.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples\gallery_examples\003_compute_stft.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_examples_gallery_examples_003_compute_stft.py>`
        to download the full example code.

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

.. _sphx_glr_examples_gallery_examples_003_compute_stft.py:


.. _compute_stft_example:

Spectrogram: compute the STFT and ISTFT
---------------------------------------

This example shows how to compute the short-time Fourier transform (STFT) of a signal, that is, its
`spectrogram`. It also shows how to use the inverse short-time Fourier transform (ISTFT) to get the
signal corresponding to a given spectrogram.

.. GENERATED FROM PYTHON SOURCE LINES 36-40

Set up analysis
~~~~~~~~~~~~~~~
Setting up the analysis consists of loading Ansys libraries, connecting to the
DPF server, and retrieving the example files.

.. GENERATED FROM PYTHON SOURCE LINES 40-51

.. code-block:: Python


    # Load Ansys libraries.
    from ansys.sound.core.examples_helpers import download_flute_wav
    from ansys.sound.core.server_helpers import connect_to_or_start_server
    from ansys.sound.core.signal_utilities import LoadWav
    from ansys.sound.core.spectrogram_processing import Istft, Stft


    # Connect to a remote DPF server or start a local DPF server.
    my_server, my_license_context = connect_to_or_start_server(use_license_context=True)








.. GENERATED FROM PYTHON SOURCE LINES 55-61

Load a signal
~~~~~~~~~~~~~
Load a signal from a WAV file using the ``LoadWav`` class. It is returned as a DPF
field container. For more information, see `fields_container
<https://dpf.docs.pyansys.com/version/stable/api/ansys.dpf.core.operators.utility.fields_container.html>`_
in the DPF-Core API documentation.

.. GENERATED FROM PYTHON SOURCE LINES 61-73

.. code-block:: Python


    # Return the input data of the example file
    path_flute_wav = download_flute_wav(server=my_server)

    # Load the WAV file
    wav_loader = LoadWav(path_flute_wav)
    wav_loader.process()
    fc_signal = wav_loader.get_output()

    # Plot the input signal
    wav_loader.plot()




.. image-sg:: /examples/gallery_examples/images/sphx_glr_003_compute_stft_001.png
   :alt: flute
   :srcset: /examples/gallery_examples/images/sphx_glr_003_compute_stft_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 74-76

Compute and plot STFT
~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 76-88

.. code-block:: Python


    # Instantiate an instance of the ``Stft`` class using the previously loaded signal
    # as an input. Use an FFT size of 1024 points and then display the STFT colormap.

    stft = Stft(fc_signal, fft_size=1024)

    # Process the STFT
    stft.process()

    # Plot the output
    stft.plot()




.. image-sg:: /examples/gallery_examples/images/sphx_glr_003_compute_stft_002.png
   :alt: STFT, Amplitude, Phase
   :srcset: /examples/gallery_examples/images/sphx_glr_003_compute_stft_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 89-91

Modify the STFT parameters using the setters of the ``Stft`` class.
Display the new STFT colormap.

.. GENERATED FROM PYTHON SOURCE LINES 91-102

.. code-block:: Python


    stft.fft_size = 4096
    stft.window_overlap = 0.95
    stft.window_type = "TRIANGULAR"

    # Reprocess the STFT with the new parameters
    stft.process()

    # Plot the modified output
    stft.plot()




.. image-sg:: /examples/gallery_examples/images/sphx_glr_003_compute_stft_003.png
   :alt: STFT, Amplitude, Phase
   :srcset: /examples/gallery_examples/images/sphx_glr_003_compute_stft_003.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 103-105

Compute and plot ISTFT
~~~~~~~~~~~~~~~~~~~~~~

.. GENERATED FROM PYTHON SOURCE LINES 105-117

.. code-block:: Python


    # Obtain a time-domain signal using the ``Istft`` class.
    # The input of the ``Istft`` class is the output STFT object previously computed.

    fc_stft = stft.get_output()

    # Instantiate the class
    istft = Istft(fc_stft)

    # Process the ISTFT
    istft.process()








.. GENERATED FROM PYTHON SOURCE LINES 118-119

Plot the output, which is the original signal.

.. GENERATED FROM PYTHON SOURCE LINES 119-121

.. code-block:: Python


    istft.plot()



.. image-sg:: /examples/gallery_examples/images/sphx_glr_003_compute_stft_004.png
   :alt: 003 compute stft
   :srcset: /examples/gallery_examples/images/sphx_glr_003_compute_stft_004.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 38.114 seconds)


.. _sphx_glr_download_examples_gallery_examples_003_compute_stft.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: 003_compute_stft.ipynb <003_compute_stft.ipynb>`

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

      :download:`Download Python source code: 003_compute_stft.py <003_compute_stft.py>`

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

      :download:`Download zipped: 003_compute_stft.zip <003_compute_stft.zip>`


.. only:: html

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

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