Wavelet analysis for rotation period extraction
===============================================

This notebook provide an example of analysis replacing the Lomb-Scargle
periodogram by a wavelet analysis of the time series. The wavelet
analysis is not a part of the PLATO MSAP4 rotation & activity baseline
algorithms but it represents an interesting alternative in order to
assess the performances of the framework.

.. code:: ipython3

    import star_privateer as sp

A simple example
----------------

.. code:: ipython3

    import importlib
    import tqdm
    import os
    import numpy as np
    import matplotlib.pyplot as plt
    
    if not os.path.exists ('stellar_analysis_features') :
        os.mkdir ('stellar_analysis_features')
    if not os.path.exists ('stellar_analysis_plots') :
        os.mkdir ('stellar_analysis_plots')    

Our working case is KIC 3733735.

.. code:: ipython3

    filename = sp.get_target_filename (sp.timeseries, '003733735')
    t, s, dt = sp.load_resource (filename)

In order to save computing time, we rebin the data in 4-hour bins.

.. code:: ipython3

    dt *= 4
    t = np.mean (t.reshape (-1,4), axis=1)
    s = np.mean (s.reshape (-1,4), axis=1)

We now run the analysis pipeline. In particular, we can take a look at
the plots made from the different analysis methods.

.. code:: ipython3

    (p_acf, gwps, wps, acf, 
     cs, coi, features, feature_names, _) = sp.analysis_pipeline (t, s, figsize=(8,12),
                                                                 wavelet_analysis=True, plot=True,
                                                                 xlim=(0,50), normscale='log', ylogscale=True,
                                                                 add_periodogram=True)



.. image:: wavelet_analysis_files/wavelet_analysis_9_0.png


It is also possible to compute the wavelet power spectrum and plot it
independently from the other methods.

.. code:: ipython3

    dt = (t[1]-t[0])*86400
    (periods, wps, gwps, 
     coi, scales) = sp.compute_wps(s, dt, normalise=True, mother=None)

.. code:: ipython3

    fig = sp.plot_wps(t-t[0], periods, wps, gwps, coi, 
                         scales, shading='auto', color_coi='darkgrey', 
                         ylogscale=True, lw=1, normscale='log', 
                         vmin=None, vmax=None, filename=None, dpi=300,
                         figsize=(8,4), ylim=(1, 100), show_contour=False) 



.. image:: wavelet_analysis_files/wavelet_analysis_12_0.png