similar to: [newbie] how to represent very skewed spatial data?

summary: image.plot-ing two sets of netCDF data, with the second derived from the first. First plots to PDF as expected (title, data, legend). Second plots the data and title, but abends before drawing the legend, with > Error in if (del == 0 && to == 0) return(to) : > missing value where TRUE/FALSE needed > Calls: plot.layers.for.timestep -> image.plot -> seq ->

summary: how to convert a 3D array (as obtained from ncdf4::ncvar_get) to a dataframe suitable for use by lattice::levelplot(), e.g., levelplot(conc ~ lon * lat | lev, data = data.frame) details: I have atmospheric data in netCDF files specifying gas concentrations over a 3D space with dimensions longitude, latitude, and (vertical) level. I need to plot the data by level. Since there are

Hi Peter, apply(t(apply(mm,1,rep,each=3)),2,rep,each=3) Jim On Wed, Jul 5, 2017 at 5:20 PM, Anthoni, Peter (IMK) <peter.anthoni at kit.edu> wrote: > Hi all, > (if me email goes out as html, than my email client don't do as told, and I apologies already.) > > We need to downscale climate data and therefore first need to expand the climate from 0.5deg to the higher

Hi R-users, I'm attempting to fit a number of mixed models, all with the same structure, across a spatial grid with data points collected at various time points within each grid cell. I'm trying to use a 'for' loop to try the model fit on each grid cell. In some cells lme does not converge, giving me the error: Error message: In lme.formula(logarea ~ year + summ_d, data =

You probably ought to be using the raster package. See the CRAN Spatial Task View. -- Sent from my phone. Please excuse my brevity. On July 5, 2017 12:20:28 AM PDT, "Anthoni, Peter (IMK)" <peter.anthoni at kit.edu> wrote: >Hi all, >(if me email goes out as html, than my email client don't do as told, >and I apologies already.) > >We need to downscale climate

I'm new but am already starting to accumulate utility functions for the fairly specialized kinds of data files with which I work. I'd like to keep those functions in a single folder, or filetree rooted at a specific folder under my $HOME (I'm running linux), for ease of * source()-ing * git commit to bitbucket * scp to clusters I'm wondering, 1 is there a canonical location for

Hi all, (if me email goes out as html, than my email client don't do as told, and I apologies already.) We need to downscale climate data and therefore first need to expand the climate from 0.5deg to the higher resolution 10min, before we can add high resolution deviations. We basically need to have the original data at each gridcell replicated into 3x3 gridcells. A simple for loop can do

I'm attempting to refactor an R script that does a lot of plotting, among other things. Ideally I'd like to do something like setup # does pdf(...) for each part of input { plot(process(part)) } cleanup # does dev.off() but have problems: 1 I'm plotting to PDF, so everytime I dev.off() creates a new file, and I want everything in one file (as does my boss :-) 2 I'm

Is there packaged code to convert geographical coordinates (e.g., longitude, latitude, elevation) to Cartesian coordinates in 3-space? I can see how to do this using 1. a spherical-to-Cartesian conversion like pracma::sph2cart(tpr) http://cran.r-project.org/web/packages/pracma/ 2. a geographical-to-spherical conversion. This seems to involve (in roughly increasing order of difficulty or

summary: e.g., how to replace '<query R for package=package_name>' in the following: for RSERVER in 'foo' 'bar' 'baz' ; do ssh ${RSERVER} '<query R for package=package_name>' done or is there a better way to script checking for an R package? details: For my work I need a few non-standard R packages. I do that work on 2 clusters. One uses

Hi all, I have used this library to create a (360 day)calendar for my rainfall data (which is divided over 9 gridcells): ## CODE## library(udunits) utInit() calendar <- att.get.nc(nc,'time','calendar') T <- var.get.nc(nc,"time") times.list <- utCalendar(T,"days since 1961-01-01",style='array',calendar=calendar) ## END CODE## **** To separate

summary: how to make image.plot print a subtitle between the title and the image, rather than under the image? details: I've got a project https://github.com/TomRoche/ioapi-hack-R that illustrates the use of (et al) the R packages {ncdf4, fields, M3} for processing and visualizing IOAPI data. The data being visualized consists of a series of layers (mostly representing emissions from a

How best to implement a decorator pattern in R? What I mean, why I ask: A group of ncdf4 users is trying to make it easier (notably for ourselves :-) to write correctly IOAPI-formatted netCDF. Since IOAPI http://www.baronams.com/products/ioapi/ decorates netCDF, one obvious way to do a package=ioapi is to decorate the netCDF API from package=ncdf4. E.g., to add a data variable (datavar) with

summary: how to structure an R file such that it can be both 1. used as a script via, e.g., (from OS commandline) $ Rscript foo.r bar=baz 2. imported and called as a function via, e.g. (from R commandline) > source('./foo.r) > foo(bar='baz') ? I'm looking for the 'R equivalent' of how python supports this usecase. details: As discussed in the thread beginning

--- sh/hivexsh.pod | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/sh/hivexsh.pod b/sh/hivexsh.pod index 7d7fc0a..8b10a6a 100644 --- a/sh/hivexsh.pod +++ b/sh/hivexsh.pod @@ -61,6 +61,13 @@ script, use: #!/usr/bin/hivexsh -f +=item B<-u> + +Use heuristics to tolerate certain levels of corruption within hives. + +This is unsafe but may allow to export/merge valid keys/values

Hello, I have a small ISP and we have a dovecot for virtual mail hosting with a postfix and openldap as backend. Now the problem is that there is one primary domain (example.com) and many other virtual domains with different users. When user from primary domain logs in, he is using username as his username (without domain part) and when user from virtual domain logs in, he uses username at

summary: Specifically, how does one do stack/FIFO operations in R? Generally, how does one code functions with side effects in R? details: I have been a coder for years, mostly using C-like semantics (e.g., Java). I am now trying to become a scientist, and to use R, but I don't yet have the sense of "good R" and R idiom (i.e., expressions that are to R what (e.g.) the Schwartzian

I would appreciate * guidance regarding translation of IDL routines to R, generally * assistance translating two IDL routines to R, specifically Why I ask: I'm slowly learning how to do atmospheric modeling. One language that has been been popular in this space is IDL http://en.wikipedia.org/wiki/IDL_(programming_language) which unfortunately is proprietary (not to mention butt-ugly, IMHO

Wanting a commandline solution (for a problem detailed @ http://mailman.unidata.ucar.edu/mailing_lists/archives/netcdfgroup/2012/msg00279.html ) I turned to Rscript, and whacked out the q'n'd https://github.com/TomRoche/GEIA_to_netCDF/blob/master/netCDF.stats.to.stdout.r However it wasn't as quick as hoped, because I spent quite a bit of time figuring out how to pass the arguments.

Hi all: I have a question on sample size calculation of 2 groups of data. If 2 groups of data are all normal distribution, then I can use the function "n.indep.t.test.eq" from samplesize package.But if 2 groups of data are all skewed distribution, but not normal distribution,how can I calculate the sample size then? I've tried many transformation (e.g. log arcsin…) in order to