similar to: [lattice] display a projected map on a layerplot

SUMMARY: Specific problem: I'm regridding biomass-burning emissions from a global/unprojected inventory to a regional projection (LCC over North America). I need to have boundaries for Canada, Mexico, and US (including US states), but also Caribbean and Atlantic nations (notably the Bahamas). I would also like to add Canadian provinces and Mexican states. How to put these together? General

Hi R users I need the map of France?s ? communes ? (towns) to build a map Is there a way to get it? More generally: How to do to get the map of a country and its different geographical levels? Best regards -- View this message in context: http://old.nabble.com/map-of-a-country-and-its-different-geographical-levels-tp26225645p26225645.html Sent from the R help mailing list archive at

Hi All, I have a netcdf gridded file with LCC projection. I can easily use image.plot to visualize it. However, as the axises are in X,Y, not Lat and Lon, I could not add state or country maps onto it (or lat lon information). I do have a grid2d file that describes the lat and lon for each (X,Y) grid, but the lat and lon are not regularly spaced, so I could not use image.plot. Does anyone know

Hola miembros de la lista, Estoy utilizando la función levelplot del paquete rasterVis para graficar un raster y quiero controlar la altura de la referencia de color (colorkey) del mapa, pero cuando cambio valores en el argumento "height" no parece provocar cambios. Alguna idea de por qué no está funcionando? > cobertura class : RasterLayer dimensions : 780, 1296, 1010880

Hi all, I'm faced with a problem applying the sp package: The projection argument in readShapePoly(Shapefile,proj4string="CRS class argument") e.g.: CRS("+proj=aea +lat_1=46 +lat_2=73 +lat_0=60 +lon_0=84 +x_0=0 +y_0=0 +ellps=clrk66 +units=m +no_defs") doesn't have any impact on the plotted object. I also tested the simple example: xy = cbind(x = 2 * runif(100) -

Hi everyone, llvm is great! But there is one exception ;) llvm components are generally fast, but instruction selection is slooow. Let me explain. I am developing a toolkit for building virtual machines which can automatically generate a JIT compiler using the interpreter specification. llvm does the hard work of machine code generation. (Thanks to you all) I discovered that JIT compilation is

You need to load the package 'rasterVis' > library(rasterVis) HTH, Eric On Thu, Mar 8, 2018 at 5:11 PM, lily li <chocold12 at gmail.com> wrote: > Hi all, > > I ran the code: > > s <- stack(replicate(2, raster(matrix(runif(100), 10)))) > > xy <- data.frame(coordinates(sampleRandom(s, 10, sp=TRUE)), > + z1=runif(10), z2=runif(10))

Hi I'm trying to analyse some data and need to set the geographic coordinate system before I can do the analysis. I've been trying to use the project command in rgdal but keep getting an error message saying: Error in project(locationsMatrix, PROJECTION.OUT) : latitude or longitude exceeded limits ( PROJECTION.OUT <- "+proj=aea +lat_1=-18 +lat_2=-36 +lat_0=0 +lon_0=132

Hello, I'm new to OGG and I must say than it's impressive. I plan to use it in my project (BASIC programming langage) but I use LccWin32 as main C compiler (free and very powerful) and OGG has some difficulties to compile. I would like to know if it was already reported. If not, here it is: - Inline ASM functions for vorbis_itoa() isn't ok for LCC (not the same syntax than VC). I

I've read something about this problem, but I don't know how can i avoid this problem. Why the order of the factors give different results? I suppose it's because the order of the factors, i've just changed "lcc" from the first position to the last in the model, and the significance change completely >

I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the covariate (continous variable) I get this results > ancova<-aov(log(peso)~edadysexo*log(lcc)) > summary(ancova) Df Sum Sq Mean Sq F value Pr(>F) edadysexo 2 31.859 15.9294 803.9843 <2e-16 *** log(lcc) 1 11.389 11.3887 574.8081 <2e-16 ***

Dear, I am trying to visualise a time-progressing line (it's supposed to represent spread patterns) using brew package and Google Earth. The idea is to have a function which takes start and end point geographic coordinates, as well as number of intervals to chop the path up, and returns the collection of points segmenting this line. Unfortunately my calculations fail for large distances,

I have a 3D field of a scalar variable (x, y, z, value). Is there a way to generate a vector field from this data--gradient at defined points? I found the rasterVis package for 2D data, but as yet nothing for 3D data. Thanks, Scott Waichler Pacific Northwest National Laboratory Richland, WA scott.waichler at pnnl.gov

*[qali at qali llvm-2.8-rev]$ find . -exec grep -n "LLVMCC_EMITIR_FLAG" ./ {} \;* ./projects/test-suite/Makefile.tests:47: -$(LCC) $(CPPFLAGS) $(CFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG) ./projects/test-suite/Makefile.tests:51: -$(LCXX) $(CPPFLAGS) $(CXXFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG)

On Jan 15, 2011, at 8:06 PM, Qingan Li wrote: > [qali at qali llvm-2.8-rev]$ find . -exec grep -n "LLVMCC_EMITIR_FLAG" ./ {} \; > ./projects/test-suite/Makefile.tests:47: -$(LCC) $(CPPFLAGS) $(CFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S $< -o $@ $(LLVMCC_EMITIR_FLAG) > ./projects/test-suite/Makefile.tests:51: -$(LCXX) $(CPPFLAGS) $(CXXFLAGS) $(LOPTFLAGS) $(X_TARGET_FLAGS) -S

Saludos estimados usuarios ! Estoy recién iniciándome en R y no he encontrado ejemplos de cómo graficar los archivos netcdf que genera el modelo meterológico WRF. ¿Alguien tiene por ahí algunos scripts que me permitan ir interiorizándome en el uso de paletas de colores, mapas y graficas de variables de este modelo? Anteriormente lo hacía vía GrADS, convirtiendo el NetCDf a GRIB, pero con las

On Monday 23 February 2009 03:23:59 Mark Shannon wrote: > I've done quite a lot of work on register allocation for stack machines. > You might want to look at my papers: > http://www.dcs.gla.ac.uk/~marks/euroforth.pdf > http://www.dcs.gla.ac.uk/~marks/thesis.pdf Hi Mark, I've read your papers, and in fact they were part of the data that convinced me that I really could go

>C--'s weakness is it's incompleteness (missing many major features), >instability/bugginess, poor performance (both time to compile and the >generated code), lack of high-level optimizations, lack of ABI >compatibility with the native tools, lack of C++ frontend support, and the >small size of its community. To quote Tony Hoare : "premature optimization is the

Hi Nicolas and Dan, Thanks for your replies. I've been playing around with various setting, as you suggested. > What version of LLVM are you using here? I'm using 2.4 My original time ratios of reg-alloc to instruction selection (1:12) referred to the local register allocator and the standard instruction selector (all passes), not a sensible comparison, I realise. > I did

Wesley, Regarding access to the source code; I would send you the code, but I might be stepping on a few toes. The person to speak to is Chris Bailey at the University of York (in the UK). However it is written for the lcc tree-based IR, rather than the SSA-based IR of LLVM, so I don't think it will be that much use. A lot of the analysis it does is to find information that is explicit in