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        "author": "Pablo Huijse",
        "author_email": "pablo.huijse@gmail.com",
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            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Programming Language :: C",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Astronomy"
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        "description": "P4J\n===\n\n**Description**\n\nP4J is a python package for period detection on irregularly sampled and\nheteroscedastic time series based on Information Theoretic objective\nfunctions. P4J was developed for astronomical light curves, irregularly\nsampled time series of stellar magnitude or flux. The core of this\npackage is a class called periodogram that sweeps an array of\nperiods/frequencies looking for the one that maximizes a given criteria.\nThe main contribution of this work is a criterion for period detection\nbased on the maximization of Cauchy-Schwarz Quadratic Mutual Information\n[1]. Information theoretic criteria incorporate information on the whole\nprobability density function of the process and are more robust than\nclassical second-order statistics based criteria [2, 3, 4]. For\ncomparison P4J also incorporates other period detection methods used in\nastronomy such as the Phase Dispersion Minimization periodogram [5],\nLafler-Kinman's string length [6] and the Orthogonal multiharmonic AoV\nperiodogram [7]\n\n**Contents**\n\n-  Quadratic Mutual Information periodogram for light curves\n-  Phase Dispersion Minimization, Analysis of Variance and String Length\n   methods\n-  Basic synthetic light curve generator\n\n**Instalation**\n\nDependencies\n\n::\n\n        Numpy\n        GCC \n        Cython (optional)\n\nIf you have a UNIX system the GCC compiler is most likely already\ninstalled. If you have a Windows system you may want to install the\nMicrosoft Visual C++ (MSVC) compiler. You can find relevant information\nat: https://wiki.python.org/moin/WindowsCompilers.\n\nNote on Cython: If Cython is found in your system, pyx are compiled to c\nsources. If not the provided c sources are used.\n\nInstall from PyPI using\n\n::\n\n        pip install P4J\n\nor clone the github repository and do\n\n::\n\n        python setup.py install --user\n\n**Example**\n\nhttps://github.com/phuijse/P4J/blob/master/examples/periodogram\\_demo.ipynb\n\n**TODO**\n\n-  Multidimensional time series support\n-  More period detection criteria (Conditional Entropy)\n\n**Authors**\n\n-  Pablo Huijse pablo.huijse@gmail.com (Millennium Institute of\n   Astrophysics and Universidad de Chile)\n-  Pavlos Protopapas (Harvard Institute of Applied Computational\n   Sciences)\n-  Pablo A. Est\u00e9vez (Millennium Institute of Astrophysics and\n   Universidad de Chile)\n-  Pablo Zegers (Universidad de los Andes, Chile)\n-  Jos\u00e9 C. Pr\u00edncipe (University of Florida)\n\n(P4J = Four Pablos and one Jose)\n\n**References**\n\n1. Jos\u00e9 C. Pr\u00edncipe, \"Information Theoretic Learning: Renyi's Entropy\n   and Kernel Perspectives\", Springer, 2010\n2. Pavlos Protopapas et al., \"A Novel, Fully Automated Pipeline for\n   Period Estimation in the EROS 2 Data Set\", The Astrophysical Journal\n   Supplement, vol. 216, n. 2, 2015\n3. Pablo Huijse et al., \"Computational Intelligence Challenges and\n   Applications on Large-Scale Astronomical Time Series Databases\", IEEE\n   Mag. Computational Intelligence, vol. 9, n. 3, pp. 27-39, 2014\n4. Pablo Huijse et al., \"An Information Theoretic Algorithm for Finding\n   Periodicities in Stellar Light Curves\", IEEE Trans. Signal Processing\n   vol. 60, n. 10, pp. 5135-5145, 2012\n5. R. F. Stellingwerf, \"Period determination using phase dispersion\n   minimization\", The Astrophysical Journal, vol. 224, pp. 953-960, 1978\n6. D. Clarke, \"String/Rope length methods using the Lafler-Kinman\n   statistic\", Astronomy & Astrophysics, vol. 386, n. 2, pp. 763-774,\n   2002\n7. A. Schwarzenberg-Czerny \"Fast and Statistically Optimal Period Search\n   in Uneven Sampled Observations\", Astrophysical Journal Letters, vol.\n   460, pp. 107, 1996\n",
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