This month | In total |
---|---|
CRAN |
---|
… is an open-access tutorial about the gimms package which has been developed using GitBook.
The default server for online file retrieval changed from ECOCAST to A Big Earth Data Platform for Three Poles operated by The National Center for Atmospheric Research. ECOCAST is currently not reachable, and will likely no longer be considered in future releases. This change does not affect the core functionality provided by the package.
Online file retrieval from ECOCAST was recently unavailable due to
SSL certificate issues. This has been fixed as of
gimms-1.1.3. In addition,
gimms:::updateNasanex()
now yields correct online filepaths
as outlined in #3.
Starting with this update, rasterized NDVI3g.v0 images are no longer
kept in memory, but properly linked to their corresponding files on disk
(only applicable if ‘filename’ is specified in
rasterizeGimms()
).
As of 2018-01-13, the next minor release of gimms has finally arrived on CRAN. Check out NEWS for a full list of changes. In addition, note that the accompanying GitBook will be updated (and hopefully extended) soon.
oldNaming
For all users who prefer to work with the now outdated NDVI3g.v0 file
names, I’ve added a function called oldNaming
to the
‘develop’ branch. It takes a vector of .nc4 file names as input and
transforms them to traditional half-monthly file names, optionally
appending a suffix e.g. in preparation for
writeRaster
. As this is not on CRAN yet, remember to
install the ‘develop’ version via
::install_github("environmentalinformatics-marburg/gimms",
devtoolsref = "develop")
to be able to use that function in the first place.
I am happy to announce that the brand-new package update (v1.0.0) has successfully been built for all platforms and is now available from CRAN. Among the major improvements are:
rasterizeGimms
. In order to make sure older scripts are
still operable, separate calls to qualityControl
are
possible, but explicitly require the specification of a 2-layered
RasterStackBrick
object (NDVI and flags).rasterizeGimms
further takes an optional argument ‘ext’
which is passed to raster::crop
which, if used, drastically
reduces computation times. At the same time, the application of a scale
factor and the rejection of ‘mask-water’ and ‘mask-nodata’ values is no
longer optional.As of today, gimms 0.5.0 is available from CRAN and has some new functionality:
rasterizeGimms
. In addition to
the raw and scaled values of NDVI3g, the function now optionally returns
flag layers which can subsequently be used for quality control. Please
refer to the official README
for further reading.I decided to add optional multi-core support to
downloadGimms
, rasterizeGimms
and
monthlyComposite
. The referring arument is called ‘cores’
and, if not specified otherwise, defaults to 1 (i.e., parallel computing
is disabled). In the course of this, the gimms package
version on branch ‘develop’ has been incremented to 0.4.0 and can be
installed via devtools::install_github
(see further
below).
It’s Friday 13th and an updated version of the gimms package has been published on CRAN. The new version includes
significantTau
to calculate pixel-based (and optionally
pre-whitened) Mann-Kendall trend tests from a previously processed GIMMS
NDVI3g (or any kind of) ‘RasterStack/Brick’ object. Note that
it also works with simple ‘numeric’ vectors (i.e., univariate time
series observations);downloadGimms
that
enabled ‘Date’ input;downloadGimms
now works with ‘Date’ inputIn response to recent user suggestions, I decided to enable ‘Date’
input for downloadGimms
which grants the user a finer
control over the temporal coverage of the data to be downloaded. The
changes are currently available from the ‘develop’ branch via
::install_github("environmentalinformatics-marburg/gimms",
devtoolsref = "develop")
and will be submitted to CRAN soon.
significantTau
In order to account for lag-1 autocorrelation when trying to deduce
reliable long-term monotonous trends, gimms now
features a function called significantTau
. The code imports
the standard (i.e., without pre-whitening) procedure included in package
Kendall (McLeod, 2011) or, if the user decides to apply
pre-whitening prior to the actual trend test, one of the algorithms
included in zyp (Bronaugh and Consortium, 2013). Check
out ?significantTau
for further details.
downloadGimms
now works properly on WindowsI recently received a bug report about some strange behavior of
downloadGimms
(when working on Windows platforms) which
resulted in a rather awkward look of the rasterized images.
The problem was obviously related to download.file
which
worked just fine on Linux when using the default settings, but
introduced distortions on Windows. In the newest package version 0.2.0
which is now brand-new on CRAN, I therefore
specified download.file(..., mode = "wb")
to explicitly
enable binary writing mode.
Thanks again for the input!