but it fitted
well visually.
I think also that the prediction grid was not well created. I wiould be
grateful to have to hints.code how to create a useful grid and also for
the spplot or other alternatives
I can send more info if required.
Cheers
Anand
On Tue, Aug 4, 2015 at 1:39 PM, Jon Skoien
Hi,
You have attached some data, but we still dont know exactly what you do
with the data (do you use the logarithm, how many bins, did you project
the data set...?). However, having had a quick look using the LatLong
coordinates (not really recommended), I can see that the variogram from
It is difficult for us to know exactly what happens as you are not
providing a reproducible example. But my guess would be that this is
related to your use of a Gaussian variogram without nugget for the first
part of the variogram. This can cause rather large weights (positive and
negative) if
Hi Zilefac,
Your problem is not really related to hydroTSM, but to the fact that
hydrokrige uses spplot for plotting, which is again based on the lattice
package. This does not use the par()-arguments.
Instead there are two other ways for producing multiple plots in one figure:
- Save each of
Hi Angel,
We cannot reproduce your problem as we dont have access to your files,
but it seems only one of the objects in your over-command is projected
(border). Probably it will work better if you set proj4string also for
pts1.
Cheers,
Jon
On 10/24/2014 5:12 PM, Angel Ferrero wrote:
.
Thanks
On 16Sep, 2014, at 3:23 PM, Jon Skoien jon.sko...@jrc.ec.europa.eu wrote:
Hi Augustin,
I guess this is related to the complexity of the border. Switzerland is defined
by some nice lines (although not as simple as some of the borders in Sahara),
Portugal and Spain have coastlines which can
Hi Augustin,
I guess this is related to the complexity of the border. Switzerland is
defined by some nice lines (although not as simple as some of the
borders in Sahara), Portugal and Spain have coastlines which can be
rather complex, including their islands. Setting
prt = gadm
che = gadm
Hi Ma,
You should be able to plot the polygon on top of your raster with a
panel function. Here is an example with the meuse data:
r - raster(system.file(external/test.grd, package=raster))
s - stack(r, r*2)
names(s) - c('meuse', 'meuse x 2')
spplot(s)
data(meuse.riv)
meuse.sr =
The result you got is the same as for a variogram model from vgm with a
nugget effect. This is the ratio of anisotropy, which is one both for
the nugget and for the correlated part of the model. See:
str(vgm(10, Exp, 300))
str(vgm(10, Exp, 300, 3))
I guess you see something like the second
It seems you cannot change the fit.method from autoKrige or
autofitVariogram, it uses the default from gstat::fit.variogram, which
is method 7.
However, you should probably first try to see why you get the error and
what is zero. I assume that your error is that you have zero distances
Hi Pablo,
sorry for a late answer again.
I am not sure what is the cause of slow execution of your code. I would either
have to look at an example, or you can run it with Rprof(). Then you can see
the most time consuming functions, although I am not sure how it works with
JIT. If you send the
Hi Sajid,
You should be able to do something like this:
setwd( name of folder)
fls = list.files() # you can add a pattern if you only want files of a
certain type
dst = stack(fls[1])
for (ifile in 2:length(fls)) dst = addLayer(dst, raster(fls[ifile]))
And I am sure someone can do this even
Hi Rui,
I think the following should give you what you are looking for:
res$area2 = sapply(slot(res,polygons), function(x) slot(x, area))
Cheers,
Jon
On 13-Dec-11 13:50, Rui Catarino wrote:
Dear all,
This may seem a very obvious question but I'm suck and for the past 2h I
haven't been able
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