Animation in iPython notebook

Some options you have for animating plots in Jupyter/IPython, using matplotlib:

• Using display in a loop Use IPython.display.display(fig) to display a figure in the output. Using a loop you would want to clear the output before a new figure is shown. Note that this technique gives in general not so smooth resluts. I would hence advice to use any of the below.

  import matplotlib.pyplot as plt
  import matplotlib.animation
  import numpy as np
  from IPython.display import display, clear_output
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  for i in range(len(x)):
      animate(i)
      clear_output(wait=True)
      display(fig)
      
  plt.show()

• %matplotlib notebook Use IPython magic %matplotlib notebook to set the backend to the notebook backend. This will keep the figure alive instead of displaying a static png file and can hence also show animations.
  Complete example:

  %matplotlib notebook
  import matplotlib.pyplot as plt
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  
  plt.show()

• %matplotlib tk Use IPython magic %matplotlib tk to set the backend to the tk backend. This will open the figure in a new plotting window, which is interactive and can thus also show animations.
  Complete example:

  %matplotlib tk
  import matplotlib.pyplot as plt
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  
  plt.show()

• Convert animation to mp4 video (option mentionned by @Perfi already):

  from IPython.display import HTML
  HTML(ani.to_html5_video())
  

  or use plt.rcParams["animation.html"] = "html5" at the beginning of the notebook.
  This will require to have ffmpeg video codecs available to convert to HTML5 video. The video is then shown inline. This is therefore compatible with %matplotlib inline backend. Complete example:

  %matplotlib inline
  import matplotlib.pyplot as plt
  plt.rcParams["animation.html"] = "html5"
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  ani

  %matplotlib inline
  import matplotlib.pyplot as plt
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  
  from IPython.display import HTML
  HTML(ani.to_html5_video())

• Convert animation to JavaScript:

  from IPython.display import HTML
  HTML(ani.to_jshtml())
  

  or use plt.rcParams["animation.html"] = "jshtml" at the beginning of the notebook.
  This will display the animation as HTML with JavaScript. This highly compatible with most new browsers and also with the %matplotlib inline backend. It is available in matplotlib 2.1 or higher.
  Complete example:

  %matplotlib inline
  import matplotlib.pyplot as plt
  plt.rcParams["animation.html"] = "jshtml"
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  ani

  %matplotlib inline
  import matplotlib.pyplot as plt
  import matplotlib.animation
  import numpy as np
  
  t = np.linspace(0,2*np.pi)
  x = np.sin(t)
  
  fig, ax = plt.subplots()
  l, = ax.plot([0,2*np.pi],[-1,1])
  
  animate = lambda i: l.set_data(t[:i], x[:i])
  
  ani = matplotlib.animation.FuncAnimation(fig, animate, frames=len(t))
  
  from IPython.display import HTML
  HTML(ani.to_jshtml())