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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_generated_gallery_system_system-tracking.py>`
        to download the full example code

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

.. _sphx_glr_generated_gallery_system_system-tracking.py:


Detect if a System is Tracking
==============================

Identifying if a system is tracking or fixed tilt

.. GENERATED FROM PYTHON SOURCE LINES 9-16

It is valuable to identify if a system is fixed tilt or tracking for
future analysis. This example shows how to use
:py:func:`pvanalytics.system.is_tracking_envelope` to determine if a
system is tracking or not by fitting data to a maximum power or
irradiance envelope, and fitting this envelope to quadratic and
quartic curves. The r^2 output from these fits is used to determine
if the system fits a tracking or fixed-tilt profile.

.. GENERATED FROM PYTHON SOURCE LINES 16-25

.. code-block:: default


    import pvanalytics
    from pvanalytics.system import is_tracking_envelope
    from pvanalytics.features.clipping import geometric
    from pvanalytics.features.daytime import power_or_irradiance
    import pandas as pd
    import pathlib
    import matplotlib.pyplot as plt








.. GENERATED FROM PYTHON SOURCE LINES 26-32

First, we import an AC power data stream from the SERF East site located at
NREL. This data set is publicly available via the PVDAQ database in the
DOE Open Energy Data Initiative (OEDI)
(https://data.openei.org/submissions/4568), under system ID 50.
This data is timezone-localized. This particular data stream is associated
with a fixed-tilt system.

.. GENERATED FROM PYTHON SOURCE LINES 32-45

.. code-block:: default


    pvanalytics_dir = pathlib.Path(pvanalytics.__file__).parent
    ac_power_file = pvanalytics_dir / 'data' / \
        'serf_east_15min_ac_power.csv'
    data = pd.read_csv(ac_power_file, index_col=0, parse_dates=True)
    data = data.sort_index()
    time_series = data['ac_power']
    time_series = time_series.asfreq('15T')

    # Plot the first few days of the time series to visualize it
    time_series[:pd.to_datetime("2016-07-06 00:00:00-07:00")].plot()
    plt.show()




.. image-sg:: /generated/gallery/system/images/sphx_glr_system-tracking_001.png
   :alt: system tracking
   :srcset: /generated/gallery/system/images/sphx_glr_system-tracking_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 46-49

Run the clipping and the daytime filters on the time series.
Both of these masks will be used as inputs to the
:py:func:`pvanalytics.system.is_tracking_envelope` function.

.. GENERATED FROM PYTHON SOURCE LINES 49-56

.. code-block:: default


    # Generate the daylight mask for the AC power time series
    daytime_mask = power_or_irradiance(time_series)

    # Generate the clipping mask for the time series
    clipping_mask = geometric(time_series)








.. GENERATED FROM PYTHON SOURCE LINES 57-60

Now, we use :py:func:`pvanalytics.system.is_tracking_envelope` to
identify if the data stream is associated with a tracking or fixed-tilt
system.

.. GENERATED FROM PYTHON SOURCE LINES 60-66

.. code-block:: default


    predicted_mounting_config = is_tracking_envelope(time_series,
                                                     daytime_mask,
                                                     clipping_mask)

    print("Estimated mounting configuration: " + predicted_mounting_config.name)




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

 .. code-block:: none

    Estimated mounting configuration: FIXED





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

   **Total running time of the script:** ( 0 minutes  1.197 seconds)


.. _sphx_glr_download_generated_gallery_system_system-tracking.py:

.. only:: html

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


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

      :download:`Download Python source code: system-tracking.py <system-tracking.py>`

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

      :download:`Download Jupyter notebook: system-tracking.ipynb <system-tracking.ipynb>`


.. only:: html

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

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