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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_api_gallery_signal_processing_plot_signal_processing_models.py>`
        to download the full example code or to run this example in your browser via JupyterLite.

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

.. _sphx_glr_api_gallery_signal_processing_plot_signal_processing_models.py:


Sampling and a signal spectrum
==============================

Compute an inspectable engineering model using SI inputs.
See the linked domain guide for assumptions and benchmark checks.

.. GENERATED FROM PYTHON SOURCE LINES 8-23



.. image-sg:: /api/gallery/signal_processing/images/sphx_glr_plot_signal_processing_models_001.png
   :alt: plot signal processing models
   :srcset: /api/gallery/signal_processing/images/sphx_glr_plot_signal_processing_models_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np

    from engineeringkit.signal_processing import Spectrum

    fs = 1000
    t = np.arange(1000) / fs
    x = np.sin(2 * np.pi * 50 * t) + 0.4 * np.sin(2 * np.pi * 120 * t)
    spectrum = Spectrum.from_signal(x, fs)
    fig, ax = spectrum.plot()
    ax.set_xlim(0, 200)
    ax.set_ylabel("unnormalized FFT magnitude")

    plt.show()


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

   **Total running time of the script:** (0 minutes 0.062 seconds)


.. _sphx_glr_download_api_gallery_signal_processing_plot_signal_processing_models.py:

.. only:: html

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

    .. container:: lite-badge

      .. image:: images/jupyterlite_badge_logo.svg
        :target: ../../../lite/lab/index.html?path=api/gallery/signal_processing/plot_signal_processing_models.ipynb
        :alt: Launch JupyterLite
        :width: 150 px

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

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

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

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

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

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


.. only:: html

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

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