def cacheMissXZ ( self, res, xtile, yslice, ztile ):
  
    # figure out the cutout (limit to max image size)
    xstart = xtile * self.tilesz
    xend = min ((xtile+1) * self.tilesz, self.proj.datasetcfg.imageSize(res)[0][0])

    # z cutouts need to get rescaled
    #  we'll map to the closest pixel range and tolerate one pixel error at the boundary
    scalefactor = self.proj.datasetcfg.getScale()[res]['xz']
    zoffset = self.proj.datasetcfg.getOffset()[res][2]
    ztilestart = int((ztile*self.tilesz)/scalefactor) + zoffset
    zstart = max ( ztilestart, zoffset ) 
    ztileend = int(math.ceil(((ztile+1)*self.tilesz)/scalefactor)) + zoffset
    zend = min ( ztileend, self.proj.datasetcfg.imageSize(res)[0][2] )

    # call the mcfc interface
    imageargs = '{}/{},{}/{},{}/{},{}/'.format(res, xstart, xend, yslice, yslice+1, zstart, zend) 

    tiledata = None
    for index,channel_name in enumerate(self.channel_list):
      ch = self.proj.getChannelObj(channel_name)
      cutout = ocpcarest.cutout(imageargs, ch, self.proj, self.db)
      # initialize the tiledata by type
      if tiledata == None:
        tiledata = np.zeros((len(self.channel_list), zend-zstart, cutout.data.shape[1], self.tilesz), dtype=cutout.data.dtype)
      tiledata[index, 0:zend-zstart, 0, 0:((xend-1)%self.tilesz+1)] = cutout.data[:, 0, :]
      
    tiledata = ocpcarest.window(tiledata, ch)

    # We have an compound array.  Now color it.
    img = mcfc.mcfcPNG (tiledata.reshape((tiledata.shape[0],tiledata.shape[1],tiledata.shape[3])), self.colors)
    return img.resize ((self.tilesz,self.tilesz))
return the internal repr of this data
dataset/ETHPy150Open neurodata/ndstore/django/catmaid/mcfccatmaid.py/MCFCCatmaid.cacheMissXZ--crossover with--dataset/ETHPy150Open pydata/pandas/pandas/core/series.py/Series._values