10x speedup of proportion_of_energy_submetered ;)

Prior to this change, the function took 154 seconds for REDD house 1
on my 2.4GHz i5 M450 HP laptop.

It now takes 16 seconds.

The change was simple: profiling revealed that
`pytables.select_coords` was the bottleneck.  We only use this
function to get the `look_ahead`.  So this patch changes the behaviour
of `DataStore.load` so it defaults to *not* load `look_ahead`.

(This change breaks a test.  Will fix that...)
fixed test which was broken by making `n_look_ahead_rows` default to 0 rows.
`dataframe.timeframe` is now set to the *requested* TimeFrame.
Part of the fix for #133
Setting the `dataframe.timeframe` should now do the right thing even
if each we do multiple subchunks per requested section (which will
happen if the `chunksize` is smaller than the number of rows of any
given `section`)