def tvb_model(dt, weight, delay, id_proxy):
"""
Initialise TVB with Wong-Wang models and default connectivity
WARNING : in this first example most of the parameter for the simulation is define. In the future, this function
will be disappear and replace only by the tvb_init. This function is only here in order to constraint the usage
of proxy
:param dt: the resolution of the raw monitor (ms)
:param weight: weight on the connexion
:param delay: delay on the connexion
:param id_proxy: id of the proxy
:return:
populations: model in TVB
white_matter: Connectivity in TVB
white_matter_coupling: Coupling in TVB
heunint: Integrator in TVB
what_to_watch: Monitor in TVB
"""
region_label = np.repeat(['real'], len(weight)) # name of region fixed can be modify for parameter of function
region_label[id_proxy] = 'proxy'
populations = ReducedWongWangProxy()
white_matter = lab.connectivity.Connectivity(region_labels=region_label,
weights=weight,
speed=np.array(1.0),
tract_lengths=delay,
# TVB don't take care about the delay only the track length and speed
# delai = tract_lengths/speed
centres=np.ones((weight.shape[0], 3))
)
white_matter_coupling = lab.coupling.Linear(a=np.array(0.0154))
heunint = lab.integrators.EulerDeterministic(dt=dt, bounded_state_variable_indices=np.array([0]),
state_variable_boundaries=np.array([[0.0, 1.0]]))
return populations, white_matter, white_matter_coupling, heunint, id_proxy
def test_with_proxy_bad_input(self):
connectivity, coupling, integrator, monitors, sim, result, result_all = self._reference_simulation()
# The modify model without proxy
np.random.seed(42)
init = np.concatenate((np.random.random_sample((385, 1, 76, 1)),
np.random.random_sample((385, 1, 76, 1))), axis=1)
np.random.seed(42)
id_proxy = range(11)
model = ReducedWongWangProxy(tau_s=np.random.rand(76))
synchronization_time = 1.
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim_4 = CoSimulator(
voi=np.array([0]),
synchronization_time=synchronization_time,
cosim_monitors=(RawCosim(),),
proxy_inds=np.asarray(id_proxy, dtype=np.int),
model=model,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors,),
initial_conditions=init,
)
sim_4.configure()
sim_4.run() # run the first steps because the history is delayed
sim_to_sync_time = int(SIMULATION_LENGTH / synchronization_time)
sync_steps = int(synchronization_time / integrator.dt)
result_4_all = [np.empty((0,)), np.empty((sync_steps, 2, 76, 1))]
for j in range(0, sim_to_sync_time):
result_4_all_step = sim_4.run(
cosim_updates=[np.array([result_all[0][0][(sync_steps * j) + i] for i in range(sync_steps)]),
np.ones((sync_steps, 1, len(id_proxy), 1)) * 0.7])
result_4_all[0] = np.concatenate((result_4_all[0], result_4_all_step[0][0]))
result_4_all[1] = np.concatenate((result_4_all[1], result_4_all_step[0][1]))
simulation_n_steps = int(SIMULATION_LENGTH / integrator.dt)
# The beggining is good for rate
for i in range(np.min(sim_4.connectivity.idelays[np.nonzero(sim_4.connectivity.idelays)])+1):
np.testing.assert_array_equal(result_all[0][1][i][0][len(id_proxy):], result_4_all[1][i+sync_steps, 0, len(id_proxy):])
np.testing.assert_array_compare(operator.__ne__,result_all[0][1][i][0][:len(id_proxy)], result_4_all[1][i+sync_steps, 0, :len(id_proxy)])
# after the delayed impact the simulation, This create some difference for rate
for i in range(np.min(sim_4.connectivity.idelays[np.nonzero(sim_4.connectivity.idelays)])+1,
simulation_n_steps):
diff = result_all[0][1][i][0][len(id_proxy):] - result_4_all[1][i+sync_steps, 0, len(id_proxy):]
assert np.sum(diff) != 0
np.testing.assert_array_compare(operator.__ne__,result_all[0][1][i][0][:len(id_proxy)], result_4_all[1][i+sync_steps, 0, :len(id_proxy)])
# The beggining is good for S
for i in range(np.min(sim_4.connectivity.idelays[np.nonzero(sim_4.connectivity.idelays)])+1):
np.testing.assert_array_equal(result_all[0][1][i][1][len(id_proxy):], result_4_all[1][i+sync_steps, 1, len(id_proxy):])
np.testing.assert_array_equal(result_all[0][1][i][1][:len(id_proxy)]*np.NAN, result_4_all[1][i+sync_steps, 1, :len(id_proxy)])
# after the delayed impact the simulation, This create some difference for S
for i in range(np.min(sim_4.connectivity.idelays[np.nonzero(sim_4.connectivity.idelays)])+1,
simulation_n_steps):
diff = result_all[0][1][i][1][len(id_proxy):] - result_4_all[1][i+sync_steps, 1, len(id_proxy):]
assert np.sum(diff) != 0
np.testing.assert_array_equal(result_all[0][1][i][1][:len(id_proxy)]*np.NAN, result_4_all[1][i+sync_steps, 1, :len(id_proxy)])
def test_with_proxy_right_input(self):
connectivity, coupling, integrator, monitors, sim, result, result_all = self._reference_simulation(
)
# The modify model without proxy
np.random.seed(42)
init = np.concatenate((np.random.random_sample(
(385, 1, 76, 1)), np.random.random_sample((385, 1, 76, 1))),
axis=1)
np.random.seed(42)
id_proxy = range(11)
model = ReducedWongWangProxy(tau_s=np.random.rand(76))
synchronization_time = 1.0
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim_5 = CoSimulator(
voi=np.array([0]),
synchronization_time=synchronization_time,
cosim_monitors=(RawCosim(), ),
proxy_inds=np.asarray(id_proxy, dtype=np.int),
model=model,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors, ),
initial_conditions=init,
)
sim_5.configure()
sim_5.run() # run the first steps because the history is delayed
sim_to_sync_time = int(SIMULATION_LENGTH / synchronization_time)
sync_steps = int(synchronization_time / integrator.dt)
result_5_all = [np.empty((0, )), np.empty((sync_steps, 2, 76, 1))]
for j in range(0, sim_to_sync_time):
result_5_all_step = sim_5.run(cosim_updates=[
np.array([
result_all[0][0][(sync_steps * j) + i]
for i in range(sync_steps)
]),
np.array([
result_all[0][1][(sync_steps * j) + i][0][id_proxy]
for i in range(sync_steps)
]).reshape((sync_steps, 1, len(id_proxy), 1))
])
result_5_all[0] = np.concatenate(
(result_5_all[0], result_5_all_step[0][0]))
result_5_all[1] = np.concatenate(
(result_5_all[1], result_5_all_step[0][1]))
for i in range(int(SIMULATION_LENGTH / integrator.dt)):
np.testing.assert_array_equal(
result_all[0][1][i][0][len(id_proxy):],
result_5_all[1][i + sync_steps, 0,
len(id_proxy):])
np.testing.assert_array_equal(
result_all[0][1][i][0][:len(id_proxy)],
result_5_all[1][i + sync_steps, 0, :len(id_proxy)])
def test_precision_with_proxy(self):
connectivity, coupling, integrator, monitors, sim, result, result_all = self._reference_simulation(
self._simulation_length)
# New simulator with proxy
np.random.seed(42)
init = np.concatenate((np.random.random_sample(
(385, 1, 76, 1)), np.random.random_sample((385, 1, 76, 1))),
axis=1)
np.random.seed(42)
model_1 = ReducedWongWangProxy(tau_s=np.random.rand(76))
synchronization_time = 1.
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim_1 = CoSimulator(
voi=np.array([0]),
synchronization_time=synchronization_time,
cosim_monitors=(RawCosim(), ),
proxy_inds=np.asarray([0], dtype=np.int),
model=model_1,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors, ),
initial_conditions=init,
)
sim_1.configure()
sim_to_sync_time = int(self._simulation_length / synchronization_time)
sync_steps = int(synchronization_time / integrator.dt)
result_1_all = [np.empty((0, )), np.empty((sync_steps, 2, 76, 1))]
sim_1.run() # run the first steps because the history is delayed
for j in range(0, sim_to_sync_time):
result_1_all_step = sim_1.run(cosim_updates=[
np.array([
result_all[0][0][(sync_steps * j) + i]
for i in range(sync_steps)
]),
np.array([
result_all[0][1][(sync_steps * j) + i][0][0]
for i in range(sync_steps)
]).reshape((sync_steps, 1, 1, 1))
])
result_1_all[0] = np.concatenate(
(result_1_all[0], result_1_all_step[0][0]))
result_1_all[1] = np.concatenate(
(result_1_all[1], result_1_all_step[0][1]))
for i in range(int(self._simulation_length / integrator.dt)):
np.testing.assert_array_equal(
result_all[0][1][i][0][1:], result_1_all[1][i + sync_steps, 0,
1:])
np.testing.assert_array_equal(
result_all[0][1][i][0][:1], result_1_all[1][i + sync_steps,
0, :1])
def _prepare_reference_simulation():
# reference simulation
np.random.seed(42)
init = np.concatenate((np.random.random_sample((385, 1, 76, 1)),
np.random.random_sample((385, 1, 76, 1))), axis=1)
np.random.seed(42)
model = ReducedWongWangProxy(tau_s=np.random.rand(76))
connectivity = lab.connectivity.Connectivity().from_file()
connectivity.speed = np.array([4.0])
connectivity.configure()
coupling = lab.coupling.Linear(a=np.array(0.0154))
integrator = lab.integrators.HeunDeterministic(dt=0.1, bounded_state_variable_indices=np.array([0]),
state_variable_boundaries=np.array([[0.0, 1.0]]))
monitors = lab.monitors.Raw(period=0.1, variables_of_interest=np.array(0, dtype=np.int))
return model, connectivity, coupling, init, integrator, monitors
def test_without_proxy_coupling(self):
connectivity, coupling, integrator, monitors, sim, result, result_all = self._reference_simulation(
)
# The modify model without proxy
np.random.seed(42)
init = np.concatenate((np.random.random_sample(
(385, 1, 76, 1)), np.random.random_sample((385, 1, 76, 1))),
axis=1)
model = ReducedWongWangProxy(tau_s=np.random.rand(76))
synchronization_time = 1.0
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim_6 = CoSimulator(
voi=np.array([0]),
synchronization_time=synchronization_time,
cosim_monitors=(CosimCoupling(coupling=coupling), ),
proxy_inds=np.asarray([0], dtype=np.int),
model=model,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors, ),
initial_conditions=init,
)
sim_6.configure()
result_2_all = sim_6.run(
)[0][1][:, 0, 0,
0] # run the first steps because the history is delayed
sim_to_sync_time = int(SIMULATION_LENGTH / synchronization_time)
sync_steps = int(synchronization_time / integrator.dt)
with pytest.raises(ValueError):
coupling_future = sim_6.loop_cosim_monitor_output(sync_steps, 1)
coupling_future = sim_6.loop_cosim_monitor_output()
for i in range(sim_to_sync_time):
result_2 = sim_6.run()[0][1][:, 0, 0, 0]
np.testing.assert_array_equal(
result[i * sync_steps:(i + 1) * sync_steps] * np.NAN, result_2)
assert np.sum(np.isnan(
sim_6.loop_cosim_monitor_output()[0][1])) == 0
def test_without_voi(self):
model, connectivity, coupling, init, integrator, monitors = self._prepare_reference_simulation()
np.random.seed(42)
id_proxy = range(11)
model = ReducedWongWangProxy(tau_s=np.random.rand(76))
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
sim = CoSimulator(
voi=np.array([], dtype=np.int),
synchronization_time=1.,
cosim_monitors=(RawCosim(),),
proxy_inds=np.asarray(id_proxy, dtype=np.int),
model=model,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors,),
initial_conditions=init,
)
with pytest.raises(ValueError):
sim.configure()
def test_monitor(self):
connectivity, coupling, integrator, monitors, sim, result, result_all = self._reference_simulation(
self._simulation_length)
# New simulator with proxy
np.random.seed(42)
init = np.concatenate((np.random.random_sample(
(385, 1, 76, 1)), np.random.random_sample((385, 1, 76, 1))),
axis=1)
np.random.seed(42)
model_1 = ReducedWongWangProxy(tau_s=np.random.rand(76))
# Initialise a Simulator -- Model, Connectivity, Integrator, and Monitors.
synchronization_time = 1.0
sim_1 = CoSimulator(
voi=np.array([0]),
synchronization_time=synchronization_time,
cosim_monitors=(RawCosim(),
RawVoiCosim(variables_of_interest=np.array([0])),
RawDelayed(),
RawVoiDelayed(variables_of_interest=np.array([0])),
CosimCoupling(coupling=coupling),
CosimCoupling(coupling=coupling,
variables_of_interest=np.array([0
]))),
proxy_inds=np.asarray([0], dtype=np.int),
model=model_1,
connectivity=connectivity,
coupling=coupling,
integrator=integrator,
monitors=(monitors, ),
initial_conditions=init,
)
sim_1.configure()
sim_to_sync_time = int(self._simulation_length / synchronization_time)
sync_steps = int(synchronization_time / integrator.dt)
result_1_all = [np.empty((0, )), np.empty((sync_steps, 2, 76, 1))]
result_cosim_monitors = []
sim_1.run() # run the first steps because the history is delayed
for j in range(0, sim_to_sync_time):
# This should fail for CosimCoupling that can only return FUTURE coupling values!!!
result_cosim_monitors.append(
sim_1.loop_cosim_monitor_output(sync_steps, 0))
result_1_all_step = sim_1.run(cosim_updates=[
np.array([
result_all[0][0][(sync_steps * j) + i]
for i in range(sync_steps)
]),
np.array([
result_all[0][1][(sync_steps * j) + i][0][0]
for i in range(sync_steps)
]).reshape((sync_steps, 1, 1, 1))
])
result_1_all[0] = np.concatenate(
(result_1_all[0], result_1_all_step[0][0]))
result_1_all[1] = np.concatenate(
(result_1_all[1], result_1_all_step[0][1]))
for i in range(int(self._simulation_length / integrator.dt)):
np.testing.assert_array_equal(
result_all[0][1][i][0][1:], result_1_all[1][i + sync_steps, 0,
1:])
np.testing.assert_array_equal(
result_all[0][1][i][0][:1], result_1_all[1][i + sync_steps,
0, :1])
for i in range(sim_to_sync_time):
result_step = result_cosim_monitors[i]
# check the dimension of the monitors
np.testing.assert_array_equal(result_step[0][1].shape,
(sync_steps, 2, 76, 1))
np.testing.assert_array_equal(result_step[1][1].shape,
(sync_steps, 1, 76, 1))
np.testing.assert_array_equal(result_step[3][1].shape,
(sync_steps, 1, 76, 1))
np.testing.assert_array_equal(result_step[4][1].shape,
(sync_steps, 1, 76, 1))
np.testing.assert_array_equal(result_step[5][1].shape,
(sync_steps, 1, 76, 1))
# compare the monitors between them
np.testing.assert_array_equal(result_step[2][1], result_step[3][1])
np.testing.assert_array_equal(result_step[4][1], result_step[5][1])
np.testing.assert_array_equal(result_step[0][1][:, 0, :, :],
result_step[1][1][:, 0, :, :])