.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "_examples/01_ERT/plot_04_pseudosections.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download__examples_01_ERT_plot_04_pseudosections.py>`
        to download the full example code.

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

.. _sphx_glr__examples_01_ERT_plot_04_pseudosections.py:


Visualizing ERT measurements using Pseudosections
=================================================

Pseudosections are **raw data representations** that aim to visualize a given
set of measurements in a spatial context.
It is important to remember that no inversion takes place when a pseudosection
is plotted, and spatial correlations should be interpreted carefully.

[TODO: 2 sentences on the basic assumption of gradually changing values]


Set up
------

.. GENERATED FROM PYTHON SOURCE LINES 18-23

.. code-block:: Python

    import os

    # import matplotlib.pylab as plt
    import reda
    ert = reda.ERT()







.. GENERATED FROM PYTHON SOURCE LINES 24-26

In this example output files are saved into subdirectories. In order to not
have problems with file paths, we store the original path here

.. GENERATED FROM PYTHON SOURCE LINES 26-28

.. code-block:: Python

    pwd = os.getcwd()








.. GENERATED FROM PYTHON SOURCE LINES 29-30

data import:

.. GENERATED FROM PYTHON SOURCE LINES 30-47

.. code-block:: Python


    # note that you should prefer importing the binary data as the text export
    # sometimes is missing some of the auxiliary data contained in the binary data.
    ert.import_syscal_txt('data_syscal_ert/data_normal.txt')

    # the second data set was measured in a reciprocal configuration by switching
    # the 24-electrode cables on the Syscal Pro input connectors. The parameter
    # "reciprocals" changes electrode notations.
    ert.import_syscal_txt(
        'data_syscal_ert/data_reciprocal.txt',
        reciprocals=48
    )

    # compute geometrical factors using the analytical half-space equation for a
    # spacing of 0.25 m
    ert.compute_K_analytical(spacing=0.25)





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

 .. code-block:: none


    array([-18.84955592, -18.84955592, -47.1238898 , ..., -47.1238898 ,
           -18.84955592, -18.84955592])



.. GENERATED FROM PYTHON SOURCE LINES 48-51

Type 1 Pseudo-sections
----------------------
Type 1 pseudo-section should be mainly used for Dipole-Dipole configurations

.. GENERATED FROM PYTHON SOURCE LINES 53-56

.. code-block:: Python

    with reda.CreateEnterDirectory('output_04'):
        ert.pseudosection_type1(
            column='r', filename='pseudosection_type1_log10_r.pdf', log10=True)



.. image-sg:: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_001.png
   :alt: plot 04 pseudosections
   :srcset: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 57-66

Type 2 Pseudo-sections
----------------------
Type 2 pseudo-sections computes pseudo-locations depending on the logical
electrode denotations
The x-position is computed by averaging over all four a,b,m,n numbers.
A heuristic tries to differentiate between Dipole-Dipole configurations and
all other configurations and assigns z-positions accordingly:
* Dipole-Dipole: 0.195 * abs(b-a)
* The rest: max. electrode distance * 0.3

.. GENERATED FROM PYTHON SOURCE LINES 66-71

.. code-block:: Python


    with reda.CreateEnterDirectory('output_04'):
        ert.pseudosection_type2(
            column='r', filename='pseudosection_type2_log10_r.pdf', log10=True)




.. image-sg:: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_002.png
   :alt: plot 04 pseudosections
   :srcset: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 72-78

Type 3 Pseudo-sections
----------------------
Type 3 pseudo-sections conduct a Finite-Element forward modelling, using a
provided mesh, and assigns pseudo-locations to the measurements by computing
center of masses for all configurations.
To use this type of pseudo-section, a working CRMod installation is required

.. GENERATED FROM PYTHON SOURCE LINES 78-94

.. code-block:: Python

    with reda.CreateEnterDirectory('output_04'):
        crmod_settings = {
            # link to file paths of elem.dat/elec.dat, CRTomo-specific mesh format
            'elem': pwd + os.sep + 'data_syscal_ert/elem.dat',
            'elec': pwd + os.sep + 'data_syscal_ert/elec.dat',
            'rho': 100,
            '2D': False,
            'sinke_node': None,
        }
        ert.pseudosection_type3(
            column='r',
            filename='pseudosection_type3_log10_r.pdf',
            log10=True,
            crmod_settings=crmod_settings,
        )




.. image-sg:: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_003.png
   :alt: plot 04 pseudosections
   :srcset: /_examples/01_ERT/images/sphx_glr_plot_04_pseudosections_003.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    This grid was sorted using CutMcK. The nodes were resorted!
    Rectangular grid found
    reading sensitivities





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

   **Total running time of the script:** (0 minutes 19.861 seconds)


.. _sphx_glr_download__examples_01_ERT_plot_04_pseudosections.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_04_pseudosections.ipynb <plot_04_pseudosections.ipynb>`

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

      :download:`Download Python source code: plot_04_pseudosections.py <plot_04_pseudosections.py>`


.. only:: html

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

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