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        "\n# Matplotlib unchained\n\nComparative path demonstration of frequency from a fake signal of a pulsar\n(mostly known because of the cover for Joy Division's Unknown Pleasures).\n\nAuthor: Nicolas P. Rougier\n\nOutput generated via `matplotlib.animation.Animation.to_jshtml`.\n"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nimport matplotlib.animation as animation\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\n\n# Create new Figure with black background\nfig = plt.figure(figsize=(8, 8), facecolor='black')\n\n# Add a subplot with no frame\nax = plt.subplot(frameon=False)\n\n# Generate random data\ndata = np.random.uniform(0, 1, (64, 75))\nX = np.linspace(-1, 1, data.shape[-1])\nG = 1.5 * np.exp(-4 * X ** 2)\n\n# Generate line plots\nlines = []\nfor i in range(len(data)):\n    # Small reduction of the X extents to get a cheap perspective effect\n    xscale = 1 - i / 200.\n    # Same for linewidth (thicker strokes on bottom)\n    lw = 1.5 - i / 100.0\n    line, = ax.plot(xscale * X, i + G * data[i], color=\"w\", lw=lw)\n    lines.append(line)\n\n# Set y limit (or first line is cropped because of thickness)\nax.set_ylim(-1, 70)\n\n# No ticks\nax.set_xticks([])\nax.set_yticks([])\n\n# 2 part titles to get different font weights\nax.text(0.5, 1.0, \"MATPLOTLIB \", transform=ax.transAxes,\n        ha=\"right\", va=\"bottom\", color=\"w\",\n        family=\"sans-serif\", fontweight=\"light\", fontsize=16)\nax.text(0.5, 1.0, \"UNCHAINED\", transform=ax.transAxes,\n        ha=\"left\", va=\"bottom\", color=\"w\",\n        family=\"sans-serif\", fontweight=\"bold\", fontsize=16)\n\n\ndef update(*args):\n    # Shift all data to the right\n    data[:, 1:] = data[:, :-1]\n\n    # Fill-in new values\n    data[:, 0] = np.random.uniform(0, 1, len(data))\n\n    # Update data\n    for i in range(len(data)):\n        lines[i].set_ydata(i + G * data[i])\n\n    # Return modified artists\n    return lines\n\n# Construct the animation, using the update function as the animation director.\nanim = animation.FuncAnimation(fig, update, interval=10, save_count=100)\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags::\n\n   component: animation\n   plot-type: line\n   purpose: fun\n\n"
      ]
    }
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