.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_4_2_2_morlet_scalogram_atoms.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_plot_4_2_2_morlet_scalogram_atoms.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_plot_4_2_2_morlet_scalogram_atoms.py:


==================================
Morlet Scalogram of Gaussian Atoms
==================================

This example demonstrates the effect of frequency-dependent smoothing that is
accomplished in a Morlet scalogram. Note that the localization at lower
frequencies is much better.

Figure 4.18 from the tutorial.

.. GENERATED FROM PYTHON SOURCE LINES 21-62



.. image-sg:: /auto_examples/images/sphx_glr_plot_4_2_2_morlet_scalogram_atoms_001.png
   :alt: Morlet scalogram of complex sinusoids, Signal in time
   :srcset: /auto_examples/images/sphx_glr_plot_4_2_2_morlet_scalogram_atoms_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    from tftb.processing import Scalogram
    from tftb.generators import atoms
    import numpy as np
    from mpl_toolkits.axes_grid1 import make_axes_locatable
    import matplotlib.pyplot as plt

    sig = atoms(128, np.array([[38, 0.1, 32, 1], [96, 0.35, 32, 1]]))
    tfr, t, freqs, _ = Scalogram(sig, fmin=0.05, fmax=0.45,
                                 time_instants=np.arange(1, 129)).run()
    t, f = np.meshgrid(t, freqs)

    fig, axContour = plt.subplots()
    axContour.contour(t, f, tfr)
    axContour.grid(True)
    axContour.set_title("Morlet scalogram of complex sinusoids")
    axContour.set_ylabel('Frequency')
    axContour.yaxis.set_label_position('right')
    axContour.set_xlabel('Time')

    divider = make_axes_locatable(axContour)
    axTime = divider.append_axes("top", 1.2, pad=0.5)
    axFreq = divider.append_axes("left", 1.2, pad=0.5)
    axTime.plot(np.real(sig))
    axTime.set_xticklabels([])
    axTime.set_xlim(0, 128)
    axTime.set_ylabel('Real part')
    axTime.set_title('Signal in time')
    axTime.grid(True)
    freq_y = np.linspace(0, 0.5, int(sig.shape[0] / 2))
    freq_x = (abs(np.fft.fftshift(np.fft.fft(sig))) ** 2)[::-1][:64]
    ix = np.logical_and(freq_y >= 0.05, freq_y <= 0.45)
    axFreq.plot(freq_x[ix], freq_y[ix])
    # axFreq.set_ylim(0.05, 0.45)
    axFreq.set_yticklabels([])
    axFreq.set_xticklabels([])
    axFreq.grid(True)
    axFreq.set_ylabel('Spectrum')
    axFreq.invert_xaxis()
    axFreq.grid(True)
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.230 seconds)


.. _sphx_glr_download_auto_examples_plot_4_2_2_morlet_scalogram_atoms.py:

.. only:: html

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


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

      :download:`Download Python source code: plot_4_2_2_morlet_scalogram_atoms.py <plot_4_2_2_morlet_scalogram_atoms.py>`

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

      :download:`Download Jupyter notebook: plot_4_2_2_morlet_scalogram_atoms.ipynb <plot_4_2_2_morlet_scalogram_atoms.ipynb>`


.. only:: html

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

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