Thanks! Solved. I have another question. This is your code for calculated the cumulative sum. how to modify the code if I want to add another criterion for calculating the cumulative sum: x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]); # cumsum if x$Qm<=c11 & x>2 x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]); #cumsum if x$Qn<=12 & y>2
d <- structure(list(m1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), n1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), x1 = c(0, 0, 0, 1, 1, 1, 2, 2, 2, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3), y1 = c(0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2), Fmm = c(0, 0, 0, 0.7, 0.59, 0.64, 1, 1, 1, 0, 0, 0, 0, 0.63, 0.7, 0.74, 0.68, 1, 1, 1, 1, 0, 0, 0, 0.62, 0.63, 0.6, 0.63, 0.6, 0.68, 1, 1, 1), Fnn = c(0, 0.64, 1, 0, 0.51, 1, 0, 0.67, 1, 0, 0.62, 0.69, 1, 0, 0.54, 0.62, 1, 0, 0.63, 0.73, 1, 0, 0.63, 1, 0, 0.7, 1, 0, 0.7, 1, 0, 0.58, 1), Qm = c(1, 1, 1, 0.65, 0.45, 0.36, 0.5, 0.165, 0, 1, 1, 1, 1, 0.685, 0.38, 0.32, 0.32, 0.5, 0.185, 0.135, 0, 1, 1, 1, 0.69, 0.37, 0.4, 0.685, 0.4, 0.32, 0.5, 0.21, 0), Qn = c(1, 0.36, 0, 0.65, 0.45, 0, 0.5, 0.165, 0, 1, 0.38, 0.31, 0, 0.685, 0.38, 0.32, 0, 0.5, 0.185, 0.135, 0, 1, 0.37, 0, 0.69, 0.3, 0, 0.685, 0.3, 0, 0.5, 0.21, 0), term1_p0 = c(0.81450625, 0.0857375, 0.00225625, 0.0857375, 0.009025, 0.0002375, 0.00225625, 0.0002375, 6.25e-06, 0.7737809375, 0.1221759375, 0.00643031249999999, 0.0001128125, 0.081450625, 0.012860625, 0.000676875, 1.1875e-05, 0.0021434375, 0.0003384375, 1.78125e-05, 3.125e-07, 0.7737809375, 0.081450625, 0.0021434375, 0.1221759375, 0.012860625, 0.0003384375, 0.00643031249999999, 0.000676875, 1.78125e-05, 0.0001128125, 1.1875e-05, 3.125e-07), term1_p1 = c(0.4096, 0.2048, 0.0256, 0.2048, 0.1024, 0.0128, 0.0256, 0.0128, 0.0016, 0.32768, 0.24576, 0.06144, 0.00512, 0.16384, 0.12288, 0.03072, 0.00256, 0.02048, 0.01536, 0.00384, 0.00032, 0.32768, 0.16384, 0.02048, 0.24576, 0.12288, 0.01536, 0.06144, 0.03072, 0.00384, 0.00512, 0.00256, 0.00032)), .Names = c("m1", "n1", "x1", "y1", "Fmm", "Fnn", "Qm", "Qn", "term1_p0", "term1_p1"), row.names = c(NA, 33L), class = "data.frame") library(zoo) lst1<- split(d,list(d$m1,d$n1)) res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){ x[,11:14]<-NA; x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]); # cumsum if x$Qm<=c11 & x>2 x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]); #cumsum if x$Qn<=12 & y>2 colnames(x)[11:14]<- c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H"); x1<-na.locf(x); x1[,11:14][is.na(x1[,11:14])]<-0; x1})) row.names(res2)<- 1:nrow(res2) res2 On Sat, Feb 23, 2013 at 10:56 PM, arun kirshna [via R] < ml-node+s789695n4659515...@n4.nabble.com> wrote: > Hi, > You can also use ?rowMins() or ?rowMaxs() from library(matrixStats) > > > library(plyr) > res2<- join(res1,d3,by=c("m1","n1"),type="inner") > > p0L<-0.05 > p0H<-0.05 > p1L<-0.20 > p1H<-0.20 > > res2<- within(res2,{p1<- x/m; p2<- y/n;term2_p0<-dbinom(x1,m1, p0L, > log=FALSE)* dbinom(y1,n1,p0H, log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)* > dbinom(y-y1,n-n1,p0H, log=FALSE);term2_p1<- dbinom(x1,m1, p1L, log=FALSE)* > dbinom(y1,n1,p1H, log=FALSE)*dbinom(x-x1,m-m1, p1L, log=FALSE)* > dbinom(y-y1,n-n1,p1H, log=FALSE)}) > > Pm2<-rbeta(1000, 0.2+res2$x, 0.8+res2$m-res2$x) > Pn2<-rbeta(1000, 0.2+res2$y, 0.8+res2$n-res2$y) > Fm2<- ecdf(Pm2) > Fn2<- ecdf(Pn2) > library(matrixStats) > res3<- within(res2,{Fmm2<-Fm2(p1);Fnn2<- Fn2(p2);R2<- > (Fmm2+Fnn2)/2;Fmm_f2<-rowMins(cbind(R2,Fmm2));Fnn_f2<-rowMaxs(cbind(R2,Fnn2));Qm2<- > 1-Fmm_f2;Qn2<- 1-Fnn_f2}) > head(res3) > # m1 n1 x1 y1 m n x y cterm1_P0L cterm1_P1L cterm1_P0H cterm1_P1H > term2_p1 > #1 2 2 0 0 4 4 0 0 0.9025 0.64 0.9025 0.64 > 0.16777216 > #2 2 2 0 0 4 4 0 1 0.9025 0.64 0.9025 0.64 > 0.08388608 > #3 2 2 0 0 4 4 0 2 0.9025 0.64 0.9025 0.64 > 0.01048576 > #4 2 2 0 0 4 4 1 0 0.9025 0.64 0.9025 0.64 > 0.08388608 > #5 2 2 0 0 4 4 1 1 0.9025 0.64 0.9025 0.64 > 0.04194304 > #6 2 2 0 0 4 4 1 2 0.9025 0.64 0.9025 0.64 > 0.00524288 > # term2_p0 p2 p1 Qn2 Qm2 Fnn_f2 Fmm_f2 R2 Fnn2 Fmm2 > #1 0.6634204313 0.00 0.00 1.000 1.0 0.000 0.0 0.0000 0.000 0.0 > #2 0.0698337296 0.25 0.00 0.593 1.0 0.407 0.0 0.2035 0.407 0.0 > #3 0.0018377297 0.50 0.00 0.302 1.0 0.698 0.0 0.3490 0.698 0.0 > #4 0.0698337296 0.00 0.25 0.800 0.8 0.200 0.2 0.2000 0.000 0.4 > #5 0.0073509189 0.25 0.25 0.593 0.6 0.407 0.4 0.4035 0.407 0.4 > # 0.0001934452 0.50 0.25 0.302 0.6 0.698 0.4 0.5490 0.698 0.4 > > > > > > > ________________________________ > From: Joanna Zhang <[hidden > email]<http://user/SendEmail.jtp?type=node&node=4659515&i=0>> > > To: arun <[hidden > email]<http://user/SendEmail.jtp?type=node&node=4659515&i=1>> > > Sent: Saturday, February 23, 2013 5:35 PM > Subject: Re: [R] cumulative sum by group and under some criteria > > > the row wise min or max of R2, Rmm2 , for example, for the first row, > suppose R2 = 0.63 and Fmm2 = 0.56, then Fmm_f2 = 0.63. > > means draw 1000 samples for each row from a beta distribution. > > > On Sat, Feb 23, 2013 at 3:49 PM, arun <[hidden > email]<http://user/SendEmail.jtp?type=node&node=4659515&i=2>> > wrote: > > Hi, > > > > >I have a doubt: > >When you say that min(R2,Fmm2) or max(R2,Fnn2), do you mean the > corresponding row wise min or max. for these two columns or the maximum > from the entire two columns. > > > >Also, why do you need rbeta(1000,...), should it be rbeta(240,..) because > if you use the former the nrow from res2 is around 240 and in the formula, > you are also using x, m , from res2, which makes no sense to me. > >Arun > > > > > > > > > > > > > > > > > >________________________________ > >From: Joanna Zhang <[hidden > >email]<http://user/SendEmail.jtp?type=node&node=4659515&i=3>> > > >To: arun <[hidden > >email]<http://user/SendEmail.jtp?type=node&node=4659515&i=4>> > > >Sent: Saturday, February 23, 2013 4:12 PM > > > >Subject: Re: [R] cumulative sum by group and under some criteria > > > > > >sorry, these are > >p0L<-0.05 > >p0H<-0.05 > >p1L<-0.20 > >p1H<-0.20 > > > > > > > >On Sat, Feb 23, 2013 at 2:48 PM, arun <[hidden > >email]<http://user/SendEmail.jtp?type=node&node=4659515&i=5>> > wrote: > > > >Hi, > >> > >>If you give only half the information, it will be difficult to solve. > >> > >> > >>d3<-structure(list(m1 = c(2, 3, 2), n1 = c(2, 2, 3), cterm1_P0L = > c(0.9025, > >>0.857375, 0.9025), cterm1_P1L = c(0.64, 0.512, 0.64), cterm1_P0H = > c(0.9025, > >>0.9025, 0.857375), cterm1_P1H = c(0.64, 0.64, 0.512)), .Names = c("m1", > >>"n1", "cterm1_P0L", "cterm1_P1L", "cterm1_P0H", "cterm1_P1H"), row.names > = c(NA, > >>3L), class = "data.frame") > >>d2<- data.frame() > >> > >>for (m1 in 2:3) { > >> for (n1 in 2:3) { > >> for (x1 in 0:(m1-1)) { > >> for (y1 in 0:(n1-1)) { > >> for (m in (m1+2): (7-n1)){ > >> for (n in (n1+2):(9-m)){ > >> > >> for (x in x1:(x1+m-m1)){ > >> > >> for(y in y1:(y1+n-n1)){ > >> d2<- rbind(d2,c(m1,n1,x1,y1,m,n,x,y)) > >> }}}}}}}} > >>colnames(d2)<-c("m1","n1","x1","y1","m","n","x","y") > >> > >> > >> > >>res1<-do.call(rbind,lapply(unique(d3$m1),function(m1) > >> do.call(rbind,lapply(unique(d3$n1),function(n1) > >> do.call(rbind,lapply(0:(m1-1),function(x1) > >> do.call(rbind,lapply(0:(n1-1),function(y1) > >> do.call(rbind,lapply((m1+2):(7-n1),function(m) > >> do.call(rbind,lapply((n1+2):(9-m),function(n) > >> do.call(rbind,lapply(x1:(x1+m-m1), function(x) > >> do.call(rbind,lapply(y1:(y1+n-n1), function(y) > >> expand.grid(m1,n1,x1,y1,m,n,x,y)) ))))))))))))))) > >> names(res1)<- c("m1","n1","x1","y1","m","n","x","y") > >> attr(res1,"out.attrs")<-NULL > >>res1[]<- sapply(res1,as.integer) > >> > >> identical(d2,res1) > >>#[1] TRUE > >> > >>library(plyr) > >>res2<- join(res1,d3,by=c("m1","n1"),type="inner") > >>res2$p1<- x/m > >> res2$p2<- y/n > >> > >> > >> > >>dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, > log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)* dbinom(y-y1,n-n1,p0H, > log=FALSE) > >>#Error in dbinom(x1, m1, p0L, log = FALSE) : object 'p0L' not found > >>A.K. > >> > >> > >> > >>________________________________ > >> > >>From: Joanna Zhang <[hidden > >>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=6>> > > >>To: arun <[hidden > >>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=7>> > > >>Sent: Friday, February 22, 2013 11:02 AM > >> > >>Subject: Re: [R] cumulative sum by group and under some criteria > >> > >> > >>Thanks! Then I need to create new variables based on the res2. I can't > find Fmm_f1, Fnn_f2, R2, Qm2, Qn2 until running the code several times and > the values of Fnn_f2, Fmm_f2 are correct. > >> > >>attach(res2) > >>res2$p1<-x/m > >>res2$p2<-y/n > >>res2$term2_p0 <- dbinom(x1,m1, p0L, log=FALSE)* dbinom(y1,n1,p0H, > log=FALSE)*dbinom(x-x1,m-m1, p0L, log=FALSE)* dbinom(y-y1,n-n1,p0H, > log=FALSE) > >>res2$term2_p1 <- dbinom(x1,m1, p1L, log=FALSE)* dbinom(y1,n1,p1H, > log=FALSE)*dbinom(x-x1,m-m1, p1L, log=FALSE)* dbinom(y-y1,n-n1,p1H, > log=FALSE) > >>Pm2<-rbeta(1000, 0.2+x, 0.8+m-x) > >>Fm2<-ecdf(Pm2) > >>res2$Fmm2<-Fm2(x/m) #not correct, it comes out after running code two > times > >>Pn2<-rbeta(1000, 0.2+y, 0.8+n-y) > >>Fn2<-ecdf(Pn2) > >>res2$Fnn2<-Fn2(y/n) > >>res2$R2<-(Fmm2+Fnn2)/2 > >>res2$Fmm_f2<-min(R2,Fmm2) # not correct > >>res2$Fnn_f2<-max(R2,Fnn2) > >>res2$Qm2<-(1-Fmm_f2) > >>res2$Qn2<-(1-Fnn_f2) > >>detach(res2) > >>res2 > >>head(res2) > >> > >> > >> > >>On Tue, Feb 19, 2013 at 4:09 PM, arun <[hidden > >>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=8>> > wrote: > >> > >>Hi, > >>> > >>>""suppose that I have a dataset 'd' > >>> m1 n1 A B C D > >>>1 2 2 0.902500 0.640 0.9025 0.64 > >>>2 3 2 0.857375 0.512 0.9025 0.64 > >>>I want to add x1 (from 0 to m1), y1(from 0 to n1), m (range from > >>>m1+2 to 7-n1), n(from n1+2 to 9-m), x (x1 to x1+m-m1), y(y1 to > y1+n-n1), expanding to another dataset 'd2' based on each row (combination > of m1 > >>>and n1)"" > >>> > >>> > >>>Try: > >>> > >>> > >>> d<-read.table(text=" > >>> > >>>m1 n1 A B C D > >>>1 2 2 0.902500 0.640 0.9025 0.64 > >>>2 3 2 0.857375 0.512 0.9025 0.64 > >>>",sep="",header=TRUE) > >>> > >>>vec1<- paste(d[,1],d[,2],d[,3],d[,4],d[,5],d[,6]) > >>>res1<- do.call(rbind,lapply(vec1,function(m1) > do.call(rbind,lapply(0:(as.numeric(substr(m1,1,1))),function(x1) > do.call(rbind,lapply(0:(as.numeric(substr(m1,3,3))),function(y1) > do.call(rbind,lapply((as.numeric(substr(m1,1,1))+2):(7-as.numeric(substr(m1,3,3))),function(m) > do.call(rbind,lapply((as.numeric(substr(m1,3,3))+2):(9-m),function(n) > >>> > >>> do.call(rbind,lapply(x1:(x1+m-as.numeric(substr(m1,1,1))), function(x) > >>> do.call(rbind,lapply(y1:(y1+n-as.numeric(substr(m1,3,3))), function(y) > >>> expand.grid(m1,x1,y1,m,n,x,y)) ))))))))))))) > >>> > >>names(res1)<- c("group","x1","y1","m","n","x","y") > >>> res1$m1<- NA; res1$n1<- NA; res1$A<- NA; res1$B<- NA; res1$C<- > NA;res1$D <- NA > >>>res1[,8:13]<-do.call(rbind,lapply(strsplit(as.character(res1$group)," > "),as.numeric)) > >>>res2<- res1[,c(8:9,2:7,10:13)] > >>> > >>> > >>> head(res2) > >>># m1 n1 x1 y1 m n x y A B C D > >>>#1 2 2 0 0 4 4 0 0 0.9025 0.64 0.9025 0.64 > >>>#2 2 2 0 0 4 4 0 1 0.9025 0.64 0.9025 0.64 > >>>#3 2 2 0 0 4 4 0 2 0.9025 0.64 0.9025 0.64 > >>>#4 2 2 0 0 4 4 1 0 0.9025 0.64 0.9025 0.64 > >>>#5 2 2 0 0 4 4 1 1 0.9025 0.64 0.9025 0.64 > >>>#6 2 2 0 0 4 4 1 2 0.9025 0.64 0.9025 0.64 > >>> > >>> > >>> > >>> > >>> > >>> > >>>________________________________ > >>>From: Joanna Zhang <[hidden > >>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=9>> > > >>>To: arun <[hidden > >>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=10>> > > >>>Sent: Tuesday, February 19, 2013 11:43 AM > >>> > >>>Subject: Re: [R] cumulative sum by group and under some criteria > >>> > >>> > >>>Thanks. I can get the data I expected (get rid of the m1=3, n1=3) using > the join and 'inner' code, but just curious about the way to expand the > data. There should be a way to expand the data based on each row > (combination of the variables), unique(d3$m1 & d3$n1) ?. > >>> > >>>or is there a way to use 'data.frame' and 'for' loop to expand directly > from the data? like res1<-data.frame (d3) for () {.... > >>> > >>> > >>>On Tue, Feb 19, 2013 at 9:55 AM, arun <[hidden > >>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=11>> > wrote: > >>> > >>>If you can provide me the output that you expect with all the rows of > the combination in the res2, I can take a look. > >>>> > >>>> > >>>> > >>>> > >>>> > >>>> > >>>>________________________________ > >>>> > >>>>From: Joanna Zhang <[hidden > >>>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=12>> > > >>>>To: arun <[hidden > >>>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=13>> > > >>>> > >>>>Sent: Tuesday, February 19, 2013 10:42 AM > >>>> > >>>>Subject: Re: [R] cumulative sum by group and under some criteria > >>>> > >>>> > >>>>Thanks. But I thougth the expanded dataset 'res1' should not have > combination of m1=3 and n1=3 because it is based on dataset 'd3' which > doesn't have m1=3 and n1=3, right?> > >>>>>In the example that you provided: > >>>>> (m1+2):(maxN-(n1+2)) > >>>>>#[1] 5 > >>>>> (n1+2):(maxN-5) > >>>>>#[1] 4 > >>>>>#Suppose > >>>>> x1<- 4 > >>>>> y1<- 2 > >>>>> x1:(x1+5-m1) > >>>>>#[1] 4 5 6 > >>>>> y1:(y1+4-n1) > >>>>>#[1] 2 3 4 > >>>>> > >>>>> datnew<-expand.grid(5,4,4:6,2:4) > >>>>> colnames(datnew)<- c("m","n","x","y") > >>>>>datnew<-within(datnew,{p1<- x/m;p2<-y/n}) > >>>>>res<-cbind(datnew,d2[rep(1:nrow(d2),nrow(datnew)),]) > >>>>> row.names(res)<- 1:nrow(res) > >>>>> res > >>>>># m n x y p2 p1 m1 n1 cterm1_P1L cterm1_P0H > >>>>>#1 5 4 4 2 0.50 0.8 3 2 0.00032 0.0025 > >>>>>#2 5 4 5 2 0.50 1.0 3 2 0.00032 0.0025 > >>>>>#3 5 4 6 2 0.50 1.2 3 2 0.00032 0.0025 > >>>>>#4 5 4 4 3 0.75 0.8 3 2 0.00032 0.0025 > >>>>>#5 5 4 5 3 0.75 1.0 3 2 0.00032 0.0025 > >>>>>#6 5 4 6 3 0.75 1.2 3 2 0.00032 0.0025 > >>>>>#7 5 4 4 4 1.00 0.8 3 2 0.00032 0.0025 > >>>>>#8 5 4 5 4 1.00 1.0 3 2 0.00032 0.0025 > >>>>>#9 5 4 6 4 1.00 1.2 3 2 0.00032 0.0025 > >>>>> > >>>>>A.K. > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> > >>>>>----- Original Message ----- > >>>>>From: Zjoanna <[hidden > >>>>>email]<http://user/SendEmail.jtp?type=node&node=4659515&i=14>> > > >>>>>To: [hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=15> > >>>>>Cc: > >>>>> > >>>>>Sent: Sunday, February 10, 2013 6:04 PM > >>>>>Subject: Re: [R] cumulative sum by group and under some criteria > >>>>> > >>>>> > >>>>>Hi, > >>>>>How to expand or loop for one variable n based on another variable? > for > >>>>>example, I want to add m (from m1 to maxN- n1-2) and for each m, I > want to > >>>>>add n (n1+2 to maxN-m), and similarly add x and y, then I need to do > some > >>>>>calculations. > >>>>> > >>>>>d3<-data.frame(d2) > >>>>> for (m in (m1+2):(maxN-(n1+2)){ > >>>>> for (n in (n1+2):(maxN-m)){ > >>>>> for (x in x1:(x1+m-m1)){ > >>>>> for (y in y1:(y1+n-n1)){ > >>>>> p1<- x/m > >>>>> p2<- y/n > >>>>>}}}} > >>>>> > >>>>>On Thu, Feb 7, 2013 at 12:16 AM, arun kirshna [via R] < > >>>>>[hidden email]<http://user/SendEmail.jtp?type=node&node=4659515&i=16>> > wrote: > >>>>> > >>>>>> Hi, > >>>>>> > >>>>>> Anyway, just using some random combinations: > >>>>>> dnew<- expand.grid(4:10,5:10,6:10,3:7,4:5,6:8) > >>>>>> names(dnew)<-c("m","n","x1","y1","x","y") > >>>>>> resF<- cbind(dnew,d2[rep(1:nrow(d2),nrow(dnew)),]) > >>>>>> > >>>>>> row.names(resF)<- 1:nrow(resF) > >>>>>> head(resF) > >>>>>> # m n x1 y1 x y m1 n1 cterm1_P1L cterm1_P0H > >>>>>> #1 4 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> #2 5 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> #3 6 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> #4 7 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> #5 8 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> #6 9 5 6 3 4 6 3 2 0.00032 0.0025 > >>>>>> > >>>>>> nrow(resF) > >>>>>> #[1] 6300 > >>>>>> I am not sure what you want to do with this. > >>>>>> A.K. > >>>>>> ________________________________ > >>>>>> From: Joanna Zhang <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=0>> > >>>>>> > >>>>>> To: arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=1>> > >>>>> > >>>>>> > >>>>>> Sent: Wednesday, February 6, 2013 10:29 AM > >>>>>> Subject: Re: cumulative sum by group and under some criteria > >>>>>> > >>>>>> > >>>>>> Hi, > >>>>>> > >>>>>> Thanks! I need to do some calculations in the expended data, the > expended > >>>>>> data would be very large, what is an efficient way, doing > calculations > >>>>>> while expending the data, something similiar with the following, or > >>>>>> expending data using the code in your message and then add > calculations in > >>>>>> the expended data? > >>>>>> > >>>>>> d3<-data.frame(d2) > >>>>>> for .......{ > >>>>>> for { > >>>>>> for .... { > >>>>>> for .....{ > >>>>>> p1<- x/m > >>>>>> p2<- y/n > >>>>>> .......... > >>>>>> }} > >>>>>> }} > >>>>>> > >>>>>> I also modified your code for expending data: > >>>>>> dnew<-expand.grid((m1+2):(maxN-(n1+2)),(n1+2):(maxN-m),0:m1,0:n1, > >>>>>> x1:(x1+m-m1),y1:(y1+n-n1)) > >>>>>> names(dnew)<-c("m","n","x1","y1","x","y") > >>>>>> dnew > >>>>>> resF<-cbind(dnew[,c(2,1)],d2[rep(1:nrow(d2),nrow(dnew)),]) # > this is > >>>>>> not correct, how to modify it. > >>>>>> resF > >>>>>> row.names(resF)<-1:nrow(resF) > >>>>>> resF > >>>>>> > >>>>>> > >>>>>> > >>>>>> > >>>>>> On Tue, Feb 5, 2013 at 2:46 PM, arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=2>> > >>>>> > >>>>>> wrote: > >>>>>> > >>>>>> Hi, > >>>>>> > >>>>>> > > >>>>>> >You can reduce the steps to reach d2: > >>>>>> >res3<- > >>>>>> > with(res2,aggregate(cbind(cterm1_P1L,cterm1_P0H),by=list(m1,n1),max)) > >>>>>> > > >>>>>> >#Change it to: > >>>>>> >res3new<- aggregate(.~m1+n1,data=res2[,c(1:2,12:13)],max) > >>>>>> >res3new > >>>>>> > m1 n1 cterm1_P1L cterm1_P0H > >>>>>> >1 2 2 0.01440 0.00273750 > >>>>>> >2 3 2 0.00032 0.00250000 > >>>>>> >3 2 3 0.01952 0.00048125 > >>>>>> >d2<-res3new[res3new[,3]<0.01 & res3new[,4]<0.01,] > >>>>>> > > >>>>>> > dnew<-expand.grid(4:10,5:10) > >>>>>> > names(dnew)<-c("n","m") > >>>>>> >resF<-cbind(dnew[,c(2,1)],d2[rep(1:nrow(d2),nrow(dnew)),]) > >>>>>> > > >>>>>> >row.names(resF)<-1:nrow(resF) > >>>>>> > head(resF) > >>>>>> ># m n m1 n1 cterm1_P1L cterm1_P0H > >>>>>> >#1 5 4 3 2 0.00032 0.0025 > >>>>>> >#2 5 5 3 2 0.00032 0.0025 > >>>>>> >#3 5 6 3 2 0.00032 0.0025 > >>>>>> >#4 5 7 3 2 0.00032 0.0025 > >>>>>> >#5 5 8 3 2 0.00032 0.0025 > >>>>>> >#6 5 9 3 2 0.00032 0.0025 > >>>>>> > > >>>>>> >A.K. > >>>>>> > > >>>>>> >________________________________ > >>>>>> >From: Joanna Zhang <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=3>> > >>>>>> > >>>>>> >To: arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=4>> > >>>>> > >>>>>> > >>>>>> >Sent: Tuesday, February 5, 2013 2:48 PM > >>>>>> > > >>>>>> >Subject: Re: cumulative sum by group and under some criteria > >>>>>> > > >>>>>> > > >>>>>> > Hi , > >>>>>> >what I want is : > >>>>>> >m n m1 n1 cterm1_P1L cterm1_P0H > >>>>>> > 5 4 3 2 0.00032 0.00250000 > >>>>>> > 5 5 3 2 0.00032 0.00250000 > >>>>>> > 5 6 3 2 0.00032 0.00250000 > >>>>>> > 5 7 3 2 0.00032 0.00250000 > >>>>>> > 5 8 3 2 0.00032 0.00250000 > >>>>>> > 5 9 3 2 0.00032 0.00250000 > >>>>>> >5 10 3 2 0.00032 0.00250000 > >>>>>> >6 4 3 2 0.00032 0.00250000 > >>>>>> >6 5 3 2 0.00032 0.00250000 > >>>>>> >6 6 3 2 0.00032 0.00250000 > >>>>>> >6 7 3 2 0.00032 0.00250000 > >>>>>> >..... > >>>>>> >6 10 3 2 0.00032 0.00250000 > >>>>>> > > >>>>>> > > >>>>>> > > >>>>>> >On Tue, Feb 5, 2013 at 1:12 PM, arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=5>> > >>>>> > >>>>>> wrote: > >>>>>> > > >>>>>> >Hi, > >>>>>> >> > >>>>>> >>Saw your message on Nabble. > >>>>>> >> > >>>>>> >> > >>>>>> >>"I want to add some more columns based on the results. Is the > following > >>>>>> code good way to create such a data frame and How to see the column > m and n > >>>>>> in the updated data? > >>>>>> >> > >>>>>> >>d2<- reres3[res3[,3]<0.01 & res3[,4]<0.01,] > >>>>>> >># should be a typo > >>>>>> >> > >>>>>> >>colnames(d2)[1:2]<- c("m1","n1"); > >>>>>> >>d2 #already a data.frame > >>>>>> >> > >>>>>> >>d3<-data.frame(d2) > >>>>>> >> for (m in (m1+2):10){ > >>>>>> >> for (n in (n1+2):10){ > >>>>>> >> d3<-rbind(d3, c(d2))}}" #this is not making much sense to me. > >>>>>> Especially, you mentioned you wanted add more columns. > >>>>>> >>#Running this step gave error > >>>>>> >>#Error: object 'm1' not found > >>>>>> >> > >>>>>> >>Not sure what you want as output. > >>>>>> >>Could you show the ouput that is expected: > >>>>>> >> > >>>>>> >>A.K. > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >>________________________________ > >>>>>> >>From: Joanna Zhang <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=6>> > >>>>>> > >>>>>> >>To: arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=7>> > >>>>> > >>>>>> > >>>>>> >>Sent: Tuesday, February 5, 2013 10:23 AM > >>>>>> >> > >>>>>> >>Subject: Re: cumulative sum by group and under some criteria > >>>>>> >> > >>>>>> >> > >>>>>> >>Hi, > >>>>>> >> > >>>>>> >>Yes, I changed code. You answered the questions. But how can I > put two > >>>>>> criteria in the code, if both the maximum value of cterm1_p1L <= > 0.01 and > >>>>>> cterm1_p1H <=0.01, the output the m1,n1. > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >> > >>>>>> >>On Tue, Feb 5, 2013 at 8:47 AM, arun <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=8>> > >>>>> > >>>>>> wrote: > >>>>>> >> > >>>>>> >> > >>>>>> >>> > >>>>>> >>> HI, > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>I am not getting the same results as yours: You must have > changed the > >>>>>> dataset. > >>>>>> >>> res2[,1:2][res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95,] > >>>>>> >>> m1 n1 > >>>>>> >>>1 2 2 > >>>>>> >>>2 2 2 > >>>>>> >>>3 2 2 > >>>>>> >>>4 2 2 > >>>>>> >>>5 2 2 > >>>>>> >>>6 2 2 > >>>>>> >>>7 2 2 > >>>>>> >>>8 2 2 > >>>>>> >>>9 2 2 > >>>>>> >>>10 3 2 > >>>>>> >>>11 3 2 > >>>>>> >>>12 3 2 > >>>>>> >>>13 3 2 > >>>>>> >>>14 3 2 > >>>>>> >>>15 3 2 > >>>>>> >>>16 3 2 > >>>>>> >>>17 3 2 > >>>>>> >>>18 3 2 > >>>>>> >>>19 3 2 > >>>>>> >>>20 3 2 > >>>>>> >>>21 3 2 > >>>>>> >>>22 2 3 > >>>>>> >>>23 2 3 > >>>>>> >>>24 2 3 > >>>>>> >>>25 2 3 > >>>>>> >>>26 2 3 > >>>>>> >>>27 2 3 > >>>>>> >>>28 2 3 > >>>>>> >>>29 2 3 > >>>>>> >>>30 2 3 > >>>>>> >>>31 2 3 > >>>>>> >>>32 2 3 > >>>>>> >>>33 2 3 > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>Regarding the maximum value within each block, haven't I > answered in > >>>>>> the earlier post. > >>>>>> >>> > >>>>>> >>>aggregate(cterm1_P1L~m1+n1,data=res2,max) > >>>>>> >>># m1 n1 cterm1_P1L > >>>>>> >>>#1 2 2 0.01440 > >>>>>> >>>#2 3 2 0.00032 > >>>>>> >>>#3 2 3 0.01952 > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > with(res2,aggregate(cbind(cterm1_P1L,cterm1_P0H),by=list(m1,n1),max)) > >>>>>> >>># Group.1 Group.2 cterm1_P1L cterm1_P0H > >>>>>> >>>#1 2 2 0.01440 0.00273750 > >>>>>> >>>#2 3 2 0.00032 0.00250000 > >>>>>> >>>#3 2 3 0.01952 0.00048125 > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>A.K. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>----- Original Message ----- > >>>>> > >>>>>> >>>From: "[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=9>";;;;;; > >>>>>> <[hidden email] < > http://user/SendEmail.jtp?type=node&node=4657773&i=10>> > >>>>>> >>>To: [hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=11> > >>>>>> >>>Cc: > >>>>>> >>> > >>>>>> >>>Sent: Tuesday, February 5, 2013 9:33 AM > >>>>>> >>>Subject: Re: cumulative sum by group and under some criteria > >>>>>> >>> > >>>>>> >>>Hi, > >>>>>> >>>If use this > >>>>>> >>> > >>>>>> >>>res2[,1:2][res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95,] > >>>>>> >>> > >>>>>> >>>the results are the following, but actually only m1=3, n1=2 > sastify the > >>>>>> criteria, as I need to look at the row with maximum value within > each > >>>>>> block,not every row. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> m1 n1 > >>>>>> >>>1 2 2 > >>>>>> >>>10 3 2 > >>>>>> >>>11 3 2 > >>>>>> >>>12 3 2 > >>>>>> >>>13 3 2 > >>>>>> >>>14 3 2 > >>>>>> >>>15 3 2 > >>>>>> >>>16 3 2 > >>>>>> >>>17 3 2 > >>>>>> >>>18 3 2 > >>>>>> >>>19 3 2 > >>>>>> >>>20 3 2 > >>>>>> >>>21 3 2 > >>>>>> >>>22 2 3 > >>>>>> >>>23 2 3 > >>>>>> >>> > >>>>>> >>> > >>>>>> >>><quote author='arun kirshna'> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>Hi, > >>>>>> >>>Thanks. This extract every row that satisfy the condition, but I > need > >>>>>> look > >>>>>> >>>at the last row (the maximum of cumulative sum) for each block > (m1,n1). > >>>>>> for > >>>>>> >>>example, if I set the criteria > >>>>>> >>> > >>>>>> >>>res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95, this should extract > m1= 3, > >>>>>> n1 = > >>>>>> >>>2. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>Hi, > >>>>>> >>>I am not sure I understand your question. > >>>>>> >>>res2$cterm1_P1L<0.6 & res2$cterm1_P0H<0.95 > >>>>>> >>> #[1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE > TRUE TRUE > >>>>>> TRUE > >>>>>> >>>TRUE > >>>>>> >>>#[16] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE > TRUE TRUE > >>>>>> TRUE > >>>>>> >>>TRUE > >>>>>> >>>#[31] TRUE TRUE TRUE > >>>>>> >>> > >>>>>> >>>This will extract all the rows. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>res2[,1:2][res2$cterm1_P1L<0.01 & res2$cterm1_P1L!=0,] > >>>>>> >>># m1 n1 > >>>>>> >>>#21 3 2 > >>>>>> >>>This extract only the row you wanted. > >>>>>> >>> > >>>>>> >>>For the different groups: > >>>>>> >>> > >>>>>> >>>aggregate(cterm1_P1L~m1+n1,data=res2,max) > >>>>>> >>># m1 n1 cterm1_P1L > >>>>>> >>>#1 2 2 0.01440 > >>>>>> >>>#2 3 2 0.00032 > >>>>>> >>>#3 2 3 0.01952 > >>>>>> >>> > >>>>>> >>> aggregate(cterm1_P1L~m1+n1,data=res2,function(x) max(x)<0.01) > >>>>>> >>> # m1 n1 cterm1_P1L > >>>>>> >>>#1 2 2 FALSE > >>>>>> >>>#2 3 2 TRUE > >>>>>> >>>#3 2 3 FALSE > >>>>>> >>> > >>>>>> >>>res4<-aggregate(cterm1_P1L~m1+n1,data=res2,function(x) > max(x)<0.01) > >>>>>> >>>res4[,1:2][res4[,3],] > >>>>>> >>># m1 n1 > >>>>>> >>>#2 3 2 > >>>>>> >>> > >>>>>> >>>A.K. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>----- Original Message ----- > >>>>> > >>>>>> >>>From: "[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=12>";;;;;; > >>>>>> <[hidden email] < > http://user/SendEmail.jtp?type=node&node=4657773&i=13>> > >>>>>> >>>To: [hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=14> > >>>>>> >>>Cc: > >>>>>> >>>Sent: Sunday, February 3, 2013 3:58 PM > >>>>>> >>>Subject: Re: cumulative sum by group and under some criteria > >>>>>> >>> > >>>>>> >>>Hi, > >>>>>> >>>Let me restate my questions. I need to get the m1 and n1 that > satisfy > >>>>>> some > >>>>>> >>>criteria, for example in this case, within each group, the > maximum > >>>>>> >>>cterm1_p1L ( the last row in this group) <0.01. I need to > extract m1=3, > >>>>>> >>>n1=2, I only need m1, n1 in the row. > >>>>>> >>> > >>>>>> >>>Also, how to create the structure from the data.frame, I am new > to R, I > >>>>>> need > >>>>>> >>>to change the maxN and run the loop to different data. > >>>>>> >>>Thanks very much for your help! > >>>>>> >>> > >>>>>> >>><quote author='arun kirshna'> > >>>>>> >>>HI, > >>>>>> >>> > >>>>>> >>>I think this should be more correct: > >>>>>> >>>maxN<-9 > >>>>>> >>>c11<-0.2 > >>>>>> >>>c12<-0.2 > >>>>>> >>>p0L<-0.05 > >>>>>> >>>p0H<-0.05 > >>>>>> >>>p1L<-0.20 > >>>>>> >>>p1H<-0.20 > >>>>>> >>> > >>>>>> >>>d <- structure(list(m1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, > 2, > >>>>>> >>>2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), > >>>>>> >>> n1 = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, > >>>>>> >>> 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), x1 = c(0, > >>>>>> >>> 0, 0, 1, 1, 1, 2, 2, 2, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, > >>>>>> >>> 2, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3), y1 = c(0, 1, 2, 0, > >>>>>> >>> 1, 2, 0, 1, 2, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, > >>>>>> >>> 2, 0, 1, 2, 0, 1, 2, 0, 1, 2), Fmm = c(0, 0, 0, 0.7, 0.59, > >>>>>> >>> 0.64, 1, 1, 1, 0, 0, 0, 0, 0.63, 0.7, 0.74, 0.68, 1, 1, 1, > >>>>>> >>> 1, 0, 0, 0, 0.62, 0.63, 0.6, 0.63, 0.6, 0.68, 1, 1, 1), Fnn > = c(0, > >>>>>> >>> 0.64, 1, 0, 0.51, 1, 0, 0.67, 1, 0, 0.62, 0.69, 1, 0, 0.54, > >>>>>> >>> 0.62, 1, 0, 0.63, 0.73, 1, 0, 0.63, 1, 0, 0.7, 1, 0, 0.7, > >>>>>> >>> 1, 0, 0.58, 1), Qm = c(1, 1, 1, 0.65, 0.45, 0.36, 0.5, > 0.165, > >>>>>> >>> 0, 1, 1, 1, 1, 0.685, 0.38, 0.32, 0.32, 0.5, 0.185, 0.135, > >>>>>> >>> 0, 1, 1, 1, 0.69, 0.37, 0.4, 0.685, 0.4, 0.32, 0.5, 0.21, > >>>>>> >>> 0), Qn = c(1, 0.36, 0, 0.65, 0.45, 0, 0.5, 0.165, 0, 1, > 0.38, > >>>>>> >>> 0.31, 0, 0.685, 0.38, 0.32, 0, 0.5, 0.185, 0.135, 0, 1, > 0.37, > >>>>>> >>> 0, 0.69, 0.3, 0, 0.685, 0.3, 0, 0.5, 0.21, 0), term1_p0 = > >>>>>> c(0.81450625, > >>>>>> >>> 0.0857375, 0.00225625, 0.0857375, 0.009025, 0.0002375, > 0.00225625, > >>>>>> >>> 0.0002375, 6.25e-06, 0.7737809375, 0.1221759375, > >>>>>> 0.00643031249999999, > >>>>>> >>> 0.0001128125, 0.081450625, 0.012860625, 0.000676875, > 1.1875e-05, > >>>>>> >>> 0.0021434375, 0.0003384375, 1.78125e-05, 3.125e-07, > 0.7737809375, > >>>>>> >>> 0.081450625, 0.0021434375, 0.1221759375, 0.012860625, > >>>>>> 0.0003384375, > >>>>>> >>> 0.00643031249999999, 0.000676875, 1.78125e-05, 0.0001128125, > >>>>>> >>> 1.1875e-05, 3.125e-07), term1_p1 = c(0.4096, 0.2048, 0.0256, > >>>>>> >>> 0.2048, 0.1024, 0.0128, 0.0256, 0.0128, 0.0016, 0.32768, > >>>>>> >>> 0.24576, 0.06144, 0.00512, 0.16384, 0.12288, 0.03072, > 0.00256, > >>>>>> >>> 0.02048, 0.01536, 0.00384, 0.00032, 0.32768, 0.16384, > 0.02048, > >>>>>> >>> 0.24576, 0.12288, 0.01536, 0.06144, 0.03072, 0.00384, > 0.00512, > >>>>>> >>> 0.00256, 0.00032)), .Names = c("m1", "n1", "x1", "y1", > "Fmm", > >>>>>> >>>"Fnn", "Qm", "Qn", "term1_p0", "term1_p1"), row.names = c(NA, > >>>>>> >>>33L), class = "data.frame") > >>>>>> >>> > >>>>>> >>>library(zoo) > >>>>>> >>>lst1<- split(d,list(d$m1,d$n1)) > >>>>>> > >>>res2<-do.call(rbind,lapply(lst1[lapply(lst1,nrow)!=0],function(x){ > >>>>>> >>>x[,11:14]<-NA; > >>>>>> >>>x[,11:12][x$Qm<=c11,]<-cumsum(x[,9:10][x$Qm<=c11,]); > >>>>>> >>>x[,13:14][x$Qn<=c12,]<-cumsum(x[,9:10][x$Qn<=c12,]); > >>>>>> >>>colnames(x)[11:14]<- > >>>>>> c("cterm1_P0L","cterm1_P1L","cterm1_P0H","cterm1_P1H"); > >>>>>> >>>x1<-na.locf(x); > >>>>>> >>>x1[,11:14][is.na(x1[,11:14])]<-0; > >>>>>> >>>x1})) > >>>>>> >>>row.names(res2)<- 1:nrow(res2) > >>>>>> >>> > >>>>>> >>> res2 > >>>>>> >>> # m1 n1 x1 y1 Fmm Fnn Qm Qn term1_p0 term1_p1 > >>>>>> cterm1_P0L > >>>>>> >>>cterm1_P1L cterm1_P0H cterm1_P1H > >>>>>> >>> > >>>>>> >>>#1 2 2 0 0 0.00 0.00 1.000 1.000 0.8145062500 0.40960 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#2 2 2 0 1 0.00 0.64 1.000 0.360 0.0857375000 0.20480 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#3 2 2 0 2 0.00 1.00 1.000 0.000 0.0022562500 0.02560 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0022562500 0.02560 > >>>>>> >>>#4 2 2 1 0 0.70 0.00 0.650 0.650 0.0857375000 0.20480 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0022562500 0.02560 > >>>>>> >>>#5 2 2 1 1 0.59 0.51 0.450 0.450 0.0090250000 0.10240 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0022562500 0.02560 > >>>>>> >>>#6 2 2 1 2 0.64 1.00 0.360 0.000 0.0002375000 0.01280 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024937500 0.03840 > >>>>>> >>>#7 2 2 2 0 1.00 0.00 0.500 0.500 0.0022562500 0.02560 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024937500 0.03840 > >>>>>> >>>#8 2 2 2 1 1.00 0.67 0.165 0.165 0.0002375000 0.01280 > >>>>>> 0.0002375000 > >>>>>> >>> 0.01280 0.0027312500 0.05120 > >>>>>> >>>#9 2 2 2 2 1.00 1.00 0.000 0.000 0.0000062500 0.00160 > >>>>>> 0.0002437500 > >>>>>> >>> 0.01440 0.0027375000 0.05280 > >>>>>> >>>#10 3 2 0 0 0.00 0.00 1.000 1.000 0.7737809375 0.32768 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#11 3 2 0 1 0.00 0.63 1.000 0.370 0.0814506250 0.16384 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#12 3 2 0 2 0.00 1.00 1.000 0.000 0.0021434375 0.02048 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0021434375 0.02048 > >>>>>> >>>#13 3 2 1 0 0.62 0.00 0.690 0.690 0.1221759375 0.24576 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0021434375 0.02048 > >>>>>> >>>#14 3 2 1 1 0.63 0.70 0.370 0.300 0.0128606250 0.12288 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0021434375 0.02048 > >>>>>> >>>#15 3 2 1 2 0.60 1.00 0.400 0.000 0.0003384375 0.01536 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024818750 0.03584 > >>>>>> >>>#16 3 2 2 0 0.63 0.00 0.685 0.685 0.0064303125 0.06144 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024818750 0.03584 > >>>>>> >>>#17 3 2 2 1 0.60 0.70 0.400 0.300 0.0006768750 0.03072 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024818750 0.03584 > >>>>>> >>>#18 3 2 2 2 0.68 1.00 0.320 0.000 0.0000178125 0.00384 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024996875 0.03968 > >>>>>> >>>#19 3 2 3 0 1.00 0.00 0.500 0.500 0.0001128125 0.00512 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024996875 0.03968 > >>>>>> >>>#20 3 2 3 1 1.00 0.58 0.210 0.210 0.0000118750 0.00256 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0024996875 0.03968 > >>>>>> >>>#21 3 2 3 2 1.00 1.00 0.000 0.000 0.0000003125 0.00032 > >>>>>> 0.0000003125 > >>>>>> >>> 0.00032 0.0025000000 0.04000 > >>>>>> >>>#22 2 3 0 0 0.00 0.00 1.000 1.000 0.7737809375 0.32768 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#23 2 3 0 1 0.00 0.62 1.000 0.380 0.1221759375 0.24576 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#24 2 3 0 2 0.00 0.69 1.000 0.310 0.0064303125 0.06144 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0000000000 0.00000 > >>>>>> >>>#25 2 3 0 3 0.00 1.00 1.000 0.000 0.0001128125 0.00512 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001128125 0.00512 > >>>>>> >>>#26 2 3 1 0 0.63 0.00 0.685 0.685 0.0814506250 0.16384 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001128125 0.00512 > >>>>>> >>>#27 2 3 1 1 0.70 0.54 0.380 0.380 0.0128606250 0.12288 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001128125 0.00512 > >>>>>> >>>#28 2 3 1 2 0.74 0.62 0.320 0.320 0.0006768750 0.03072 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001128125 0.00512 > >>>>>> >>>#29 2 3 1 3 0.68 1.00 0.320 0.000 0.0000118750 0.00256 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001246875 0.00768 > >>>>>> >>>#30 2 3 2 0 1.00 0.00 0.500 0.500 0.0021434375 0.02048 > >>>>>> 0.0000000000 > >>>>>> >>> 0.00000 0.0001246875 0.00768 > >>>>>> >>>#31 2 3 2 1 1.00 0.63 0.185 0.185 0.0003384375 0.01536 > >>>>>> 0.0003384375 > >>>>>> >>> 0.01536 0.0004631250 0.02304 > >>>>>> >>>#32 2 3 2 2 1.00 0.73 0.135 0.135 0.0000178125 0.00384 > >>>>>> 0.0003562500 > >>>>>> >>> 0.01920 0.0004809375 0.02688 > >>>>>> >>>#33 2 3 2 3 1.00 1.00 0.000 0.000 0.0000003125 0.00032 > >>>>>> 0.0003565625 > >>>>>> >>> 0.01952 0.0004812500 0.02720 > >>>>>> >>> > >>>>>> >>>#Sorry, some values in my previous solution didn't look right. I > >>>>>> didn't > >>>>>> >>>A.K. > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>----- Original Message ----- > >>>>>> >>>From: Zjoanna <[hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=15>> > >>>>>> > >>>>>> >>>To: [hidden email]< > http://user/SendEmail.jtp?type=node&node=4657773&i=16> > >>>>> > >>>>>> >>>Cc: > >>>>>> >>>Sent: Friday, February 1, 2013 12:19 PM > >>>>>> >>>Subject: Re: [R] cumulative sum by group and under some criteria > >>>>>> >>> > >>>>>> >>>Thank you very much for your reply. Your code work well with > this > >>>>>> example. > >>>>>> >>>I modified a little to fit my real data, I got an error massage. > >>>>>> >>> > >>>>>> >>>Error in split.default(x = seq_len(nrow(x)), f = f, drop = drop, > ...) : > >>>>>> >>> Group length is 0 but data length > 0 > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>On Thu, Jan 31, 2013 at 12:21 PM, arun kirshna [via R] < > >>>>>> >>>[hidden email] < > http://user/SendEmail.jtp?type=node&node=4657773&i=17>> > >>>>> > >>>>>> wrote: > >>>>>> >>> > >>>>>> >>>> Hi, > >>>>>> >>>> Try this: > >>>>>> >>>> colnames(d)<-c("m1","n1","x1","y1","p11","p12") > >>>>>> >>>> library(zoo) > >>>>>> >>>> res1<- > >>>>>> do.call(rbind,lapply(lapply(split(d,list(d$m1,d$n1)),function(x) > >>>>>> >>>> {x$cp11[x$x1>1]<- cumsum(x$p11[x$x1>1]);x$cp12[x$y1>1]<- > >>>>>> >>>> cumsum(x$p12[x$y1>1]);x}),function(x) > >>>>>> >>>> {x$cp11<-na.locf(x$cp11,na.rm=F);x$cp12<- > >>>>>> na.locf(x$cp12,na.rm=F);x})) > >>>>>> >>>> #there would be a warning here as one of the list element is > NULL. > >>>>>> The, > >>>>>> >>>> warning is okay > >>>>>> >>>> row.names(res1)<- 1:nrow(res1) > >>>>>> >>>> res1[,7:8][is.na(res1[,7:8])]<- 0 > >>>>>> >>>> res1 > >>>>>> >>>> # m1 n1 x1 y1 p11 p12 cp11 cp12 > >>>>>> >>>> #1 2 2 0 0 0.00 0.00 0.00 0.00 > >>>>>> >>>> #2 2 2 0 1 0.00 0.50 0.00 0.00 > >>>>>> >>>> #3 2 2 0 2 0.00 1.00 0.00 1.00 > >>>>>> >>>> #4 2 2 1 0 0.50 0.00 0.00 1.00 > >>>>>> >>>> #5 2 2 1 1 0.50 0.50 0.00 1.00 > >>>>>> >>>> #6 2 2 1 2 0.50 1.00 0.00 2.00 > >>>>>> >>>> #7 2 2 2 0 1.00 0.00 1.00 2.00 > >>>>>> >>>> #8 2 2 2 1 1.00 0.50 2.00 2.00 > >>>>>> >>>> #9 2 2 2 2 1.00 1.00 3.00 3.00 > >>>>>> >>>> #10 3 2 0 0 0.00 0.00 0.00 0.00 > >>>>>> >>>> #11 3 2 0 1 0.00 0.50 0.00 0.00 > >>>>>> >>>> #12 3 2 0 2 0.00 1.00 0.00 1.00 > >>>>>> >>>> #13 3 2 1 0 0.33 0.00 0.00 1.00 > >>>>>> >>>> #14 3 2 1 1 0.33 0.50 0.00 1.00 > >>>>>> >>>> #15 3 2 1 2 0.33 1.00 0.00 2.00 > >>>>>> >>>> #16 3 2 2 0 0.67 0.00 0.67 2.00 > >>>>>> >>>> #17 3 2 2 1 0.67 0.50 1.34 2.00 > >>>>>> >>>> #18 3 2 2 2 0.67 1.00 2.01 3.00 > >>>>>> >>>> #19 3 2 3 0 1.00 0.00 3.01 3.00 > >>>>>> >>>> #20 3 2 3 1 1.00 0.50 4.01 3.00 > >>>>>> >>>> #21 3 2 3 2 1.00 1.00 5.01 4.00 > >>>>>> >>>> #22 2 3 0 0 0.00 0.00 0.00 0.00 > >>>>>> >>>> #23 2 3 0 1 0.00 0.33 0.00 0.00 > >>>>>> >>>> #24 2 3 0 2 0.00 0.67 0.00 0.67 > >>>>>> >>>> #25 2 3 0 3 0.00 1.00 0.00 1.67 > >>>>>> >>>> #26 2 3 1 0 0.50 0.00 0.00 1.67 > >>>>>> >>>> #27 2 3 1 1 0.50 0.33 0.00 1.67 > >>>>>> >>>> #28 2 3 1 2 0.50 0.67 0.00 2.34 > >>>>>> >>>> #29 2 3 1 3 0.50 1.00 0.00 3.34 > >>>>>> >>>> #30 2 3 2 0 1.00 0.00 1.00 3.34 > >>>>>> >>>> #31 2 3 2 1 1.00 0.33 2.00 3.34 > >>>>>> >>>> #32 2 3 2 2 1.00 0.67 3.00 4.01 > >>>>>> >>>> #33 2 3 2 3 1.00 1.00 4.00 5.01 > >>>>>> >>>> A.K. > >>>>>> >>>> > >>>>>> >>>> ------------------------------ > >>>>>> >>>> If you reply to this email, your message will be added to the > >>>>>> discussion > >>>>>> >>>> below: > >>>>>> >>>> > >>>>>> >>>> > >>>>>> > 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provide commented, minimal, self-contained, reproducible > code. > >>>>>> >>> > >>>>>> >>></quote> > >>>>>> >>>Quoted from: > >>>>>> >>> > >>>>>> > http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657360.html > >>>>>> >>> > >>>>>> >>> > >>>>>> >>>______________________________________________ > >>>>>> >>>[hidden email] < > http://user/SendEmail.jtp?type=node&node=4657773&i=20>mailing list > >>>>> > >>>>>> >>>https://stat.ethz.ch/mailman/listinfo/r-help > >>>>>> >>>PLEASE do read the posting guide > >>>>>> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html> > <http://www.r-project.org/posting-guide.html> > >>>>> > >>>>>> >>>and provide commented, minimal, self-contained, reproducible > code. > >>>>>> >>> > >>>>>> >>></quote> > >>>>>> >>>Quoted from: > >>>>>> >>> > >>>>>> > http://r.789695.n4.nabble.com/cumulative-sum-by-group-and-under-some-criteria-tp4657074p4657582.html > >>>>>> >>> > >>>>>> >>> > >>>>>> >> > 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[[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.