Metadata-Version: 2.1
Name: periodicity
Version: 0.1.0b2
Summary: Useful tools for analysis of periodicities in time series data
Home-page: https://github.com/dioph/periodicity
Author: Eduardo Nunes
Author-email: diofanto.nunes@gmail.com
License: MIT
Description: # Periodicity
        
        Useful tools for analysis of periodicities in time series data.
        
        Includes:
        * Auto-Correlation Function
        * Fourier methods:
            * Lomb-Scargle periodogram
            * Wavelet Transform (in progress)
        * Phase-folding methods:
            * String Length
            * Analysis of Variance (in progress)
        * Gaussian Processes:
            * `george` implementation
            * `celerite` implementation
            * `pymc3` implementation (in progress)
        
        ## Quick start
        ### Installing current release from pypi (v0.1.0-alpha)
            $ pip install periodicity
        ### Installing current development version
            $ git clone https://github.com/dioph/periodicity.git
            $ cd periodicity
            $ python setup.py install
        ## Example using GP with astronomical data
        ```python
        from periodicity.gp import *
        from lightkurve import search_lightcurvefile
        
        lcs = search_lightcurvefile(target=9895037, quarter=[4,5]).download_all()
        lc = lcs[0].PDCSAP_FLUX.normalize().append(lcs[1].PDCSAP_FLUX.normalize())
        lc = lc.remove_nans().remove_outliers().bin(binsize=4)
        
        t, x = lc.time, lc.flux
        x = x - x.mean()
        
        model = FastGPModeler(t, x)
        model.prior = make_gaussian_prior(t, x, pmin=2)
        model.minimize()
        samples = model.mcmc(nwalkers=32, nsteps=5000, burn=500)
        
        print('Median period: {:.2f}'.format(np.exp(np.median(samples[:, 4]))))
        ```
        
        ### Visualization of this example:
        
        ![gp_example](https://github.com/dioph/periodicity/blob/master/figures/example2.png?raw=True)
        
        ![gp_example](https://github.com/dioph/periodicity/blob/master/figures/example1.png?raw=True)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/markdown
