Hi,
res3<-with(res2,aggregate(cbind(cterm1_P1L,cterm1_P0H),by=list(m1,n1),max))
res3[res3[,3]<0.6 & res3[,4]<0.95,] #this doesn't change the result as the
conditions are not met
# 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
res3[res3[,3]<0.01 & res3[,4]<0.01,]
# Group.1 Group.2 cterm1_P1L cterm1_P0H
#2 3 2 0.00032 0.0025
Hope it helps.
A.K.
________________________________
From: Joanna Zhang <zjoanna2...@gmail.com>
To: arun <smartpink...@yahoo.com>
Sent: Tuesday, February 5, 2013 9:43 AM
Subject: Re: cumulative sum by group and under some criteria
Yes, it did answer my question, max(x) look at the maximum value. However, how
to put both criteria in the code, like both the maximum value of cterm1_p1L
<0.6 and the maximum value of cterm1_p0L<0.95. Thanks a lot!
On Mon, Feb 4, 2013 at 4:26 PM, arun <smartpink...@yahoo.com> wrote:
>
>Hi,
>
>Did this answered your question?
>
>A.K.
>
>
>----- Original Message -----
>
>From: arun <smartpink...@yahoo.com>
>To: "zjoanna2...@gmail.com" <zjoanna2...@gmail.com>
>Cc: R help <r-help@r-project.org>
>Sent: Monday, February 4, 2013 4:44 PM
>Subject: Re: cumulative sum by group and under some criteria
>
>
>
>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: "zjoanna2...@gmail.com" <zjoanna2...@gmail.com>
>To: smartpink...@yahoo.com
>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 <zjoanna2...@gmail.com>
>To: r-help@r-project.org
>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] <
>ml-node+s789695n4657196...@n4.nabble.com> 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.
>>
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