starting reversion to geoquery lib

getting all the detectors in an area and then pumping them all to a
couchdb query is a slow way to go.  Using geoQuery, you only get
features that actually have data.  So it is either faster, or the same
speed, in theory.

The psql query is probably slower

and I have to post sort the features to group by identical features

Anyway, this is the first commit on this trail.  Refactored the query
service, splitting out the json or csv handler.  added logging via
winston, although that is untested. added winston to package.json
more refactoring and editing.  ready to start testing things

using json_or_csv_handler in both area_query versions

using groupBy in geo query handler to group by identical detector_ids

expect an array of features, or force it to be so in query_couch.
When the array is done getting passed to couchCache get function, then
the reducer function is called.

These options *should* produce correct results, with collation over
detectors and no duplicate detectors for a time period
area query service test is passing

forgot lodash in a_q_s
abandoning second way for the moment
skip local reducer and couch_cacher in favor of standalone ones
commented everything out

if I use couchCacher or reducer, there isn't anything there anyway.
also commenting out prevents node crashing because I am using
something or other in those that I don't want to require anymore
add switch to external libs  to tests too

now the test_couch_fetch code is actually an integrated test of
calvad_couch_cacher and calvad_reducer.
added new dependencies to package.json
tiny edit to readme to note that code is live on server
update for newer reducer library, outliers paths work

checked tests are passing and are properly calling the view that grabs
data that do not have outliers.
Merge branch 'refactor/fasterarea'