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Corrected stimulus preparation and update for cosimulator.py #672

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Corrected stimulus preparation and update for cosimulator.py #672

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56e9f26
Corrected stimulus preparetion for cosimulator.py
dionperd May 3, 2023
d588af0
Overwrote _loop_update_stimulus for cosimulator.py to use stim_step=s…
dionperd May 3, 2023
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15 changes: 12 additions & 3 deletions tvb_contrib/tvb/contrib/cosimulation/cosimulator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@ class CoSimulator(Simulator):
good_cosim_update_values_shape = (0, 0, 0, 0)
cosim_history = None # type: CosimHistory
_cosimulation_flag = False
_current_stimulus = None
_compute_requirements = True
number_of_cosim_monitors = 0
_cosim_monitors_noncoupling_indices = []
Expand Down Expand Up @@ -171,6 +172,7 @@ def configure(self, full_configure=True):
else:
self._cosimulation_flag = False
self.synchronization_n_step = 0
self._current_stimulus = self._prepare_stimulus()

def _loop_update_cosim_history(self, step, state):
"""
Expand Down Expand Up @@ -210,6 +212,12 @@ def _update_cosim_history(self, current_steps, cosim_updates):
raise NumericalInstability("There are missing values for continue the simulation")
super(CoSimulator,self)._loop_update_history(step, state)

def _loop_update_stimulus(self, step, stimulus):
"""Update stimulus values for current time step."""
# TODO: Think about how to have the same behavior as for the Simulator for continuous simulation!
if self.stimulus is not None:
stimulus[self.model.stvar, :, :] = self.stimulus(step-1).reshape((1, -1, 1))

def __call__(self, simulation_length=None, random_state=None, n_steps=None,
cosim_updates=None, recompute_requirements=False):
"""
Expand Down Expand Up @@ -274,15 +282,16 @@ def __call__(self, simulation_length=None, random_state=None, n_steps=None,
self.integrator.set_random_state(random_state)

local_coupling = self._prepare_local_coupling()
stimulus = self._prepare_stimulus()
state = self.current_state
if self._current_stimulus is None:
self._current_stimulus = self._prepare_stimulus()
start_step = self.current_step + 1
node_coupling = self._loop_compute_node_coupling(start_step)

# integration loop
for step in range(start_step, start_step + n_steps):
self._loop_update_stimulus(step, stimulus)
state = self.integrate_next_step(state, self.model, node_coupling, local_coupling, stimulus)
self._loop_update_stimulus(step, self._current_stimulus)
state = self.integrate_next_step(state, self.model, node_coupling, local_coupling, self._current_stimulus)
state_output = self._loop_update_cosim_history(step, state)
node_coupling = self._loop_compute_node_coupling(step + 1)
output = self._loop_monitor_output(step-self.synchronization_n_step, state_output, node_coupling)
Expand Down