When I run the code without stopifnot, the code takes 5 min to run and then it throws an error listed below without producing any results. Error: node stack overflow In addition: There were 50 or more warnings (use warnings() to see the first 50) Error during wrapup: node stack overflow
Thanks. Nilesh From: William Dunlap [mailto:wdun...@tibco.com] Sent: Thursday, December 14, 2017 11:26 AM To: DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com> Cc: Eric Berger <ericjber...@gmail.com>; r-help <r-help@r-project.org> Subject: Re: [R] help with recursive function Your code contains the lines stopifnot(!(any(data1$norm_sd >= 1))) if (!(any(data1$norm_sd >= 1))) { df1 <- dat1 return(df1) } stop() "throws an error", causing the current function and all functions in the call stack to abort and return nothing. It does not mean to stop now and return a result. Does the function give the correct results if you just leave out the stopifnot line? Bill Dunlap TIBCO Software wdunlap tibco.com<http://tibco.com> On Thu, Dec 14, 2017 at 9:11 AM, DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com>> wrote: Eric: I will try and see if I can figure out the issue by debugging as you suggested. I don’t know why my code after stopifnot is not getting executed where I like the code to run the funlp2 function when the if statement is TRUE but when it is false, I like it to keep running until the stopifnot condition is met. When the stopifnot condition is met, I like to get the output from if statement saved. Anyway, I will keep trying. Again, Thanks for your help! Nilesh From: Eric Berger [mailto:ericjber...@gmail.com<mailto:ericjber...@gmail.com>] Sent: Thursday, December 14, 2017 10:29 AM To: DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com>> Cc: r-help <r-help@r-project.org<mailto:r-help@r-project.org>> Subject: Re: [R] help with recursive function If you are trying to understand why the "stopifnot" condition is met you can replace it by something like: if ( any(dat2$norm_sd >= 1) ) browser() This will put you in a debugging session where you can examine your variables, e.g. > dat$norm_sd HTH, Eric On Thu, Dec 14, 2017 at 5:33 PM, Eric Berger <ericjber...@gmail.com<mailto:ericjber...@gmail.com><mailto:ericjber...@gmail.com<mailto:ericjber...@gmail.com>>> wrote: The message is coming from your stopifnot() condition being met. On Thu, Dec 14, 2017 at 5:31 PM, DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com><mailto:nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com>>> wrote: Hi, I accidently left out few lines of code from the calclp function. Updated function is pasted below. I am still getting the same error “Error: !(any(data1$norm_sd >= 1)) is not TRUE“ I would appreciate any help. Nilesh dput(calclp) function (dataset) { dat1 <- funlp1(dataset) recursive_funlp <- function(dataset = dat1, func = funlp2) { dat2 <- dataset %>% select(uniqueid, field_rep, lp) %>% mutate(field_rep = paste(field_rep, "lp", sep = ".")) %>% spread(key = field_rep, value = lp) %>% mutate_at(.vars = grep("_", names(.)), funs(norm = round(scale(.), 3))) dat2$norm_sd <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, sd, na.rm = TRUE), 3) dat2$norm_max <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, function(x) { max(abs(x), na.rm = TRUE) }), 3) data1 <- dat2 %>% gather(key, value, -uniqueid, -norm_max, -norm_sd) %>% separate(key, c("field_rep", "treatment"), "\\.<file://.><file://.%3cfile:/.%3e>") %>% spread(treatment, value) %>% mutate(outlier = NA) stopifnot(!(any(data1$norm_sd >= 1))) if (!(any(data1$norm_sd >= 1))) { df1 <- dat1 return(df1) } else { df2 <- recursive_funlp() return(df2) } } df3 <- recursive_funlp(dataset = dat1, func = funlp2) df3 } From: DIGHE, NILESH [AG/2362] Sent: Thursday, December 14, 2017 9:01 AM To: 'Eric Berger' <ericjber...@gmail.com<mailto:ericjber...@gmail.com><mailto:ericjber...@gmail.com<mailto:ericjber...@gmail.com>>> Cc: r-help <r-help@r-project.org<mailto:r-help@r-project.org><mailto:r-help@r-project.org<mailto:r-help@r-project.org>>> Subject: RE: [R] help with recursive function Eric: Thanks for taking time to look into my problem. Despite of making the change you suggested, I am still getting the same error. I am wondering if the logic I am using in the stopifnot and if functions is a problem. I like the recursive function to stop whenever the norm_sd column has zero values that are above or equal to 1. Below is the calclp function after the changes you suggested. Thanks. Nilesh dput(calclp) function (dataset) { dat1 <- funlp1(dataset) recursive_funlp <- function(dataset = dat1, func = funlp2) { dat2 <- dataset %>% select(uniqueid, field_rep, lp) %>% mutate(field_rep = paste(field_rep, "lp", sep = ".")) %>% spread(key = field_rep, value = lp) %>% mutate_at(.vars = grep("_", names(.)), funs(norm = round(scale(.), 3))) dat2$norm_sd <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, sd, na.rm = TRUE), 3) dat2$norm_max <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, function(x) { max(abs(x), na.rm = TRUE) }), 3) stopifnot(!(any(dat2$norm_sd >= 1))) if (!(any(dat2$norm_sd >= 1))) { df1 <- dat1 return(df1) } else { df2 <- recursive_funlp() return(df2) } } df3 <- recursive_funlp(dataset = dat1, func = funlp2) df3 } From: Eric Berger [mailto:ericjber...@gmail.com<mailto:ericjber...@gmail.com>] Sent: Thursday, December 14, 2017 8:17 AM To: DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com><mailto:nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com>>> Cc: r-help <r-help@r-project.org<mailto:r-help@r-project.org><mailto:r-help@r-project.org<mailto:r-help@r-project.org>>> Subject: Re: [R] help with recursive function My own typo ... whoops ... !( any(dat2$norm_sd >= 1 )) On Thu, Dec 14, 2017 at 3:43 PM, Eric Berger <ericjber...@gmail.com<mailto:ericjber...@gmail.com><mailto:ericjber...@gmail.com<mailto:ericjber...@gmail.com>>> wrote: You seem to have a typo at this expression (and some others like it) Namely, you write any(!dat2$norm_sd) >= 1 when you possibly meant to write !( any(dat2$norm_sd) >= 1 ) i.e. I think your ! seems to be in the wrong place. HTH, Eric On Thu, Dec 14, 2017 at 3:26 PM, DIGHE, NILESH [AG/2362] <nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com><mailto:nilesh.di...@monsanto.com<mailto:nilesh.di...@monsanto.com>>> wrote: Hi, I need some help with running a recursive function. I like to run funlp2 recursively. When I try to run recursive function in another function named "calclp" I get this "Error: any(!dat2$norm_sd) >= 1 is not TRUE". I have never built a recursive function before so having trouble executing it in this case. I would appreciate any help or guidance to resolve this issue. Please see my data and the three functions that I am using below. Please note that calclp is the function I am running and the other two functions are within this calclp function. # code: Test<- calclp(dataset = dat) # calclp function calclp<- function (dataset) { dat1 <- funlp1(dataset) recursive_funlp <- function(dataset = dat1, func = funlp2) { dat2 <- dataset %>% select(uniqueid, field_rep, lp) %>% mutate(field_rep = paste(field_rep, "lp", sep = ".")) %>% spread(key = field_rep, value = lp) %>% mutate_at(.vars = grep("_", names(.)), funs(norm = round(scale(.), 3))) dat2$norm_sd <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, sd, na.rm = TRUE), 3) dat2$norm_max <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, function(x) { max(abs(x), na.rm = TRUE) }), 3) stopifnot(any(!dat2$norm_sd) >= 1) if (any(!dat2$norm_sd) >= 1) { df1 <- dat1 return(df1) } else { df2 <- recursive_funlp() return(df2) } } df3 <- recursive_funlp(dataset = dat1, func = funlp2) df3 } # funlp1 function funlp1<- function (dataset) { dat2 <- dataset %>% select(field, set, ent_num, rep_num, lp) %>% unite(uniqueid, set, ent_num, sep = ".") %>% unite(field_rep, field, rep_num) %>% mutate(field_rep = paste(field_rep, "lp", sep = ".")) %>% spread(key = field_rep, value = lp) %>% mutate_at(.vars = grep("_", names(.)), funs(norm = round(scale(.), 3))) dat2$norm_sd <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, sd, na.rm = TRUE), 3) dat2$norm_max <- round(apply(dat2[, grep("lp_norm", names(dat2))], 1, function(x) { max(abs(x), na.rm = TRUE) }), 3) data1 <- dat2 %>% gather(key, value, -uniqueid, -norm_max, -norm_sd) %>% separate(key, c("field_rep", "treatment"), "\\.<file://.><file://.%3cfile:/.%3e>") %>% spread(treatment, value) %>% mutate(outlier = NA) df_clean <- with(data1, data1[norm_sd < 1, ]) datD <- with(data1, data1[norm_sd >= 1, ]) s <- split(datD, datD$uniqueid) sdf <- lapply(s, function(x) { data.frame(x, x$outlier <- ifelse(is.na<http://is.na><http://is.na>(x$lp_norm), NA, ifelse(abs(x$lp_norm) == x$norm_max, "yes", "no")), x$lp <- with(x, ifelse(outlier == "yes", NA, lp))) x }) sdf2 <- bind_rows(sdf) all_dat <- bind_rows(df_clean, sdf2) all_dat } # funlp2 function funlp2<-function (dataset) { data1 <- dataset df_clean <- with(data1, data1[norm_sd < 1, ]) datD <- with(data1, data1[norm_sd >= 1, ]) s <- split(datD, datD$uniqueid) sdf <- lapply(s, function(x) { data.frame(x, x$outlier <- ifelse(is.na<http://is.na><http://is.na>(x$lp_norm), NA, ifelse(abs(x$lp_norm) == x$norm_max, "yes", "no")), x$lp <- with(x, ifelse(outlier == "yes", NA, lp))) x }) sdf2 <- bind_rows(sdf) all_dat <- bind_rows(df_clean, sdf2) all_dat } # dataset dput(dat) structure(list(field = c("LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", 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"seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta", "seta"), ent_num = c(23L, 14L, 43L, 30L, 44L, 60L, 17L, 34L, 41L, 40L, 9L, 36L, 38L, 19L, 61L, 51L, 45L, 42L, 3L, 39L, 21L, 11L, 12L, 7L, 35L, 5L, 70L, 47L, 28L, 16L, 72L, 13L, 49L, 67L, 56L, 32L, 27L, 46L, 24L, 63L, 15L, 66L, 26L, 29L, 48L, 1L, 54L, 37L, 2L, 50L, 52L, 31L, 33L, 25L, 6L, 69L, 53L, 10L, 18L, 55L, 59L, 4L, 58L, 22L, 20L, 64L, 71L, 57L, 11L, 17L, 43L, 13L, 1L, 16L, 34L, 47L, 52L, 72L, 59L, 22L, 54L, 18L, 25L, 61L, 56L, 41L, 27L, 14L, 49L, 19L, 29L, 31L, 64L, 6L, 53L, 35L, 37L, 67L, 39L, 51L, 40L, 15L, 69L, 60L, 38L, 4L, 23L, 3L, 48L, 32L, 42L, 24L, 28L, 33L, 57L, 8L, 21L, 46L, 7L, 30L, 45L, 2L, 63L, 36L, 68L, 20L, 66L, 70L, 58L, 5L, 10L, 12L, 62L, 50L, 71L, 9L, 55L, 26L, 44L, 65L, 14L, 63L, 46L, 58L, 62L, 19L, 59L, 2L, 5L, 6L, 40L, 21L, 44L, 37L, 55L, 35L, 71L, 56L, 10L, 36L, 53L, 25L, 61L, 12L, 26L, 23L, 4L, 13L, 28L, 38L, 57L, 54L, 72L, 48L, 66L, 9L, 70L, 15L, 39L, 60L, 17L, 34L, 51L, 67L, 42L, 49L, 31L, 30L, 3L, 18L, 65L, 32L, 27L, 52L, 22L, 11L, 47L, 64L, 8L, 43L, 41L, 16L, 20L, 33L, 7L, 50L, 68L, 24L, 1L, 69L, 45L, 29L, 37L, 30L, 55L, 54L, 43L, 32L, 21L, 27L, 33L, 40L, 67L, 57L, 68L, 31L, 17L, 13L, 6L, 62L, 19L, 22L, 3L, 10L, 44L, 34L, 69L, 70L, 4L, 1L, 25L, 11L, 51L, 5L, 63L, 71L, 12L, 38L, 58L, 39L, 49L, 59L, 56L, 65L, 2L, 64L, 8L, 35L, 46L, 45L, 29L, 53L, 36L, 42L, 23L, 18L, 50L, 26L, 14L, 48L, 66L, 20L, 24L, 7L, 15L, 53L, 22L, 39L, 20L, 60L, 59L, 43L, 19L, 41L, 6L, 62L, 1L, 55L, 34L, 50L, 38L, 40L, 44L, 4L, 46L, 29L, 65L, 57L, 48L, 33L, 69L, 14L, 35L, 67L, 72L, 54L, 3L, 49L, 2L, 12L, 18L, 30L, 10L, 70L, 31L, 15L, 63L, 71L, 21L, 45L, 28L, 56L, 27L, 64L, 61L, 51L, 5L, 24L, 68L, 25L, 66L, 16L, 36L, 58L, 37L, 52L, 26L, 9L, 42L, 7L, 11L, 8L, 32L, 23L, 13L, 47L, 17L, 61L, 72L, 47L, 60L, 16L, 9L, 28L, 52L, 41L, 1L, 61L, 6L, 23L, 58L, 63L, 25L, 28L, 30L, 36L, 62L, 9L, 32L, 19L, 31L, 56L, 45L, 2L, 22L, 27L, 40L, 14L, 11L, 50L, 13L, 70L, 20L, 64L, 39L, 26L, 21L, 43L, 29L, 35L, 54L, 52L, 37L, 17L, 16L, 72L, 48L, 12L, 18L, 44L, 42L, 49L, 68L, 5L, 55L, 69L, 51L, 66L, 59L, 53L, 15L, 71L, 41L, 57L, 4L, 60L, 8L, 7L, 33L, 34L, 24L, 10L, 67L, 47L, 38L, 3L, 65L, 46L, 20L, 34L, 71L, 1L, 33L, 57L, 13L, 21L, 66L, 29L, 3L, 61L, 69L, 24L, 62L, 39L, 49L, 47L, 31L, 53L, 52L, 43L, 17L, 7L, 8L, 12L, 60L, 63L, 50L, 2L, 51L, 46L, 10L, 23L, 48L, 11L, 26L, 40L, 70L, 42L, 59L, 15L, 56L, 58L, 27L, 6L, 35L, 4L, 37L, 5L, 65L, 44L, 28L, 14L, 32L, 36L, 45L, 9L, 18L, 55L, 68L, 30L, 54L, 41L, 25L, 22L, 38L, 16L, 67L, 64L, 19L, 72L, 68L, 28L, 33L, 15L, 51L, 4L, 47L, 36L, 8L, 57L, 48L, 1L, 52L, 39L, 32L, 50L, 13L, 30L, 63L, 2L, 9L, 62L, 22L, 6L, 61L, 16L, 53L, 38L, 37L, 20L, 69L, 44L, 56L, 29L, 26L, 14L, 17L, 46L, 66L, 58L, 42L, 60L, 19L, 45L, 3L, 59L, 70L, 31L, 24L, 55L, 40L, 43L, 25L, 65L, 12L, 67L, 21L, 7L, 27L, 49L, 72L, 54L, 41L, 23L, 34L, 5L, 64L, 35L, 18L, 71L, 11L, 24L, 19L, 38L, 14L, 4L, 56L, 5L, 54L, 34L, 64L, 55L, 33L, 69L, 71L, 52L, 61L, 48L, 23L, 43L, 41L, 20L, 39L, 11L, 63L, 36L, 22L, 9L, 25L, 27L, 51L, 53L, 37L, 57L, 13L, 18L, 64L, 22L, 53L, 16L, 5L, 28L, 60L, 31L, 11L, 29L, 45L, 59L, 72L, 49L, 67L, 13L, 20L, 3L, 42L, 44L, 69L, 33L, 38L, 15L, 70L, 35L, 48L, 26L, 56L, 19L, 39L, 43L, 40L, 14L, 2L, 68L, 51L, 12L, 47L, 10L, 55L, 23L, 4L, 71L, 41L, 50L, 7L, 24L, 61L, 27L, 54L, 46L, 58L, 37L, 66L, 57L, 1L, 36L, 32L, 18L, 62L, 9L, 30L, 21L, 6L, 52L, 8L, 65L, 17L, 25L, 63L, 34L, 65L, 22L, 56L, 9L, 7L, 11L, 31L, 4L, 63L, 29L, 61L, 54L, 12L, 62L, 59L, 5L, 23L, 53L, 36L, 24L, 35L, 66L, 49L, 72L, 18L, 70L, 32L, 43L, 20L, 45L, 34L, 46L, 28L, 6L, 44L, 71L, 39L, 13L, 27L, 1L, 58L, 30L, 68L, 17L, 33L, 26L, 57L, 15L, 21L, 52L, 48L, 42L, 16L, 40L, 38L, 8L, 69L, 2L, 51L, 67L, 55L, 64L, 47L, 60L, 19L, 41L, 50L, 3L, 14L, 25L, 10L, 37L, 6L, 15L, 45L, 49L, 8L, 17L, 50L, 16L, 58L, 72L, 26L, 60L, 7L, 32L, 1L, 46L, 66L, 68L, 62L, 47L, 35L, 70L, 10L, 31L, 65L, 2L, 3L, 21L, 12L, 30L, 40L, 28L, 59L, 42L, 67L, 44L, 29L ), rep_num = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), lp = c(NA, 41.64, 38.8, 44.45, 40.54, 38.54, 41.94, 39.6, 37.39, 40.95, 38.45, 43.47, 41.66, 40.91, 42.68, 43.12, 38.22, 40.95, 46.24, 42.95, 38.95, 39.88, 40.57, 40.13, 38.57, 45.45, 40.78, 43.52, 39.75, 39.93, 40.35, 37.6, 37.7, 43.05, 43.32, 41.31, 39.03, 42.5, 43.18, 41.32, 39.58, 40.62, 39.64, 39.85, 38.75, 40.18, 41.44, 40.5, 40.87, 40.75, 38.37, 40.26, 35.11, 40.89, 41.67, 38.87, 37.32, 35.85, 38.25, 42.21, 43.15, 38.69, 38.8, 38.77, 37.98, 39.8, 33.37, 40.09, 42.87, 44.07, 43.78, 42.47, 42.8, 41.1, 41.17, 44.07, 44.24, 43.16, 46.12, 42.64, 43.92, 42.16, 43.69, 42.89, 42.63, 43.58, 44.4, 43.17, 43.3, 42.5, 42.6, 44.05, 44.63, 43.09, 45.17, 45.17, 42.78, 42.38, 45.76, 42.16, 44.22, 43.67, 40.45, 41.95, 42.49, 41.98, 45.15, 46.01, 38.51, 43.08, 45.19, 44.53, 43.14, 39.93, 46.84, 43.59, 41.68, 43.7, 44.63, 44.02, 42.07, 43.88, 43.2, 46.2, 40.84, 39.14, 43.89, 42.58, 41.53, 45.32, 39.56, 43.77, 45.45, 45.16, 43.4, 40.08, 42.27, 43.74, 43.77, 41.31, 41.38, 45.01, 45.76, 40.4, 48.39, 46.27, 15.44, 44.76, 47.45, 44.87, 46.8, 41.83, 43.03, 43.96, 42.51, 45.06, 45.55, 44.9, 42.47, 44.9, 45, 44.77, 43.79, 44.26, 44.57, 44.4, 43.42, 42.31, 47.18, 43.83, 45.72, 44.83, 44.96, 40.28, 42.85, 41.23, 45.23, 47.09, 43.61, 42.69, 46.27, 45.16, 44.14, 43.34, 45.97, 43.81, 43.01, 39.82, 45.91, 45.97, 43.61, 45.12, 46.37, 42.67, 42.47, 45.86, 44.19, 44.46, 42.64, 43.95, 44.93, 40.33, 42.75, 39.92, 44.17, 44.49, 41.51, 42.43, 44.14, 40.5, 41.29, 44.89, 37.98, 39.02, 39.62, 42.13, 39.03, 44.16, 39.15, 41.49, 42.63, 40.11, 39.97, 42.85, 35.98, 39.45, 40.99, 42.44, 42.11, 37.36, 40.63, 40.69, 43.57, 39.04, 39.3, 42.19, 36.88, 40.39, 37.78, 38.6, 40.2, 40.98, 36.58, 43.59, 42.49, 39.96, 39.84, 40.43, 38.94, 42.72, 39.43, 42.13, 40.36, 40.58, 40.01, 42.17, 42.17, 41.35, 43.27, 40.15, 39.76, 40.94, 40.87, 42.32, 41.81, 41.97, 43.72, 41.32, 40.83, 37.64, 41.03, 38.98, 40.61, 41.17, 41.96, 40.07, 38.48, 42.85, 38.68, 39.09, 42.16, 38.14, 37.99, 41.06, 37.4, 41.88, 39.35, 39.73, 38.38, 41.34, 40.67, 40.89, 39.28, 37.59, 39.3, 39.72, 40.79, 39.42, 34.5, 37.61, 37.76, 40.24, 41.17, 41.24, 42.14, 42.53, 39.71, 39.44, 40.19, 42.51, 40.15, 36.26, 37.48, 40.43, 37.5, 42.11, 41.44, 40.29, 39.75, 37.58, 41.25, 40.39, 41.63, 42.18, 43.71, 38.69, 43.47, 41.98, 35.51, 42.22, 38.51, 40.17, 39.4, 39.54, 41.7, 40.93, 40.01, 35.97, 41.44, 41.89, 40.9, 39.95, 40.69, 43.18, 37.03, 39.91, 36.75, 42.75, 41.61, 42.6, 38.55, 42.84, 38.41, 42.55, 41.44, 41.03, 40, 41.35, 42.18, 42.66, 40.06, 42.48, 41.33, 41.92, 40.88, 40.99, 42.78, 38.26, 40.81, 39.95, 37.89, 40.81, 38.33, 39.33, 39.67, 40.12, 41.75, 39.81, 41.92, 44.59, 37.8, 40.54, 40.49, 41.82, 42.13, 39.93, 39.94, 42.54, 41.74, 43.06, 41.72, 41.27, 39.42, 42.07, 40.06, 42.1, 38.91, 39.28, 42.94, 39.94, 41.86, 38.56, 38.15, 41.47, 42.34, 38.14, 40.19, 40.2, 43.01, 42.35, 40.89, 41.44, 42.89, 44.49, 39.1, 38.42, 37.44, 43.28, 37.96, 40.56, 41.53, 41.59, 41.45, 42.55, 40.6, 44.04, 39.31, 41.08, 37.14, 40.03, 41.49, 40.82, 38.47, 43.43, 38.82, 40.4, 41.09, 42.26, 41.85, 41.13, 37.27, 41.97, 45.24, 43.35, 40.53, 43.14, 39.71, 42.77, 42.2, 42.13, 41.91, 42.59, 41.99, 42.11, 40.43, 40.02, 43.53, 43.01, 39.55, 43.2, 39.95, 42.51, 42, 42.26, 42.39, 42.64, 39.9, 41.89, 43.05, 41.02, 41.95, 39.92, 43.42, 44.01, 42.6, 40.84, 42.86, 44.31, 42.24, 41.25, 42.38, 44.99, 41.24, 43.97, 41.12, 37.88, 41.53, 41.56, 39.18, 40.83, 42.96, 41.92, 43.86, 42.48, 42.65, 43.3, 41.99, 42.51, 40.65, 42.77, 34.71, 40.97, 38.15, 39.76, 36.74, 37.95, 39.17, 38.22, 39.31, 43.57, 37.21, 39.35, 42.37, 42.01, 42.39, 43.21, 36.91, 36.69, 41.07, 41.91, 34.63, 40.61, 36.23, 38.12, 40.76, 39.14, 41.81, 39.14, 41.04, 37.32, 40.83, 40.81, 38.29, 39.61, 40.96, 40.71, 40.47, 38.64, 39.76, 38.19, 39.05, 38.04, 41.14, 38.35, 42.3, 34.44, 40.93, 39.3, 41.44, 38.3, 42.74, 36.66, 40.02, 36.62, 40.48, 41.72, 41.23, 41.81, 42.07, 40.22, 37.83, 36.54, 37.77, 40.49, 38.65, 43.2, 43.32, 40.67, 41.95, 36.11, 39.28, 42.38, 40.35, 40.3, 43.48, 40.55, 40.54, 44.03, 41.94, 37.97, 41.98, 41.53, 38.19, 38.66, 41.18, 41.95, 42.53, 38.7, 44.55, 42.39, 41.55, 38.46, 42.27, 42.19, 41.95, 41.81, 39.81, 38.12, 42.94, 42.99, 38.85, 41.26, 43.13, 44.21, 38.54, 44.02, 43.46, 41.64, 42.06, 42.11, 42.34, 41.86, 37.91, 40.89, 40.5, 39.54, 37.87, 40.86, 41.36, 41.77, 42.03, 39.15, 40.04, 44.11, 41.34, 42.97, 38.42, 37.28, 41.04, 41.48, 38.82, 41.94, 37.95, 40.9, 40.39, 40.31, 43.19, 41.22, 41.49, 41.25, 40.07, 36.7, 39.97, 39.99, 41.7, 37.09, 42.58, 43.01, 37.7, 41.81, 39.99, 42.95, 43.19, 42.69, 41.5, 40.64, 43.24, 41.14, 41.21, 41.29, 41.43, 44.21, 38.52, 42.54, 40.54, 42.49, 43.2, 38.12, 40.08, 39.02, 41.45, 42.33, 41.11, 38.93, 41.63, 44.22, 41.41, 39.08, 40.9, 41.1, 43.88, 40.96, 46.75, 47.54, 40.35, 41.97, 44.94, 44.91, 44.66, 44.5, 44.4, 46.4, 47.97, 46.05, 45.57, 42.83, 41.48, 47.48, 45.43, 41.98, 43.14, 45.6, 44.78, 45.45, 45.69, 44.82, 44.24, 41.14, 43.14, 46.61, 43.92, 43.56, 43.68, 45.37, 45.15, 40.76, 43.78, 44.67, 41.36, 41.4, 40.97, 41.87, 39.83, 43.8, 48.36, 44.28, 43.29, 44.69, 43.26, 43.35, 44.34, 45.08, 42.26, 39.7, 42.4, 44.03, 43.22, 42.71, 45.89, 44.89, 44.81, 42.59, 40.85, 43.82, 44.85, 47.47, 43.64, 42.65, 45.67, 43.24, 42.33, 40.61, 38.3, 39.84, 41.08, 42.33, 44.44, 40.85, 39.58, 42.55, 41.75, 39.44, 41.79, 39.31, 41.34, 42.76, 40.79, 37.31, 42.85, 42.88, 42.01, 44.63, 38.85, 41.13, 40.43, 41.34, 43.14, 40.58, 42.21, 38.94, 44.88, 42.33, 42.61, 41.88, 41.13, 41.83, 42.8)), .Names = c("field", "set", "ent_num", "rep_num", "lp"), class = "data.frame", row.names = c(NA, -787L)) # session info R version 3.4.1 (2017-06-30) Platform: i386-w64-mingw32/i386 (32-bit) Running under: Windows 7 x64 (build 7601) Service Pack 1 Matrix products: default locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] bindrcpp_0.2 tidyr_0.6.3 dplyr_0.7.4 loaded via a namespace (and not attached): [1] compiler_3.4.1 magrittr_1.5 assertthat_0.2.0 R6_2.2.2 tools_3.4.1 [6] glue_1.1.1 tibble_1.3.3 Rcpp_0.12.11 stringi_1.1.5 pkgconfig_2.0.1 [11] rlang_0.1.2 bindr_0.1 This email and any attachments were sent from a Monsanto email account and may contain confidential and/or privileged information. 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All emails and attachments sent to or from Monsanto email accounts may be subject to monitoring, reading, and archiving by Monsanto, including its affiliates and subsidiaries, as permitted by applicable law. Thank you. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org<mailto:R-help@r-project.org> mailing list -- To UNSUBSCRIBE and more, see 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. This email and any attachments were sent from a Monsanto email account and may contain confidential and/or privileged information. If you are not the intended recipient, please contact the sender and delete this email and any attachments immediately. Any unauthorized use, including disclosing, printing, storing, copying or distributing this email, is prohibited. All emails and attachments sent to or from Monsanto email accounts may be subject to monitoring, reading, and archiving by Monsanto, including its affiliates and subsidiaries, as permitted by applicable law. Thank you. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
