def _start_finish(self):
# A live feed (for example) may have learnt something about the
# timezones after the start and that's why the date/time related
# parameters are converted at this late stage
# Get the output timezone (if any)
self._tz = self._gettz()
# Lines have already been create, set the tz
self.lines.datetime._settz(self._tz)
# This should probably be also called from an override-able method
self._tzinput = bt.utils.date.Localizer(self._gettzinput())
# Convert user input times to the output timezone (or min/max)
if self.p.fromdate is None:
self.fromdate = float('-inf')
else:
self.fromdate = self.date2num(self.p.fromdate)
if self.p.todate is None:
self.todate = float('inf')
else:
self.todate = self.date2num(self.p.todate)
# FIXME: These two are never used and could be removed
self.sessionstart = time2num(self.p.sessionstart)
self.sessionend = time2num(self.p.sessionend)
self._calendar = cal = self.p.calendar
if cal is None:
self._calendar = self._env._tradingcal
elif isinstance(cal, string_types):
self._calendar = PandasMarketCalendar(calendar=cal)
self._started = True
def _start_finish(self):
# A live feed (for example) may have learnt something about the
# timezones after the start and that's why the date/time related
# parameters are converted at this late stage
# Get the output timezone (if any)
self._tz = self._gettz()
# Lines have already been create, set the tz
self.lines.datetime._settz(self._tz)
# This should probably be also called from an override-able method
self._tzinput = bt.utils.date.Localizer(self._gettzinput())
# Convert user input times to the output timezone (or min/max)
if self.p.fromdate is None:
self.fromdate = float('-inf')
else:
self.fromdate = self.date2num(self.p.fromdate)
if self.p.todate is None:
self.todate = float('inf')
else:
self.todate = self.date2num(self.p.todate)
# FIXME: These two are never used and could be removed
self.sessionstart = time2num(self.p.sessionstart)
self.sessionend = time2num(self.p.sessionend)
self._calendar = cal = self.p.calendar
if cal is None:
self._calendar = self._env._tradingcal
elif isinstance(cal, string_types):
self._calendar = PandasMarketCalendar(calendar=cal)
self._started = True
def dopostinit(cls, _obj, *args, **kwargs):
_obj, args, kwargs = \
super(MetaAbstractDataBase, cls).dopostinit(_obj, *args, **kwargs)
_obj._name = _obj.p.name
_obj._compression = _obj.p.compression
_obj._timeframe = _obj.p.timeframe
if _obj.p.sessionstart is None:
_obj.p.sessionstart = datetime.time(0, 0, 0)
if _obj.p.sessionend is None:
_obj.p.sessionend = datetime.time(23, 59, 59)
if isinstance(_obj.p.fromdate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.fromdate = datetime.datetime.combine(
_obj.p.fromdate, _obj.p.sessionstart)
if isinstance(_obj.p.todate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.todate = datetime.datetime.combine(
_obj.p.todate, _obj.p.sessionend)
_obj.fromdate = date2num(_obj.p.fromdate)
_obj.todate = date2num(_obj.p.todate)
_obj.sessionstart = time2num(_obj.p.sessionstart)
_obj.sessionend = time2num(_obj.p.sessionend)
# hold datamaster points corresponding to own
_obj.mlen = list()
return _obj, args, kwargs
def dopostinit(cls, _obj, *args, **kwargs):
_obj, args, kwargs = \
super(MetaAbstractDataBase, cls).dopostinit(_obj, *args, **kwargs)
_obj._name = _obj.p.name
_obj._compression = _obj.p.compression
_obj._timeframe = _obj.p.timeframe
if isinstance(_obj.p.sessionstart, datetime.datetime):
_obj.p.sessionstart = _obj.p.sessionstart.time()
if _obj.p.sessionstart is None:
_obj.p.sessionstart = datetime.time(0, 0, 0)
if isinstance(_obj.p.sessionend, datetime.datetime):
_obj.p.sessionend = _obj.p.sessionend.time()
if _obj.p.sessionend is None:
_obj.p.sessionend = datetime.time(23, 59, 59)
if isinstance(_obj.p.fromdate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.fromdate = datetime.datetime.combine(
_obj.p.fromdate, _obj.p.sessionstart)
if isinstance(_obj.p.todate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.todate = datetime.datetime.combine(_obj.p.todate,
_obj.p.sessionend)
_obj.fromdate = date2num(_obj.p.fromdate)
_obj.todate = date2num(_obj.p.todate)
_obj.sessionstart = time2num(_obj.p.sessionstart)
_obj.sessionend = time2num(_obj.p.sessionend)
# hold datamaster points corresponding to own
_obj.mlen = list()
_obj._barstack = collections.deque() # for filter operations
_obj._filters = list()
_obj._ffilters = list()
for fp in _obj.p.filters:
if inspect.isclass(fp):
fp = fp(_obj)
if hasattr(fp, 'last'):
_obj._ffilters.append((fp, [], {}))
_obj._filters.append((fp, [], {}))
return _obj, args, kwargs
def dopostinit(cls, _obj, *args, **kwargs):
_obj, args, kwargs = \
super(MetaAbstractDataBase, cls).dopostinit(_obj, *args, **kwargs)
_obj._name = _obj.p.name
_obj._compression = _obj.p.compression
_obj._timeframe = _obj.p.timeframe
if isinstance(_obj.p.sessionstart, datetime.datetime):
_obj.p.sessionstart = _obj.p.sessionstart.time()
if _obj.p.sessionstart is None:
_obj.p.sessionstart = datetime.time(0, 0, 0)
if isinstance(_obj.p.sessionend, datetime.datetime):
_obj.p.sessionend = _obj.p.sessionend.time()
if _obj.p.sessionend is None:
_obj.p.sessionend = datetime.time(23, 59, 59)
if isinstance(_obj.p.fromdate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.fromdate = datetime.datetime.combine(
_obj.p.fromdate, _obj.p.sessionstart)
if isinstance(_obj.p.todate, datetime.date):
# push it to the end of the day, or else intraday
# values before the end of the day would be gone
_obj.p.todate = datetime.datetime.combine(
_obj.p.todate, _obj.p.sessionend)
_obj.fromdate = date2num(_obj.p.fromdate)
_obj.todate = date2num(_obj.p.todate)
_obj.sessionstart = time2num(_obj.p.sessionstart)
_obj.sessionend = time2num(_obj.p.sessionend)
# hold datamaster points corresponding to own
_obj.mlen = list()
_obj._barstack = collections.deque() # for filter operations
_obj._filters = list()
_obj._ffilters = list()
for fp in _obj.p.filters:
if inspect.isclass(fp):
fp = fp(_obj)
if hasattr(fp, 'last'):
_obj._ffilters.append((fp, [], {}))
_obj._filters.append((fp, [], {}))
return _obj, args, kwargs
def __init__(self, data):
self.tmnum = time2num(self.p.endtime)
def __init__(self, data):
self.tmnum = time2num(self.p.endtime)
