.. 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_5_4_2_hough_simultaneous_chirp.py: ================================================= Hough-Wigner Transform of Two Simultaneous Chirps ================================================= Compute the Hough transform of the Wigner-Ville distribution of a signal composed of two chirps. Two peaks corresponding to the two chirps can be seen. Figure 5.6 from the tutorial. .. image:: /auto_examples/images/sphx_glr_plot_5_4_2_hough_simultaneous_chirp_001.png :class: sphx-glr-single-img .. code-block:: default from tftb.generators import fmlin, sigmerge from tftb.processing.cohen import WignerVilleDistribution from tftb.processing.postprocessing import hough_transform import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt N = 64 sig = sigmerge(fmlin(N, 0, 0.4)[0], fmlin(N, 0.3, 0.5)[0], 1) tfr, _, _ = WignerVilleDistribution(sig).run() ht, rho, theta = hough_transform(tfr, N, N) theta, rho = np.meshgrid(theta, rho) fig = plt.figure() ax = fig.gca(projection='3d') ax.plot_wireframe(theta, rho, ht) ax.set_xlabel('Theta') ax.set_ylabel('Rho') plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 2.401 seconds) .. _sphx_glr_download_auto_examples_plot_5_4_2_hough_simultaneous_chirp.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_5_4_2_hough_simultaneous_chirp.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_5_4_2_hough_simultaneous_chirp.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_