How to update a plot in matplotlib

Question

I m having issues with redrawing the figure here  I allow the user to specify the units in the time scale  x-axis  and then I recalculate and call this function plots    I want the plot to simply update  not append another plot to the figure   def plots        global vlgaBuffSorted     cntr        result   collections defaultdict list      for d in vlgaBuffSorted          result d  event    append d       result list   result values        f   Figure       graph1   f add subplot 211      graph2   f add subplot 212 sharex graph1       for item in result list          tL              vgsL              vdsL              isubL              for dict in item              tL append dict  time                vgsL append dict  vgs                vdsL append dict  vds                isubL append dict  isub            graph1 plot tL vdsL  bo  label  a           graph1 plot tL vgsL  rp  label  b           graph2 plot tL isubL  b-  label  c        plotCanvas   FigureCanvasTkAgg f  pltFrame      toolbar   NavigationToolbar2TkAgg plotCanvas  pltFrame      toolbar pack side BOTTOM      plotCanvas get tk widget   pack side TOP

User · Answer

I have released a package called python-drawnow that provides functionality to let a figure update, typically called within a for loop, similar to Matlab's drawnow.

An example usage:

from pylab import figure, plot, ion, linspace, arange, sin, pi
def draw_fig():
    # can be arbitrarily complex; just to draw a figure
    #figure() # don't call!
    plot(t, x)
    #show() # don't call!

N = 1e3
figure() # call here instead!
ion()    # enable interactivity
t = linspace(0, 2*pi, num=N)
for i in arange(100):
    x = sin(2 * pi * i**2 * t / 100.0)
    drawnow(draw_fig)

This package works with any matplotlib figure and provides options to wait after each figure update or drop into the debugger.

User · Answer

This worked for me  Repeatedly calls a function updating the graph every time   import matplotlib pyplot as plt import matplotlib animation as anim  def plot cont fun  xmax       y          fig   plt figure       ax   fig add subplot 1 1 1       def update i           yi   fun           y append yi          x   range len y           ax clear           ax plot x  y          print i        yi      a   anim FuncAnimation fig  update  frames xmax  repeat False      plt show      fun  is a function that returns an integer  FuncAnimation will repeatedly call  update   it will do that  xmax  times

User · Answer

In case anyone comes across this article looking for what I was looking for  I found examples at   How to visualize scalar 2D data with Matplotlib    and   http   mri brechmos org 2009 07 automatically-update-a-figure-in-a-loop   on web archive org   then modified them to use imshow with an input stack of frames  instead of generating and using contours on the fly       Starting with a 3D array of images of shape  nBins  nBins  nBins   called frames   def animate frames frames       nBins     frames shape 0      frame     frames 0      tempCS1   plt imshow frame  cmap plt cm gray      for k in range nBins           frame     frames k          tempCS1   plt imshow frame  cmap plt cm gray          del tempCS1         fig canvas draw            time sleep 1e-2   unnecessary  but useful         fig clf    fig   plt figure   ax    fig add subplot 111   win   fig canvas manager window fig canvas manager window after 100  animate frames  frames    I also found a much simpler way to go about this whole process  albeit less robust   fig   plt figure    for k in range nBins       plt clf       plt imshow frames k  cmap plt cm gray      fig canvas draw       time sleep 1e-6   unnecessary  but useful   Note that both of these only seem to work with ipython --pylab tk  a k a backend   TkAgg  Thank you for the help with everything

User · Answer

You essentially have two options    Do exactly what you re currently doing  but call graph1 clear   and graph2 clear   before replotting the data   This is the slowest  but most simplest and most robust option  Instead of replotting  you can just update the data of the plot objects   You ll need to make some changes in your code  but this should be much  much faster than replotting things every time   However  the shape of the data that you re plotting can t change  and if the range of your data is changing  you ll need to manually reset the x and y axis limits    To give an example of the second option   import matplotlib pyplot as plt import numpy as np  x   np linspace 0  6 np pi  100  y   np sin x     You probably won t need this if you re embedding things in a tkinter plot    plt ion    fig   plt figure   ax   fig add subplot 111  line1    ax plot x  y   r-     Returns a tuple of line objects  thus the comma  for phase in np linspace 0  10 np pi  500       line1 set ydata np sin x   phase       fig canvas draw       fig canvas flush events

User · Answer

This worked for me   from matplotlib import pyplot as plt from IPython display import clear output import numpy as np for i in range 50       clear output wait True      y   np random random  10 1       plt plot y      plt show

User · Answer

You can also do like the following  This will draw a 10x1 random matrix data on the plot for 50 cycles of the for loop   import matplotlib pyplot as plt import numpy as np  plt ion   for i in range 50       y   np random random  10 1       plt plot y      plt draw       plt pause 0 0001      plt clf

User · Answer

All of the above might be true  however for me  online-updating  of figures only works with some backends  specifically wx  You just might try to change to this  e g  by starting ipython pylab by ipython --pylab wx  Good luck

[python] How to update a plot in matplotlib?

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