Find the closest enclosing FALSE value positions












3














Is there a more elegant way to solve this problem?



For every TRUE value I'm looking for the positions of the closest previous and following FALSE values.



data:



vec <- c(FALSE, TRUE, TRUE, FALSE, TRUE, FALSE)


desired outcome: (something like)



     pos start end

[1,] 2   1     4  

[2,] 3   1     4  

[3,] 5   4     6


explanation of the first row of the outcome:




  • pos = 2, position of the first TRUE,

  • start = 1, position of the closest FALSE in front of pos = 2

  • end = 4, position of the closest FALSE after pos = 2.


Already working solution:



pos = which(vec)

f_pos = which(!vec)



t(

sapply(pos, function(x){ s <- rev(f_pos[f_pos < x])[1]; e <- f_pos[x < f_pos][1]; return(data.frame(pos = x, start = s, end = e)) })

)





r







share|improve this question
























  • what if vec ended with TRUE?
    – Cath
    Nov 14 '18 at 9:05










  • good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
    – Andre Elrico
    Nov 14 '18 at 9:07


















3














Is there a more elegant way to solve this problem?



For every TRUE value I'm looking for the positions of the closest previous and following FALSE values.



data:



vec <- c(FALSE, TRUE, TRUE, FALSE, TRUE, FALSE)


desired outcome: (something like)



     pos start end

[1,] 2   1     4  

[2,] 3   1     4  

[3,] 5   4     6


explanation of the first row of the outcome:




  • pos = 2, position of the first TRUE,

  • start = 1, position of the closest FALSE in front of pos = 2

  • end = 4, position of the closest FALSE after pos = 2.


Already working solution:



pos = which(vec)

f_pos = which(!vec)



t(

sapply(pos, function(x){ s <- rev(f_pos[f_pos < x])[1]; e <- f_pos[x < f_pos][1]; return(data.frame(pos = x, start = s, end = e)) })

)





r







share|improve this question
























  • what if vec ended with TRUE?
    – Cath
    Nov 14 '18 at 9:05










  • good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
    – Andre Elrico
    Nov 14 '18 at 9:07
















3












3








3


1





Is there a more elegant way to solve this problem?



For every TRUE value I'm looking for the positions of the closest previous and following FALSE values.



data:



vec <- c(FALSE, TRUE, TRUE, FALSE, TRUE, FALSE)


desired outcome: (something like)



     pos start end

[1,] 2   1     4  

[2,] 3   1     4  

[3,] 5   4     6


explanation of the first row of the outcome:




  • pos = 2, position of the first TRUE,

  • start = 1, position of the closest FALSE in front of pos = 2

  • end = 4, position of the closest FALSE after pos = 2.


Already working solution:



pos = which(vec)

f_pos = which(!vec)



t(

sapply(pos, function(x){ s <- rev(f_pos[f_pos < x])[1]; e <- f_pos[x < f_pos][1]; return(data.frame(pos = x, start = s, end = e)) })

)





r







share|improve this question















Is there a more elegant way to solve this problem?



For every TRUE value I'm looking for the positions of the closest previous and following FALSE values.



data:



vec <- c(FALSE, TRUE, TRUE, FALSE, TRUE, FALSE)


desired outcome: (something like)



     pos start end

[1,] 2   1     4  

[2,] 3   1     4  

[3,] 5   4     6


explanation of the first row of the outcome:




  • pos = 2, position of the first TRUE,

  • start = 1, position of the closest FALSE in front of pos = 2

  • end = 4, position of the closest FALSE after pos = 2.


Already working solution:



pos = which(vec)

f_pos = which(!vec)



t(

sapply(pos, function(x){ s <- rev(f_pos[f_pos < x])[1]; e <- f_pos[x < f_pos][1]; return(data.frame(pos = x, start = s, end = e)) })

)





r




r






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edited Nov 14 '18 at 9:22









Konrad Rudolph

394k1017791025




394k1017791025










asked Nov 14 '18 at 8:59









Andre Elrico

5,63311027




5,63311027












  • what if vec ended with TRUE?
    – Cath
    Nov 14 '18 at 9:05










  • good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
    – Andre Elrico
    Nov 14 '18 at 9:07




















  • what if vec ended with TRUE?
    – Cath
    Nov 14 '18 at 9:05










  • good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
    – Andre Elrico
    Nov 14 '18 at 9:07


















what if vec ended with TRUE?
– Cath
Nov 14 '18 at 9:05




what if vec ended with TRUE?
– Cath
Nov 14 '18 at 9:05












good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
– Andre Elrico
Nov 14 '18 at 9:07






good question, my solution gives back NA. If TRUE values are on the borders. That's fine.
– Andre Elrico
Nov 14 '18 at 9:07














2 Answers
2






active

oldest

votes


















3














Using findInterval



pos <- which(vec)

b <- which(!vec)



ix <- findInterval(pos, b)

cbind(pos, from = b[ix], to = b[ix + 1])

#      pos from to

# [1,]   2    1  4

# [2,]   3    1  4

# [3,]   5    4  6


If we stretch your "something like" slightly, a simple cut will do:



data.frame(pos, rng = cut(pos, b))

#   pos   rng

# 1   2 (1,4]

# 2   3 (1,4]

# 3   5 (4,6]



If the vector ends with TRUE, the findInterval solution will give NA in 'to' column. In cut, the last 'interval' is then coded as NA.






share|improve this answer























  • b[ix + 1] very clever
    – Andre Elrico
    Nov 14 '18 at 9:35



















3














You can do as if FALSE defined intervals and use data.table::foverlaps to find the right ones:



library(data.table)



# put your objects in data.tables:

f_pos_inter <- data.table(start=head(f_pos, -1), end=tail(f_pos, -1))

pos_inter <- data.table(start=pos, end=pos)



# define the keys:

setkeyv(pos_inter, c("start", "end")); setkeyv(f_pos_inter, c("start", "end"))



res <- foverlaps(pos_inter, f_pos_inter)

#   start end i.start i.end

#1:     1   4       2     2

#2:     1   4       3     3

#3:     4   6       5     5


You can further reorder the columns and keep only the ones you need:



res[, i.end:=NULL]

setcolorder(res, c(3, 1, 2))

setnames(res, "i.start", "pos")

res

#   pos start end

#1:   2     1   4

#2:   3     1   4

#3:   5     4   6


N.B: this will give NA in both columns start and end if vec ends with TRUE






share|improve this answer























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    2 Answers
    2






    active

    oldest

    votes








    2 Answers
    2






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes









    3














    Using findInterval



    pos <- which(vec)
    
b <- which(!vec)
    

    
ix <- findInterval(pos, b)
    
cbind(pos, from = b[ix], to = b[ix + 1])
    
#      pos from to
    
# [1,]   2    1  4
    
# [2,]   3    1  4
    
# [3,]   5    4  6


    If we stretch your "something like" slightly, a simple cut will do:



    data.frame(pos, rng = cut(pos, b))
    
#   pos   rng
    
# 1   2 (1,4]
    
# 2   3 (1,4]
    
# 3   5 (4,6]



    If the vector ends with TRUE, the findInterval solution will give NA in 'to' column. In cut, the last 'interval' is then coded as NA.






    share|improve this answer























    • b[ix + 1] very clever
      – Andre Elrico
      Nov 14 '18 at 9:35
















    3














    Using findInterval



    pos <- which(vec)
    
b <- which(!vec)
    

    
ix <- findInterval(pos, b)
    
cbind(pos, from = b[ix], to = b[ix + 1])
    
#      pos from to
    
# [1,]   2    1  4
    
# [2,]   3    1  4
    
# [3,]   5    4  6


    If we stretch your "something like" slightly, a simple cut will do:



    data.frame(pos, rng = cut(pos, b))
    
#   pos   rng
    
# 1   2 (1,4]
    
# 2   3 (1,4]
    
# 3   5 (4,6]



    If the vector ends with TRUE, the findInterval solution will give NA in 'to' column. In cut, the last 'interval' is then coded as NA.






    share|improve this answer























    • b[ix + 1] very clever
      – Andre Elrico
      Nov 14 '18 at 9:35














    3












    3








    3






    Using findInterval



    pos <- which(vec)
    
b <- which(!vec)
    

    
ix <- findInterval(pos, b)
    
cbind(pos, from = b[ix], to = b[ix + 1])
    
#      pos from to
    
# [1,]   2    1  4
    
# [2,]   3    1  4
    
# [3,]   5    4  6


    If we stretch your "something like" slightly, a simple cut will do:



    data.frame(pos, rng = cut(pos, b))
    
#   pos   rng
    
# 1   2 (1,4]
    
# 2   3 (1,4]
    
# 3   5 (4,6]



    If the vector ends with TRUE, the findInterval solution will give NA in 'to' column. In cut, the last 'interval' is then coded as NA.






    share|improve this answer














    Using findInterval



    pos <- which(vec)
    
b <- which(!vec)
    

    
ix <- findInterval(pos, b)
    
cbind(pos, from = b[ix], to = b[ix + 1])
    
#      pos from to
    
# [1,]   2    1  4
    
# [2,]   3    1  4
    
# [3,]   5    4  6


    If we stretch your "something like" slightly, a simple cut will do:



    data.frame(pos, rng = cut(pos, b))
    
#   pos   rng
    
# 1   2 (1,4]
    
# 2   3 (1,4]
    
# 3   5 (4,6]



    If the vector ends with TRUE, the findInterval solution will give NA in 'to' column. In cut, the last 'interval' is then coded as NA.







    share|improve this answer














    share|improve this answer



    share|improve this answer








    edited Nov 14 '18 at 10:07

























    answered Nov 14 '18 at 9:24









    Henrik

    40.8k992107




    40.8k992107












    • b[ix + 1] very clever
      – Andre Elrico
      Nov 14 '18 at 9:35


















    • b[ix + 1] very clever
      – Andre Elrico
      Nov 14 '18 at 9:35
















    b[ix + 1] very clever
    – Andre Elrico
    Nov 14 '18 at 9:35




    b[ix + 1] very clever
    – Andre Elrico
    Nov 14 '18 at 9:35













    3














    You can do as if FALSE defined intervals and use data.table::foverlaps to find the right ones:



    library(data.table)
    

    
# put your objects in data.tables:
    
f_pos_inter <- data.table(start=head(f_pos, -1), end=tail(f_pos, -1))
    
pos_inter <- data.table(start=pos, end=pos)
    

    
# define the keys:
    
setkeyv(pos_inter, c("start", "end")); setkeyv(f_pos_inter, c("start", "end"))
    

    
res <- foverlaps(pos_inter, f_pos_inter)
    
#   start end i.start i.end
    
#1:     1   4       2     2
    
#2:     1   4       3     3
    
#3:     4   6       5     5


    You can further reorder the columns and keep only the ones you need:



    res[, i.end:=NULL]
    
setcolorder(res, c(3, 1, 2))
    
setnames(res, "i.start", "pos")
    
res
    
#   pos start end
    
#1:   2     1   4
    
#2:   3     1   4
    
#3:   5     4   6


    N.B: this will give NA in both columns start and end if vec ends with TRUE






    share|improve this answer




























      3














      You can do as if FALSE defined intervals and use data.table::foverlaps to find the right ones:



      library(data.table)
      

      
# put your objects in data.tables:
      
f_pos_inter <- data.table(start=head(f_pos, -1), end=tail(f_pos, -1))
      
pos_inter <- data.table(start=pos, end=pos)
      

      
# define the keys:
      
setkeyv(pos_inter, c("start", "end")); setkeyv(f_pos_inter, c("start", "end"))
      

      
res <- foverlaps(pos_inter, f_pos_inter)
      
#   start end i.start i.end
      
#1:     1   4       2     2
      
#2:     1   4       3     3
      
#3:     4   6       5     5


      You can further reorder the columns and keep only the ones you need:



      res[, i.end:=NULL]
      
setcolorder(res, c(3, 1, 2))
      
setnames(res, "i.start", "pos")
      
res
      
#   pos start end
      
#1:   2     1   4
      
#2:   3     1   4
      
#3:   5     4   6


      N.B: this will give NA in both columns start and end if vec ends with TRUE






      share|improve this answer


























        3












        3








        3






        You can do as if FALSE defined intervals and use data.table::foverlaps to find the right ones:



        library(data.table)
        

        
# put your objects in data.tables:
        
f_pos_inter <- data.table(start=head(f_pos, -1), end=tail(f_pos, -1))
        
pos_inter <- data.table(start=pos, end=pos)
        

        
# define the keys:
        
setkeyv(pos_inter, c("start", "end")); setkeyv(f_pos_inter, c("start", "end"))
        

        
res <- foverlaps(pos_inter, f_pos_inter)
        
#   start end i.start i.end
        
#1:     1   4       2     2
        
#2:     1   4       3     3
        
#3:     4   6       5     5


        You can further reorder the columns and keep only the ones you need:



        res[, i.end:=NULL]
        
setcolorder(res, c(3, 1, 2))
        
setnames(res, "i.start", "pos")
        
res
        
#   pos start end
        
#1:   2     1   4
        
#2:   3     1   4
        
#3:   5     4   6


        N.B: this will give NA in both columns start and end if vec ends with TRUE






        share|improve this answer














        You can do as if FALSE defined intervals and use data.table::foverlaps to find the right ones:



        library(data.table)
        

        
# put your objects in data.tables:
        
f_pos_inter <- data.table(start=head(f_pos, -1), end=tail(f_pos, -1))
        
pos_inter <- data.table(start=pos, end=pos)
        

        
# define the keys:
        
setkeyv(pos_inter, c("start", "end")); setkeyv(f_pos_inter, c("start", "end"))
        

        
res <- foverlaps(pos_inter, f_pos_inter)
        
#   start end i.start i.end
        
#1:     1   4       2     2
        
#2:     1   4       3     3
        
#3:     4   6       5     5


        You can further reorder the columns and keep only the ones you need:



        res[, i.end:=NULL]
        
setcolorder(res, c(3, 1, 2))
        
setnames(res, "i.start", "pos")
        
res
        
#   pos start end
        
#1:   2     1   4
        
#2:   3     1   4
        
#3:   5     4   6


        N.B: this will give NA in both columns start and end if vec ends with TRUE







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 14 '18 at 9:19

























        answered Nov 14 '18 at 9:10









        Cath

        19.7k43464




        19.7k43464






























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