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        "author": "Luca Cappelletti",
        "author_email": "cappelletti.luca94@gmail.com",
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        "description": "ddd_subplots\n=========================================================================================\n|travis| |sonar_quality| |sonar_maintainability| |codacy| |code_climate_maintainability| |pip| |downloads|\n\nPython package making it easier to handle mixed 3d and 2d subplots.\n\nHow do I install this package?\n----------------------------------------------\nAs usual, just download it using pip:\n\n.. code:: shell\n\n    pip install ddd_subplots\n\nTests Coverage\n----------------------------------------------\nSince some software handling coverages sometime get slightly different results, here's three of them:\n\n|coveralls| |sonar_coverage| |code_climate_coverage|\n\nUsage Example\n-----------------------------------------------\n\n3D subplots\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nTo get a set of 3d subplots just import `subplots`:\n\n.. code:: python\n\n    from ddd_subplots import subplots\n\n    fig, axes = subplots(1, 3, figsize=(15, 5))\n\n\nRotating 3D scatter plots\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nThe library also offers a method to render 3D scatter plots. Here's a complete example:\n\n.. code:: python\n\n    from ddd_subplots import subplots, rotate\n    import numpy as np\n    from sklearn import datasets\n    from sklearn.decomposition import PCA\n\n\n    def my_func(xs: np.ndarray, ys: np.ndarray, zs: np.ndarray, *args, **kwargs):\n        fig, axes = subplots(1, 3, figsize=(9, 3))\n        axs = axes.flatten()\n        axs[0].scatter(xs, ys, zs, **kwargs)\n        axs[1].scatter(ys, zs, xs, **kwargs)\n        axs[2].scatter(zs, xs, ys, **kwargs)\n        fig.tight_layout()\n        return fig, axes\n\n\n    X, y = datasets.load_iris(return_X_y=True)\n    X_reduced = PCA(n_components=3).fit_transform(X)\n    colors = np.array([\"red\", \"green\", \"blue\"])[y]\n    rotate(my_func, *X_reduced.T, path=\"test.gif\",\n        duration=2, fps=24, c=colors, marker='o', s=20)\n\n\n\nOutput:\n\n.. image:: https://github.com/LucaCappelletti94/ddd_subplots/blob/master/test.gif?raw=true\n\n\nKnown limits\n----------------------------------------------\nThere is an error with `CoreFoundations and multiprocessing on MacOS <https://turtlemonvh.github.io/python-multiprocessing-and-corefoundation-libraries.html>`_, which states the following:\n\n.. code:: bash\n\n    The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec().\n    Break on __THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__() to debug.\n\nThis is a weird known error of MacOS Sierra. For now, the only available solution is to disable multiprocessing when dealing with matplotlib.\nAny alternative valid solutions are welcome:\n\n.. code:: python\n\n    rotate(my_func, *X_reduced.T, path=\"test.gif\",\n        duration=2, fps=24, parallelize=False, c=colors, marker='o', s=20)\n\n.. |travis| image:: https://travis-ci.org/LucaCappelletti94/ddd_subplots.png\n   :target: https://travis-ci.org/LucaCappelletti94/ddd_subplots\n   :alt: Travis CI build\n\n.. |sonar_quality| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_ddd_subplots&metric=alert_status\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_ddd_subplots\n    :alt: SonarCloud Quality\n\n.. |sonar_maintainability| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_ddd_subplots&metric=sqale_rating\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_ddd_subplots\n    :alt: SonarCloud Maintainability\n\n.. |sonar_coverage| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_ddd_subplots&metric=coverage\n    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_ddd_subplots\n    :alt: SonarCloud Coverage\n\n.. |coveralls| image:: https://coveralls.io/repos/github/LucaCappelletti94/ddd_subplots/badge.svg?branch=master\n    :target: https://coveralls.io/github/LucaCappelletti94/ddd_subplots?branch=master\n    :alt: Coveralls Coverage\n\n.. |pip| image:: https://badge.fury.io/py/ddd-subplots.svg\n    :target: https://badge.fury.io/py/ddd-subplots\n    :alt: Pypi project\n\n.. |downloads| image:: https://pepy.tech/badge/ddd-subplots\n    :target: https://pepy.tech/badge/ddd-subplots\n    :alt: Pypi total project downloads \n\n.. |codacy|  image:: https://api.codacy.com/project/badge/Grade/07125d5f5f4d4d1a838349b004553cd4\n    :target: https://www.codacy.com/manual/LucaCappelletti94/ddd_subplots?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=LucaCappelletti94/ddd_subplots&amp;utm_campaign=Badge_Grade\n    :alt: Codacy Maintainability\n\n.. |code_climate_maintainability| image:: https://api.codeclimate.com/v1/badges/5c07f15635098d958e08/maintainability\n    :target: https://codeclimate.com/github/LucaCappelletti94/ddd_subplots/maintainability\n    :alt: Maintainability\n\n.. |code_climate_coverage| image:: https://api.codeclimate.com/v1/badges/5c07f15635098d958e08/test_coverage\n    :target: https://codeclimate.com/github/LucaCappelletti94/ddd_subplots/test_coverage\n    :alt: Code Climate Coverate",
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