The new TradingCalendar method is called `minute_index_to_session_labels`.
It takes a DatetimeIndex of in-order market minutes and returns a
DatetimeIndex of the corresponding sessions.
The new method is approximately 100x faster than mapping
`minute_to_session_label` over a large DatetimeIndex.
Encapsulate the shared global calendar map in an object.
This allows consumers that don't want to participate in custom
registration to pass around a calendar dispatcher, and would make it
easier to support contextual management of the global calendar map if we
want to do that in the future.
As a bonus, we now only create one instance of each calendar, instead of
one per alias.
Previously, run_algorithm caused an error if run on raw (non-bundle)
data, because of uninitialized variables. Initializing those variables
to None to allow run_algorithm to work with Panel data, etc.
Also, run_algorithm did not create sim_params for the TradingAlgorithm
instance it created; this kicked the can to TradingAlgorithm, which
gets default sim_params with data_frequency 'daily'. To support minute
bars, changing run_algorithm to create its own sim_params with the
data_frequency specified in its arguments.
Changes the overlap behavior so that it is an error to write data which
would have two companies holding the same ticker. Other than one test
around which company would win in that case, all the other tests are
passing. That single test has been changed to check the write-time
error.
* 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.
Instead of having separate ExchangeCalendar and TradingSchedule objects, we
now just have TradingCalendar. The TradingCalendar keeps track of each
session (defined as a contiguous set of minutes between an open and a close).
It's also responsible for handling the grouping logic of any given minute
to its containing session, or the next/previous session if it's not a market
minute for the given calendar.
In preparation of adding futures, add equity to the names of both the
classes and methods for writing bcolz data. Futures data will use a
different minutes per day with a separate reader. This change will allow
both equity and futures fixtures to be side by side.
Also, break out the method which generates the dataframes and trading
days member into fixtures (`EquityMinuteBarData` and
`EquityDailyBarData`) on which the `*BarReader` fixture depends. This
fixture is separated out to enable reader/writers in different formats
to use the same data setup. (There is internal code which needs to write
minute and daily bar data in a database format.)
Jean Bredeche