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

.. only:: html

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

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

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

.. _sphx_glr_examples_plot_annual_variation.py:


Annual variation
----------------

This example demonstrates how to calculate the
difference from the annual mean at a single location.

.. GENERATED FROM PYTHON SOURCE LINES 9-52



.. image-sg:: /examples/images/sphx_glr_plot_annual_variation_001.png
   :alt: plot annual variation
   :srcset: /examples/images/sphx_glr_plot_annual_variation_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    import pymsis


    lon = 0
    lat = 0
    alt = 200
    f107 = 150
    f107a = 150
    ap = 7
    # One years worth of data at the 12th hour every day
    dates = np.arange("2003-01", "2004-01", dtype="datetime64[D]") + np.timedelta64(12, "h")
    ndates = len(dates)
    # (F107, F107a, ap) all need to be specified at the same length as dates
    f107s = [f107] * ndates
    f107as = [f107a] * ndates
    aps = [[ap] * 7] * ndates

    output = pymsis.calculate(dates, lon, lat, alt, f107s, f107as, aps)
    #  output is now of the shape (ndates, 1, 1, 1, 11)
    # Get rid of the single dimensions
    output = np.squeeze(output)

    # Lets get the percent variation from the annual mean for each variable
    variation = 100 * (output / output.mean(axis=0) - 1)

    _, ax = plt.subplots()
    for variable in pymsis.Variable:
        if variable.name == "NO":
            # There is currently no NO data
            continue
        ax.plot(dates, variation[:, variable], label=variable.name)

    ax.legend(
        loc="upper center", bbox_to_anchor=(0.5, 1.15), fancybox=True, shadow=True, ncol=5
    )
    ax.set_xlabel(f"Longitude: {lon}, Latitude: {lat}, Altitude: {alt} km")
    ax.set_ylabel("Difference from annual mean (%)")

    plt.show()


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

   **Total running time of the script:** (0 minutes 0.115 seconds)


.. _sphx_glr_download_examples_plot_annual_variation.py:

.. only:: html

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

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

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_annual_variation.zip <plot_annual_variation.zip>`


.. only:: html

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

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