{
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        "author": "J Gomez-Dans",
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            "Development Status :: 4 - Beta",
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            "Intended Audience :: End Users/Desktop",
            "Intended Audience :: Science/Research",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "# GP emulators\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.45259.svg)](https://doi.org/10.5281/zenodo.45259)\n[![Coverage Status](https://coveralls.io/repos/github/jgomezdans/gp_emulator/badge.svg?branch=tests)](https://coveralls.io/github/jgomezdans/gp_emulator?branch=tests)\n[![Build Status](https://travis-ci.org/jgomezdans/gp_emulator.svg?branch=master)](https://travis-ci.org/jgomezdans/gp_emulator)\n[![codecov](https://codecov.io/gh/jgomezdans/gp_emulator/branch/master/graph/badge.svg?longCache=true&style=flat)](https://codecov.io/gh/jgomezdans/gp_emulator)\n[![Anaconda-Server Badge](https://anaconda.org/jgomezdans/gp_emulator/badges/version.svg)](https://anaconda.org/jgomezdans/gp_emulator)\n[![PyPI version](https://badge.fury.io/py/gp_emulator.svg)](https://badge.fury.io/py/gp_emulator)\n[![Documentation](https://readthedocs.org/projects/gp-emulator/badge/?version=latest)](https://gp-emulator.readthedocs.io/en/latest/?badge=latest)\n\n## Gaussian process (GP) emulators for Python\n\n### Author  \nJ G\u00f3mez-Dans <j.gomez-dans@ucl.ac.uk>\n<p><img src=\"http://www.multiply-h2020.eu/wp-content/uploads/2018/08/multiply_banner_2018_klein.jpg\" align=\"center\" \\></p>\n<p><img src=\"https://www.nceo.ac.uk/wp-content/themes/nceo/assets/images/logos/img_logo_purple.svg\" align=\"left\" />\n\n<img src=\"http://www.esa.int/esalogo/images/logotype/img_colorlogo_darkblue.gif\" scale=\"20%\" align=\"right\" />\n</p>\n\n\n\n\nThis repository contains an implementation of GPs for emulation of radiative transfer models in Python. This particular implementation is focused on emulating univariate output models (e.g. emulating reflectance or radiance for a single sensor band) and multivariate outputs (e.g. emulating reflectance/radiance over the entire solar reflective domain). The emulators also calculate the gradient of the emulated model and the Hessian.\n\n### Documentation\n\nYou can read the documentation in [http://http://gp-emulator.readthedocs.io]<http://gp-emulator.readthedocs.io>\n\n### Installation\n\n\nYou can install the software with either [conda]<https://docs.anaconda.com/anaconda/>\n\n    conda install -c jgomezdans gp_emulators\n\nor using `pip`...\n\n    pip install gp_emulator\n\nor just clone/download the repository and invoke the `setup.py` script:\n\n    python setup.py install\n\nThe only requirements are (if memory serves) numpy and scipy. \n\nAt some point, pointers to a library of emulators of popular vegetation and atmospheric RT codes will be provided.\n\n### Citation\n\n\nIf you use this code, we would be grateful if you cited the following paper:\n\n    G\u00f3mez-Dans, J.L.; Lewis, P.E.; Disney, M. Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences. Remote Sens. 2016, 8, 119. <DOI:10.3390/rs8020119> <http://www.mdpi.com/2072-4292/8/2/119>\n\n\n\n",
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