              self._ewma_vectorized(self._data[-leftover:],
                                    self._out[-leftover:],
                                    offset=out_main_view[-1, -1])
  
      def _ewma_vectorized(self, data, out, offset=None):
          """ Calculates the exponential moving average over a vector. Will fail for large inputs.
  
          The result is processed in place into the array passed to the `out` parameter
  
          Parameters
 
</s> remove     def _ewma_vectorized_2d(self, data, out):
 </s> add     def _ewma_vectorized_2d(self, data: np.ndarray, out: np.ndarray) -> None: </s> remove     def _ewma_vectorized_safe(self):
 </s> add     def _ewma_vectorized_safe(self) -> None: </s> remove     def __call__(self):
 </s> add     def __call__(self) -> np.ndarray: </s> remove         trend = np.poly1d(np.polyfit(x_range, data, 3))(x_range)
        logger.debug("Calculated Trend")
 </s> add         trend = np.poly1d(np.polyfit(x_range, np.nan_to_num(data), 3))(x_range)
        logger.debug("Calculated Trend: shape: %s", trend.shape) </s> remove         frame: `tkinter.ttk.Frame`
 </s> add         frame: :class:`tkinter.ttk.Frame`
    def _ewma_vectorized(self,
                         data: np.ndarray,
                         out: np.ndarray,
                         offset: Optional[float] = None) -> None:
              self._ewma_vectorized(self._data[-leftover:],
                                    self._out[-leftover:],
                                    offset=out_main_view[-1, -1])
  
    def _ewma_vectorized(self,
                         data: np.ndarray,
                         out: np.ndarray,
                         offset: Optional[float] = None) -> None:
          """ Calculates the exponential moving average over a vector. Will fail for large inputs.
  
          The result is processed in place into the array passed to the `out` parameter
  
          Parameters
keep keep keep keep replace keep keep keep keep keep
 Bugfixes:
  - Stats graph - Handle NaNs in data
  - logger - de-elevate matplotlib font messages 
lib/gui/analysis/stats.py