features.py 文件源码

def add_observation(self, observation, indx=None):
        """
        Parameters
        ----------
        indx : ints
            The indices of the healpixel map that have been observed by observation
        """
        if observation['filter'][0] in self.filtername:
            self.feature[indx] += 1

        if self.mask_indx is not None:
            overlap = np.intersect1d(indx, self.mask_indx)
            if overlap.size > 0:
                # interpolate over those pixels that are DD fields.
                # XXX.  Do I need to kdtree this? Maybe make a dict on init
                # to lookup the N closest non-masked pixels, then do weighted average.
                pass