The second argument animate is the function we created to call at each frame to update the plot.The first argument fig is the reference to the figure we created.def animate(frame_num): y = np.sin( x + 2*np.pi * frame_num/100) t_data((x, y)) return lineįinally, we create our animation object by calling FuncAnimation with 4 arguments What we want to do here is to change data for our line according to the frame number.
The function takes one argument frame_num - the current frame number. We then create a function animate() that’s going to be called by the FuncAnimation. fig, ax = plt.subplots() line, = ax.plot() # A tuple unpacking to unpack the only plot ax. We set the x range to (0, 2*Pi) and y range to (-1.1,1.1) to avoid them to be constantly changing. We call subplots() without any arguments to create a Figure fig and a single Axes ax. Next, we need to create an initial state of the animation figure. import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation Especially FuncAnimation class that can be used to create an animation for you. In order to create an interactive plot in Jupyter Notebook, you first need to enable interactive plot as follows: # Enable interactive plot %matplotlib notebookĪfter that, we import the required libraries.
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