def foveate_defoveate_channel(self, image, rings, encoded_size, bs=1):
        output = np.zeros((bs, encoded_size))
        foveate_channel(image, rings, output, 0)
        defoveate_channel(image, rings, output, 0)
        refoveated_output = np.zeros((bs, encoded_size))
        foveate_channel(image, rings, refoveated_output, 0)
        np.testing.assert_allclose(refoveated_output, output)
Returns validated Property data, ready to be saved in the DB.
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/datasets/tests/test_retina.py/test_retina.foveate_defoveate_channel--crossover with--dataset/ETHPy150Open espeed/bulbs/bulbs/model.py/Model._get_property_data