.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/austin.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_austin.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_austin.py:


================
Austin Weather
================

.. GENERATED FROM PYTHON SOURCE LINES 6-14

.. code-block:: Python

    if __name__ == '__main__':
        import os
        import site
        # add parent directory to path
        et_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
        print(et_dir)
        site.addsitedir(et_dir)



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

.. code-block:: pytb

    Traceback (most recent call last):
      File "/home/docs/checkouts/readthedocs.org/user_builds/etutil/checkouts/latest/examples/austin.py", line 10, in <module>
        et_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
    NameError: name '__file__' is not defined




.. GENERATED FROM PYTHON SOURCE LINES 15-58

.. code-block:: Python

    import pandas as pd

    from ETUtil import PenmanMonteith


    # This example shows when solar radiation is not given then it can be calculated from temperature data.

    fpath = "/mnt/datawaha/hyex/atr/datasets_1923_3359_austin_weather.csv"
    # https://www.kaggle.com/grubenm/austin-weather?select=austin_weather.csv
    df = pd.read_csv(fpath, na_values="-")
    df.index = pd.to_datetime(df['Date'])
    df.index.freq = pd.infer_freq(df.index)

    df = df[['TempHighF', 'TempLowF', 'DewPointAvgF', 'HumidityAvgPercent', 'WindAvgMPH']]

    df = df.rename(columns={'TempHighF': 'tmax',
                            'TempLowF': 'tmin',
                            'HumidityAvgPercent': 'rel_hum',
                            'DewPointAvgF': 'tdew',
                            'WindAvgMPH': 'wind_speed',
                            })

    df = df.apply(pd.to_numeric)

    units = {'tmin': 'Fahrenheit',
             'tmax': 'Fahrenheit',
             'rel_hum': 'percent',
             'tdew': 'Fahrenheit',
             'wind_speed': 'MilesPerHour'}

    constants = dict()
    constants['lat_dec_deg'] = 30.266666
    constants['altitude'] = 305
    # These values are not accurate
    constants['a_s'] = 0.23
    constants['albedo'] = 0.23
    constants['b_s'] = 0.5
    constants['wind_z'] = 2

    eto_model = PenmanMonteith(df, units=units, constants=constants, verbosity=2)
    pet = eto_model()
    eto_model.plot_outputs()
    eto_model.plot_inputs()


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

   **Total running time of the script:** (0 minutes 0.001 seconds)


.. _sphx_glr_download_auto_examples_austin.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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