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

.. only:: html

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

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

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

.. _sphx_glr_examples_ucb_plot_galactic_coordinates.py:


3D map of the galaxy
=====================

Create inferred map of the galaxy from chirping binaries

.. GENERATED FROM PYTHON SOURCE LINES 9-12

This example demonstrates using chirping binaries to map the galaxy.
Samples from the high SNR chirping binaries are reparameterized into galactic cartesian coordinates and plotted.
Import modules

.. GENERATED FROM PYTHON SOURCE LINES 12-107

.. code-block:: default

    import matplotlib.cm as cm
    import matplotlib.colors as colors
    import matplotlib.pyplot as plt
    import numpy as np
    from matplotlib.patches import Ellipse

    from lisacattools import confidence_ellipse
    from lisacattools import convert_ecliptic_to_galactic
    from lisacattools import convert_galactic_to_cartesian
    from lisacattools import get_DL
    from lisacattools.catalog import GWCatalogs
    from lisacattools.catalog import GWCatalogType

    # Start by loading the main catalog file processed from GBMCMC outputs
    catPath = "../../tutorial/data/ucb"
    catalogs = GWCatalogs.create(GWCatalogType.UCB, catPath, "cat15728640_v2.h5")
    final_catalog = catalogs.get_last_catalog()
    detections_attr = final_catalog.get_attr_detections()
    detections = final_catalog.get_detections(detections_attr)

    # Get dataframe of only high SNR chirping events
    selected_detections = detections[
        (detections["Frequency Derivative"] > 0) & (detections["SNR"] > 100)
    ]

    # set up the figure
    fig, axs = plt.subplots(1, 2, figsize=(12, 6), dpi=100)

    axs[0].grid()
    axs[1].grid()

    axs[0].set(
        xlim=(-10, 10),
        ylim=(-10, 10),
        xlabel=r"$x_{\rm GC}\ [{\rm kpc}]$",
        ylabel=r"$y_{\rm GC}\ [{\rm kpc}]$",
    )
    axs[1].set(
        xlim=(-10, 10),
        ylim=(-10, 10),
        xlabel=r"$x_{\rm GC}\ [{\rm kpc}]$",
        ylabel=r"$z_{\rm GC}\ [{\rm kpc}]$",
    )


    # color ellipses by log SNR
    cNorm = colors.LogNorm(
        vmin=selected_detections["SNR"].min(),
        vmax=selected_detections["SNR"].max(),
    )
    scalarMap = cm.ScalarMappable(norm=cNorm, cmap=plt.cm.get_cmap("plasma_r"))
    cbar = fig.colorbar(scalarMap)
    cbar.set_label("SNR")

    # plot 1-sigma ellipses of 3D localization for each source
    sources = list(selected_detections.index)
    for source in sources:

        # get chain samples
        samples = final_catalog.get_source_samples(source)
        # convert from ecliptic to galactic coordinates
        convert_ecliptic_to_galactic(samples)
        # enforce GR prior
        samples = samples[samples["Frequency Derivative"] > 0]
        # add distance parameter
        get_DL(samples)

        # add galactic cartesian coordinates
        convert_galactic_to_cartesian(
            samples,
            "Galactic Longitude",
            "Galactic Latitude",
            "Luminosity Distance",
        )

        # plot galactic X-Y plane
        confidence_ellipse(
            samples[["X", "Y"]],
            axs[0],
            n_std=1.0,
            edgecolor=scalarMap.to_rgba(np.array(detections.loc[source].SNR)),
            linewidth=1.0,
        )

        # plot galactic X-Z plane
        confidence_ellipse(
            samples[["X", "Z"]],
            axs[1],
            n_std=1.0,
            edgecolor=scalarMap.to_rgba(np.array(detections.loc[source].SNR)),
            linewidth=1.0,
        )


    plt.show()



.. image:: /examples_ucb/images/sphx_glr_plot_galactic_coordinates_001.png
    :alt: plot galactic coordinates
    :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    /home/runner/work/lisacattools/lisacattools/docs/examples_ucb/plot_galactic_coordinates.py:63: MatplotlibDeprecationWarning: Unable to determine Axes to steal space for Colorbar. Using gca(), but will raise in the future. Either provide the *cax* argument to use as the Axes for the Colorbar, provide the *ax* argument to steal space from it, or add *mappable* to an Axes.
      cbar = fig.colorbar(scalarMap)





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

   **Total running time of the script:** ( 0 minutes  18.880 seconds)


.. _sphx_glr_download_examples_ucb_plot_galactic_coordinates.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_galactic_coordinates.py <plot_galactic_coordinates.py>`



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

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


.. only:: html

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

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