Spatial components of the motion energy filters

This example shows the spatial components of the spatio-temporal filters used in motion energy features. It does not show the temporal components, since this gallery does not support animation. To visualize the filters with their temporal components, you can use moten.viz.plot_3dgabor(). Here we demonstrate how the spatial filters vary in term of spatial frequencies, locations, and directions.

First, let’s define a motion energy pyramid, using MotionEnergyPyramid. It defines a set of spatio-temporal Gabor filters.

import moten
pyramid = moten.pyramids.MotionEnergyPyramid(stimulus_vhsize=(300, 400),

Then, we define a plotting function, to show the spatial part of these spatio-temporal Gabor filters.

import matplotlib.pyplot as plt  # noqa

def plot_spatial_gabors(pyramid, indices):
    """Plot the two quadrature spatial components of a list of Gabor filters.

    Note this only show the spatial components of the spatio-temporal filters.

    pyramid : moten.pyramid.MotionEnergyPyramid instance
    indices : list of int
    vdim = pyramid.definition['vdim']

    size = 0.6
    fig, axs = plt.subplots(
        2, len(indices), figsize=((len(indices) * 4.25 + 0.25) * size,
                                  7.5 * size), squeeze=False,
        sharex=True, sharey=True)

    axs.T[0][0].set_ylabel('spatial Gabor (cos)')
    axs.T[0][1].set_ylabel('spatial Gabor (sin)')

    for ii, axs_ in zip(indices, axs.T):

        spatial_sin, spatial_cos = pyramid.get_filter_spatial_quadrature(ii)
        axs_[0].imshow(spatial_cos, aspect='equal')
        axs_[1].imshow(spatial_sin, aspect='equal')
        axs_[0].set_title('filter %d' % ii)

        gabor = pyramid.filters[ii]
        for ax in axs_:
            ax.scatter(gabor['centerh'] * vdim, gabor['centerv'] * vdim,
                       color='k', marker='+')


Different spatial frequencies

plot_spatial_gabors(pyramid, [0, 23, 88, 577])
filter 0, filter 23, filter 88, filter 577

Different locations

plot_spatial_gabors(pyramid, [46, 52, 58, 64])
filter 46, filter 52, filter 58, filter 64

Different directions

plot_spatial_gabors(pyramid, [88, 157, 202, 247])
filter 88, filter 157, filter 202, filter 247

Total running time of the script: ( 0 minutes 1.209 seconds)

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