def history_bars(self, instrument, bar_count, frequency, fields, dt,
skip_suspended=True, include_now=False,
adjust_type='pre', adjust_orig=None):
if frequency != '1d':
raise NotImplementedError
if skip_suspended and instrument.type == 'CS':
bars = self._filtered_day_bars(instrument)
else:
bars = self._all_day_bars_of(instrument)
if bars is None or not self._are_fields_valid(fields, bars.dtype.names):
return None
dt = np.uint64(convert_date_to_int(dt))
i = bars['datetime'].searchsorted(dt, side='right')
left = i - bar_count if i >= bar_count else 0
bars = bars[left:i]
if adjust_type == 'none' or instrument.type in {'Future', 'INDX'}:
# 期货及指数无需复权
return bars if fields is None else bars[fields]
if isinstance(fields, str) and fields not in FIELDS_REQUIRE_ADJUSTMENT:
return bars if fields is None else bars[fields]
return adjust_bars(bars, self.get_ex_cum_factor(instrument.order_book_id),
fields, adjust_type, adjust_orig)
def history_bars(self, instrument, bar_count, frequency, fields, dt,
skip_suspended=True, include_now=False,
adjust_type='pre', adjust_orig=None):
if frequency != '1d':
raise NotImplementedError
if skip_suspended and instrument.type == 'CS':
bars = self._filtered_day_bars(instrument)
else:
bars = self._all_day_bars_of(instrument)
if bars is None or not self._are_fields_valid(fields, bars.dtype.names):
return None
dt = np.uint64(convert_date_to_int(dt))
i = bars['datetime'].searchsorted(dt, side='right')
left = i - bar_count if i >= bar_count else 0
bars = bars[left:i]
if adjust_type == 'none' or instrument.type in {'Future', 'INDX'}:
# 期货及指数无需复权
return bars if fields is None else bars[fields]
if isinstance(fields, str) and fields not in FIELDS_REQUIRE_ADJUSTMENT:
return bars if fields is None else bars[fields]
return adjust_bars(bars, self.get_ex_cum_factor(instrument.order_book_id),
fields, adjust_type, adjust_orig)
def history_bars(self,
instrument,
bar_count,
frequency,
fields,
dt,
skip_suspended=True,
include_now=False,
adjust_type='pre',
adjust_orig=None):
if self.is_base_frequency(instrument, frequency):
bars = self.raw_history_bars(instrument,
frequency,
end_dt=dt,
length=bar_count)
else:
num = int(frequency[:-1])
freq = frequency[-1]
if freq == "m":
lower_bar_count = (bar_count + 1) * num
bars = self.raw_history_bars(instrument,
"1" + freq,
end_dt=dt,
length=lower_bar_count)
if bars is None:
return super(OddFrequencyDataSource, self).history_bars(
instrument,
bar_count,
frequency,
fields,
dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=adjust_orig)
else:
if bars.size:
bars = self._resample_bars(bars, frequency)
dti = convert_dt_to_int(dt)
if bars["datetime"][-1] != dti and not include_now:
bars = bars[:-1]
bars = bars[-bar_count:]
else:
bars = bars[-bar_count:]
# TODO 跳过停牌
else:
return super(OddFrequencyDataSource,
self).history_bars(instrument,
bar_count,
frequency,
fields,
dt,
skip_suspended=skip_suspended,
include_now=include_now,
adjust_type=adjust_type,
adjust_orig=adjust_orig)
# if fields is not None:
# if not isinstance(fields, six.string_types):
# fields = [field for field in fields if field in bar_data]
if adjust_type == "none" or instrument.type in {"Future", "INDX"}:
return bars if fields is None else bars[fields]
if isinstance(fields, str) and fields not in FIELDS_REQUIRE_ADJUSTMENT:
return bars if fields is None else bars[fields]
return adjust_bars(bars,
self.get_ex_cum_factor(instrument.order_book_id),
fields, adjust_type, adjust_orig)