def test_compute_debiasing():
    rng = np.random.RandomState(42)
    G = rng.randn(10, 4)
    X = rng.randn(4, 20)
    debias_true = np.arange(1, 5, dtype=np.float)
    M = np.dot(G, X * debias_true[:, np.newaxis])
    debias = compute_bias(M, G, X, max_iter=10000, n_orient=1, tol=1e-7)
    assert_almost_equal(debias, debias_true, decimal=5)
    debias = compute_bias(M, G, X, max_iter=10000, n_orient=2, tol=1e-5)
    assert_almost_equal(debias, [1.8, 1.8, 3.72, 3.72], decimal=2)
Show reconstructions of a given DBM model.
dataset/ETHPy150Open mne-tools/mne-python/mne/inverse_sparse/tests/test_mxne_debiasing.py/test_compute_debiasing--crossover with--dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/scripts/dbm/show_reconstructions.py/show_reconstructions