def make_bar_data(asset_info, calendar):
 assert (PSEUDO_EPOCH.value < calendar.normalize().min().value <= asset_info['start_date'].min().value), ("calendar.min(): %s\nasset_info['start_date'].min(): %s" % (calendar.min(), asset_info['start_date'].min()))
 assert (asset_info['start_date'] < asset_info['end_date']).all()
 def _raw_data_for_asset(asset_id):
  "\n        Generate 'raw' data that encodes information about the asset.\n\n        See docstring for a description of the data format.\n        "
  datetimes = calendar[calendar.slice_indexer(asset_start(asset_info, asset_id), asset_end(asset_info, asset_id))]
  data = full((len(datetimes), len(US_EQUITY_PRICING_BCOLZ_COLUMNS)), ((asset_id * 100) * 1000), dtype=uint32)
  data[:, :5] += (arange(5, dtype=uint32) * 1000)
  data[:, :5] += (datetimes - PSEUDO_EPOCH).days[:, None].astype(uint32)
  frame = DataFrame(data, index=datetimes, columns=US_EQUITY_PRICING_BCOLZ_COLUMNS)
  frame['day'] = nanos_to_seconds(datetimes.asi8)
  frame['id'] = asset_id
  return frame
 for asset in asset_info.index:
  (yield (asset, _raw_data_for_asset(asset)))

def make_bar_data ( asset_info , calendar ) : assert ( PSEUDO_EPOCH . value < calendar . normalize ( ) . min ( ) . value <= asset_info [ 'start_date' ] . min ( ) . value ) , ( "calendar.min(): %s\nasset_info['start_date'].min(): %s" % ( calendar . min ( ) , asset_info [ 'start_date' ] . min ( ) ) ) assert ( asset_info [ 'start_date' ] < asset_info [ 'end_date' ] ) . all ( ) def _raw_data_for_asset ( asset_id ) : datetimes = calendar [ calendar . slice_indexer ( asset_start ( asset_info , asset_id ) , asset_end ( asset_info , asset_id ) ) ] data = full ( ( len ( datetimes ) , len ( US_EQUITY_PRICING_BCOLZ_COLUMNS ) ) , ( ( asset_id * 100 ) * 1000 ) , dtype = uint32 ) data [ : , : 5 ] += ( arange ( 5 , dtype = uint32 ) * 1000 ) data [ : , : 5 ] += ( datetimes - PSEUDO_EPOCH ) . days [ : , None ] . astype ( uint32 ) frame = DataFrame ( data , index = datetimes , columns = US_EQUITY_PRICING_BCOLZ_COLUMNS ) frame [ 'day' ] = nanos_to_seconds ( datetimes . asi8 ) frame [ 'id' ] = asset_id return frame for asset in asset_info . index : ( yield ( asset , _raw_data_for_asset ( asset ) ) )
for a given asset/date/column combination .