class_docstr: Base class for PipelineLoaders that supports loading the next and previous
  value of an event field.
  
  Does not currently support adjustments.
  
  Parameters
  ----------
  events : pd.DataFrame
      A DataFrame representing events (e.g. share buybacks or
      earnings announcements) associated with particular companies.
  
      ``events`` must contain at least three columns::
          sid : int64
              The asset id associated with each event.
  
          event_date : datetime64[ns]
              The date on which the event occurred.
  
          timestamp : datetime64[ns]
              The date on which we learned about the event.
  
  next_value_columns : dict[BoundColumn -> str]
      Map from dataset columns to raw field names that should be used when
      searching for a next event value.
  
  previous_value_columns : dict[BoundColumn -> str]
      Map from dataset columns to raw field names that should be used when
      searching for a previous event value.
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code: def load_adjusted_array(self, domain, columns, dates, sids, mask):
      data_query = domain.data_query_cutoff_for_sessions(dates)
      n, p = self.split_next_and_previous_event_columns(columns)
      return merge(
          self.load_next_events(
              domain, n, dates, data_query, sids, mask
          ),
          self.load_previous_events(
              domain, p, dates, data_query, sids, mask
          ),
      )
  
imports: import numpy
  import pandas
  from interface import implements
  from six import viewvalues
  from toolz import groupby, merge
  from .base import PipelineLoader
  from zipline.pipeline.common import EVENT_DATE_FIELD_NAME, SID_FIELD_NAME, TS_FIELD_NAME
  from zipline.pipeline.loaders.frame import DataFrameLoader
  from zipline.pipeline.loaders.utils import next_event_indexer, previous_event_indexer
label_desc: Use image node_id 8 for calling the EventsLoader obj's underlying member method code with example usage: obj.load_adjusted_array(domain, columns, dates, sids, mask) and returns: merge