class_docstr: An abstract pipeline loader for the events datasets that loads
  data from a blaze expression.
  
  Parameters
  ----------
  expr : Expr
      The expression representing the data to load.
  next_value_columns : dict[BoundColumn -> raw column name]
      A dict mapping 'next' BoundColumns to their column names in `expr`.
  previous_value_columns : dict[BoundColumn -> raw column name]
      A dict mapping 'previous' BoundColumns to their column names in `expr`.
  resources : dict, optional
      Mapping from the loadable terms of ``expr`` to actual data resources.
  odo_kwargs : dict, optional
      Extra keyword arguments to pass to odo when executing the expression.
  data_query_time : time, optional
      The time to use for the data query cutoff.
  data_query_tz : tzinfo or str
      The timezone to use for the data query cutoff.
  
  Notes
  -----
  The expression should have a tabular dshape of::
  
     Dim * {{
         {SID_FIELD_NAME}: int64,
         {TS_FIELD_NAME}: datetime,
         {EVENT_DATE_FIELD_NAME}: datetime,
     }}
  
  And other dataset-specific fields, where each row of the table is a
  record including the sid to identify the company, the timestamp where we
  learned about the announcement, and the event date.
  
  If the '{TS_FIELD_NAME}' field is not included it is assumed that we
  start the backtest with knowledge of all announcements.
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code: def load_adjusted_array(self, columns, dates, assets, mask):
      raw = load_raw_data(
          assets,
          dates,
          self._data_query_time,
          self._data_query_tz,
          self._expr,
          self._odo_kwargs,
      )
  
      return EventsLoader(
          events=raw,
          next_value_columns=self._next_value_columns,
          previous_value_columns=self._previous_value_columns,
      ).load_adjusted_array(
          columns,
          dates,
          assets,
          mask,
      )
  
file_path: catalyst/catalyst/pipeline/loaders/blaze/events.py
imports: from datashape import istabular
  from .core import bind_expression_to_resources
  from catalyst.pipeline.common import SID_FIELD_NAME, TS_FIELD_NAME, EVENT_DATE_FIELD_NAME
  from catalyst.pipeline.loaders.base import PipelineLoader
  from catalyst.pipeline.loaders.blaze.utils import load_raw_data
  from catalyst.pipeline.loaders.events import EventsLoader, required_event_fields
  from catalyst.pipeline.loaders.utils import check_data_query_args
  from catalyst.utils.input_validation import ensure_timezone, optionally
  from catalyst.utils.preprocess import preprocess
label_desc: Use image node_id 2 for calling the BlazeEventsLoader obj's underlying member method code with example usage: obj.load_adjusted_array(columns, dates, assets, mask) and returns: EventsLoader