.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "tutorial-config/eg_03_quick_configuration.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_tutorial-config_eg_03_quick_configuration.py>`
        to download the full example code

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

.. _sphx_glr_tutorial-config_eg_03_quick_configuration.py:


Quick configuration
^^^^^^^^^^^^^^^^^^^

If no configuration is passed, the quick processing functions in resistics will
use the default configuration. However, it is possible to use a different
configuration if preferred.

The dataset in this example has been provided for use by the SAMTEX consortium.
For more information, please refer to [Jones2009]_. Additional details about the
dataset can be found at https://www.mtnet.info/data/kap03/kap03.html.

.. GENERATED FROM PYTHON SOURCE LINES 13-22

.. code-block:: default

    from pathlib import Path
    import seedir as sd
    import plotly
    import resistics.letsgo as letsgo
    from resistics.config import Configuration
    from resistics.time import InterpolateNans, RemoveMean, Multiply
    from resistics.decimate import DecimationSetup
    from resistics.window import WindowerTarget








.. GENERATED FROM PYTHON SOURCE LINES 23-24

Define the data path. This is dependent on where the data is stored.

.. GENERATED FROM PYTHON SOURCE LINES 24-27

.. code-block:: default

    time_data_path = Path("..", "..", "data", "time", "quick", "kap123")
    sd.seedir(str(time_data_path), style="emoji")





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 .. code-block:: none

    📁 kap123/
    ├─📄 data.npy
    └─📄 metadata.json




.. GENERATED FROM PYTHON SOURCE LINES 28-29

Quick calculation of the transfer function using default parameters.

.. GENERATED FROM PYTHON SOURCE LINES 29-42

.. code-block:: default

    soln_default = letsgo.quick_tf(time_data_path)
    fig = soln_default.tf.plot(
        soln_default.freqs,
        soln_default.components,
        to_plot=["ExHy", "EyHx"],
        x_lim=[1, 5],
        res_lim=[0, 4],
        legend="Default config",
        symbol="circle",
    )
    fig.update_layout(height=800)
    plotly.io.show(fig)




.. raw:: html
    :file: images/sphx_glr_eg_03_quick_configuration_001.html


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.. GENERATED FROM PYTHON SOURCE LINES 43-51

Looking at the transfer function, it's clear that the phases are in the wrong
quadrants. A new time process can be added to correct this by multiplying the
electric channels by -1.

Further, let's use a different windower that will change the window size
(subject to a minimum) to try and generate a target number of windows. The
WindowTarget ignores the min_size in the WindowSetup and uses its own. This
alternative windower will be combined with a modified decimation setup.

.. GENERATED FROM PYTHON SOURCE LINES 51-63

.. code-block:: default

    config = Configuration(
        name="custom",
        time_processors=[
            InterpolateNans(),
            RemoveMean(),
            Multiply(multiplier={"Ex": -1, "Ey": -1}),
        ],
        dec_setup=DecimationSetup(n_levels=3, per_level=7),
        windower=WindowerTarget(target=2_000, min_size=180),
    )
    config.summary()





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 .. code-block:: none

    {
        'name': 'custom',
        'time_readers': [
            {
                'name': 'TimeReaderAscii',
                'apply_scalings': True,
                'extension': '.txt',
                'delimiter': None,
                'n_header': 0
            },
            {
                'name': 'TimeReaderNumpy',
                'apply_scalings': True,
                'extension': '.npy'
            }
        ],
        'time_processors': [
            {'name': 'InterpolateNans'},
            {'name': 'RemoveMean'},
            {'name': 'Multiply', 'multiplier': {'Ex': -1.0, 'Ey': -1.0}}
        ],
        'dec_setup': {
            'name': 'DecimationSetup',
            'n_levels': 3,
            'per_level': 7,
            'min_samples': 256,
            'div_factor': 2,
            'eval_freqs': None
        },
        'decimator': {
            'name': 'Decimator',
            'resample': True,
            'max_single_factor': 3
        },
        'win_setup': {
            'name': 'WindowSetup',
            'min_size': 128,
            'min_olap': 32,
            'win_factor': 4,
            'olap_proportion': 0.25,
            'min_n_wins': 5,
            'win_sizes': None,
            'olap_sizes': None
        },
        'windower': {
            'name': 'WindowerTarget',
            'target': 2000,
            'min_size': 180,
            'olap_proportion': 0.25
        },
        'fourier': {
            'name': 'FourierTransform',
            'win_fnc': ['kaiser', 14],
            'detrend': 'linear',
            'workers': -2
        },
        'spectra_processors': [],
        'evals': {'name': 'EvaluationFreqs'},
        'sensor_calibrator': {
            'name': 'SensorCalibrator',
            'chans': None,
            'readers': [
                {
                    'name': 'SensorCalibrationJSON',
                    'extension': '.json',
                    'file_str': 'IC_$sensor$extension'
                }
            ]
        },
        'tf': {
            'name': 'ImpedanceTensor',
            'variation': 'default',
            'out_chans': ['Ex', 'Ey'],
            'in_chans': ['Hx', 'Hy'],
            'cross_chans': ['Hx', 'Hy'],
            'n_out': 2,
            'n_in': 2,
            'n_cross': 2
        },
        'regression_preparer': {'name': 'RegressionPreparerGathered'},
        'solver': {
            'name': 'SolverScikitTheilSen',
            'fit_intercept': False,
            'normalize': False,
            'n_jobs': -2,
            'max_subpopulation': 2000,
            'n_subsamples': None
        }
    }




.. GENERATED FROM PYTHON SOURCE LINES 64-66

Quick calculate the impedance tensor using the new custom configuration and
plot the result.

.. GENERATED FROM PYTHON SOURCE LINES 66-79

.. code-block:: default

    soln_custom = letsgo.quick_tf(time_data_path, config)
    fig = soln_custom.tf.plot(
        soln_custom.freqs,
        soln_custom.components,
        to_plot=["ExHy", "EyHx"],
        x_lim=[1, 5],
        res_lim=[0, 4],
        phs_lim=[0, 100],
        legend="Custom config",
        symbol="diamond",
    )
    fig.update_layout(height=800)
    plotly.io.show(fig)



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    :file: images/sphx_glr_eg_03_quick_configuration_002.html


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.. _sphx_glr_download_tutorial-config_eg_03_quick_configuration.py:


.. only :: html

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



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

     :download:`Download Python source code: eg_03_quick_configuration.py <eg_03_quick_configuration.py>`



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

     :download:`Download Jupyter notebook: eg_03_quick_configuration.ipynb <eg_03_quick_configuration.ipynb>`


.. only:: html

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

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