René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"[ENH]: Adapt 2-dim histogram axis limits to content","articleBody":"### Problem\n\nPlotting a 2-dim histogram using the `hist2d` function can leave a lot of excess space in the plot when using the argument `cmin` to exclude bins with insufficient numbers of data-points. (There's presumably a similar problem when using the argument `cmax`).\r\n\r\n    %matplotlib inline\r\n    import numpy as np\r\n    import matplotlib.pyplot as plt\r\n\r\n    # Generate random x/y values.\r\n    rng = np.random.default_rng(1234)\r\n    size = 100000\r\n    x = rng.normal(scale=10, size=size)\r\n    y = rng.normal(size=size)\r\n\r\n    # This plot has properly adjusted axis-limits.\r\n    plt.hist2d(x, y, bins=100, cmin=1);\r\n\r\n![image](https://github.com/matplotlib/matplotlib/assets/13588114/f9d89963-89f3-4cf1-86dd-55ff4efed47e)\r\n\r\n    # This plot has a lot of excess space.\r\n    plt.hist2d(x, y, bins=100, cmin=20);\r\n\r\n![image](https://github.com/matplotlib/matplotlib/assets/13588114/2df600a7-d988-466a-83f4-5bc7c3cf19c7)\r\n\n\n### Proposed solution\n\nThe following is a quick solution that seems to work. But it may be possible to make a better solution when integrating it into the `hist2d` function. It should be made as an optional argument such as `hist2d(adapt_lim=True, ...)` to adapt both x and y-axis, or specify a given axis such as `hist2d(adapt_lim='x', ...)` \r\n\r\nI don't really have time to add this to Matplotlib's code-base myself, and make sure everything is made according to your standards etc. So hopefully someone else can do it, if you like the feature. Thanks!\r\n\r\n    # Plot 2-dim histogram and get bins and edges.\r\n    h, xedges, yedges, _ = plt.hist2d(x, y, bins=100, cmin=20);\r\n\r\n    # Boolean mask whether a bin is actually used in the 2-dim grid.\r\n    mask = ~np.isnan(h)\r\n\r\n    # Flattened boolean masks whether a bin is actually used for each axis.\r\n    mask_flat_x = np.any(mask, axis=1)\r\n    mask_flat_y = np.any(mask, axis=0)\r\n\r\n    # Get x-axis min/max for bins that are actually used.\r\n    x_min = xedges[:-1][mask_flat_x].min()\r\n    x_max = xedges[1:][mask_flat_x].max()\r\n\r\n    # Get y-axis min/max for bins that are actually used.\r\n    y_min = yedges[:-1][mask_flat_y].min()\r\n    y_max = yedges[1:][mask_flat_y].max()\r\n\r\n    # Adjust x-axis limits to have a little padding.\r\n    x_pad = 0.01 * (x_max - x_min)\r\n    plt.xlim(x_min - x_pad, x_max + x_pad)\r\n\r\n    # Adjust y-axis limits to have a little padding.\r\n    y_pad = 0.01 * (y_max - y_min)\r\n    plt.ylim(y_min - y_pad, y_max + y_pad)\r\n\r\n    plt.show();\r\n\r\n![image](https://github.com/matplotlib/matplotlib/assets/13588114/c22e7bbb-5666-41f8-bda4-28229a297d16)\r\n","author":{"url":"https://github.com/Hvass-Labs","@type":"Person","name":"Hvass-Labs"},"datePublished":"2023-07-11T15:47:28.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":9},"url":"https://github.com/26288/matplotlib/issues/26288"}