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(2006). Visualization of large hierarchical data by circle packing. *Proc of the SIGCHI*, 517-520.\n\n\u003cimg src=\"https://raw.githubusercontent.com/mhtchan/packcircles/master/images/packing.gif\" width=\"400\" height=\"400\"\u003e\n\n# Installation\nUsing `pip`:\n```\npip install packcircles\n```\nor directly using `setup.py`:\n```\ngit clone https://github.com/mhtchan/packcircles.git\ncd packcircles\npython setup.py install\n```\n\n# Usage\nThe function `pack` takes an iterable of the radii of the circles to pack and returns a generator that yields the layout of each circle as tuples in the form `(x_coordinate, y_coordinate, radius)`.\n\n# Example\n```python\nimport packcircles as pc\ncircles = pc.pack([15,5,7,12])\nprint(list(circles))\n## [(-15.579319782711305, 4.287939798231928, 15), (4.4206802172886945, 4.287939798231928, 5), (2.9206802172886945, -7.6179411015587295, 7), (20.647637933172685, -0.7801804930509242, 12)]\n```\n\nThe layout in the gif at the top of the page can be generated by the following code:\n```python\nimport packcircles as pc\nimport matplotlib.pyplot as plt\nfrom matplotlib import colormaps\nradii =  [28,12,51,26,10,16,24,25,59,11,29,40,16,11,10,26,39,16,48,36,28]\nfig, ax = plt.subplots()\ncmap = colormaps['coolwarm_r']\ncircles = pc.pack(radii)\nfor (x,y,radius) in circles:\n    patch = plt.Circle(\n        (x,y),\n        radius,\n        color=cmap(radius/max(radii)),\n        alpha=0.65\n    )\n    ax.add_patch(patch)\nfig.set_figheight(15)\nfig.set_figwidth(15)\nax.set(xlim=(-150, 140), ylim=(-180, 170))\nplt.axis('off')\nplt.show()\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmhtchan%2Fpackcircles","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmhtchan%2Fpackcircles","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmhtchan%2Fpackcircles/lists"}