Hi Folks,
We are pleased to announce the release of LAS 7.2
(ftp://ftp.pmel.noaa.gov/pub/las/las.v7.2.tar.gz). This version
includes new features for vector variables and new products and
capabilities for multiple variables. The release notes
(http://ferret.pmel.noaa.gov/LAS/documentation/las-release-notes-7-2/)
have several example plots showing off the new features.
Please upgrade to this release and send your feedback to the list.
Roland
LAS Release Notes (7.2)
by
roland —
last modified 2010-12-16 19:38
The current release is LAS 7.2
(December 2010)
This version of LAS requires Ferret 6.65.
Important Housekeeping Detail
The server configuration directory will now be installed under
$TOMCAT_HOME/content/las/ instead of the the directory where you
unpack
your LAS and run configure. You'll need to locate this directory
and apply your changes to the configuration there after the
install.
Major New Features
Multiple Variable Selection
LAS now supports selection of more than one variable from the
same data set on the main interface. When more than one variable
is
selected you can make new visualizations appropriate for the
number of
variables you have chosen.
- Time series line plots will include all of the variables
selected with multiple axis scales and line colors.
-
You can make property-property scatter plots of two different
variables.
- You can also color the symbols in a property-property plot by
the value of a third variable.
Vector Variables
- Vector variables and vector plots are now supported (in XY, XT
and YT dimensions).
- Vectors can be plotted in the vizGal comparison
tool and the difference between to vector variable can be
plotted in XY
using vizGal.
- vizGal itself has new layout and some new features that allow
comparisons along any axis. For example, you can make time
series
plots with a different point in XY selected in each of the
panels.
- The addXML utility automatically detects and configures many
vector variable when scanning a THREDDS catalog or other netCDF
data source with containing multiple variables.