def load_decoder(self):
self.ssm = StateSpaceEndptVel2D()
A, B, W = self.ssm.get_ssm_matrices()
filt = MachineOnlyFilter(A, W)
units = []
self.decoder = Decoder(filt, units, self.ssm, binlen=0.1)
self.decoder.n_features = 1
def __init__(self, *args, **kwargs):
self.ssm = StateSpaceEndptVel2D()
A, B, _ = self.ssm.get_ssm_matrices()
Q = np.mat(np.diag([.5, .5, .5, .1, .1, .1, 0]))
R = 10**6 * np.mat(np.eye(B.shape[1]))
self.fb_ctrl = feedback_controllers.LQRController(A, B, Q, R)
super(SimObs, self).__init__(*args, **kwargs)
def __init__(self, *args, **kwargs):
dec_fname = os.path.expandvars('$FA_GROM_DATA/grom20160201_01_RMLC02011515.pkl')
self.decoder = pickle.load(open(dec_fname))
self.ssm = StateSpaceEndptVel2D()
A, B, _ = self.ssm.get_ssm_matrices()
Q = np.mat(np.diag([.5, .5, .5, .1, .1, .1, 0]))
R = 10**6*np.mat(np.eye(B.shape[1]))
self.fb_ctrl = feedback_controllers.LQRController(A, B, Q, R)
super(SimObsCLDA, self).__init__(*args, **kwargs)
def main_xz_CL_obstacles(session_length, task_kwargs=None):
ssm_xz = StateSpaceEndptVel2D()
Task = experiment.make(Sim_FA_Obs_BMI, [SaveHDF])
targets = BMIResettingObstacles.centerout_2D_discrete_w_obstacle()
task = Task(ssm_xz,
targets,
plant_type='cursor_14x14',
session_length=session_length,
**task_kwargs)
task.run_sync()
return task
def __init__(self, *args, **kwargs):
from riglib.bmi.state_space_models import StateSpaceEndptVel2D
ssm = StateSpaceEndptVel2D()
A, B, W = ssm.get_ssm_matrices()
Q = np.mat(np.diag([1., 1, 1, 0, 0, 0, 0]))
R = 10000 * np.mat(np.diag([1., 1., 1.]))
self.fb_ctrl = LQRController(A, B, Q, R)
self.ssm = ssm
super(SimBMIControlMulti, self).__init__(*args, **kwargs)
def __init__(self,
cost_err_ratio=10000.,
include_vel_in_error=True,
**kwargs):
ssm = StateSpaceEndptVel2D()
A, B, W = ssm.get_ssm_matrices()
if include_vel_in_error:
Q = np.mat(np.diag(np.array([1, 1, 1, 1, 1, 1, 0])))
else:
Q = np.mat(np.diag(np.array([1, 1, 1, 0, 0, 0, 0])))
R = cost_err_ratio * np.mat(np.eye(len(ssm.drives_obs_inds)))
super(EndPtAssisterOFC, self).__init__(A, B, Q, R)
def main_xz_CL(session_length, task_kwargs=None):
ssm_xz = StateSpaceEndptVel2D()
Task = experiment.make(Sim_FA_BMI, [SaveHDF])
targets = manualcontrolmultitasks.ManualControlMulti.centerout_2D_discrete(
)
task = Task(ssm_xz,
targets,
plant_type='cursor_14x14',
session_length=session_length,
**task_kwargs)
task.run_sync()
return task
def main_xz(session_length):
ssm_xz = StateSpaceEndptVel2D()
Task = experiment.make(SimVFB, [SaveHDF])
#targets = SimVFB.centerout_3D_discrete()
targets = manualcontrolmultitasks.ManualControlMulti.centerout_2D_discrete(
)
task = Task(ssm_xz,
SimVFB.xz_sim,
targets,
plant_type='cursor_14x14',
session_length=session_length)
task.run_sync()
return task
def main_xz_obs(session_length, task_kwargs=None):
ssm_xz = StateSpaceEndptVel2D()
Task = experiment.make(SimVFB_obs, [SaveHDF])
targets = BMIResettingObstacles.centerout_2D_discrete_w_obstacle()
C = np.random.normal(0, 2, (20, 7))
task = Task(ssm_xz,
C,
targets,
plant_type='cursor_14x14',
session_length=session_length,
**task_kwargs)
task.run_sync()
return task
def main_xz(session_length, task_kwargs=None):
ssm_xz = StateSpaceEndptVel2D()
Task = experiment.make(SimVFB, [SaveHDF])
targets = manualcontrolmultitasks.ManualControlMulti.centerout_2D_discrete(
)
C = np.random.normal(0, 2, (20, 7))
task = Task(ssm_xz,
C,
targets,
plant_type='cursor_14x14',
session_length=session_length,
**task_kwargs)
task.run_sync()
return task
def __init__(self, *args, **kwargs):
from riglib.bmi.state_space_models import StateSpaceEndptVel2D
ssm = StateSpaceEndptVel2D()
A, B, W = ssm.get_ssm_matrices(update_rate=1. / 180)
Q = np.mat(np.diag([1., 1, 1, 0, 0, 0, 0]))
R = 100 * np.mat(np.diag([1., 1., 1.]))
self.fb_ctrl = LQRController(A, B, Q, R)
self.ssm = ssm
super(SimCLDAControlMultiDispl2D_PPF, self).__init__(*args, **kwargs)
self.batch_time = 1. / 10 #60. # TODO 10 Hz running seems to be hardcoded somewhere
self.assist_level = 0., 0.
self.assist_level_time = 120.
self.last_get_spike_counts_time = -1. / 60
self.learn_flag = True