>>> """
========================
MATPLOTLIB **UNCHAINED**
========================

Comparative path demonstration of frequency from a fake signal of a pulsar
(mostly known because of the cover for Joy Division's Unknown Pleasures).

Author: Nicolas P. Rougier
"""
... 
... import numpy as np
... import matplotlib.pyplot as plt
... import matplotlib.animation as animation
... 
... # Fixing random state for reproducibility
... np.random.seed(19680801)
... 
... 
... # Create new Figure with black background
... fig = plt.figure(figsize=(8, 8), facecolor='black')
... 
... # Add a subplot with no frame
... ax = plt.subplot(frameon=False)
... 
... # Generate random data
... data = np.random.uniform(0, 1, (64, 75))
... X = np.linspace(-1, 1, data.shape[-1])
... G = 1.5 * np.exp(-4 * X ** 2)
... 
... # Generate line plots
... lines = []
... for i in range(len(data)):
...     # Small reduction of the X extents to get a cheap perspective effect
...     xscale = 1 - i / 200.
...     # Same for linewidth (thicker strokes on bottom)
...     lw = 1.5 - i / 100.0
...     line, = ax.plot(xscale * X, i + G * data[i], color="w", lw=lw)
...     lines.append(line)
... 
... # Set y limit (or first line is cropped because of thickness)
... ax.set_ylim(-1, 70)
... 
... # No ticks
... ax.set_xticks([])
... ax.set_yticks([])
... 
... # 2 part titles to get different font weights
... ax.text(0.5, 1.0, "MATPLOTLIB ", transform=ax.transAxes,
...         ha="right", va="bottom", color="w",
...         family="sans-serif", fontweight="light", fontsize=16)
... ax.text(0.5, 1.0, "UNCHAINED", transform=ax.transAxes,
...         ha="left", va="bottom", color="w",
...         family="sans-serif", fontweight="bold", fontsize=16)
... 
... 
... def update(*args):
...     # Shift all data to the right
...     data[:, 1:] = data[:, :-1]
... 
...     # Fill-in new values
...     data[:, 0] = np.random.uniform(0, 1, len(data))
... 
...     # Update data
...     for i in range(len(data)):
...         lines[i].set_ydata(i + G * data[i])
... 
...     # Return modified artists
...     return lines
... 
... # Construct the animation, using the update function as the animation director.
... anim = animation.FuncAnimation(fig, update, interval=10)
... plt.show()
...