else: # run a simulation with parameters as set in simulation_parameters
GP = simulation_parameters.global_parameters()
GP.write_parameters_to_file() # write_parameters_to_file MUST be called before every simulation
params = GP.params
# TODO: update VisualInputParameters and possibly remove it completely
# decide whether to load the default parameters or to take parameters from a file
VIP = VisualInputParameters.VisualInputParameters()
VIP.update_values(params)
vi_params = VIP.params
VI = VisualInput.VisualInput(vi_params) # pass parameters to the VisualInput module
MT = MotionPrediction.MotionPrediction(params)
BG = BasalGanglia.BasalGanglia(params)
CC = CreateConnections.CreateConnections(params)
CC.connect_mt_to_bg(MT, BG)
for iteration in xrange(params['n_iterations']):
# integrate the real world trajectory and the eye direction and compute spike trains from that
stim = VI.compute_input(params['t_iteration'], BG.get_eye_direction())
MT.compute_state(stim) # run the network for some time
BG.move_eye(MT.current_state)
# """
# First the stimulus is computed for a certain time
# """
# stimulus = VI.compute_input(params['t_integrate'])
