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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_data_processing_data_smoothing.py:


Data Smoothing
==============

This example shows how to smooth a dataset.

.. GENERATED FROM PYTHON SOURCE LINES 9-10

Load the data

.. GENERATED FROM PYTHON SOURCE LINES 10-20

.. code-block:: Python

    import lumispy as lum

    cl1 = lum.data.asymmetric_peak_map()
    cl1 = cl1.remove_background(signal_range=(550.0, 620.0), background_type="Offset")
    cl1 = cl1.isig[:-3]
    cl1.spikes_removal_tool(interactive=False)

    cl2 = cl1.deepcopy()
    cl3 = cl1.deepcopy()








.. GENERATED FROM PYTHON SOURCE LINES 21-22

Display the original data

.. GENERATED FROM PYTHON SOURCE LINES 22-25

.. code-block:: Python


    cl1.inav[0, 0].plot()




.. image-sg:: /auto_examples/data_processing/images/sphx_glr_data_smoothing_001.png
   :alt: 880_30K_map2a Signal
   :srcset: /auto_examples/data_processing/images/sphx_glr_data_smoothing_001.png, /auto_examples/data_processing/images/sphx_glr_data_smoothing_001_5_00x.png 5.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 26-29

The current dataset is quite noisy.
One way to improve that is by smoothing the data using :py:meth:`hyperspy.api.signals.Signal1D.smooth_lowess`
(see docstring for detailed explanation of the parameters).

.. GENERATED FROM PYTHON SOURCE LINES 29-34

.. code-block:: Python


    cl1.smooth_lowess(smoothing_parameter=0.1, number_of_iterations=2)

    cl1.inav[0, 0].plot()




.. image-sg:: /auto_examples/data_processing/images/sphx_glr_data_smoothing_002.png
   :alt: 880_30K_map2a Signal
   :srcset: /auto_examples/data_processing/images/sphx_glr_data_smoothing_002.png, /auto_examples/data_processing/images/sphx_glr_data_smoothing_002_5_00x.png 5.00x
   :class: sphx-glr-single-img


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

 .. code-block:: none


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.. GENERATED FROM PYTHON SOURCE LINES 35-38

Another algorithm which can be used is :py:meth:`hyperspy.api.signals.Signal1D.smooth_savitzky_golay`.

This way is often better to maintain the shape of the peaks, but it can be less efficient in removing noise.

.. GENERATED FROM PYTHON SOURCE LINES 38-43

.. code-block:: Python


    cl2.smooth_savitzky_golay(window_length=11, polynomial_order=3)

    cl2.inav[0, 0].plot()




.. image-sg:: /auto_examples/data_processing/images/sphx_glr_data_smoothing_003.png
   :alt: 880_30K_map2a Signal
   :srcset: /auto_examples/data_processing/images/sphx_glr_data_smoothing_003.png, /auto_examples/data_processing/images/sphx_glr_data_smoothing_003_5_00x.png 5.00x
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 44-47

Also :py:meth:`hyperspy.api.signals.Signal1D.smooth_tv` can be used.

This method is very efficient in removing noise while preserving the edges of the peaks.

.. GENERATED FROM PYTHON SOURCE LINES 47-52

.. code-block:: Python


    cl3.smooth_tv(smoothing_parameter=10.0)

    cl3.inav[0, 0].plot()




.. image-sg:: /auto_examples/data_processing/images/sphx_glr_data_smoothing_004.png
   :alt: 880_30K_map2a Signal
   :srcset: /auto_examples/data_processing/images/sphx_glr_data_smoothing_004.png, /auto_examples/data_processing/images/sphx_glr_data_smoothing_004_5_00x.png 5.00x
   :class: sphx-glr-single-img


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

 .. code-block:: none


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.. GENERATED FROM PYTHON SOURCE LINES 53-55

To evaluate optimum parameters, each of the algorithms is run interactively if at least one parameter is missing in
the function call and thus the result of the smoothing can be directly previewed while adapting the parameters.


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

   **Total running time of the script:** (0 minutes 14.014 seconds)


.. _sphx_glr_download_auto_examples_data_processing_data_smoothing.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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