code: def load_raw_data(
      assets,
      dates,
      data_query_time,
      data_query_tz,
      expr,
      odo_kwargs,
      checkpoints=None,
  ):
      """
      Given an expression representing data to load, perform normalization and
      forward-filling and return the data, materialized. Only accepts data with a
      `sid` field.
  
      Parameters
      ----------
      assets : pd.int64index
          the assets to load data for.
      dates : pd.datetimeindex
          the simulation dates to load data for.
      data_query_time : datetime.time
          the time used as cutoff for new information.
      data_query_tz : tzinfo
          the timezone to normalize your dates to before comparing against
          `time`.
      expr : expr
          the expression representing the data to load.
      odo_kwargs : dict
          extra keyword arguments to pass to odo when executing the expression.
      checkpoints : expr, optional
          the expression representing the checkpointed data for `expr`.
  
      Returns
      -------
      raw : pd.dataframe
          The result of computing expr and materializing the result as a
          dataframe.
      """
      lower_dt, upper_dt = normalize_data_query_bounds(
          dates[0],
          dates[-1],
          data_query_time,
          data_query_tz,
      )
      raw = ffill_query_in_range(
          expr,
          lower_dt,
          upper_dt,
          checkpoints=checkpoints,
          odo_kwargs=odo_kwargs,
      )
      sids = raw[SID_FIELD_NAME]
      raw.drop(sids[~sids.isin(assets)].index, inplace=True)
      if data_query_time is not None:
          normalize_timestamp_to_query_time(
              raw,
              data_query_time,
              data_query_tz,
              inplace=True,
              ts_field=TS_FIELD_NAME,
          )
      return raw
  
imports: from catalyst.pipeline.common import SID_FIELD_NAME, TS_FIELD_NAME
  from catalyst.pipeline.loaders.blaze.core import ffill_query_in_range
  from catalyst.pipeline.loaders.utils import normalize_data_query_bounds, normalize_timestamp_to_query_time
label_desc: Use image node_id 1 for calling a global function with example usage: load_raw_data(assets, dates, data_query_time, data_query_tz, expr, odo_kwargs, checkpoints) and returns: raw