'Collect split adjustments for previous quarters and apply them to the
given dictionary of splits for the given sid. Since overwrites just
replace all estimates before the new quarter with NaN, we don\'t need to
worry about re-applying split adjustments.
Parameters
adjustments_for_sid : dict[str -> dict[int -> list]]
The dictionary of adjustments to which splits need to be added.
Initially it contains only overwrites.
requested_qtr_data : pd.DataFrame
The requested quarter data for each calendar date per sid.
dates : pd.DatetimeIndex
The calendar dates for which estimates data is requested.
sid : int
The sid for which adjustments need to be collected.
sid_idx : int
The index of `sid` in the adjusted array.
sid_estimates : pd.DataFrame
The raw estimates data for the given sid.
split_adjusted_asof_idx : int
The index in `dates` as-of which the data is split adjusted.
pre_adjustments : tuple(list(float), list(int), pd.DatetimeIndex)
The adjustment values and indexes in `dates` for
adjustments that happened before the split-asof-date.
post_adjustments : tuple(list(float), list(int), pd.DatetimeIndex)
The adjustment values, indexes in `dates`, and timestamps for
adjustments that happened after the split-asof-date.
requested_split_adjusted_columns : list of str
List of requested split adjusted column names.'

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):

    (pre_adjustments_dict, post_adjustments_dict) = self._collect_adjustments(requested_qtr_data, sid, sid_idx, sid_estimates, split_adjusted_asof_idx, pre_adjustments, post_adjustments, requested_split_adjusted_columns)
    self.merge_split_adjustments_with_overwrites(pre_adjustments_dict, post_adjustments_dict, adjustments_for_sid, requested_split_adjusted_columns)
