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BUG: Group and aggregate downsampling by trading day.

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Otherwise, out of market events would result in a mishaped
panel.
This commit is contained in:
fawce
2013-10-17 21:18:28 -04:00
committed by Eddie Hebert
parent 17b8980fb9
commit 0ceabb590b
1 changed files with 30 additions and 16 deletions
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zipline/transforms/batch_transform.py
+30 -16
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@@ -49,7 +49,7 @@ def get_sample_func(item):
return 'last'
def downsample_panel(minute_rp, daily_rp, dt):
def downsample_panel(minute_rp, daily_rp, mkt_close):
"""
@minute_rp is a rolling panel, which should have minutely rows
@daily_rp is a rolling panel, which should have daily rows
@@ -63,14 +63,27 @@ def downsample_panel(minute_rp, daily_rp, dt):
cur_panel = minute_rp.get_current()
sids = minute_rp.minor_axis
day_frame = pd.DataFrame(columns=sids, index=cur_panel.items)
dt1 = trading.environment.normalize_date(mkt_close)
dt2 = trading.environment.next_trading_day(mkt_close)
by_close = functools.partial(get_date, mkt_close, dt1, dt2)
for item in minute_rp.items:
frame = cur_panel[item]
func = get_sample_func(item)
dframe = frame.groupby(lambda d: d.date()).resample('1d', how=func)
# group by trading day, using the market close of the current
# day. If events occurred after the last close (yesterday) but
# before today's close, group them into today.
dframe = frame.groupby(lambda d: by_close(d)).agg(func)
for stock in sids:
day_frame[stock][item] = dframe[stock][dframe.index[-1][0]]
day_frame[stock][item] = dframe[stock].ix[dt1]
# store the frame at midnight instead of the close
daily_rp.add_frame(trading.environment.normalize_date(dt), day_frame)
daily_rp.add_frame(dt1, day_frame)
def get_date(mkt_close, d1, d2, d):
if d > mkt_close:
return d2
else:
return d1
class BatchTransform(object):
@@ -276,24 +289,25 @@ class BatchTransform(object):
if self.rolling_panel is None:
self._init_panels(sids)
# update trading day counters
_, mkt_close = trading.environment.get_open_and_close(event.dt)
if self.bars == 'daily':
# Daily bars have their dt set to midnight.
mkt_close = trading.environment.normalize_date(mkt_close)
if event.dt >= mkt_close:
if self.downsample:
downsample_panel(self.rolling_panel,
self.daily_rolling_panel,
mkt_close)
self.trading_days_total += 1
# Store event in rolling frame
self.rolling_panel.add_frame(event.dt,
pd.DataFrame(event.data,
index=self.field_names,
columns=sids))
# update trading day counters
_, mkt_close = trading.environment.get_open_and_close(event.dt)
if self.bars == 'daily':
# Daily bars have their dt set to midnight.
mkt_close = trading.environment.normalize_date(mkt_close)
if event.dt == mkt_close:
if self.downsample:
downsample_panel(self.rolling_panel,
self.daily_rolling_panel,
mkt_close
)
self.trading_days_total += 1
self.last_dt = event.dt
if self.trading_days_total >= self.window_length: