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        "author": "Eduardo Nunes",
        "author_email": "diofanto.nunes@gmail.com",
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            "Programming Language :: Python :: 3"
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        "description": "# Periodicity\n\nUseful tools for analysis of periodicities in time series data.\n\nIncludes:\n* Auto-Correlation Function\n* Fourier methods:\n    * Lomb-Scargle periodogram\n    * Wavelet Transform (in progress)\n* Phase-folding methods:\n    * String Length\n    * Analysis of Variance (in progress)\n* Gaussian Processes:\n    * `george` implementation\n    * `celerite` implementation\n    * `pymc3` implementation (in progress)\n\n## Quick start\n### Installing current release from pypi (v0.1.0-alpha)\n    $ pip install periodicity\n### Installing current development version\n    $ git clone https://github.com/dioph/periodicity.git\n    $ cd periodicity\n    $ python setup.py install\n## Example using GP with astronomical data\n```python\nfrom periodicity.gp import *\nfrom lightkurve import search_lightcurvefile\n\nlcs = search_lightcurvefile(target=9895037, quarter=[4,5]).download_all()\nlc = lcs[0].PDCSAP_FLUX.normalize().append(lcs[1].PDCSAP_FLUX.normalize())\nlc = lc.remove_nans().remove_outliers().bin(binsize=4)\n\nt, x = lc.time, lc.flux\nx = x - x.mean()\n\nmodel = FastGPModeler(t, x)\nmodel.prior = make_gaussian_prior(t, x, pmin=2)\nmodel.minimize()\nsamples = model.mcmc(nwalkers=32, nsteps=5000, burn=500)\n\nprint('Median period: {:.2f}'.format(np.exp(np.median(samples[:, 4]))))\n```\n\n### Visualization of this example:\n\n![gp_example](https://github.com/dioph/periodicity/blob/master/figures/example2.png?raw=True)\n\n![gp_example](https://github.com/dioph/periodicity/blob/master/figures/example1.png?raw=True)\n\n\n",
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        "license": "MIT",
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        "summary": "Useful tools for analysis of periodicities in time series data",
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