def init(self, boot_spec):
ExpSwitcher.init(self, boot_spec)
# TODO: check float
if len(boot_spec.get_observations().shape()) != 2:
raise UnsupportedSpec('I assume 2D signals.')
self.y_stats = ImageStats()
class EstStats2D(ExpSwitcher):
'''
A simple agent that estimates various statistics
of the observations. Assumes 2D signals.
'''
def init(self, boot_spec):
ExpSwitcher.init(self, boot_spec)
# TODO: check float
if len(boot_spec.get_observations().shape()) != 2:
raise UnsupportedSpec('I assume 2D signals.')
self.y_stats = ImageStats()
def merge(self, other):
self.y_stats.merge(other.y_stats)
def process_observations(self, obs):
y = obs['observations']
dt = obs['dt'].item()
self.y_stats.update(y, dt)
def get_state(self):
return dict(y_stats=self.y_stats)
def set_state(self, state):
self.y_stats = state['y_stats']
def publish(self, pub):
if self.y_stats.get_num_samples() == 0:
pub.text('warning', 'Too early to publish anything.')
return
self.y_stats.publish(pub)