title: Keeping multiple figures open with matplotlib after script is executed
body: <p>I have a question regarding windows/figures in matplotlib. I'm not sure if this is possible, but would like to know if it is. 
  Basically when I run my whole script, at the end a graph is plotted using matplotlib. In order to produce a new graph after running my script again I have to close that graph window. </p>
  
  <p>Is there a way of keeping open the figure without closing it? </p>
  
  <p>Let me give an example:</p>
  
  <p>I would plot graph x by running my script.</p>
  
  <p>I would then like to keep this graph on my screen, make a change to my script, plot the graph again so you may see the old graph and the new graph. Therefore n number of graphs may be visible.</p>
  
  <p>Please note that I do NOT want to plot a new figure within my script. I simply would like to be able to see the graph, make a change and see the new graph WITHOUT having to save the graph.</p>
  
  <p><strong>EDIT</strong>:</p>
  
  <p>This is the plotting secion of my code:</p>
  
  <pre><code>def plot_data(atb_mat_2, sd_index, sd_grad):#, rtsd):#, sd_index, sd_grad):
      fig = plt.figure()
      fig, (ax0, ax1, ax4, ax2, ax3) = plt.subplots(nrows=5, figsize=(15,10), num='Current Relative Method'+'  ' + path)
      ax0.plot(atb_mat_2)
      ax0.set_title('Relative Track',fontsize=11)
      ax0.set_ylim([-10,10])
      if len(sd_index)!=0:
          if len(sd_index)&gt;1:
              for i in range(1, len(sd_index)):
                  if sd_grad[i]==1:
                      ax0.axvspan(sd_index[i-1],sd_index[i], edgecolor='r', lw=None, alpha=0.1)
      ax1.plot(rtsd)
      ax1.set_title('RT Standard Deviation',fontsize=11)
      ax1.set_ylim([0,250])
      ax4.plot(abs_track_data)
      ax4.set_title('Absolute Track',fontsize=11)
      ax4.set_ylim([3000,5000])
      ax2.plot(splitpo)
      ax2.set_title('Track Split',fontsize=11)
      ax2.set_ylim([0,20])
      ax3.plot(ts)
      ax3.set_title('TS Standard Deviation',fontsize=11)
      ax3.set_ylim([0,100])
  
      fig.tight_layout()
      plt.show()
  </code></pre>
  
  <p>Thanks alot of any advice and sorry if this answer is obvious as I'm fairly new.</p>