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

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

.. _sphx_glr_examples_The_GS_Standard_plot_csv_to_netcdf.py:


CSV to NetCDF conversion
-------------------------
Dataset Reference:
Burton, B.L., Minsley, B.J., Bloss, B.R., and Kress, W.H., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2018 - February 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9XBBBUU.

.. GENERATED FROM PYTHON SOURCE LINES 9-13

.. code-block:: default

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








.. GENERATED FROM PYTHON SOURCE LINES 14-16

Convert the CSV data folder to netcdf
++++++++++++++++++++++++++++++++++++++

.. GENERATED FROM PYTHON SOURCE LINES 16-45

.. code-block:: default


    # raise Exception("Get the resolve model 0 working. json files need changing etc.")

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

    metadata = join(data_path, "data//Resolve_survey_md.json")

    # Establish the Survey
    survey = Survey(metadata)

    # Define input CSV-format data file and associated variable mapping file
    d_data = join(data_path, 'data//Resolve.csv')
    d_supp = join(data_path, 'data//Resolve_data_md.json')

    # Read data and format
    survey.add_tabular(type='csv', data_filename=d_data, metadata_file=d_supp)

    # Define input CSV-format model file and associated variable mapping file
    m_data = join(data_path, 'model//Resolve_model.csv')
    m_supp = join(data_path, 'model//Resolve_model_md.json')

    # Read model data and format
    survey.add_tabular(type='csv', data_filename=m_data, metadata_file=m_supp)

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








.. GENERATED FROM PYTHON SOURCE LINES 46-47

Read in the netcdf files

.. GENERATED FROM PYTHON SOURCE LINES 47-52

.. code-block:: default

    new_survey = Survey().read_netcdf(d_out)

    print(type(new_survey))
    print(type(new_survey.tabular[0]))





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

 .. code-block:: none

    <class 'gspy.src.classes.survey.Survey.Survey'>
    <class 'xarray.core.dataset.Dataset'>




.. GENERATED FROM PYTHON SOURCE LINES 53-54

Plotting

.. GENERATED FROM PYTHON SOURCE LINES 54-65

.. code-block:: default

    plt.figure()
    new_survey.tabular[0].gs_tabular.scatter('DTM', vmin=30, vmax=50)
    plt.xlim([500000, 540000])
    plt.ylim([1175000, 1210000])

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

    # print(new_survey.tabular[0]['qd_final'])
    print(new_survey.tabular[1])

    plt.show()


.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /examples/The_GS_Standard/images/sphx_glr_plot_csv_to_netcdf_001.png
         :alt: plot csv to netcdf
         :srcset: /examples/The_GS_Standard/images/sphx_glr_plot_csv_to_netcdf_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/The_GS_Standard/images/sphx_glr_plot_csv_to_netcdf_002.png
         :alt: plot csv to netcdf
         :srcset: /examples/The_GS_Standard/images/sphx_glr_plot_csv_to_netcdf_002.png
         :class: sphx-glr-multi-img


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

 .. code-block:: none

    <xarray.Dataset>
    Dimensions:           (index: 9999, layer_depth: 30, nv: 2)
    Coordinates:
        spatial_ref       float64 ...
      * index             (index) int32 0 1 2 3 4 5 ... 9994 9995 9996 9997 9998
      * layer_depth       (layer_depth) float64 0.5 1.55 2.7 ... 109.2 119.7 132.5
      * nv                (nv) int64 0 1
        x                 (index) float64 5.36e+05 5.36e+05 ... 5.298e+05 5.297e+05
        y                 (index) float64 1.205e+06 1.205e+06 ... 1.197e+06
        z                 (index) float64 ...
    Data variables: (12/18)
        layer_depth_bnds  (layer_depth, nv) float64 ...
        LINE              (index) int64 ...
        LAT_WGS84_dd      (index) float64 ...
        LON_WGS84_dd      (index) float64 ...
        X_WGS84_Albers    (index) float64 ...
        Y_WGS84_Albers    (index) float64 ...
        ...                ...
        RESDATA           (index) float64 ...
        RESTOTAL          (index) float64 ...
        RHO_I             (index, layer_depth) float64 ...
        RHO_I_STD         (index, layer_depth) float64 ...
        DOI_CONSERVATIVE  (index) float64 ...
        DOI_STANDARD      (index) float64 ...
    Attributes:
        content:  inverted resistivity models
        comment:  This dataset includes inverted resistivity models derived from ...





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

   **Total running time of the script:** ( 0 minutes  1.642 seconds)


.. _sphx_glr_download_examples_The_GS_Standard_plot_csv_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_csv_to_netcdf.py <plot_csv_to_netcdf.py>`

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

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


.. only:: html

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

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