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)
You essentially have two options:
Do exactly what you're currently doing, but call
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()
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()