def _compute(self, start_dt, end_dt):
previous_tick = self._storage.load_previous_tick(start_dt)
if previous_tick is None:
previous_tick_end = self._params['start']
else:
previous_tick_end = previous_tick.name
# Calculate ticks from the previous ticks until the interval that we are currently interested in
request = [FeatureRequest.from_feature(self)]
if previous_tick_end != start_dt:
self._runner.compute_dataframes(request, previous_tick_end, start_dt)
new_previous_tick = self._storage.load_previous_tick(start_dt)
if new_previous_tick is None or new_previous_tick.empty:
new_previous_tick = previous_tick
# Should be up-to-date now, so get the updated latest tick
# If there is still no previous tick then we have to start from the beginning
if new_previous_tick is None:
start = self._params['start']
elif new_previous_tick.empty:
raise ValueError('This should not be possible')
else:
start = new_previous_tick.name + dt.timedelta(microseconds=1)
return self._compute_recursion(previous_tick, start, end_dt)
def _compute(self, start_dt, end_dt):
if end_dt < self._params['start']:
msg = 'Can''t calculate this range as {} is before the clock start {}'
raise ValueError(msg.format(end_dt, self._params['start']))
previous_tick = self._storage.load_previous_tick(start_dt)
if previous_tick is None:
previous_tick_end = self._params['start']
else:
previous_tick_end = previous_tick.name + datetime.timedelta(microseconds=1)
# Calculate ticks from the previous ticks until the interval that we are currently interested in
request = [FeatureRequest.from_feature(self)]
if previous_tick_end != start_dt:
self._runner.compute_dataframes(request, previous_tick_end, start_dt)
new_previous_tick = self._storage.load_previous_tick(start_dt)
if new_previous_tick is None or new_previous_tick.empty:
new_previous_tick = previous_tick
else:
new_previous_tick = previous_tick
# Should be up-to-date now, so get the updated latest tick
# If there is still no previous tick then we have to start from the beginning
if new_previous_tick is None:
start = self._params['start']
elif new_previous_tick.empty:
raise ValueError('This should not be possible')
else:
start = new_previous_tick.name + datetime.timedelta(microseconds=1)
clock = self._clock_feature(start, end_dt)
if len(clock) == 0:
# There are no ticks in this range, so nothing to do
return None
input = self._input_feature(clock.iloc[0]['previous'], clock.iloc[-1].name)
clock['tick'] = clock.index.to_series(keep_tz=True)
merged_data = pd.merge_asof(input, clock.set_index('previous', drop=False),
left_index=True, right_index=True)
ticks = []
for tick, df in merged_data.groupby('tick'):
clock_tick = clock.loc[tick]
new_previous_tick = pd.Series(self._compute_recursive_tick(clock_tick, new_previous_tick, df),
name=tick)
ticks.append(new_previous_tick)
return pd.DataFrame([t for t in ticks if end_dt > t.name >= start_dt])