def generate_synthetic_data():
    rs = np.random.RandomState(0)
    n_pts = 36.
    x, y = np.ogrid[0:l, 0:l]
    mask_outer = (x - l / 2) ** 2 + (y - l / 2) ** 2 < (l / 2) ** 2
    mask = np.zeros((l, l))
    points = l * rs.rand(2, n_pts)
    mask[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1
    mask = ndimage.gaussian_filter(mask, sigma=l / n_pts)
    res = np.logical_and(mask > mask.mean(), mask_outer)
    return res - ndimage.binary_erosion(res)


# Generate synthetic images, and projections
Test --lines
dataset/ETHPy150Open scikit-learn/scikit-learn/examples/applications/plot_tomography_l1_reconstruction.py/generate_synthetic_data--crossover with--dataset/ETHPy150Open dcos/dcos-cli/cli/tests/integrations/test_task.py/test_log_lines