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        "\n# Hinton diagrams\n\nHinton diagrams are useful for visualizing the values of a 2D array (e.g.\na weight matrix): Positive and negative values are represented by white and\nblack squares, respectively, and the size of each square represents the\nmagnitude of each value.\n\nInitial idea from David Warde-Farley on the SciPy Cookbook\n"
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    {
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      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\n\ndef hinton(matrix, max_weight=None, ax=None):\n    \"\"\"Draw Hinton diagram for visualizing a weight matrix.\"\"\"\n    ax = ax if ax is not None else plt.gca()\n\n    if not max_weight:\n        max_weight = 2 ** np.ceil(np.log2(np.abs(matrix).max()))\n\n    ax.patch.set_facecolor('gray')\n    ax.set_aspect('equal', 'box')\n    ax.xaxis.set_major_locator(plt.NullLocator())\n    ax.yaxis.set_major_locator(plt.NullLocator())\n\n    for (x, y), w in np.ndenumerate(matrix):\n        color = 'white' if w > 0 else 'black'\n        size = np.sqrt(abs(w) / max_weight)\n        rect = plt.Rectangle([x - size / 2, y - size / 2], size, size,\n                             facecolor=color, edgecolor=color)\n        ax.add_patch(rect)\n\n    ax.autoscale_view()\n    ax.invert_yaxis()\n\n\nif __name__ == '__main__':\n    # Fixing random state for reproducibility\n    np.random.seed(19680801)\n\n    hinton(np.random.rand(20, 20) - 0.5)\n    plt.show()"
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