MATPLOTLIB UNCHAINED

脉冲星的假信号频率的比较路径演示（主要是因为Joy Division的未知乐趣的封面而闻名）。

作者：Nicolas P. Rougier

MATPLOTLIB UNCHAINED示例

  1. import numpy as np
  2. import matplotlib.pyplot as plt
  3. import matplotlib.animation as animation
  5. # Fixing random state for reproducibility
  6. np.random.seed(19680801)
  9. # Create new Figure with black background
  10. fig = plt.figure(figsize=(8, 8), facecolor='black')
  12. # Add a subplot with no frame
  13. ax = plt.subplot(111, frameon=False)
  15. # Generate random data
  16. data = np.random.uniform(0, 1, (64, 75))
  17. X = np.linspace(-1, 1, data.shape[-1])
  18. G = 1.5 * np.exp(-4 * X ** 2)
  20. # Generate line plots
  21. lines = []
  22. for i in range(len(data)):
  23.     # Small reduction of the X extents to get a cheap perspective effect
  24.     xscale = 1 - i / 200.
  25.     # Same for linewidth (thicker strokes on bottom)
  26.     lw = 1.5 - i / 100.0
  27.     line, = ax.plot(xscale * X, i + G * data[i], color="w", lw=lw)
  28.     lines.append(line)
  30. # Set y limit (or first line is cropped because of thickness)
  31. ax.set_ylim(-1, 70)
  33. # No ticks
  34. ax.set_xticks([])
  35. ax.set_yticks([])
  37. # 2 part titles to get different font weights
  38. ax.text(0.5, 1.0, "MATPLOTLIB ", transform=ax.transAxes,
  39.         ha="right", va="bottom", color="w",
  40.         family="sans-serif", fontweight="light", fontsize=16)
  41. ax.text(0.5, 1.0, "UNCHAINED", transform=ax.transAxes,
  42.         ha="left", va="bottom", color="w",
  43.         family="sans-serif", fontweight="bold", fontsize=16)
  46. def update(*args):
  47.     # Shift all data to the right
  48.     data[:, 1:] = data[:, :-1]
  50.     # Fill-in new values
  51.     data[:, 0] = np.random.uniform(0, 1, len(data))
  53.     # Update data
  54.     for i in range(len(data)):
  55.         lines[i].set_ydata(i + G * data[i])
  57.     # Return modified artists
  58.     return lines
  60. # Construct the animation, using the update function as the animation director.
  61. anim = animation.FuncAnimation(fig, update, interval=10)
  62. plt.show()

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