code: def precompute(self, mask=None, radius_of_influence=50000, epsilon=0,
                     reduce_data=True, nprocs=1,
                     cache_dir=False, **kwargs):
          
  
          del kwargs
  
          if self.resampler is None:
              kwargs = dict(source_geo_def=self.source_geo_def,
                            target_geo_def=self.target_geo_def,
                            radius_of_influence=radius_of_influence,
                            neighbours=32,
                            epsilon=epsilon,
                            reduce_data=reduce_data)
  
              self.resampler = XArrayResamplerBilinear(**kwargs)
              try:
                  self.load_bil_info(cache_dir, **kwargs)
                  LOG.debug("Loaded bilinear parameters")
              except IOError:
                  LOG.debug("Computing bilinear parameters")
                  self.resampler.get_bil_info()
                  self.save_bil_info(cache_dir, **kwargs)
docs: Create bilinear coefficients and store them for later use.
  
          Note: The `mask` keyword should be provided if geolocation may be valid
          where data points are invalid. This defaults to the `mask` attribute of
          the `data` numpy masked array passed to the `resample` method.