def evaluate_fitness(self, candidate, args):
self.update_cell(candidate)
v_candidate, t_candidate = iclamp(self.cell, **self.simulation_params)
#self.data_to_fit = [0] # TODO !!!!
#self.args['candidate'] = candidate # TODO
vars_to_fit = [fitfun(v_candidate, t_candidate, self.simulation_params['i_inj'], self.args)
for fitfun in self.fitfuns]
num_nones = 0
fitness = 0
for i in range(len(vars_to_fit)):
if vars_to_fit[i] is None:
num_nones += 1
else:
fitness += self.fitnessweights[i] * self.errfun(vars_to_fit[i], self.data_to_fit[i])
if num_nones == len(vars_to_fit):
return float("inf")
return fitness
def simulate(self):
return iclamp(self.fitter.cell, **self.fitter.simulation_params)
def simulate_cell(self, candidate):
self.update_cell(candidate)
v_candidate, t_candidate = iclamp(self.cell, **self.simulation_params)
return v_candidate, t_candidate, self.simulation_params['i_inj']
