class_docstr: Estimates loader that loads data that needs to be split-adjusted.
  
  Parameters
  ----------
  split_adjustments_loader : SQLiteAdjustmentReader
      The loader to use for reading split adjustments.
  split_adjusted_column_names : iterable of str
      The column names that should be split-adjusted.
  split_adjusted_asof : pd.Timestamp
      The date that separates data into 2 halves: the first half is the set
      of dates up to and including the split_adjusted_asof date. All
      adjustments occurring during this first half are applied  to all
      dates in this first half. The second half is the set of dates after
      the split_adjusted_asof date. All adjustments occurring during this
      second half are applied sequentially as they appear in the timeline.
class_docstr_tok: ["Estimates","loader","that","loads","data","that","needs","to","be","split-adjusted",".","Parameters","--","--","--","--","--","split_adjustments_loader",":","SQLiteAdjustmentReader","The","loader","to","use","for","reading","split","adjustments",".","split_adjusted_column_names",":","iterable","of","str","The","column","names","that","should","be","split-adjusted",".","split_adjusted_asof",":","pd.Timestamp","The","date","that","separates","data","into","2","halves",":","the","first","half","is","the","set","of","dates","up","to","and","including","the","split_adjusted_asof","date",".","All","adjustments","occurring","during","this","first","half","are","applied","to","all","dates","in","this","first","half",".","The","second","half","is","the","set","of","dates","after","the","split_adjusted_asof","date",".","All","adjustments","occurring","during","this","second","half","are","applied","sequentially","as","they","appear","in","the","timeline","."]
code: def collect_split_adjustments(
      self,
      adjustments_for_sid,
      requested_qtr_data,
      dates,
      sid,
      sid_idx,
      sid_estimates,
      split_adjusted_asof_idx,
      pre_adjustments,
      post_adjustments,
      requested_split_adjusted_columns,
  ):
      raise NotImplementedError("collect_split_adjustments")
  
imports: from abc import abstractmethod, abstractproperty
  import numpy
  import pandas
  from six import viewvalues
  from toolz import groupby
  from catalyst.lib.adjusted_array import AdjustedArray
  from catalyst.lib.adjustment import Datetime641DArrayOverwrite, Datetime64Overwrite, Float641DArrayOverwrite, Float64Multiply, Float64Overwrite
  from catalyst.pipeline.common import EVENT_DATE_FIELD_NAME, FISCAL_QUARTER_FIELD_NAME, FISCAL_YEAR_FIELD_NAME, SID_FIELD_NAME, TS_FIELD_NAME
  from catalyst.pipeline.loaders.base import PipelineLoader
  from catalyst.utils.numpy_utils import datetime64ns_dtype, float64_dtype
  from catalyst.pipeline.loaders.utils import ffill_across_cols, last_in_date_group
label_desc: Use image node_id 2 for calling the SplitAdjustedEstimatesLoader obj's underlying member method code with example usage: obj.collect_split_adjustments(adjustments_for_sid, requested_qtr_data, dates, sid, sid_idx, sid_estimates, split_adjusted_asof_idx, pre_adjustments, post_adjustments, requested_split_adjusted_columns) without return types