.. 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_dflandrin_hyperbolic_gd.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_4_2_2_dflandrin_hyperbolic_gd.py: ========================================================== D-Flandrin Distribution of a Hyperbolic Group Delay Signal ========================================================== This example shows the D-Flandrin distribution of a signal having hyperbolic group delay. This is the only type of distribution that almost perfectly localizes signals having a group delay in :math:`1 / \sqrt{\nu}` Figure 4.22 from the tutorial. .. GENERATED FROM PYTHON SOURCE LINES 20-28 .. image-sg:: /auto_examples/images/sphx_glr_plot_4_2_2_dflandrin_hyperbolic_gd_001.png :alt: D-FLANDRIN, Signal in time :srcset: /auto_examples/images/sphx_glr_plot_4_2_2_dflandrin_hyperbolic_gd_001.png :class: sphx-glr-single-img .. code-block:: default from tftb.processing import DFlandrinDistribution from tftb.generators import gdpower sig = gdpower(128, 1.0 / 2)[0] spec = DFlandrinDistribution(sig, fmin=0.01, fmax=0.22, n_voices=128) spec.run() spec.plot() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.405 seconds) .. _sphx_glr_download_auto_examples_plot_4_2_2_dflandrin_hyperbolic_gd.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_dflandrin_hyperbolic_gd.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_4_2_2_dflandrin_hyperbolic_gd.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_