def __init__(self, pre, post, solver=LstsqL2(), **kwargs):
if isinstance(pre, nengo.Ensemble):
solver = BiasedSolver(solver)
bias = nengo.Node(output=solver.bias_function(post.size_in),
label="Bias")
nengo.Connection(bias, post, synapse=None)
super(Connection, self).__init__(pre, post, solver=solver, **kwargs)
def __init__(self, pre, post, solver=LstsqL2(), bias_magnitude=1.0,
**kwargs):
if isinstance(pre, nengo.Ensemble):
solver = BiasedSolver(solver, magnitude=bias_magnitude)
nengo.Connection(
nengo.Node(output=bias_magnitude, label="Bias"), post,
function=solver.bias_function(post.size_in), synapse=None)
super(Connection, self).__init__(pre, post, solver=solver, **kwargs)
def test_biased_solver(Simulator, seed, d):
solver = BiasedSolver()
function = solver.bias_function(d)
assert solver.bias is None
assert np.allclose(function(np.ones(d)), np.zeros(d))
with Network(seed=seed) as model:
x = nengo.Ensemble(100, d)
conn = nengo.Connection(x, x, solver=solver)
with Simulator(model) as sim:
bias = sim.data[conn].solver_info['bias']
assert np.allclose(solver.bias, bias)
assert np.allclose(function(np.ones(d)), bias)
def test_multiple_builds(Simulator, seed):
# this is not a separate test because of nengo issue #1011
solver = BiasedSolver()
A, Y = np.ones((1, 1)), np.ones((1, 1))
assert solver.bias is None
solver(A, Y)
assert solver.bias is not None
with warns(UserWarning):
solver(A, Y)
# issue: #99
with Network(seed=seed) as model:
stim = nengo.Node(output=0)
x = nengo.Ensemble(100, 1)
out = nengo.Node(size_in=1)
nengo.Connection(stim, x, synapse=None)
conn = Connection(x, out, synapse=None)
p = nengo.Probe(out, synapse=0.1)
assert isinstance(conn.solver, BiasedSolver)
with Simulator(model):
pass
with Simulator(model) as sim:
sim.run(0.1)
assert rmse(sim.data[p], 0) < 0.01
def test_biased_solver(Simulator, d):
solver = BiasedSolver()
function = solver.bias_function(d)
assert solver.bias is None
assert np.allclose(function(np.ones(d)), np.zeros(d))
with Network() as model:
x = nengo.Ensemble(100, d)
conn = nengo.Connection(x, x, solver=solver)
sim = Simulator(model)
bias = sim.data[conn].solver_info['bias']
assert np.allclose(solver.bias, bias)
assert np.allclose(function(np.ones(d)), bias)
def test_biased_solver_weights(Simulator):
solver = BiasedSolver(nengo.solvers.LstsqL2(weights=True))
assert solver.weights
with Network() as model:
x = nengo.Ensemble(100, 1)
nengo.Connection(x, x, solver=solver)
Simulator(model)
