def __init__(self, wrapper, records_arr, close, idx_field='idx', **kwargs):
Records.__init__(
self,
wrapper,
records_arr,
idx_field=idx_field,
close=close,
**kwargs
)
self._close = broadcast_to(close, wrapper.dummy(group_by=False))
if not all(field in records_arr.dtype.names for field in order_dt.names):
raise TypeError("Records array must match order_dt")
def __init__(self, records_arr, ts, freq=None, idx_field='end_idx', group_by=None):
Records.__init__(
self,
records_arr,
ArrayWrapper.from_obj(ts, freq=freq),
idx_field=idx_field,
group_by=group_by
)
PandasIndexer.__init__(self, _indexing_func)
if not all(field in records_arr.dtype.names for field in drawdown_dt.names):
raise ValueError("Records array must have all fields defined in drawdown_dt")
self.ts = ts
def __init__(self, wrapper, records_arr, ts, idx_field='end_idx'):
Records.__init__(self, wrapper, records_arr, idx_field=idx_field)
Configured.__init__(self,
wrapper=wrapper,
records_arr=records_arr,
ts=ts,
idx_field=idx_field)
self._ts = ts
if not all(field in records_arr.dtype.names
for field in drawdown_dt.names):
raise ValueError(
"Records array must have all fields defined in drawdown_dt")
PandasIndexer.__init__(self, _indexing_func)
def __init__(self, wrapper, records_arr, close, idx_field='exit_idx'):
Records.__init__(self, wrapper, records_arr, idx_field=idx_field)
Configured.__init__(self,
wrapper=wrapper,
records_arr=records_arr,
close=close,
idx_field=idx_field)
self.close = close
if not all(field in records_arr.dtype.names
for field in event_dt.names):
raise ValueError(
"Records array must have all fields defined in event_dt")
PandasIndexer.__init__(self, _indexing_func)
def _indexing_func(self, pd_indexing_func):
"""Perform indexing on `Drawdowns`."""
new_wrapper, new_records_arr, _, col_idxs = \
Records._indexing_func_meta(self, pd_indexing_func)
new_ts = new_wrapper.wrap(self.ts.values[:, col_idxs], group_by=False)
return self.copy(wrapper=new_wrapper,
records_arr=new_records_arr,
ts=new_ts)
def __init__(self,
wrapper,
records_arr,
ts,
idx_field='end_idx',
**kwargs):
Records.__init__(self,
wrapper,
records_arr,
idx_field=idx_field,
ts=ts,
**kwargs)
self._ts = ts
if not all(field in records_arr.dtype.names
for field in drawdown_dt.names):
raise TypeError("Records array must match drawdown_dt")
def __init__(self,
wrapper: ArrayWrapper,
records_arr: tp.RecordArray,
ts: tp.ArrayLike,
idx_field: str = 'end_idx',
**kwargs) -> None:
Records.__init__(self,
wrapper,
records_arr,
idx_field=idx_field,
ts=ts,
**kwargs)
self._ts = broadcast_to(ts, wrapper.dummy(group_by=False))
if not all(field in records_arr.dtype.names
for field in drawdown_dt.names):
raise TypeError("Records array must match drawdown_dt")
def __init__(self,
records_arr,
main_price,
freq=None,
idx_field='exit_idx'):
Records.__init__(self,
records_arr,
ArrayWrapper.from_obj(main_price, freq=freq),
idx_field=idx_field)
PandasIndexer.__init__(self, _indexing_func)
if not all(field in records_arr.dtype.names
for field in event_dt.names):
raise ValueError(
"Records array must have all fields defined in event_dt")
self.main_price = main_price
def _indexing_func_meta(self, pd_indexing_func):
"""Perform indexing on `Orders` and return metadata."""
new_wrapper, new_records_arr, group_idxs, col_idxs = \
Records._indexing_func_meta(self, pd_indexing_func)
new_close = new_wrapper.wrap(to_2d(self.close, raw=True)[:, col_idxs],
group_by=False)
return self.copy(wrapper=new_wrapper,
records_arr=new_records_arr,
close=new_close), group_idxs, col_idxs
def indexing_func(self: DrawdownsT,
pd_indexing_func: tp.PandasIndexingFunc,
**kwargs) -> DrawdownsT:
"""Perform indexing on `Drawdowns`."""
new_wrapper, new_records_arr, _, col_idxs = \
Records.indexing_func_meta(self, pd_indexing_func, **kwargs)
new_ts = new_wrapper.wrap(self.ts.values[:, col_idxs], group_by=False)
return self.copy(wrapper=new_wrapper,
records_arr=new_records_arr,
ts=new_ts)
def __init__(self, wrapper, records_arr, close, idx_field='exit_idx',
trade_type=TradeType.Trade, **kwargs):
Records.__init__(
self,
wrapper,
records_arr,
idx_field=idx_field,
close=close,
trade_type=trade_type,
**kwargs
)
self._close = broadcast_to(close, wrapper.dummy(group_by=False))
self._trade_type = trade_type
if trade_type == TradeType.Trade:
if not all(field in records_arr.dtype.names for field in trade_dt.names):
raise TypeError("Records array must match trade_dt")
else:
if not all(field in records_arr.dtype.names for field in position_dt.names):
raise TypeError("Records array must match position_dt")
def indexing_func_meta(
self: OrdersT, pd_indexing_func: tp.PandasIndexingFunc,
**kwargs) -> tp.Tuple[OrdersT, tp.MaybeArray, tp.Array1d]:
"""Perform indexing on `Orders` and return metadata."""
new_wrapper, new_records_arr, group_idxs, col_idxs = \
Records.indexing_func_meta(self, pd_indexing_func, **kwargs)
new_close = new_wrapper.wrap(to_2d(self.close, raw=True)[:, col_idxs],
group_by=False)
return self.copy(wrapper=new_wrapper,
records_arr=new_records_arr,
close=new_close), group_idxs, col_idxs
def indexing_func(self: RangesT, pd_indexing_func: tp.PandasIndexingFunc,
**kwargs) -> RangesT:
"""Perform indexing on `Ranges`."""
new_wrapper, new_records_arr, _, col_idxs = \
Records.indexing_func_meta(self, pd_indexing_func, **kwargs)
if self.ts is not None:
new_ts = new_wrapper.wrap(self.ts.values[:, col_idxs],
group_by=False)
else:
new_ts = None
return self.replace(wrapper=new_wrapper,
records_arr=new_records_arr,
ts=new_ts)
def indexing_func(self: OrdersT, pd_indexing_func: tp.PandasIndexingFunc, **kwargs) -> OrdersT:
"""Perform indexing on `Orders`."""
new_wrapper, new_records_arr, group_idxs, col_idxs = \
Records.indexing_func_meta(self, pd_indexing_func, **kwargs)
if self.close is not None:
new_close = new_wrapper.wrap(to_2d_array(self.close)[:, col_idxs], group_by=False)
else:
new_close = None
return self.replace(
wrapper=new_wrapper,
records_arr=new_records_arr,
close=new_close
)
