def test_encoder_decoder_with_views(RefSimulator):
foo = Signal([1.0], name="foo")
decoders = np.asarray([.2, .1])
m = Model(dt=0.001)
sig_in, sig_out = build_pyfunc(lambda t, x: x + 1, True, 2, 2, None, m)
m.operators += [
DotInc(Signal([[1.0], [2.0]]), foo[:], sig_in),
ProdUpdate(Signal(decoders * 0.5), sig_out, Signal(0.2), foo[:])
]
def check(sig, target):
assert np.allclose(sim.signals[sig], target)
sim = RefSimulator(None, model=m)
sim.step()
# DotInc to pop.input_signal (input=[1.0,2.0])
# produpdate updates foo (foo=[0.2])
# pop updates pop.output_signal (output=[2,3])
check(foo, .2)
check(sig_in, [1, 2])
check(sig_out, [2, 3])
sim.step()
# DotInc to pop.input_signal (input=[0.2,0.4])
# (note that pop resets its own input signal each timestep)
# produpdate updates foo (foo=[0.39]) 0.2*0.5*2+0.1*0.5*3 + 0.2*0.2
# pop updates pop.output_signal (output=[1.2,1.4])
check(foo, .39)
check(sig_in, [0.2, 0.4])
check(sig_out, [1.2, 1.4])
def test_encoder_decoder_with_views(RefSimulator):
foo = Signal([1.0], name="foo")
decoders = np.asarray([.2, .1])
m = Model(dt=0.001)
sig_in, sig_out = build_pyfunc(lambda t, x: x + 1, True, 2, 2, None, m)
m.operators += [
DotInc(Signal([[1.0], [2.0]]), foo[:], sig_in),
ProdUpdate(Signal(decoders * 0.5), sig_out, Signal(0.2), foo[:])
]
def check(sig, target):
assert np.allclose(sim.signals[sig], target)
sim = RefSimulator(None, model=m)
sim.step()
# DotInc to pop.input_signal (input=[1.0,2.0])
# produpdate updates foo (foo=[0.2])
# pop updates pop.output_signal (output=[2,3])
check(foo, .2)
check(sig_in, [1, 2])
check(sig_out, [2, 3])
sim.step()
# DotInc to pop.input_signal (input=[0.2,0.4])
# (note that pop resets its own input signal each timestep)
# produpdate updates foo (foo=[0.39]) 0.2*0.5*2+0.1*0.5*3 + 0.2*0.2
# pop updates pop.output_signal (output=[1.2,1.4])
check(foo, .39)
check(sig_in, [0.2, 0.4])
check(sig_out, [1.2, 1.4])
def test_encoder_decoder_pathway(RefSimulator):
"""Verifies (like by hand) that the simulator does the right
things in the right order."""
foo = Signal([1.0], name="foo")
decoders = np.asarray([.2, .1])
decs = Signal(decoders * 0.5)
m = Model(dt=0.001)
sig_in, sig_out = build_pyfunc(lambda t, x: x + 1, True, 2, 2, None, m)
m.operators += [
DotInc(Signal([[1.0], [2.0]]), foo, sig_in),
ProdUpdate(decs, sig_out, Signal(0.2), foo)
]
def check(sig, target):
assert np.allclose(sim.signals[sig], target)
sim = RefSimulator(None, model=m)
check(foo, 1.0)
check(sig_in, 0)
check(sig_out, 0)
sim.step()
# DotInc to pop.input_signal (input=[1.0,2.0])
# produpdate updates foo (foo=[0.2])
# pop updates pop.output_signal (output=[2,3])
check(sig_in, [1, 2])
check(sig_out, [2, 3])
check(foo, .2)
check(decs, [.1, .05])
sim.step()
# DotInc to pop.input_signal (input=[0.2,0.4])
# (note that pop resets its own input signal each timestep)
# produpdate updates foo (foo=[0.39]) 0.2*0.5*2+0.1*0.5*3 + 0.2*0.2
# pop updates pop.output_signal (output=[1.2,1.4])
check(decs, [.1, .05])
check(sig_in, [0.2, 0.4])
check(sig_out, [1.2, 1.4])
# -- foo is computed as a prodUpdate of the *previous* output signal
# foo <- .2 * foo + dot(decoders * .5, output_signal)
# .2 * .2 + dot([.2, .1] * .5, [2, 3])
# .04 + (.2 + .15)
# <- .39
check(foo, .39)
def test_encoder_decoder_pathway(RefSimulator):
"""Verifies (like by hand) that the simulator does the right
things in the right order."""
foo = Signal([1.0], name="foo")
decoders = np.asarray([.2, .1])
decs = Signal(decoders * 0.5)
m = Model(dt=0.001)
sig_in, sig_out = build_pyfunc(lambda t, x: x + 1, True, 2, 2, None, m)
m.operators += [
DotInc(Signal([[1.0], [2.0]]), foo, sig_in),
ProdUpdate(decs, sig_out, Signal(0.2), foo)
]
def check(sig, target):
assert np.allclose(sim.signals[sig], target)
sim = RefSimulator(None, model=m)
check(foo, 1.0)
check(sig_in, 0)
check(sig_out, 0)
sim.step()
# DotInc to pop.input_signal (input=[1.0,2.0])
# produpdate updates foo (foo=[0.2])
# pop updates pop.output_signal (output=[2,3])
check(sig_in, [1, 2])
check(sig_out, [2, 3])
check(foo, .2)
check(decs, [.1, .05])
sim.step()
# DotInc to pop.input_signal (input=[0.2,0.4])
# (note that pop resets its own input signal each timestep)
# produpdate updates foo (foo=[0.39]) 0.2*0.5*2+0.1*0.5*3 + 0.2*0.2
# pop updates pop.output_signal (output=[1.2,1.4])
check(decs, [.1, .05])
check(sig_in, [0.2, 0.4])
check(sig_out, [1.2, 1.4])
# -- foo is computed as a prodUpdate of the *previous* output signal
# foo <- .2 * foo + dot(decoders * .5, output_signal)
# .2 * .2 + dot([.2, .1] * .5, [2, 3])
# .04 + (.2 + .15)
# <- .39
check(foo, .39)
def test_simple_pyfunc(RefSimulator):
dt = 0.001
time = Signal(np.zeros(1), name="time")
sig = Signal(np.zeros(1), name="sig")
m = Model(dt=dt)
sig_in, sig_out = build_pyfunc(lambda t, x: np.sin(x), True, 1, 1, None, m)
m.operators += [
ProdUpdate(Signal(dt), Signal(1), Signal(1), time),
DotInc(Signal([[1.0]]), time, sig_in),
ProdUpdate(Signal([[1.0]]), sig_out, Signal(0), sig),
]
sim = RefSimulator(None, model=m)
for i in range(5):
sim.step()
t = (i + 1) * dt
assert np.allclose(sim.signals[time], t)
assert np.allclose(sim.signals[sig], np.sin(t - dt))
def test_simple_pyfunc(RefSimulator):
dt = 0.001
time = Signal(np.zeros(1), name="time")
sig = Signal(np.zeros(1), name="sig")
m = Model(dt=dt)
sig_in, sig_out = build_pyfunc(lambda t, x: np.sin(x), True, 1, 1, None, m)
m.operators += [
ProdUpdate(Signal(dt), Signal(1), Signal(1), time),
DotInc(Signal([[1.0]]), time, sig_in),
ProdUpdate(Signal([[1.0]]), sig_out, Signal(0), sig),
]
sim = RefSimulator(None, model=m)
sim.step()
for i in range(5):
sim.step()
t = (i + 2) * dt
assert np.allclose(sim.signals[time], t)
assert np.allclose(sim.signals[sig], np.sin(t - dt * 2))
