.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "_auto_examples/1_basic/plot_circadian_spectrogram.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_1_basic_plot_circadian_spectrogram.py>`
        to download the full example code

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

.. _sphx_glr__auto_examples_1_basic_plot_circadian_spectrogram.py:


Circadian soundscape
====================

When dealing with large amounts of audio recordings, visualization plays a key role to evidence
the main patterns in the data. In this example we show how to easily combine 96 audio 
files to build a visual representation of a 24 hour natural soundscape.

.. GENERATED FROM PYTHON SOURCE LINES 14-15

Load packages and set variables.

.. GENERATED FROM PYTHON SOURCE LINES 15-22

.. code-block:: Python

    import glob
    import matplotlib.pyplot as plt
    from maad import sound, util

    fpath = '../../data/indices/'  # location of audio files
    sample_len = 3  # length in seconds of each audio slice








.. GENERATED FROM PYTHON SOURCE LINES 23-24

Build a long list of audio slices of length `sample_len`.

.. GENERATED FROM PYTHON SOURCE LINES 24-32

.. code-block:: Python

    flist = glob.glob(fpath+'*.wav')
    flist.sort()
    long_wav = list()
    for idx, fname in enumerate(flist):
        s, fs = sound.load(fname)
        s = sound.trim(s, fs, 0, sample_len)
        long_wav.append(s)








.. GENERATED FROM PYTHON SOURCE LINES 33-35

Combine all audio recordings applying a crossfade and compute the spectrogram of
the resulting mixed audio.

.. GENERATED FROM PYTHON SOURCE LINES 35-39

.. code-block:: Python

    long_wav = util.crossfade_list(long_wav, fs, fade_len=0.5)
    Sxx, tn, fn, ext = sound.spectrogram(long_wav, fs, 
                                         window='hann', nperseg=1024, noverlap=512)








.. GENERATED FROM PYTHON SOURCE LINES 40-42

Display the spectrogram. We can see clearly the bird chorus at dawn (5-10 h) and 
dusk (20-21 h), as well as the wind and airplanes sounds at low frequencies.

.. GENERATED FROM PYTHON SOURCE LINES 42-46

.. code-block:: Python

    fig, ax = plt.subplots(1,1, figsize=(10,3))
    util.plot_spectrogram(Sxx, extent=[0, 24, 0, 11],
                          ax=ax, db_range=80, gain=25, colorbar=False)
    ax.set_xlabel('Time [Hours]')
    ax.set_xticks(range(0,25,4))


.. image-sg:: /_auto_examples/1_basic/images/sphx_glr_plot_circadian_spectrogram_001.png
   :alt: plot circadian spectrogram
   :srcset: /_auto_examples/1_basic/images/sphx_glr_plot_circadian_spectrogram_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 1.109 seconds)


.. _sphx_glr_download__auto_examples_1_basic_plot_circadian_spectrogram.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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