code: def load_adjusted_array(self, domain, columns, dates, sids, mask):
      """
      Load data for ``columns`` as AdjustedArrays.
  
      Parameters
      ----------
      domain : zipline.pipeline.domain.Domain
          The domain of the pipeline for which the requested data must be
          loaded.
      columns : list[zipline.pipeline.data.dataset.BoundColumn]
          Columns for which data is being requested.
      dates : pd.DatetimeIndex
          Dates for which data is being requested.
      sids : pd.Int64Index
          Asset identifiers for which data is being requested.
      mask : np.array[ndim=2, dtype=bool]
          Boolean array of shape (len(dates), len(sids)) indicating dates on
          which we believe the requested assets were alive/tradeable. This is
          used for optimization by some loaders.
  
      Returns
      -------
      arrays : dict[BoundColumn -> zipline.lib.adjusted_array.AdjustedArray]
          Map from column to an AdjustedArray representing a point-in-time
          rolling view over the requested dates for the requested sids.
      """
  
imports: from interface import default, Interface
label_desc: Use image node_id 1 for calling the PipelineLoader obj's underlying member method code with example usage: obj.load_adjusted_array(domain, columns, dates, sids, mask) without return types