def test_linsys():
A = np.random.randn(50, 20)
x = np.random.randn(20, )
y = A.dot(x)
op = proxops.linsys(A, y)
assert np.allclose(op(x, 1.), x)
assert np.allclose(op(np.zeros(x.size), 0.), x)
def test_linsys():
A = np.random.randn(50,20)
x = np.random.randn(20,)
y = A.dot(x)
op = proxops.linsys(A, y)
assert np.allclose(op(x, 1.), x)
assert np.allclose(op(np.zeros(x.size), 0.), x)
def test_consensus():
"""Test the consensus optimizer (ADMM)"""
A, y, x_true, xls, ls_error = generate_sparse_system()
# optimizer
opt = Consensus()
opt.add(linsys(A, y))
opt.add(sparse(10.0))
# run it
res = opt.minimize(xls, display=None, maxiter=5000)
# test
assert relative_error(res.x, x_true, ls_error) <= 0.05
def test_consensus():
"""Test the consensus optimizer (ADMM)"""
A, y, x_true, xls, ls_error = generate_sparse_system()
# optimizer
opt = Consensus()
opt.add(linsys(A, y))
opt.add(sparse(10.0))
# run it
res = opt.minimize(xls, display=None, maxiter=5000)
# test
assert relative_error(res.x, x_true, ls_error) <= 0.05