def transform_observation_data(self, observation_data: List[ObservationData], observation_features: List[ObservationFeatures]) -> List[ObservationData]:
    'Winsorize observation data in place.'
    for obsd in observation_data:
        for (i, m) in enumerate(obsd.metric_names):
            if (m in self.metric_names):
                transform = self.power_transforms[m].transform
                (obsd.means[i], obsd.covariance[(i, i)]) = match_ci_width_truncated(mean=obsd.means[i], variance=obsd.covariance[(i, i)], transform=(lambda y: transform(np.array(y, ndmin=2))), lower_bound=(- np.inf), upper_bound=np.inf)
    return observation_data
Winsorize observation data in place.
def transform_observation_data(self, observation_data: List[ObservationData], observation_features: List[ObservationFeatures]) -> List[ObservationData]:
    
    for obsd in observation_data:
        for (i, m) in enumerate(obsd.metric_names):
            if (m in self.metric_names):
                transform = self.power_transforms[m].transform
                (obsd.means[i], obsd.covariance[(i, i)]) = match_ci_width_truncated(mean=obsd.means[i], variance=obsd.covariance[(i, i)], transform=(lambda y: transform(np.array(y, ndmin=2))), lower_bound=(- np.inf), upper_bound=np.inf)
    return observation_data