.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/representation/plot_discrete_representation.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_representation_plot_discrete_representation.py>`
        to download the full example code. or to run this example in your browser via Binder

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

.. _sphx_glr_auto_examples_representation_plot_discrete_representation.py:


Discretized function representation
===================================

Shows how to make a discretized representation of a function.

.. GENERATED FROM PYTHON SOURCE LINES 7-13

.. code-block:: Python


    # Author: Carlos Ramos Carreño <vnmabus@gmail.com>
    # License: MIT

    # sphinx_gallery_thumbnail_number = 2








.. GENERATED FROM PYTHON SOURCE LINES 14-16

We will construct a dataset containing several sinusoidal functions with
random displacements.

.. GENERATED FROM PYTHON SOURCE LINES 16-26

.. code-block:: Python

    import numpy as np

    random_state = np.random.RandomState(0)

    grid_points = np.linspace(0, 1)
    data = np.array([
        np.sin((grid_points + random_state.randn()) * 2 * np.pi)
        for _ in range(5)
    ])








.. GENERATED FROM PYTHON SOURCE LINES 27-29

The FDataGrid class is used for datasets containing discretized functions
that are measured at the same points.

.. GENERATED FROM PYTHON SOURCE LINES 29-41

.. code-block:: Python

    from skfda import FDataGrid

    fd = FDataGrid(
        data,
        grid_points,
        dataset_name="Sinusoidal curves",
        argument_names=["t"],
        coordinate_names=["x(t)"],
    )

    fd = fd[:5]








.. GENERATED FROM PYTHON SOURCE LINES 42-43

We can plot the measured values of each function in a scatter plot.

.. GENERATED FROM PYTHON SOURCE LINES 43-48

.. code-block:: Python

    import matplotlib.pyplot as plt

    fd.scatter(s=0.5)
    plt.show()




.. image-sg:: /auto_examples/representation/images/sphx_glr_plot_discrete_representation_001.png
   :alt: Sinusoidal curves
   :srcset: /auto_examples/representation/images/sphx_glr_plot_discrete_representation_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 49-50

We can also plot the interpolated functions.

.. GENERATED FROM PYTHON SOURCE LINES 50-53

.. code-block:: Python


    fd.plot()
    plt.show()



.. image-sg:: /auto_examples/representation/images/sphx_glr_plot_discrete_representation_002.png
   :alt: Sinusoidal curves
   :srcset: /auto_examples/representation/images/sphx_glr_plot_discrete_representation_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.118 seconds)


.. _sphx_glr_download_auto_examples_representation_plot_discrete_representation.py:

.. only:: html

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

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/GAA-UAM/scikit-fda/develop?filepath=examples/representation/plot_discrete_representation.py
        :alt: Launch binder
        :width: 150 px

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

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

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

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

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

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


.. only:: html

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

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