def resample(self, sampling_frequency: str) -> Optional['TradeBars']:
'''
Downsample the trade bars data into a new bar frequency
Args:
sampling_frequency: See sampling frequency in pandas
'''
if sampling_frequency is None:
return self
df = self.df()
# Rename timestamps to timestamp
df.index.name = 'timestamp'
df = resample_trade_bars(df, sampling_frequency)
o = df.o if 'o' in df.columns else None
h = df.h if 'h' in df.columns else None
_l = df.l if 'l' in df.columns else None
v = df.v if 'v' in df.columns else None
vwap = df.vwap if 'vwap' in df.columns else None
trade_bar = TradeBars(df.timestamp, df.c, o, h, _l, v, vwap)
trade_bar._set_valid_rows()
return trade_bar
def _resample(self, sampling_frequency: Optional[str]) -> None:
if sampling_frequency is None: return None
for data in self.data_list:
if isinstance(data, TimeSeries) or isinstance(data, TradeSet):
data.timestamps, data.values = resample_ts(data.timestamps, data.values, sampling_frequency)
elif isinstance(data, TradeBarSeries):
df_dict = {}
cols = ['timestamps', 'o', 'h', 'l', 'c', 'v', 'vwap']
for col in cols:
val = getattr(data, col)
if val is not None:
df_dict[col] = val
df = pd.DataFrame(df_dict)
df = df.set_index('timestamps')
df = resample_trade_bars(df, sampling_frequency)
for col in cols:
if col in df:
setattr(data, col, df[col].values)
else:
raise Exception(f'unknown type: {data}')