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        "author": "Krishna Naidoo",
        "author_email": "krishna.naidoo.11@ucl.ac.uk",
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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: Fortran",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Astronomy",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Physics",
            "Topic :: Scientific/Engineering :: Visualization"
        ],
        "description": "# MiSTree\n\nAuthor:         Krishna Naidoo                          \nVersion:        1.2.0                               \nHomepage:       https://github.com/knaidoo29/mistree    \nDocumentation:  https://knaidoo29.github.io/mistreedoc/\n\n[![Build Status](https://travis-ci.org/knaidoo29/mistree.svg?branch=master)](https://travis-ci.org/knaidoo29/mistree) [![codecov](https://codecov.io/gh/knaidoo29/mistree/branch/master/graph/badge.svg)](https://codecov.io/gh/knaidoo29/mistree) [![PyPI version](https://badge.fury.io/py/mistree.svg)](https://badge.fury.io/py/mistree) [![status](https://joss.theoj.org/papers/461d79e9e5faf21029c0a7b1c928be28/status.svg)](https://joss.theoj.org/papers/461d79e9e5faf21029c0a7b1c928be28) [![DOI](https://zenodo.org/badge/170473458.svg)](https://zenodo.org/badge/latestdoi/170473458) [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/knaidoo29/mistree/master?filepath=tutorials%2Fnotebooks%2F)\n\n## Introduction\n\nThe *minimum spanning tree* (MST), a graph constructed from a distribution of points, draws lines between pairs of points so that all points are linked in a single skeletal structure that contains no loops and has minimal total edge length. The MST has been used in a broad range of scientific fields such as particle physics, in astronomy and cosmology. Its success in these fields has been driven by its sensitivity to the spatial distribution of points and the patterns within. ``MiSTree``, a public ``Python`` package, allows a user to construct the MST in a variety of coordinates systems, including Celestial coordinates used in astronomy. The package enables the MST to be constructed quickly by initially using a *k*-nearest neighbour graph (*k* NN, rather than a matrix of pairwise distances) which is then fed to Kruskal's algorithm to construct the MST. ``MiSTree`` enables a user to measure the statistics of the MST and provides classes for binning the MST statistics (into histograms) and plotting the distributions. Applying the MST will enable the inclusion of high-order statistics information from the cosmic web which can provide additional information to improve cosmological parameter constraints. This information has not been fully exploited due to the computational cost of calculating *N*-point statistics. ``MiSTree`` was designed to be used in cosmology but could be used in any field which requires extracting non-Gaussian information from point distributions.\n\n## Dependencies\n\n* Python 2.7 or 3.4+\n* `numpy`\n* `matplotlib`\n* `scipy`\n* `scikit-learn`\n* `f2py` (should be installed with numpy)\n\nFor testing you will require `nose` or `pytest`.\n\n## Installation\n\nMiSTree can be installed as follows:\n\n```\npip install mistree [--user]\n```\n\nThe `--user` is optional and only required if you don\u2019t have write permission. If you\nwant to work on the Github version you can clone the repository and install an editable version:\n\n```\ngit clone https://github.com/knaidoo29/mistree.git\ncd mistree\npip install -e . [--user]\n```\n\nFrom the `mistree` directory you can then test the install using `nose`:\n\n```\npython setup.py test\n```\n\nor using `pytest`:\n\n```\npython -m pytest\n```\n\nYou should now be able to import the module:\n\n```python\nimport mistree as mist\n```\n\n## Documentation\n\nIn depth documentation and tutorials are provided [here](https://knaidoo29.github.io/mistreedoc/).\n\n## Tutorials\n\nThe tutorials in the documentation are supplied as ipython notebooks which can be downloaded from [here](https://github.com/knaidoo29/mistree/tree/master/tutorials/notebooks) or can be run online using [binder](https://mybinder.org/v2/gh/knaidoo29/mistree/master?filepath=tutorials%2Fnotebooks%2F).\n\n## Support\n\nIf you have any issues with the code or want to suggest ways to improve it please open a new issue ([here](https://github.com/knaidoo29/mistree/issues))\nor (if you don't have a github account) email _krishna.naidoo.11@ucl.ac.uk_.\n\n\n",
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