summary: When regridding a 4D Brick (e.g., the netCDF data variable
Fraction_of_Emissions(TSTEP, LAY, ROW, COL) in
> netcdf GFED-3.1_2008_N2O_3hourly_fractions {
> dimensions:
> TSTEP = 12 ;
> LAY = 8 ;
> ROW = 360 ;
> COL = 720 ;
> variables:
> float Fraction_of_Emissions(TSTEP, LAY,
Hi Craig, see the "array" method for ?brick:
brick(x, xmn=0, xmx=1, ymn=0, ymx=1, crs=NA
So, something like
x <- brick(test$data[[2], xmn = min(test$data[[5]]), ymx =
max(test$data[[5]]), ymn = min(test$data[[4]]), ymx = max(test$data[[4]]))
You might need to mess around to get the x/y ranges
Hi Shannon,
The other requirement to read tables from MS SQL Server is that details of
the table with geometry columns must be registered in a table called
geometry_columns in your database. If your database doesn't have this table,
do the following;
1) write a small point or polygon object back
Craig, thanks for the idea. I did create a DSN using ODBC as well as using an
explicit string connection. Both give me the same result of: 'Cannot open data
source'
Thus, I am thoroughly confused because I can connect to the SQL Server via all
of my other methods (RODBC) and software with no is
cforest with factors are currently not supported (although they may work in
some cases). I will change the predict function to make it more general by
adding a 'levels' argument such that you can indicate (for models with a
non-standard structure such as cforest) which variables are factors and
wha
Hein,
I think this problem goes away if you use a clean formula, like this:
> model <- glm(t0~ycoord+prec+tempmean+tempmax+tempmin,
family=binomial(link="logit"), data=c3p)
Robert
On Thu, Apr 4, 2013 at 7:42 AM, Jesse Berman wrote:
> Hi Hein,
>
> I'm not sure if this will help, but one thin
Hi Hein,
I'm not sure if this will help, but one thing to check is that your
prediction grid has covariate data for each of the 40,000 cells. If a large
number of cells have 'NA' as data values, then sometimes the prediction will
not work. Offhandedly, it strikes me that ycoord may be limited to
Hi All,
I have been provided with a .mat file containing a time series of Sea
Surface Temperature data (50 x 42 cells with 92 time layers). It was a
"Struct" object in Matlab. I can happily import the file in to R using
R.matlab, creating a list as follows. My question is how then to convert
this
Hi Shannon,
The following syntax has worked for me for the past year.
projstring <- CRS('+init=epsg:28355')
##Establish the dsn
# Note: use the odbc tool in Windows to create a dsn for your SQL Server
database beforehand
myMSSQLdsn <-
c("MSSQL:server=mysqlservername;database=mydatabase;trusted_c
Dear list,
How can I obtain the latitude/longitude of various countries?
In addition, does anyone know how to calculate absolute latitude?
wanhai
Best regards
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Hi,
I would like to make a raster, based on the regression coefficients with 5
other rasters (Predictors). In theory this should be easy using the predict
function of the raster package
(http://cran.r-project.org/web/packages/raster/raster.pdf). But I fail to get
it to work.
First I fit a glm
Hi all,
I have a problem with the function raster::predict very similar to the one
described here [1], [2] using raster package version 2.0-41 and party package
version 1.0-6, where my model is a conditional inference forest
(party::cforest). Could not find a solution in either post.
The p
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