.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples_ucb/plot_time_evolving_parameters.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_examples_ucb_plot_time_evolving_parameters.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_ucb_plot_time_evolving_parameters.py:


Connecting catalogs
===================

Locate a source in an updated catalog and compare parameters.

.. GENERATED FROM PYTHON SOURCE LINES 9-12

This example shows how to find a particular source after the catalog has been updated
based on the `parent` meta data, and produces a corner plot showing how the parameter
estimation evolves with time.

.. GENERATED FROM PYTHON SOURCE LINES 12-22

.. code-block:: default

    import os

    import numpy as np
    import pandas as pd
    from chainconsumer import ChainConsumer

    from lisacattools.catalog import GWCatalog
    from lisacattools.catalog import GWCatalogs
    from lisacattools.catalog import GWCatalogType








.. GENERATED FROM PYTHON SOURCE LINES 23-24

Start by loading the 03 month catalog and selecting a source to follow

.. GENERATED FROM PYTHON SOURCE LINES 24-41

.. code-block:: default

    catPath = "../../tutorial/data/ucb"

    meta_catalog = GWCatalogs.create(
        GWCatalogType.UCB, catPath, "cat7864320_v3.h5"
    )
    old_catalog = meta_catalog.get_last_catalog()

    detections_attr = old_catalog.get_attr_detections()
    old_cat = old_catalog.get_detections(detections_attr)

    # pick a source, any source
    old_source = "LDC0027827268"
    sample_attr = old_catalog.get_attr_source_samples(old_source)
    old_samples = old_catalog.get_source_samples(old_source, sample_attr)

    old_cat.loc[[old_source], ["SNR", "Frequency", "Amplitude"]]






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>SNR</th>
          <th>Frequency</th>
          <th>Amplitude</th>
        </tr>
        <tr>
          <th>name</th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>LDC0027827268</th>
          <td>69.6613</td>
          <td>0.002783</td>
          <td>2.514195e-22</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 42-43

Load the 06 month catalog and find the current name for `old_source`

.. GENERATED FROM PYTHON SOURCE LINES 43-60

.. code-block:: default

    meta_catalog = GWCatalogs.create(
        GWCatalogType.UCB, catPath, "cat15728640_v2.h5"
    )
    new_catalog = meta_catalog.get_last_catalog()

    detections_attr = new_catalog.get_attr_detections()
    new_cat = new_catalog.get_detections(detections_attr)

    # select source that lists old_source as parent
    new_cat = new_cat[(new_cat["parent"] == old_source)]
    new_source = new_cat.index.values[0]

    sample_attr = new_catalog.get_attr_source_samples(new_source)
    new_samples = new_catalog.get_source_samples(new_source, sample_attr)

    new_cat.loc[[new_source], ["parent", "SNR", "Frequency", "Amplitude"]]






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>parent</th>
          <th>SNR</th>
          <th>Frequency</th>
          <th>Amplitude</th>
        </tr>
        <tr>
          <th>name</th>
          <th></th>
          <th></th>
          <th></th>
          <th></th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>LDC0027827155</th>
          <td>LDC0027827268</td>
          <td>101.446</td>
          <td>0.002783</td>
          <td>2.147934e-22</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 61-62

Plot the posteriors for the 03 and 06 months inferences for the source

.. GENERATED FROM PYTHON SOURCE LINES 62-104

.. code-block:: default


    c = ChainConsumer()

    # Select which parameters to plot & format the axes labels
    parameters = [
        "Frequency",
        "Amplitude",
        "Ecliptic Longitude",
        "Ecliptic Latitude",
        "Inclination",
    ]
    parameter_labels = [
        r"$f_0\ [{\rm Hz}]$",
        r"$\mathcal{A}$",
        r"$\phi\ [{\rm rad}]$",
        r"$\theta\ [{\rm rad}]$",
        r"$\iota\ [{\rm rad}]$",
    ]


    # add chains
    c.add_chain(
        old_samples[parameters].values,
        parameters=parameter_labels,
        cloud=True,
        name=old_source,
    )
    c.add_chain(
        new_samples[parameters].values,
        parameters=parameter_labels,
        cloud=True,
        name=new_source,
    )

    # plot!
    c.configure(
        sigmas=[1, 2, 3],
        linestyles=["-", "--"],
        legend_color_text=False,
        legend_kwargs={"fontsize": 18},
    )
    fig = c.plotter.plot(figsize=1.5)



.. image:: /examples_ucb/images/sphx_glr_plot_time_evolving_parameters_001.png
    :alt: plot time evolving parameters
    :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  2.785 seconds)


.. _sphx_glr_download_examples_ucb_plot_time_evolving_parameters.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_time_evolving_parameters.py <plot_time_evolving_parameters.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_time_evolving_parameters.ipynb <plot_time_evolving_parameters.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_