In [1]:

    

import sys
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation


    

In [2]:

    

fig, ax = plt.subplots()
#fig.set_tight_layout(True)


    

In [3]:

    

# Query the figure's on-screen size and DPI. Note that when saving the figure to
# a file, we need to provide a DPI for that separately.
print('fig size: {0} DPI, size in inches {1}'.format(
    fig.get_dpi(), fig.get_size_inches()))


    

    




fig size: 72.0 DPI, size in inches [ 6.  4.]

In [4]:

    

# Plot a scatter that persists (isn't redrawn) and the initial line.
x = np.arange(0, 20, 0.1)
ax.scatter(x, x + np.random.normal(0, 3.0, len(x)))
line, = ax.plot(x, x - 5, 'r-', linewidth=2)


    

In [5]:

    

def update(i):
    label = 'timestep {0}'.format(i)
    print(label)
    # Update the line and the axes (with a new xlabel). Return a tuple of
    # "artists" that have to be redrawn for this frame.
    line.set_ydata(x - 5 + i)
    ax.set_xlabel(label)
    return line, ax


    

In [6]:

    

# FuncAnimation will call the 'update' function for each frame; here
# animating over 10 frames, with an interval of 200ms between frames.
anim = FuncAnimation(fig, update, frames=np.arange(0, 10), interval=200)
anim.save('line.gif', dpi=80, writer='imagemagick')


    

    




timestep 0
timestep 0
timestep 1
timestep 2
timestep 3
timestep 4
timestep 5
timestep 6
timestep 7
timestep 8
timestep 9