Dear Roger,
Thank You very much for Your swift response. I did some testing of the
rgdal revision.
crds - matrix(data=c(9.05, 48.52), ncol=2)
spPoint - SpatialPoints(coords=crds,
proj4string=CRS(paste(+proj=ob_tran +o_proj=longlat +o_lon_p=-162,
+o_lat_p=39.25 +lon_0=180 +ellps=sphere
On Thu, 16 Aug 2012, Martin Ivanov wrote:
Dear Roger,
Thank You very much for Your swift response. I did some testing of the rgdal
revision.
crds - matrix(data=c(9.05, 48.52), ncol=2)
spPoint - SpatialPoints(coords=crds,
proj4string=CRS(paste(+proj=ob_tran +o_proj=longlat +o_lon_p=-162,
Dear List members,
after reading several old mail from R-sig-geo and checking the gstat
manual there is still sth. confusion about the way how gstat
calculates the Regressions.
On the on hand some mails, as the the following one, tell that GLS is
used to estimate the
Dear colleagues,
To mask this image (note max and min values):
lai.cal
class : RasterLayer
dimensions : 5568, 8289, 46153152 (nrow, ncol, ncell)
resolution : 0.00898, 0.00898 (x, y)
extent : -104.4326, -29.99736, -40.00064, 10 (xmin, xmax, ymin, ymax)
coord. ref. :
Dear Roger,
Thank You very much for Your responsiveness. I tested Your new revision
with points, data frames and pixels and
everything seems to be ok. It is now only this annoying
counter-intuitive discrepancy between source and target proj,
but it is not really an obstacle. It seems to come
Hi Thiago,
mask() simply creates a new raster which sets any cells in the calls first
argument (lai.cal) to NA if they are NA in the second argument (qc.cal), the
mask raster. As far as I am aware it does not otherwise manipulate values in
your original raster.
I would conclude, that since
Hello,
I am new to this group and am still working to figure out many things. I have
a kind of basic question, regarding using R and interacting with plots. I have
been exploring using the spplot in the sp package as a means to interact with
plots, but haven't figured out how to use the
(I am new to this group.) I have a two-part question. I have a shape
file for the US states (excluding Alaska and Hawaii)
I am trying to export (or save) the nearest neighbor list to a csv or
text file.
This is what I did
***
USs - readShapeSpatial(usa)
# Creating Neighbor List
USs.nb
On Thu, 16 Aug 2012, Alok K Bohara, PhD wrote:
(I am new to this group.) I have a two-part question. I have a shape file
for the US states (excluding Alaska and Hawaii)
I am trying to export (or save) the nearest neighbor list to a csv or text
file.
This is what I did
***
USs -
Dear users and experts,
I know that my question is not strictly R-related, but... Is there any good
strategy (preferably already implemented in R) for estimating interaction radii
of a MultiStrauss model?
I have been working with function profilepl in spatstat, but I frequently have
to
You could try something like:
library(rgdal)
library(sp)
scot_BNG - readOGR(dsn=dsn, layer=scot_BNG)
plot(scot_BNG)
tmp - SpatialPoints(locator(1))
proj4string(tmp) - proj4string(scot_BNG)
over(tmp, scot_BNG)
# or
tmp2 - over(scot_BNG, tmp)
plot( scot_BNG[!is.na(tmp2),], add=TRUE, col='green')
Hi Greg,
That works but I can only chose one polygon and have its attributes identified.
I want to plot my map, then be able to pan and zoom, and chose several
polygons to have their attributes identified (one at a time would be fine).
Should I be exploring maptools?
Thanks,
Ty
On Aug 16,
My example used locator(1) to get one click, but if you just use
locator() (without the 1) then you can click in as many places as you
want, then it should show you the info for all of them). If you want
to click and see the results, then click again and see the new
results, etc. then you could
Simon,
Thanks for this valuable discussion. Yes, I do think that having the range
changed could be an issue. In the case I showed, mask operation appears to have
changed all 0 values of the original raster to 0.1 and all 7 values to
6.9, therefore creating differences in the image. This is
Hi Greg,
The example works fine, but running the
tmp - SpatialPoints(locator())
takes a really long time to execute on my map of 12,438 features each with 3
fields.
Is there anyway to speed it up?
BTW -- I'm running on MacOS Lion with R 2.14.0.
Also, the output plots to Quartz, which
Frazier, Tyler James skreiv:
That works but I can only chose one polygon and have its attributes
identified. I want to plot my map, then be able to pan and zoom, and
chose several polygons to have their attributes identified (one at a time
would be fine).
I would recommend using QGIS
Determining if a point is in a polygon is not as simple a task as
might be assumed (I can see that it is in there, why can't the
computer?). So the computer has to do this check for all (or maybe
just some) 12,438 features, so it is not surprising if it is a little
slow. The people who created
On 17/08/12 04:23, José M. Blanco Moreno wrote:
Dear users and experts,
I know that my question is not strictly R-related, but... Is there any good
strategy (preferably already implemented in R) for estimating interaction radii
of a MultiStrauss model?
I have been working with function
Thank you Rolf for your very detailed response. As you said, these lists are
bloody amazing, and the people who participate actively much more (I mean,
those giving advice, not so much for those of us who can, at most, pose
partially interesting questions).
Points a b understood.
(c) Gamma
On 17/08/12 14:11, José M. Blanco Moreno wrote:
SNIP
(c) Gamma parameters greater than 1 are OK for interactions between
points of
different type. For points of the same type they are not just
undesirable, they
are verboten. The model is undefined if any gamma_{ii} 1.
So if I
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