def init_tick_key_list_for_retrospection(self, retrospective_ticks: int):
offset_time_stamp = MyDate.get_offset_timestamp(days=-retrospective_ticks)
self._tick_key_list_for_retrospection = []
while offset_time_stamp < MyDate.time_stamp_now():
offset_time_stamp += self._seconds_unit
date_str = str(MyDate.get_date_from_epoch_seconds(offset_time_stamp))
self._tick_key_list_for_retrospection.append(date_str)
def get_grouped_by_for_wave_peak_plotting(self,
wave_peak_date_type: str,
aggregation=1,
offset_date=''):
if wave_peak_date_type in [WPDT.DAILY_DATE, WPDT.INTRADAY_DATE]:
where_clause = "{}='{}'".format(
DC.PERIOD, PRD.DAILY
if wave_peak_date_type == WPDT.DAILY_DATE else PRD.INTRADAY)
columns = [
DC.EQUITY_INDEX, DC.PERIOD, DC.PERIOD_AGGREGATION,
DC.WAVE_TYPE, DC.WAVE_END_DATE, DC.TICKER_ID
]
if offset_date != '':
where_clause += " AND {}>'{}'".format(DC.WAVE_END_DATE,
offset_date)
else: # here we take only the intraday waves with the proper aggregation
columns = [
DC.EQUITY_INDEX, DC.PERIOD, DC.PERIOD_AGGREGATION,
DC.WAVE_TYPE, DC.WAVE_END_TS, DC.WAVE_END_DT, DC.TICKER_ID
]
offset_ts = MyDate.get_offset_timestamp(days=-10)
where_clause = "{}='{}' AND {}>{} AND {}={}".format(
DC.PERIOD, PRD.INTRADAY, DC.WAVE_END_TS, offset_ts,
DC.PERIOD_AGGREGATION, aggregation)
df = self.get_all_as_data_frame(columns=columns,
where_clause=where_clause)
if df.empty:
return df
df = df.groupby(columns[:-1]).count()
return df.reset_index(drop=False)