I apologize for the naive question but I haven’t been able to find an explanation for the meaning of the square boxes that appear around my lines layer’s nodes, when I display topological informations on the map.
I thought they could indicate errors, but my layer appear to be topologically ok.
I’m sorry for asking so much difficult questions! 
giovanni
Sent from Nexus
On Thu, Apr 11, 2013 at 3:21 PM, G. Allegri <giohappy@gmail.com> wrote:
I apologize for the naive question but I haven't been able to find an
explanation for the meaning of the square boxes that appear around my lines
layer's nodes, when I display topological informations on the map.
These square boxes are the bounding boxes for each line.
I thought they could indicate errors, but my layer appear to be
topologically ok.I'm sorry for asking so much difficult questions!
giovanni
Sent from Nexus
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These square boxes are the bounding boxes for each line.
???
http://img543.imageshack.us/img543/8425/maptopo.png
I have other layers which do not show them…
giovanni
I thought they could indicate errors, but my layer appear to be
topologically ok.I’m sorry for asking so much difficult questions!
giovanni
Sent from Nexus
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Giovanni Allegri
http://about.me/giovanniallegri
blog: http://blog.spaziogis.it
GEO+ geomatica in Italia http://bit.ly/GEOplus
Hello All,
I am trying to find a way to process a fuzzy K-mean cluster using multiple rasters/grids in GRASS. Is anyone aware of a grass add-on or another simple process I can use to accomplish this?
Thanks,
Robert Brown
PhD Student
Purdue University
Department of Agronomy
Robert
I would recommend a combination of GRASS and R (http://cran.r-project.org/). R has fuzzy K-mean cluster capability, using the R addon package spgrass6 to read/write to/from GRASS and R. Also, see this: http://www.r-bloggers.com/fuzzy-clustering-with-fanny/ and this: http://stats.stackexchange.com/questions/31906/fuzzy-k-means-cluster-sizes as starting points.
Tom
On Thu, Apr 11, 2013 at 12:48 PM, Robert A Brown <brown782@purdue.edu> wrote:
Hello All,
I am trying to find a way to process a fuzzy K-mean cluster using multiple rasters/grids in GRASS. Is anyone aware of a grass add-on or another simple process I can use to accomplish this?Thanks,
Robert Brown
PhD Student
Purdue University
Department of Agronomy
grass-user mailing list
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http://lists.osgeo.org/mailman/listinfo/grass-user
Hi Tom,
I am an avid R user and forgot about the spgrass6 addon. I have linked to grass through R and read in my rasters with the following script. The process worked beautifully and I appreciate you reminding me of the package and process!!!
Script for reading the rasters
#######
require(spgrass6)
require(EMCluster)
require(rgdal)
initGRASS("C:/Program Files (x86)/GRASS GIS 7.0.svn", gisDbase="C:/Users/brown782/Desktop",location="grass_data",mapset ="PERMANENT", override=T)
require(spgrass6)
require(EMCluster)
require(rgdal)
rasters <- readRAST6(c("slope_pct", "wetness_indx", "nomralized_height"), cat=c(T, F, F), useGDAL=T)
#####
I decided to use the EMCluster package in R instead of the cmeans package. Yesterday, I only tried to work in the R interface with the raster and cmeans("e1071") packages and read in the grids as ascii files. My issue was that when I stacked the grids and tried using cmeans it seemed that the fuzzy cluster process did not seem to understand that my stacked grids were spatial data.
So now that I am using the EMCluster package R is giving me an error that the "rasters" object needs to be a matrix. I used the following script to convert the data to a matrix.
rasters2 = as.matrix(rasters)
It seemed to work but R gave me the below warning that the Spatial.Data.Frame
######
In as.matrix.SpatialGridDataFrame(rasters) :
as.matrix.SpatialPixelsDataFrame uses first column;
pass subset or for other columns
#####
It seems that the as.matrix function somehow combined the three rasters into one because when I looked at the dimensions of the newly formed matrix it only gave me one set of dimensions. All of the rasters have the same dimensions. Where the Dimensions are below for the three rasters and the newly formed matrix.
slope_pct = raster:
rows: 6750
columns 9152
wetness_indx = raster:
rows: 6750
columns 9152
normalized_height = raster
rows: 6750
columns 9152
rasters2 = Matrix
rows: 6750
columns 9152
can I convert the three individual grids to their own matrix then in run the EMCluster with the following script?
results = simple.init(slope_pct, wetness_indx, normalized_height, nclass = 5)
results = simple.init(slope_pct + wetness_indx + normalized_height, nclass = 5)
I tried the second above option and it failed to produce any kind of meaningful cluster it just gave me a short list of NA and NAN Errors.
Below I used the following code for the EMCluster package with the "rasters2" matrix but would like to replace it with either of the codes above?
results = simple.init(rasters2, nclass = 5)
This may be something I need to post in the R discussion forum.
Thanks for all of your help!
Robert Brown
----- Original Message -----
From: "Thomas Adams" <tea3rd@gmail.com>
To: "Robert A Brown" <brown782@purdue.edu>
Cc: grass-user@lists.osgeo.org, "Markus Metz" <markus.metz.giswork@gmail.com>
Sent: Thursday, April 11, 2013 1:30:25 PM
Subject: Re: [GRASS-user] Fuzzy K-mean
Robert
I would recommend a combination of GRASS and R ( http://cran.r-project.org/ ). R has fuzzy K-mean cluster capability, using the R addon package spgrass6 to read/write to/from GRASS and R. Also, see this: http://www.r-bloggers.com/fuzzy-clustering-with-fanny/ and this: http://stats.stackexchange.com/questions/31906/fuzzy-k-means-cluster-sizes as starting points.
Tom
On Thu, Apr 11, 2013 at 12:48 PM, Robert A Brown < brown782@purdue.edu > wrote:
Hello All,
I am trying to find a way to process a fuzzy K-mean cluster using multiple rasters/grids in GRASS. Is anyone aware of a grass add-on or another simple process I can use to accomplish this?
Thanks,
Robert Brown
PhD Student
Purdue University
Department of Agronomy
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grass-user@lists.osgeo.org
http://lists.osgeo.org/mailman/listinfo/grass-user
