search for: kparama

Hi, I am trying to convert a 2D correlation matrix to 3 columns for graphical representation: rdata = replicate(100, rnorm(15)) #construct a 2D matrix c1 = cor(rdata) #outputs a correlation matrix Now I want to convert the 2D c1 to (row#, col#, correlation) 1 1 cor1 1 2 cor2 1 3 cor3 ... 2 1 cor.. Is there a way to do this? The main reason I am doing this is to find a correlation based graph

Hi, I have a huge table with 134,000 entries. I want to choose only rows 60,000 to 90,000. Please help me on how to do this. V1 V2 V3 V4 1 31.10267 168.3204 41 0.4 2 31.19941 168.1488 41 0.4 3 31.29580 167.9764 41 0.4 4 31.39183 167.8034 41 0.4 5 31.48750 167.6297 41 0.4 6 31.58280 167.4553 41 0.4 7 31.67774 167.2803 41 0.4 8 31.77229 167.1045 41 0.4 9 31.86648 166.9281

Hi, I wish to calculate the characteristic path length of a graph. Is average.path.length(g) in 'igraph' the same as calculating the characteristic path length of the graph? Thanks, Kumar -- View this message in context: http://r.789695.n4.nabble.com/Characteristic-Path-length-calculation-tp3398048p3398048.html Sent from the R help mailing list archive at Nabble.com.

Hi, I am plotting a graph with kamada.kawai layout. But I am getting direction arrows in the graphs. Please let me know how to avoid this. g <- watts.strogatz.game(1, 2000, 5, 0.4) comps <- clusters(g)$membership colbar <- rainbow(max(comps)+1) V(g)$color <- colbar[comps+1] png(filename) plot(g, layout=layout.kamada.kawai, vertex.size=2, vertex.label=NA) dev.off() Please find

In barplot for degree distribution x-axis is not seen. See the example below > g = barabasi.game(500, 0.4) > dd1 = degree.distribution(g) > plot(dd1, xlab="degree", ylab = "frequency") whereas barplot doesnot have any x-axis > barplot(dd1, xlab = "degree", ylab = "frequency") Please see the figures attached.

Hi, I am plotting degree distribution of a graph using the function, library(igraph) dd1 = degree.distribution(G) plot(dd1, xlab = "degree", ylab="frequency") I would like to plot the mean of the distribution as a vertical line in the attached plot. Please let me know how to do this. Thanks, Kumar http://r.789695.n4.nabble.com/file/n3334375/cdata3_dd.png cdata3_dd.png --

I have this function and want to run it parallel with different sets of data. Using SNOW and clusterApplyLB. system.time(out <- mclapply(cData, plotGraph)) #each cData contains 100X6000 doubles system.time(out <- mclapply(cData2, plotGraph)) system.time(out <- mclapply(cData3, plotGraph)) system.time(out <- mclapply(cData4, plotGraph)) system.time(out <- mclapply(cData5,

Hi, I have a erdos-renyi game with 6000 nodes and probability 0.003. g1 = erdos.renyi.game(6000, 0.003) How to create a Watts Strogatz game with the same probability. g1 = watts.strogatz.game(1, 6000, ?, ?) What should be the third and fourth parameter to this argument. -- View this message in context: http://r.789695.n4.nabble.com/Watts-Strogatz-game-tp3491922p3491922.html Sent from the R

Hi, I am running my code in a cluster at Arizona State University. I have a huge climate data, 66000 X 500 I am not sure if I can find correlation of such a huge data in the cluster. Normally I allocate 20000M and operate on 5 X 20000. Even this is taking lot of time. Is there any way I can find cl = cor(cdata) utilizing the computers in the clusters(I am using 32 nodes ). I am using the