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

.. only:: html

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

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

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

.. _sphx_glr_source_auto_examples_retrievals_plot_cbh_sobel.py:


Cloud Base Height Retrievals
----------------------------

This example shows how to calculate the cloud base heights
using the sobel edge detection method.  This can be used
for vertical radar and lidar data.

Author: Adam Theisen

.. GENERATED FROM PYTHON SOURCE LINES 12-42



.. image-sg:: /source/auto_examples/retrievals/images/sphx_glr_plot_cbh_sobel_001.png
   :alt: SGP Ceilometer with Lidar-Calculated CBH Overplotted, SGP Ceilometer with CBH Overplotted
   :srcset: /source/auto_examples/retrievals/images/sphx_glr_plot_cbh_sobel_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    Average difference between ceilomter and sobel heights  84.37419






|

.. code-block:: Python


    from arm_test_data import DATASETS
    from matplotlib import pyplot as plt
    import act
    import numpy as np

    # Read Ceilometer data for an example
    filename_ceil = DATASETS.fetch('sgpceilC1.b1.20190101.000000.nc')
    ds = act.io.arm.read_arm_netcdf(filename_ceil)

    ds = act.retrievals.cbh.generic_sobel_cbh(
        ds, variable='backscatter', height_dim='range', var_thresh=1000.0, fill_na=0.0
    )

    # Plot the cloud base height data
    display = act.plotting.TimeSeriesDisplay(ds, subplot_shape=(1, 2), figsize=(16, 6))
    display.plot('backscatter', subplot_index=(0, 0))
    title = 'SGP Ceilometer with Lidar-Calculated CBH Overplotted'
    display.plot('first_cbh', subplot_index=(0, 0), color='k', set_title=title)

    display.plot('backscatter', subplot_index=(0, 1))
    title = 'SGP Ceilometer with CBH Overplotted'
    display.plot('cbh_sobel_backscatter', color='k', subplot_index=(0, 1), set_title=title)

    diff = ds['first_cbh'].values - ds['cbh_sobel_backscatter'].values

    print("Average difference between ceilomter and sobel heights ", np.nanmean(diff))

    ds.close()
    plt.show()


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

   **Total running time of the script:** (0 minutes 4.551 seconds)


.. _sphx_glr_download_source_auto_examples_retrievals_plot_cbh_sobel.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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