Use the segmented images to create per-image graphics

        Args:
            verbose (bool): output more details if true
            measured_regions (pandas.DataFrame): explicitly list the measured images and regions
            measured_phenotypes (list): explicitly list the phenotypes present

        Returns:
            NearestNeighbors: returns a class that holds nearest neighbor information for whatever phenotypes were in the CellDataFrame before execution.  This class is suitable for nearest neighbor and proximity operations.

def nearestneighbors(self,*args,**kwargs):
        """
        Use the segmented images to create per-image graphics

        Args:
            verbose (bool): output more details if true
            measured_regions (pandas.DataFrame): explicitly list the measured images and regions
            measured_phenotypes (list): explicitly list the phenotypes present

        Returns:
            NearestNeighbors: returns a class that holds nearest neighbor information for whatever phenotypes were in the CellDataFrame before execution.  This class is suitable for nearest neighbor and proximity operations.
        """
        n = NearestNeighbors.read_cellframe(self,*args,**kwargs)
        if 'measured_regions' in kwargs: n.measured_regions = kwargs['measured_regions']
        else: n.measured_regions = self.get_measured_regions()
        if 'measured_phenotypes' in kwargs: n.measured_phenotypes = kwargs['measured_phenotypes']
        else: n.measured_phenotypes = self.phenotypes
        n.microns_per_pixel = self.microns_per_pixel
        return n