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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_examples_The_GS_Standard_plot_aseg_to_netcdf.py>`
        to download the full example code

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

.. _sphx_glr_examples_The_GS_Standard_plot_aseg_to_netcdf.py:


ASEG to NetCDF conversion
-------------------------
Dataset Reference:
Minsley, B.J., James, S.R., Bedrosian, P.A., Pace, M.D., Hoogenboom, B.E., and Burton, B.L., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9E44CTQ.

.. GENERATED FROM PYTHON SOURCE LINES 10-14

.. code-block:: default

    import matplotlib.pyplot as plt
    from os.path import join
    from gspy import Survey








.. GENERATED FROM PYTHON SOURCE LINES 15-17

Convert the ASEG data to netcdf
+++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 17-50

.. code-block:: default


    # Path to example files
    data_path = '..//..//supplemental//region//MAP'

    # Survey Metadata file
    ..//supplemental = join(data_path, "data//Tempest_survey_md.json")

    # Establish survey instance
    survey = Survey(..//supplemental)

    # Define input ASEG-format data file and associated variable mapping file
    d_data = join(data_path, 'data//Tempest.dat')
    d_supp = join(data_path, 'data//Tempest_data_md.json')

    # Read data and format as Tabular class object
    survey.add_tabular(type='aseg', data_filename=d_data, metadata_file=d_supp)

    # Define input TIF-format data file and associated variable mapping file
    d_grid_supp = join(data_path, 'data//Tempest_raster_md.json')
    # Read data and format as Griddata class object
    survey.add_raster(metadata_file = d_grid_supp)

    # Define input ASEG-format model file and associated variable mapping file
    m_data = join(data_path, 'model//Tempest_model.dat')
    m_supp = join(data_path, 'model//Tempest_model_md.json')

    # Read model data and format as Tabular class object
    survey.add_tabular(type='aseg', data_filename=m_data, metadata_file=m_supp)

    # Save NetCDF file
    d_out = join(data_path, 'data//Tempest.nc')
    survey.write_netcdf(d_out)








.. GENERATED FROM PYTHON SOURCE LINES 51-52

Read in the netcdf files

.. GENERATED FROM PYTHON SOURCE LINES 52-57

.. code-block:: default

    new_survey = Survey().read_netcdf(d_out)

    print(new_survey.raster.magnetic_tmi)

    # Once the survey is read in, we can access variables like a standard xarray dataset.




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

 .. code-block:: none

    <xarray.DataArray 'magnetic_tmi' (y: 1212, x: 599)>
    [725988 values with dtype=float64]
    Coordinates:
        spatial_ref  float64 ...
      * x            (x) float64 2.928e+05 2.934e+05 2.94e+05 ... 6.51e+05 6.516e+05
      * y            (y) float64 1.607e+06 1.606e+06 ... 8.808e+05 8.802e+05
    Attributes:
        standard_name:  total_magnetic_intensity
        null_value:     -9999.99
        units:          nT
        valid_range:    [-17504.6640625   11490.32324219]
        long_name:      Total magnetic intensity, diurnally corrected and filtered




.. GENERATED FROM PYTHON SOURCE LINES 58-59

Plotting

.. GENERATED FROM PYTHON SOURCE LINES 59-72

.. code-block:: default

    plt.figure()
    new_survey.tabular[0].gs_tabular.scatter('X_PrimaryField', cmap='jet')

    # plt.figure()
    # new_survey.raster.gs_raster.pcolor('magnetic_tmi', vmin=-1000, vmax=1000, cmap='jet')

    # plt.figure()
    # new_survey.tabular[1].gs_tabular.scatter('PhiD')

    # print(new_survey.tabular[0])
    # print(new_survey.tabular[0]['x'].attrs)
    # print(new_survey.tabular[0]['EMX_HPRG'])

    plt.show()


.. image-sg:: /examples/The_GS_Standard/images/sphx_glr_plot_aseg_to_netcdf_001.png
   :alt: plot aseg to netcdf
   :srcset: /examples/The_GS_Standard/images/sphx_glr_plot_aseg_to_netcdf_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 0 minutes  1.950 seconds)


.. _sphx_glr_download_examples_The_GS_Standard_plot_aseg_to_netcdf.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_aseg_to_netcdf.py <plot_aseg_to_netcdf.py>`

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

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


.. only:: html

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

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