similar to: Quadrat counting with spatstat

Hi, I know there are older threads discussing the quadratcount function in spatstat. Unfortunately, I could not find a solution to my problem there. I'm analyzing a point pattern in an irregular polygonal window. Both the window (an entire country) and the points are projected using WGS84. When I do quadratcount with only one quadrat for the entire country it holds all my 154 points:

Hi all, I am using quadratcount in spatstat to divide a window containing a point pattern into a grid of quadrats containing the intensity of points in each quadrat. My data is in UTM co-ordinates. My window is defined as follows: >p15<-ppp(x,y,window=owin(c(341710,342100),c(3126465,3126780)),marks=NUL L, checks=TRUE) Giving me a distance of 390m in the 'x' direction and 315m in

Hello, I am trying to plot a quadratcount object over a ppp object in the spatstat package. I ultimately want to get something like this http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png http://bg9.imslab.co.jp/Rhelp/R-2.4.0/src/library/spatstat/man/images/big_quadratcount_001.png See

Hi, With the following code i can divides window into quadrats and counts the numbers of points in each quadrat. library(spatstat) X <- runifpoint(50) quadratcount(X) quadratcount(X, 4, 5) quadratcount(X, xbreaks=c(0, 0.3, 1), ybreaks=c(0, 0.4, 0.8, 1)) qX <-? quadratcount(X, 4, 5) plot(X) plot(qX, add=TRUE) But I want to mark each? quadrats? and select/ extract only those points by

Dear all, I've run into a question of handling large matrices in R. I'd like to define a 70000*70000 matrix in R on Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit), but it seems to run out of memory to handle this. Is it due to R memory limiting size or RAM of my laptop? If I use a cluster with larger RAM, will that be able to handle this large matrix in R? Thanks much! Best, Hui

I noticed that nls treats weights as relative and that the absolute size of the weights w in the following script has therefore no influence on the errors of the parameters reported in the summary a<-1 b<-3 x<--100:100 y<-a*x+b yeps<-y+rnorm(length(x),sd=1) w<-rep(1,length(x)) plot(x,yeps) lines(x,y) fit<-nls(yeps~p1*x+p2,start=list(p1=a*1.5,p2=b*1.5),weights=w)

Hi all, Lets say I have a matrix A which is m x n. I also have a mask matrix MASK which is m x n with values in T/F, where T values make a sub-matrix in regutangular shape... I applied B=A[MASK] and it didn't work as expected... Any thoughts? [[alternative HTML version deleted]]

Hello, (Sorry for the repost, i am resending in plain text) I have a function 'ewrap' (see below for definition). It takes 3 expressions and returns another expression e.g. map <- ewrap({ len <- length(r$addon) rhcollect(len,1) }) becomes: expression({ NULL result <- mapply(function(.index, k, r) { { len <- length(r$addon)

hello I want a code which can correct the spelling mistakes as well as grammatical mistakes in the sentences...that is if I am writing following sentence: I want too meet my frnd bt due to hectic shcedule I cant I want output in following way: I want to met my friend but due to hectic schedule I can't. Thanks in advance Shilpa Rai MSc IIT Bomaby -- View this message in context:

Hi, here i have some code... a <-1 b <- b+1 c <- b+a/20 if c >5 { d<- 1 } else { d<- 0 } i want to repeat this code from the 2nd line [b <- b+1] without using loop. Actulay i want to use "*Label *" and call *GoTo* method like in other coding Languages. For eg:- like this, a <-1 *LabelBegin :* b <-

Dear R Users: I'm a STATA user converting to R, and I'd like to be to do the following. #Assign var_1 and var_2 a value 10->var1 20->var2 #Now I'd like to print the values of var_1 and var_2 by looping through var_1 and var_2 in such a manner: while(y<3){ print(var_y) y+1->y } In STATA, the "y" appended to " var_" is called the local variable and

I normally use the following code to create a figure displaying the mark correlation function for the point pattern process "A": M<-markcorr(A) plot(M) I have now started to use the following code to perform 1000 Monte Carlo simulations of Complete Spatial Randomness (CSR). It is a Monte Carlo test based on envelopes of the Mark correlation function obtained from simulated point

Hi, Using the quadrats and quadratcount functions in spatstat, when I go to plot either of these, I get the quadrats coloured by their identity, i.e., using a color ramp applied to the sequence of quadrats. This only happens when the quadrats are applied to an owin which is polygonal, i.e., when I have an irregularly shaped study area. There doesn't seem to be any obvious way to

Dear All, I have been searching online for help increasing my R code more efficiently for almost a whole day, however, there is no solution to my case. So if anyone could give any clue to solve my problem, I would be very appreciate for you help. Thanks in advance. Here is my issue: My desktop is with i7-950 Quad-core CPU with 24Gb memory, and a NVIDIA GTX 480 graphic card, and I am using a

I have presence/absence data in the following format: 1 2 3 4 5 6 7 8 9 10 11 12 1 1 1 1 1 1 1 1 1 1 1 1 0 2 1 1 1 1 0 1 1 1 1 1 1 0 3 1 1 1 1 1 1 1 1 1 1 0 1 4 1 1 1 1 1 0 1 1 1 1 0 1 5 1 1 1 1 1 1 1 0 0 1 1 1 6 1 1 1 0 0 1 0 0 1 1 1 1 7 1 1 1 1 0 1 1 0 0 0 1 1 8 1 1 1 1 1 1 1 0 0 0 1 0 9 1 1 1 1 0 0 1 0 0 0 1 1 10 1 1 1 1 1 1 1 0 0 0 0 1 11 1 1 1 1 1 1 1 1 1 0 0 1 12 1 1 1 1 1 0 0 0 1 1 1 1

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

Hello R Users, I am trying to do a quadrat count defined by covariate properties in spatstat. I have read my elevation raster into R (from ascii) and converted to class "im" for use in spatstat. Now I have point data of class "ppp" which window is the same extent as the elevation image. I can conveniently plot the image and the points on the image as follows:

Hello, Is there a convenient way to import RDF/OWL data into R? I'm interested in importing BioPAX/SBPAX data into R to make them available for a wider audience. One exciting application would be to use pathway data to explain differential microarray measurements by identifying upstream nodes that are likely involved in causing the differences. This could also be used to validate

Is there any package or operation in R designed to conduct or facilitate Quadrat Variance analysis of spatial data? Any leads would be much appreciated as I have found very little in my searches thus far. Tyler -- View this message in context: http://www.nabble.com/Quadrat-Variance-analysis-tp22752517p22752517.html Sent from the R help mailing list archive at Nabble.com.

Hi, I'm new to this mailing list so apologies if this is too basic. I have confocal images 512x512 from which I have extracted x,y positions of the coordiates of labelled cells exported from ImageJ as a.csv file. I also have images that define an underlying pattern in the tissue defined as areas of different pixel values 0 or 255 (also 512x512) I've exported these images as .txt