- (snr, \chi^2) numerators are computed analytically.  previously, changes
  to the KDE used to estimate the denominator PDF from sample histograms
  could change sensitivity measurements simply because of the effects those
  changes were having on the numerator signal model.  this patch removes
  that confusion.
- because the limited set of discrete prefactors used for constructing the
  numerator creates a stair-step effect, some amount of smoothing is
  desired in the numerator regardless.  this is smoothing, not density
  estimation, they are distinct from one another although the same code has
  been used to accomplish both in the past.  this patch moves that
  smoothing to where the source of the banding is in the code to
  disentangle it from the background density estimation.  if the prefactor
  banding is adjusted, that smoothing can be adjusted as well without
  entangling it with the denominator's kernel design.
- refs #2339

- refs #2429

- replace
	if blah:
		...

  with
  	if not blah:
		return
	...

- a histogram of likelihood ratios assigned to zero-lag candidates is
  required to implement the low-significance extinction model.  this patch
  reorganizes the source and sink of that information to be a separate file
  rather than piggy backing the data on the candidate parameter PDF file
  supplied to the trigger generator, e.g., during online running.

- immediately, this allows the statistics uploaded to gracedb along with
  each candidate to contain the actual ranking statistic PDF data used to
  rank the event, whereas prior to this patch it contains a mix of the
  candidate parameter PDFs and whatever was in the zero-lag histogram data
  supplied on input.  going forward, keeping distinct, unrelated, pieces of
  information in distinct places with different names that get supplied to
  programs using distinct command line options will prevent confusion over
  what is being stored where.

- refs #2429

- when doing online injection runs.
- online injection runs use an externally supplied coinc params
  distributions object, and the way that feature had been put in led to
  .finish() being invoked on such an object twice.  only need to do it
  once, on whichever will actually be used for computing ranking
  statistics.  this patch reorders a few statements and comments to remove
  the second .finish()

- this is only required for online running, and is actually forbidden for offline running.

- each time through the loop this script causes a relatively small number of ranking statistic samples to be generated, with the original intention being that over time the total number of samples would accumulate to something large.  this script discards the samples from the previous iteration, however, and starts over again from scratch each time.
- this patch modifies the script to include the output from the previous iteration in this iteration so that the ranking statistic histogram gathers additional samples over time.
- surprisingly the results seemed to be OK in the past, so it's possible that we don't need to do this.  in that case, this is a trivial stand-alone patch that can be easily reverted at a later time if desired.

- allows plots to be hacked to show the results had a ranking statistic threshold been imposed.

- move .finish() invocations into load_distributions() function

- because that's a more convenient indication of the contribution of these parameters to the ranking statistic than either the raw value or log-base-10 of the value.

- for consistency with other plots.

- in summary pages.
- refs #2427

CIT

running

- add override_dh_python2 target

- bump required version to 0.11.5
- update client library package names on Debian

(assuming the file necessary for its generation exists)

due to a bug in the pcdev3.phys.uwm.edu verison of matplotlib (1.1.1rc2) that
causes colorbars to overlap with their plots
gstlal_ll_inspiral_pipe: Made the offline summary page job optional, it will
only be included in the dag if --injection-file is provided

 - Introduced safety features to try and prevent file corruption
 - Introduced checks so that the program can identify and replace corrupt input
   files
plotsensitivity.py:
 - Fixed bug where plot cannot be finished due to having a missed injection at
   a time that segment information has not been downloaded for yet