          :class:`numpy.ndarray`
              The data with outliers removed
          """
          logger.debug("Flattening outliers: %s", data.shape)
          mean = np.mean(data)
          limit = np.std(data)
          logger.debug("mean: %s, limit: %s", mean, limit)
          retdata = np.where(abs(data - mean) < limit, data, mean)
          logger.debug("Flattened outliers")
          return retdata
  
 
</s> remove     def _remove_raw(self):
 </s> add     def _remove_raw(self) -> None: </s> remove     def _get_raw(self):
 </s> add     def _get_raw(self) -> None: </s> remove         logger.debug("Calculating Average")
 </s> add         logger.debug("Calculating Average. Data points: %s", len(data)) </s> remove     def __init__(self, data, amount):
 </s> add     def __init__(self, data: np.ndarray, amount: float) -> None: </s> remove         logger.debug("Got Raw Data")
 </s> add         logger.debug("Got Raw Data: %s", {k: f"Total: {len(v)}, Min: {np.nanmin(v)}, "
                                             f"Max: {np.nanmax(v)}, "
                                             f"nans: {np.count_nonzero(np.isnan(v))}"
                                          for k, v in self.stats.items()})
        mean = np.mean(np.nan_to_num(data))
        limit = np.std(np.nan_to_num(data))
          :class:`numpy.ndarray`
              The data with outliers removed
          """
          logger.debug("Flattening outliers: %s", data.shape)
        mean = np.mean(np.nan_to_num(data))
        limit = np.std(np.nan_to_num(data))
        mean = np.mean(np.nan_to_num(data))
        limit = np.std(np.nan_to_num(data))
          logger.debug("mean: %s, limit: %s", mean, limit)
          retdata = np.where(abs(data - mean) < limit, data, mean)
          logger.debug("Flattened outliers")
          return retdata
  
keep keep keep keep replace replace keep keep keep keep keep
 Bugfixes:
  - Stats graph - Handle NaNs in data
  - logger - de-elevate matplotlib font messages 
lib/gui/analysis/stats.py