation   init   self  self fig  interval   50  blit   True          return      def new frame seq self           return iter range self n size        def  init draw self           lines    self line1  self line1 tail  self line1 head          for l in lines              l set data                 return      def addData self  value           self addedData append value          return      def zoomIn self  value           bottom   self ax1 get ylim   0          top   self ax1 get ylim   1          bottom    value         top -  value         self ax1 set ylim bottom top          self draw           return      def  step self   args             Extends the  step   method for the TimedAnimation class          try              TimedAnimation  step self   args          except Exception as e              self abc    1             print str self abc               TimedAnimation  stop self              pass         return      def  draw frame self  framedata           margin   2         while len self addedData   gt  0               self y   np roll self y  -1              self y -1    self addedData 0              del self addedData 0            self line1 set data self n  0   self n size - margin    self y  0   self n size - margin            self line1 tail set data np append self n -10 -1 - margin   self n -1 - margin    np append self y -10 -1 - margin   self y -1 - margin            self line1 head set data self n -1 - margin   self y -1 - margin           self  drawn artists    self line1  self line1 tail  self line1 head          return      End Class         You need to setup a signal slot mechanism  to   send data to your GUI in a thread-safe way    Believe me  if you don t do this right  things   go very very wrong   class Communicate QObject       data signal   pyqtSignal float       End Class        def dataSendLoop addData callbackFunc         Setup the signal-slot mechanism      mySrc   Communicate       mySrc data signal connect addData callbackFunc         Simulate some data     n   np linspace 0  499  500      y   50   25  np sin n   8 3     10  np sin n   7 5   - 5  np sin n   1 5       i   0      while True           if i  gt  499               i   0         time sleep 0 1          mySrc data signal emit y i      lt - Here you emit a signal          i    1              if   name        main         app   QApplication sys argv      QApplication setStyle QStyleFactory create  Plastique        myGUI   CustomMainWindow       sys exit app exec       Just try it out  Copy-paste this code in a new python-file  and run it  You should get a beautiful  smoothly moving graph

User · Answer

I know this question is old  but there s now a package available called drawnow on GitHub as  python-drawnow   This provides an interface similar to MATLAB s drawnow -- you can easily update a figure   An example for your use case   import matplotlib pyplot as plt from drawnow import drawnow  def make fig        plt scatter x  y     I think you meant this  plt ion      enable interactivity fig   plt figure      make a figure  x   list   y   list    for i in range 1000       temp y   np random random       x append i      y append temp y     or any arbitrary update to your figure s data     i    1     drawnow make fig    python-drawnow is a thin wrapper around plt draw but provides the ability to confirm  or debug  after figure display

User · Answer

Here s the working version of the code in question  requires at least version Matplotlib 1 1 0 from 2011-11-14    import numpy as np import matplotlib pyplot as plt  plt axis  0  10  0  1    for i in range 10       y   np random random       plt scatter i  y      plt pause 0 05   plt show     Note some of the changes     Call plt pause 0 05  to both draw the new data and it runs the GUI s event loop  allowing for mouse interaction

User · Answer

The top  and many other  answers were built upon plt pause    but that was an old way of animating the plot in matplotlib  It is not only slow  but also causes focus to be grabbed upon each update  I had a hard time stopping the plotting python process    TL DR  you may want to use matplotlib animation  as mentioned in documentation    After digging around various answers and pieces of code  this in fact proved to be a smooth way of drawing incoming data infinitely for me   Here is my code for a quick start  It plots current time with a random number in  0  100  every 200ms infinitely  while also handling auto rescaling of the view   from datetime import datetime from matplotlib import pyplot from matplotlib animation import FuncAnimation from random import randrange  x data  y data           figure   pyplot figure   line    pyplot plot date x data  y data   -    def update frame       x data append datetime now        y data append randrange 0  100       line set data x data  y data      figure gca   relim       figure gca   autoscale view       return line   animation   FuncAnimation figure  update  interval 200   pyplot show     You can also explore blit for even better performance as in FuncAnimation documentation     An example from the blit documentation     import numpy as np import matplotlib pyplot as plt from matplotlib animation import FuncAnimation  fig  ax   plt subplots   xdata  ydata          ln    plt plot          ro    def init        ax set xlim 0  2 np pi      ax set ylim -1  1      return ln   def update frame       xdata append frame      ydata append np sin frame       ln set data xdata  ydata      return ln   ani   FuncAnimation fig  update  frames np linspace 0  2 np pi  128                       init func init  blit True  plt show

User · Answer

An example use-case to plot CPU usage in real-time   import time import psutil import matplotlib pyplot as plt  fig   plt figure   ax   fig add subplot 111   i   0 x  y           while True      x append i      y append psutil cpu percent         ax plot x  y  color  b        fig canvas draw        ax set xlim left max 0  i - 50   right i   50      fig show       plt pause 0 05      i    1

User · Answer

The problem seems to be that you expect plt show   to show the window and then to return  It does not do that  The program will stop at that point and only resume once you close the window  You should be able to test that  If you close the window and then another window should pop up   To resolve that problem just call plt show   once after your loop  Then you get the complete plot   But not a  real-time plotting    You can try setting the keyword-argument block like this  plt show block False  once at the beginning and then use  draw   to update

User · Answer

If you re interested in realtime plotting  I d recommend looking into matplotlib s animation API  In particular  using blit to avoid redrawing the background on every frame can give you substantial speed gains   10x       usr bin env python  import numpy as np import time import matplotlib matplotlib use  GTKAgg   from matplotlib import pyplot as plt   def randomwalk dims  256  256   n 20  sigma 5  alpha 0 95  seed 1           A simple random walk with memory          r  c   dims     gen   np random RandomState seed      pos   gen rand 2  n      r     c        old delta   gen randn 2  n    sigma      while True          delta    1  - alpha    gen randn 2  n    sigma   alpha   old delta         pos    delta         for ii in xrange n               if not  0   lt   pos 0  ii   lt  r                   pos 0  ii    abs pos 0  ii    r              if not  0   lt   pos 1  ii   lt  c                   pos 1  ii    abs pos 1  ii    c          old delta   delta         yield pos   def run niter 1000  doblit True               Display the simulation using matplotlib  optionally using blit for speed              fig  ax   plt subplots 1  1      ax set aspect  equal       ax set xlim 0  255      ax set ylim 0  255      ax hold True      rw   randomwalk       x  y   rw next        plt show False      plt draw        if doblit            cache the background         background   fig canvas copy from bbox ax bbox       points   ax plot x  y   o   0      tic   time time        for ii in xrange niter              update the xy data         x  y   rw next           points set data x  y           if doblit                restore background             fig canvas restore region background                 redraw just the points             ax draw artist points                 fill in the axes rectangle             fig canvas blit ax bbox           else                redraw everything             fig canvas draw        plt close fig      print  Blit    s  average FPS    2f              str doblit   niter    time time   - tic    if   name         main         run doblit False      run doblit True    Output   Blit   False  average FPS  54 37 Blit   True  average FPS  438 27

User · Answer

Here is a version that I got to work on my system   import matplotlib pyplot as plt from drawnow import drawnow import numpy as np  def makeFig        plt scatter xList yList    I think you meant this  plt ion     enable interactivity fig plt figure     make a figure  xList list   yList list    for i in np arange 50       y np random random       xList append i      yList append y      drawnow makeFig       makeFig        The drawnow makeFig  command can be replaced      plt draw       with makeFig    plt draw       plt pause 0 001    The drawnow makeFig  line can be replaced with a makeFig    plt draw   sequence and it still works OK

User · Answer

If you want draw and not freeze your thread as more point are drawn you should use plt pause   not time sleep    im using the following code to plot a series of xy coordinates   import matplotlib pyplot as plt  import math   pi   3 14159  fig  ax   plt subplots    x      y       def PointsInCircum r n 20       circle     math cos 2 pi n x  r math sin 2 pi n x  r  for x in xrange 0 n 1       return circle  circle list   PointsInCircum 3  50   for t in range len circle list        if t    0          points    ax plot x  y  marker  o   linestyle  --           ax set xlim -4  4           ax set ylim -4  4       else          x coord  y coord   circle list pop           x append x coord          y append y coord          points set data x  y      plt pause 0 01

User · Answer

Another option is to go with bokeh  IMO  it is a good alternative at least for real-time plots  Here is a bokeh version of the code in the question   from bokeh plotting import curdoc  figure import random import time  def update        global i     temp y   random random       r data source stream   x    i    y    temp y        i    1  i   0 p   figure   r   p circle         curdoc   add root p  curdoc   add periodic callback update  100    and for running it   pip3 install bokeh bokeh serve --show test py   bokeh shows the result in a web browser via websocket communications  It is especially useful when data is generated by remote headless server processes

User · Answer

None of the methods worked for me  But I have found this Real time matplotlib plot is not working while still in a loop  All you need is to add  plt pause 0 0001    and then you could see the new plots   So your code should look like this  and it will work  import matplotlib pyplot as plt import numpy as np plt ion      Note this correction fig plt figure   plt axis  0 1000 0 1    i 0 x list   y list    while i  lt 1000      temp y np random random        x append i       y append temp y       plt scatter i temp y       i  1      plt show       plt pause 0 0001   Note this correction

[python] How do I plot in real-time in a while loop using matplotlib?

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