search for: set2

...ften want to extract a particular result from each simulation for plotting and, ideally, put it in a matrix. A simple example v1 <- 1:5 v2 <- 6:10 other1 <- "stuff" other2 <- "stuff" set1 <- list(v1,other1) names(set1) <- c("vec","other") set2 <- list(v2,other2) names(set2) <- c("vec","other") output <- list(set1, set2) Is there some form of lapply() that will allow me to extract v1 and v2 (ie, the $vec elements) from both sets? Bonus if I can then put it into a matrix tidily. many thanks Jennifer Young

...1 14:25:00 haul1 9 Start.hauling 2011-01-01 21:28:00 haul1 10 Start.hauling 2011-01-02 03:38:00 haul1 11 Start.hauling 2011-01-02 09:28:00 haul1 12 Start.hauling 2011-01-02 14:22:00 haul1 13 Start.setting 2011-01-02 20:51:00 set2 14 Start.setting 2011-01-02 21:33:00 set2 15 Start.setting 2011-01-02 22:47:00 set2 16 Start.setting 2011-01-02 23:27:00 set2 17 Start.setting 2011-01-03 00:35:00 set2 18 Start.setting 2011-01-03 01:16:00 set2 19 St...

...ake simple inst-by-inst scan unscalable and oftentimes fail. It also breaks the load-and-or-store pattern. An example is below: Before coalescing done by earlycse/loadpre: %bf.load = load i64, i64* %0, align 8 %bf.clear = and i64 %bf.load, -65536 %bf.set = or i64 %bf.value, %bf.clear store i64 %bf.set2, i64* %9, align 8 ..... %bf.load1 = load i64, i64* %0, align 8 %bf.clear1 = and i64 %bf.load1, -4294901761 %bf.set1 = or i64 %bf.value1, %bf.clear1 store i64 %bf.set2, i64* %9, align 8 ..... %bf.load2 = load i64, i64* %0, align 8 %bf.clear2 = and i64 %bf.load2, -4294901761 %bf.set2 = or i64 %bf.val...

Colleagues, (R: 2.13.0; OS X) I often receive sequential datasets in which there are new rows interposed between existing rows. For example: SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4, 6:10))) SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10)) > SET1 LETTERS NUMBERS 1 A 1 2 B 2 3 C 3 4 D 4 5 F 6 6 G 7 7 H 8 8 I 9 9 J 10 > SET2 LETTERS NUMBERS 1 A 1...

...t also >> breaks the load-and-or-store pattern. An example is below: >> >> Before coalescing done by earlycse/loadpre: >> %bf.load = load i64, i64* %0, align 8 >> %bf.clear = and i64 %bf.load, -65536 >> %bf.set = or i64 %bf.value, %bf.clear >> store i64 %bf.set2, i64* %9, align 8 >> ..... >> %bf.load1 = load i64, i64* %0, align 8 >> %bf.clear1 = and i64 %bf.load1, -4294901761 >> %bf.set1 = or i64 %bf.value1, %bf.clear1 >> store i64 %bf.set2, i64* %9, align 8 >> ..... >> %bf.load2 = load i64, i64* %0, align 8 >&g...

...tion. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1'] set2=set[!is.na(set$set2),'set2'] library(Matching) ks.b=ks.boot(set1,set2,1000) ks.b Thank you!

...is: rset[1] <- reviewer1 rset[2] <- reviewer2 . So when I try to do adjustedRandIndex(rset[1],rset[2]) I get an error message: Error in FUN(X, Y, ...) : comparison of these types is not implemented And If I do this: > rset[1] [[1]] [1] set1 set2 set1 set2 set1 set2 set1 set2 set1 set2 Levels: set1 set2 PROBLEM 2) Some of my reviewers have put single cards into two piles (which was allowed). However, this routine for the Adjusted Rand Index doesn't seem to be able to handle that sort of category as an input. Is that a problem fo...

Dear all, I have two sets of data (say set1 and set2) as follow: set1 x1 x2 x3 0.30 0.43 3.88 0.38 0.59 3.53 0.30 0.42 2.12 0.33 0.53 2.12 0.30 0.47 3.76 set2 y1 y2 y3 0.32 0.47 5.18 0.23 0.26 1.06 0.42 0.65 3.88 0.28 0.38 3.76 0.35 0.47 1.41 The "pairs" function (such as pairs(~x1+x2+x3 data=set1, main=&...

...cle through datasets. When each dataset is of equal length, it works fine as I can combine the datasets and have each loop pick up a different column, but when the datasets are differing lengths, I am struggling. Here is an example: A<-1:10 B<-1:15 C<-1:18 Set1<-data.frame(A,runif(10)) Set2<-data.frame(B,runif(15)) Set3<-data.frame(C,runif(18)) for (i in 1:3){ if (i==1) Data<-Set1 else if (i==2) Data<-Set2 else Data<-Set3 dev.new() plot(Data[,1],Data[,2]) } I don't always want to plot them and instead do other things, such as fit a non-linear equation to the data...

...t also >> breaks the load-and-or-store pattern. An example is below: >> >> Before coalescing done by earlycse/loadpre: >> %bf.load = load i64, i64* %0, align 8 >> %bf.clear = and i64 %bf.load, -65536 >> %bf.set = or i64 %bf.value, %bf.clear >> store i64 %bf.set2, i64* %9, align 8 >> ..... >> %bf.load1 = load i64, i64* %0, align 8 >> %bf.clear1 = and i64 %bf.load1, -4294901761 >> %bf.set1 = or i64 %bf.value1, %bf.clear1 >> store i64 %bf.set2, i64* %9, align 8 >> ..... >> %bf.load2 = load i64, i64* %0, align 8 >&g...

...ate the data and get the medians of each of the 23 columns for each of the years. In other words my output should be like this Year Median 1991 123 1992 145 1993 132 etc. The sample lines of code to do this operation is set1 <- subset(as.data.frame(dataset),rep1==1) set2 <- subset(as.data.frame(dataset),rep1==0) lst <- list(unique(yeara)) y1 <- aggregate(set1,lst,median) y2 <- aggregate(set2,lst,median) However I'm getting an error as follows Error in FUN(X[[1]], ...) : arguments must have same length Can somebody please help me with what I'm...

All, I'm sure that this is covered somewhere, but I can't seem to find a good explanation. I have an existing table that contains information grouped by date. This is as so: Day NumberOfCustomers NumberOfComplaints 20060512 10040 40 20060513 32420 11 ... I also have a table at the detail level as so: Day Meal PricePaid UsedCupon 20060512 Fish 14 Y 20060512 Chicken 20 N

...t;- nrow - ii.table.row + 1} for(ii.col in seq(1, ncol)){ ii.table <- ii.p if(ii.p > n) break print(dots[[ii.table]], vp=vp.layout(ii.table.row, ii.col)) ii.p <- ii.p + 1 } } } set <- read.table(file="http://www.jovian.nl/set.csv", head=1, sep=",") set2 <- read.table(file="http://www.jovian.nl/set2.csv", head=1, sep=",") library(ggplot2) s <- ggplot(set, aes(x = time, y = hours)) + geom_area(colour = 'red', fill = 'red', alpha = 0.5) + geom_area(stat = 'smooth', span = 0.2, alpha = 0.3) + yli...

...per id (i.e. a 1 to n relationship). For the ease of modeling I now want to generate a new data frame c, which is basically a copy of data frame 'a' augmented by the values of b. If I have a <- data.frame(id = rep(1:3, each=3), val=rnorm(9)) b <- data.frame(id=1:3, set1=LETTERS[1:3], set2=5:7) the resulting data frame should look like: c <- data.frame(id = rep(1:3, each=3), val = a$val, set1=rep(LETTERS[1:3], each=3), set2 = rep(5:7, each = 3)) While this task is just an application of some 'rep's and 'c's for structured data frames, it is somehow cumber...

...set t-ipv6-set { type ipv6_address } chain c-filter { type filter hook input priority 0; } } # With a ipv6-set $ sudo nft add table ip6 t-ipv6 $ sudo nft add chain ip6 t-ipv6 c-filter { type filter hook input priority 0 \; } $ sudo nft add set ip6 t-ipv6 ipv6-set2 { type ipv6_address\;} $ sudo nft add set ip6 t-ipv6 ipv4-set2 { type ipv4_address\;} $ sudo nft list table ip6 t-ipv6 table ip6 t-ipv6 { set ipv6-set2 { type ipv6_address } set ipv4-set2 { type ipv4_address } chain c-filter { type filter hook input...

...4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of commands I should be looking into would be very much appreciated. I'm using R 1.9.0 on Windows XP. Thanks! Paul # load libraries library(stats); # working copy of data set1 <- as.matrix(data); set2 <- t(set1); # genes genes.distance <- as.dist(1-cor(set2)); genes.clusters <- hclust(genes.distance); genes.dendrogr <- as.dendrogram(genes.clusters); # samples samples.distance <- as.dist(1-cor(set1)); samples.clusters <- hclust(samples.distance1); samples.dendrogr <- as.den...

Hi, This question should be simple to answer. I am a new R user. I have a data.frame called appended. I would like to break it into 7 smaller datasets based on the value of a categorical variable dp (which has values 1:7). I would like to name the smaller datasets set1, set2, set3,....,set7. I don't know how to refer to the variable in the for loop, when naming the output datasets. In STATA (which I am much more familiar with) each i in the foreach loop would be refered to as `i'. This is the code I've included below. I've also tried set[[i]] and set[i]...

Dear list, I have two martix like these, each rows with name in the matrix. I try to select rows with identical name from two matrix and calculate their correlation. Matrix1: 2-Sep 9 5.5 1 7.18 10.0 8 139.45 2-Sep 7 4.9 15 8.22 61.68 9 123.62 4-Sep 5-Sep AAMP A2M A2M . . . Matrix2: 2-Sep 4 7 1 6.8 12 8 19.4

...and then plot at will. I thought to convert the whole thing to a PostScript file then get it back into R via grImport, but surely (please!) there must be a less roundabout way to do this. Any help is appreciated. Here is my code: # Wrapper function to draw Venn diagram Venn2 <- function(set1, set2, names, title,...){ stopifnot( length(names) == 2) # Form universe as union of both sets universe <- sort( unique( c(set1, set2) ) ) Counts <- matrix(0, nrow=length(universe), ncol=2) colnames(Counts) <- names for (i in 1:length(universe)) { Counts[i,1] <- universe[i] %...

I would like to create 15 box plots from two sets of data. Set1 - containts PayGrade, Min_Salary, Max_Salary data for 15 pay grades Set2 - contains PayGrade, Actual_Min, Actual_Max, and Actual_Mean for the 15 pay grades I would like 15 box plots (one for each paygrade) whose whiskers were the Min_Salary and Max_Salary data and whose ''box'' was Actual_Min, Actual_Mean, Actual_Max in order to show -- for each of te...