minimal update so that output of pism_python.py runs with current dev
maintaining pism_matlab.m as well
separated volume and area scaling factors (exponents) in summary-to-stdout
first try on set up of laboratory validation case based on Sayag & Worster (2012)
This version of the run script uses the bedsmoother result as a smoothed bed.  Not ideal; better interpolation (e.g. nco conservative regridding) would be better than this gross smoothing.
Removes the last mention of MASK_FLOATING_AT_TIME_0 from the manual.
Attempt to document -ocean_kill and -eigen_calving models better.
Some edits to manual, but mostly renaming sections and moving subsections around.  Feedback sought.
This is a better name for the .tex file which has sections 3 and 4.
summaryPrintLine() now uses configuration parameter summary_time_unit_name so that model time is printed to stdout with user-preferred units.  Cleaned up documentation on summaryPrintLine().
Make duration of preliminary step configurable.
Removed magic small numbers ('epsilon') from adaptive time stepping.  This makes very small difference in two verif test regressions (E and L); will fix those.
Updating laboratory validation case stuff, but not there yet.
Update test E and test L regressions.  Very small changes.  Attempt to make test L faster by doing 21,31 grids instead of 31,43.
Found two more magic numbers, and made them configurable: these are the thickness standards for icefree and floating mask criteria.  (And those are the last of the magic numbers ... see next commit.)
This version runs and produces flows very much like Sayag & Worster (2012).  (But now I need to know what numbers they really got.)
This example is ready to go, if only we had the raw data to compare to.  Note that sqrt(iarea/pi) is r(t) to compare to data in Figure 4(a) in Sayag & Worster (2012).
For laboratory validation to compare to Sayag & Worster (2012):  Now I can plot results the right way.  I need the raw data to compare to.
Change of radius of pipe.  Still just a guess.
Minor: add spatial diagnostics.  Looks good.