[R] extracting data coincident with the beginning and end of multiple streaks (rle)

[arun]

Hi,
May be this helps:

###Added more lines of fake data

fn_hp<- read.table(text="
id       date              wl_m    wet    cuml_day 
585 fn 2012-03-03   0.1527048   1        1              
586 fn 2012-03-04   0.2121408   1        2              
587 fn 2012-03-05   0.1877568   1        3              
588 fn 2012-03-06   0.1709928   1        4              
589 fn 2012-03-07   0.1642872   1        5              
598 fn 2012-03-16   0.0182880   0        1              
599 fn 2012-03-17  -0.0076200   0        2              
600 fn 2012-03-18  -0.0067056   0        3              
601 fn 2012-03-19  -0.0097536   0        4              
602 fn 2012-03-20   0.0015240   0        5              
603 fn 2012-03-21  -0.0067056   0        6              
604 fn 2012-03-22   0.0003048   0        7              
605 fn 2012-03-23   0.0024384   0        8              
606 fn 2012-03-24  -0.0054864   0        9
607 fn 2012-03-25  -0.0067056   1        1              
608 fn 2012-03-26   0.0003048   1        2              
609 fn 2012-03-27   0.0024384   1        3              
610 fn 2012-03-28  -0.0054864   1        4
",sep="",header=TRUE,stringsAsFactors=FALSE)
fn_hp1<- fn_hp
fn_hp$DESIRED.col<-NA
fn_hp$IDNew<- cumsum(c(1,abs(diff(fn_hp$cuml_day)))>1)+1
res1<-  unsplit(lapply(split(fn_hp,fn_hp$IDNew),function(x){ x$DESIRED.col[1]<-tail(x$cuml_day,1);x$DESIRED.col[nrow(x)]<- x$DESIRED.col[1];x}),fn_hp$IDNew)[,-7]
res1[!is.na(res1$DESIRED.col),]
#    id       date       wl_m wet cuml_day DESIRED.col
#585 fn 2012-03-03  0.1527048   1        1           5
#589 fn 2012-03-07  0.1642872   1        5           5
#598 fn 2012-03-16  0.0182880   0        1           9
#606 fn 2012-03-24 -0.0054864   0        9           9
#607 fn 2012-03-25 -0.0067056   1        1           4
#610 fn 2012-03-28 -0.0054864   1        4           4

#or
fn_hp1$IDNew<-cumsum(c(1,abs(diff(fn_hp1$cuml_day)))>1)+1
library(plyr)
res2<-ddply(fn_hp1,.(IDNew),mutate,DESIRED.col=c(tail(cuml_day,1),rep(NA,length(cuml_day)-2),tail(cuml_day,1)))[,-6]
row.names(res2)<- row.names(fn_hp1)
 res2[!is.na(res2$DESIRED.col),-6]
#    id       date       wl_m wet cuml_day
#585 fn 2012-03-03  0.1527048   1        1
#589 fn 2012-03-07  0.1642872   1        5
#598 fn 2012-03-16  0.0182880   0        1
#606 fn 2012-03-24 -0.0054864   0        9
#607 fn 2012-03-25 -0.0067056   1        1
#610 fn 2012-03-28 -0.0054864   1        4

#or
#if the `DESIRED.col` is not needed
res3<- ddply(fn_hp1,.(IDNew),function(x) x[c(1,nrow(x)),])[,-6]
res3
#  id       date       wl_m wet cuml_day
#1 fn 2012-03-03  0.1527048   1        1
#2 fn 2012-03-07  0.1642872   1        5
#3 fn 2012-03-16  0.0182880   0        1
#4 fn 2012-03-24 -0.0054864   0        9
#5 fn 2012-03-25 -0.0067056   1        1
#6 fn 2012-03-28 -0.0054864   1        4


A.K.


Good day: 

I used rle to calculate the wet and dry duration (cuml_day) of wetlands using the "wet" variable from the sample data below. 

>cum_day<- unlist( lapply( rle(fn_hp$wet)$lengths, seq_len)) ### counts consecutive 1 and 0 ###   
>fn_hp<-cbind(fn_hp,cum_day) ### bind cumul. days to org dataframe 

 I would now like to extract the rows of data that correspond to
 the beginning and end of each streak so I can look at both the duration
 of the streak and the date ranges where it occurred (to see if wet 
periods coincide with amphibian breeding periods). 

- An alternative solution would be to add the streak length from rle to each row that was included in the particular streak (DESIRED.col) 

I am a relatively new R user and not sure the best way to approach this. Any insight is appreciated. 
-Jeff 
      
       id       date              wl_m    wet    cuml_day   DESIRED.col
585 fn 2012-03-03   0.1527048   1        1                       5 
586 fn 2012-03-04   0.2121408   1        2                       . 
587 fn 2012-03-05   0.1877568   1        3                       . 
588 fn 2012-03-06   0.1709928   1        4                       . 
589 fn 2012-03-07   0.1642872   1        5                       5 
598 fn 2012-03-16   0.0182880   0        1                       9 
599 fn 2012-03-17  -0.0076200   0        2                       . 
600 fn 2012-03-18  -0.0067056   0        3                       . 
601 fn 2012-03-19  -0.0097536   0        4                       . 
602 fn 2012-03-20   0.0015240   0        5                       . 
603 fn 2012-03-21  -0.0067056   0        6                       . 
604 fn 2012-03-22   0.0003048   0        7                       . 
605 fn 2012-03-23   0.0024384   0        8                       . 
606 fn 2012-03-24  -0.0054864   0        9                      9