TimeseriesFactory.get_timeseries() pads to the requested interval with NaNs,
filling in start/end gaps. TimeseriesFactory.put_timeseries() is supposed to
do this (according to Jeremy Fee), but it was trimming NaNs from the start/
end before writing to file. This PR fixes this by using ObsPy's Stream.trim()
method, in a similar manner to TimesereisFactory.get_timeseries(), to pad to
the specified start and end of the urlInterval..

We recently reviewed our various data products and found discrepancy in some of the metadata.  We have updated these values based on recent measurements.  I've modified these values in ObservatoryMetadata.py to be consistent with our other data products.

By default, each element of the SQ vector (i.e., shat returned from additive())
is treated as if it is independent of its nearest neighbors in time. This is
not generally true, but to treat this in a completely statistically robust
manner would be computationally prohibitive. Instead, we apply a Gaussian
smoother/filter to a limited set of SQ elements in the neighborhood of the
current time step. The configuration parameter 'smooth' specifies the period
(in samples) at which one requires the amplitude to be attenuated by half.
Longer periods will be less attenuated, while shorter periods will be more
attenuated.

Also, added the running estimate of the standard error (i.e., sigmahat) to
the stream returned by process_one().

Fixes #131

- changed default values for alpha and gamma for command line script
  to zero, which means SV and/or SQ do not evolve over time
- modified SqDist_usage.md to show how to explicitly set alpha and
  gamma to desired values
- MUST modify production scripts to explicitly set alpha and gamma
  before accpeting this pull request.

Changed how Popen is calling parameters,  to take care of the case of spaces in passwords and/or user names.

Reworked to pass kwargs to the base classes,  and retreived _post_process from the old IMFV283Factory.py