search for: 10000x10000

Hi, I have a comma separated file with element names in first column like shown below : Name_1,0 Name_2,0.8878,0 Name_3,0.6777,0.7643,0 Name_4,0.9844,0.1234,0.1414,0 Original data is a 10000x10000 symmetric matrix (600 MB). To reduce file size, I have minimized matrix to only lower triangle. Is there a (memory) efficient way to 1) read file 2) compute first and second principal components and 3) and plot first vs second PC's ? In the past, I could do this by : b <- read.csv("dis...

Sorry if this answer was already given, or if I miss the point, but did you have a look to "lowerTriangle" and "upperTriangle" functions in the "gdata" package ? # example # A<-matrix(rnorm(9),3,3) # B<-B<-matrix(NA,dim(A)[1],dim(A)[2]) # lowerTriangle(B)<-lowerTriangle(A) # upperTriangle(B)<-lowerTriangle(A) # diag(B)<-diag(A) Hope this helps,

...ol=10000) >> system.time(a[1,1] <- 1903908.80385) > user system elapsed > 30.840 6.226 41.416 >> is.matrix(a) > [1] TRUE > > Is there a better way to enter values into large matrices? If I have > to > spend 41 secs each time I enter into a cell and I have 10000x10000 > cells to > enter that is impractical! > > --Nnamdi > > Rolf Turner-3 wrote: >> >> >> On 17/04/2008, at 9:33 AM, Charles C. Berry wrote: >> >> <snip> >> >>> I'll lay odds that Matthew's 'matrix' is actually...