class_docstr: A PipelineLoader for loading daily OHLCV data.
  
  Parameters
  ----------
  raw_price_reader : zipline.data.session_bars.SessionBarReader
      Reader providing raw prices.
  adjustments_reader : zipline.data.adjustments.SQLiteAdjustmentReader
      Reader providing price/volume adjustments.
  fx_reader : zipline.data.fx.FXRateReader
     Reader providing currency conversions.
class_docstr_tok: ["A","PipelineLoader","for","loading","daily","OHLCV","data",".","Parameters","--","--","--","--","--","raw_price_reader",":","zipline.data.session_bars.SessionBarReader","Reader","providing","raw","prices",".","adjustments_reader",":","zipline.data.adjustments.SQLiteAdjustmentReader","Reader","providing","price\/volume","adjustments",".","fx_reader",":","zipline.data.fx.FXRateReader","Reader","providing","currency","conversions","."]
code: def load_adjusted_array(self, domain, columns, dates, sids, mask):
      # load_adjusted_array is called with dates on which the user's algo
      # will be shown data, which means we need to return the data that would
      # be known at the **start** of each date. We assume that the latest
      # data known on day N is the data from day (N - 1), so we shift all
      # query dates back by a trading session.
      sessions = domain.all_sessions()
      shifted_dates = shift_dates(
          sessions, dates[0], dates[-1], shift=1
      )
  
      ohlcv_cols, currency_cols = self._split_column_types(columns)
      del columns  # From here on we should use ohlcv_cols or currency_cols.
      ohlcv_colnames = [c.name for c in ohlcv_cols]
  
      raw_ohlcv_arrays = self.raw_price_reader.load_raw_arrays(
          ohlcv_colnames,
          shifted_dates[0],
          shifted_dates[-1],
          sids,
      )
  
      # Currency convert raw_arrays in place if necessary. We use shifted
      # dates to load currency conversion rates to make them line up with
      # dates used to fetch prices.
      self._inplace_currency_convert(
          ohlcv_cols,
          raw_ohlcv_arrays,
          shifted_dates,
          sids,
      )
  
      adjustments = self.adjustments_reader.load_pricing_adjustments(
          ohlcv_colnames,
          dates,
          sids,
      )
  
      out = {}
      for c, c_raw, c_adjs in zip(
          ohlcv_cols, raw_ohlcv_arrays, adjustments
      ):
          out[c] = AdjustedArray(
              c_raw.astype(c.dtype),
              c_adjs,
              c.missing_value,
          )
  
      for c in currency_cols:
          codes_1d = self.raw_price_reader.currency_codes(sids)
          codes = repeat_first_axis(codes_1d, len(dates))
          out[c] = AdjustedArray(
              codes,
              adjustments={},
              missing_value=None,
          )
  
      return out
  
file_path: zipline/zipline/pipeline/loaders/equity_pricing_loader.py
imports: from collections import defaultdict
  from interface import implements
  from numpy import iinfo, uint32, multiply
  from zipline.data.fx import ExplodingFXRateReader
  from zipline.lib.adjusted_array import AdjustedArray
  from zipline.utils.numpy_utils import repeat_first_axis
  from .base import PipelineLoader
  from .utils import shift_dates
  from ..data.equity_pricing import EquityPricing
label_desc: Use image node_id 3 for calling the EquityPricingLoader obj's underlying member method code with example usage: obj.load_adjusted_array(domain, columns, dates, sids, mask) and returns: out