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

    Click :ref:`here <sphx_glr_download_auto_examples_plot_1_3_1_noisy_chirp.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_1_3_1_noisy_chirp.py:


========================
Generating a Noisy Chirp
========================

This example shows how to generate a chirp signal, with some analytical
gaussian noise, and the usage of the :ref:`sigmerge` function to combine them.

Figure 1.4 from the tutorial.



.. image:: /auto_examples/images/sphx_glr_plot_1_3_1_noisy_chirp_001.png
    :class: sphx-glr-single-img





.. code-block:: default


    from tftb.generators import fmlin, sigmerge, noisecg
    import matplotlib.pyplot as plt
    import numpy as np

    # Generate a chirp signal

    n_points = 128
    fmin, fmax = 0.0, 0.5

    signal, _ = fmlin(n_points, fmin, fmax)

    # Noisy chirp

    noisy_signal = sigmerge(signal, noisecg(128), 0)
    plt.plot(np.real(noisy_signal))
    plt.xlim(0, 128)
    plt.title('Noisy chirp')
    plt.ylabel('Real Part')
    plt.xlabel('Time')
    plt.grid()
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.149 seconds)


.. _sphx_glr_download_auto_examples_plot_1_3_1_noisy_chirp.py:


.. only :: html

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



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_1_3_1_noisy_chirp.py <plot_1_3_1_noisy_chirp.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_1_3_1_noisy_chirp.ipynb <plot_1_3_1_noisy_chirp.ipynb>`


.. only:: html

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

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