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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_auto_examples_timeseries_plot_pittsburg.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_timeseries_plot_pittsburg.py:


Pittsburg Pandora vs TEMPO
===========================

Timeseries comparison of NO2 from the Pittsburg Pandora
during unvalidated release 2023-12-17 to 2023-12-30.

.. GENERATED FROM PYTHON SOURCE LINES 8-66



.. image-sg:: /auto_examples/timeseries/images/sphx_glr_plot_pittsburg_001.png
   :alt: plot pittsburg
   :srcset: /auto_examples/timeseries/images/sphx_glr_plot_pittsburg_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    import matplotlib.pyplot as plt
    import pyrsig
    import pandas as pd
    import os

    # Create an RSIG api isntance
    # Define a Time and Space Scope during unvalidated release around Pittsburg Pandora
    rsigapi = pyrsig.RsigApi(
        bdate='2023-12-28T00', edate='2023-12-29T23:59:59',
        bbox=(-80.0608, 40.3655, -79.8608, 40.5655), workdir='pitt'
    )

    # For the unvalidated data release, you do not need a key. To expand,
    # outside the release, use a key.
    # tkey = open(os.path.expandusrer('~/.tempokey'), 'r').read().strip()
    api_key = 'none'
    rsigapi.tempo_kw['api_key'] = api_key

    # Get Pandora NO2 with dates parsed and units removed from column names
    pandorakey = 'pandora.L2_rnvs3p1_8.nitrogen_dioxide_vertical_column_amount'
    pandoracol = 'nitrogen_dioxide_vertical_column_amount'
    padf = rsigapi.to_dataframe(
        pandorakey, parse_dates=True, unit_keys=False, backend='xdr'
    )

    # Get TEMPO NO2
    tempokey = 'tempo.l2.no2.vertical_column_troposphere'
    tempocol = 'no2_vertical_column_troposphere'
    tempodf = rsigapi.to_dataframe(
        tempokey, unit_keys=False, parse_dates=True, backend='xdr'
    )


    # Create spatial medians for TEMPO and Pandora
    gb = pd.Grouper(key='time', freq='1h')
    tempods = tempodf.groupby(gb).median(numeric_only=True)[tempocol]
    gb = pd.Grouper(key='time', freq='900s')
    pads = padf.groupby(gb).median(numeric_only=True)[pandoracol]

    # Create axes with shared x
    gkw = dict(bottom=0.25, left=0.05, right=0.95)
    fig, ax = plt.subplots(figsize=(12, 4), gridspec_kw=gkw)
    ax.tick_params(axis='x', labelrotation=90)

    # Add Pandora with markers at overpasses
    ax.plot(pads.index.values, pads.values, color='k', label='Pandora (15min)')

    # Add TEMPO NO2
    ax.plot(tempods.index.values, tempods.values, marker='s', color='r', label='TEMPO (w/in 0.1deg)')

    # Configure axes
    ax.set(ylabel='NO2 [molecules/cm$^2$]')
    ax.legend()

    plt.show()
    # Or save out figure
    fig.savefig('pitt.png')


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

   **Total running time of the script:** ( 0 minutes  55.526 seconds)


.. _sphx_glr_download_auto_examples_timeseries_plot_pittsburg.py:

.. only:: html

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




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

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

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

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


.. only:: html

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

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