- Instead of maintaining a separate `j` value, set the bounds of the range so
that `i` is the values emitted by the range.
- Change `close_loc` to `prev_close_loc` since the market close location is used
to ensure that the data index stops at the market open if the entire day is
nans.
- Change the setting of `loc` to be done before the loop which check for nans,
instead of setting to the previous close loc at the end of the loop.
This prepares for a separate fix to prevent out of bounds access when the first
session has nans for all minutes.
The minute to session sampling reading was creating two DataFrame
objects, the first to hold the minute data, and then a second returned
by the `DataFrame.groupby` to sample down to sessions.
Instead use the arrays returned by the minute readers `load_raw_arrays`
and implement sampling logic which takes advantage that the minutes
being passed start with the first minute of the first session and end
with the last minute of the last session.
On my machine this takes the tests in `test/test_continuous_futures`
from ~4.0 to about ~0.1 seconds.
dmichalowicz