`for s in data` and methods like `for s in data.keys` were not producing
the same list of active sids
Make the other iteration methods match __iter__ by using the contains
method to check whether or not the sid is active.
For use of data outside of the algoscript context, which needs access
to all data fields use data._data
So that each reference to `.portfolio` in the algoscript,
cache the value of the portfolio, and mark the need for a new
value at the end of each dt in the tradesimulation loop.
The market_open_and_close method was a performance bottleneck,
since it was creating new dates on each query for open and close.
Instead use the pre-rendered frame of open and closes values
from the trading environment.
The code that was consuming noop_environment now uses a
real trading environment.
As more behavior relies on an accurate trading calendar, maintaining
the noop environment was a constraint that was more overhead than it
is worth.
Passing the exchange time timestamp to is_market_hours was ending
up with odd behavior due to conversion back to UTC when checking
the is_trading_day boolean.
Use the early closes to populate a DataFrame which includes
the open and close minute for each day.
To be used by the environment instead of calculating each value
mid-backtest.
In the performance period the max_leverage, max_capital_used,
cumulative_capital_used were calculated but not used.
At least one of those calculations, max_leverage, was causing a
divide by zero error.
Instead of papering over that error, the entire calculation was
a bit suspect so removing, with possibility of adding it back in
later with handling the case (or raising appropriate errors) when
the algorithm has little cash on hand.
Check for whether or not the index's timezone is UTC or not before
attempting to localize, since an already localized index throws an
error when tz_localize is called.
Instead of nesting order direction and related stop and limit logic,
derive a bitwise mask from the combination of order configurations
and use the mask as a 'switch'.
Remove the lists of DailyReturn objects in favor of using pd.Series
to store the return values.
Should make it easier to inspect the values when stepping through,
make the windowing of data to a certain range more facile by using,
and have some performance increases due to removing object creation
and member access.
This reverts commit 17b8980fb9.
Backing out rigidness of market and close, while sorting out how
to handle events that are not on a day in the trading calendar.
Eddie Hebert