- Added test coverage for grouped and masked top/bottom.
- Added test coverage for grouped rank on datetime factors.
- Fixed an issue where grouped rank would fail on datetime inputs
because unary-negative isn't defined for datetimes. We now instead
directly invoke a function from rank.pyx that does the normalizations
as neeeded.
- Fixed an issue where GroupedRowTransform assumed that it produced the
same dtype as its input. This isn't true for rank() of a
datetime-dtype factor. GroupedRowTransform now takes a required dtype
parameter.
- Similarly, fixed an issue where GroupedRowTransform assumed that its
missing_value was the same as its parent's, which isn't true for
rank() of a datetime-dtype factor. GroupedRowTransform now takes a
required dtype parameter.
- Fixed an issue where Factor.demean() and Factor.zscore() weren't
properly cached because their static_identity included a closure that
was dynamically generated on each invocation. They both now always
use a function defined at module scope.
AlgorithmSimulator will no longer check for capital changes.
Instead, TradingAlgorithm find and calculate the changes, and
PerformanceTracker will apply the changes
* BUG: Further corrections for days_at_time
- Revert to using DateOffset, as Timedelta doesn't handle offsetting by
one day over a tz change properly:
In [12]: pd.Timestamp('2004-04-05', tz='America/Chicago') + pd.Timedelta(days=-1)
Out[12]: Timestamp('2004-04-03 23:00:00-0600', tz='America/Chicago')
In [13]: pd.Timestamp('2004-04-05', tz='America/Chicago') + pd.DateOffset(days=-1)
Out[13]: Timestamp('2004-04-04 00:00:00-0600', tz='America/Chicago')
By creating a DateOffset using the `days` kwarg, the issue previously
fixed in bcc867b is addressed.
- To preempt any other pandas issues around day offsets, changes to
performing these with no timezone, then localizing to the local
timezone when shifting the time.
- Adds unit test for days_at_time
* STY: Remove unused import
Prior to pandas 17, there were issues with offsetting dates with
DateOffset around discontinuities (like the start of DST). We can use
Timedelta here instead, which handles these edge cases.
Scott Sanderson