[R] help with recursive function
Eric Berger
ericjberger at gmail.com
Thu Dec 14 17:28:41 CET 2017
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 <ericjberger at 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.dighe at 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$norm_max <- round(apply(dat2[, grep("lp_norm",
>> names(dat2))],
>>
>> 1, function(x) {
>>
>> max(abs(x), na.rm = TRUE)
>>
>> }), 3)
>>
>> data1 <- dat2 %>% gather(key, value, -uniqueid, -norm_max,
>>
>> -norm_sd) %>% separate(key, c("field_rep", "treatment"),
>>
>> "\\.") %>% spread(treatment, value) %>% mutate(outlier = NA)
>>
>> stopifnot(!(any(data1$norm_sd >= 1)))
>>
>> if (!(any(data1$norm_sd >= 1))) {
>>
>> df1 <- dat1
>>
>> return(df1)
>>
>> }
>>
>> else {
>>
>> df2 <- recursive_funlp()
>>
>> return(df2)
>>
>> }
>>
>> }
>>
>> df3 <- recursive_funlp(dataset = dat1, func = funlp2)
>>
>> df3
>>
>> }
>>
>>
>>
>>
>>
>> *From:* DIGHE, NILESH [AG/2362]
>> *Sent:* Thursday, December 14, 2017 9:01 AM
>> *To:* 'Eric Berger' <ericjberger at gmail.com>
>> *Cc:* r-help <r-help at r-project.org>
>> *Subject:* RE: [R] help with recursive function
>>
>>
>>
>> Eric: Thanks for taking time to look into my problem. Despite of making
>> the change you suggested, I am still getting the same error. I am
>> wondering if the logic I am using in the stopifnot and if functions is a
>> problem.
>>
>> I like the recursive function to stop whenever the norm_sd column has
>> zero values that are above or equal to 1. Below is the calclp function
>> after the changes you suggested.
>>
>> Thanks. Nilesh
>>
>>
>>
>> dput(calclp)
>>
>> function (dataset)
>>
>> {
>>
>> dat1 <- funlp1(dataset)
>>
>> recursive_funlp <- function(dataset = dat1, func = funlp2) {
>>
>> dat2 <- dataset %>% select(uniqueid, field_rep, lp) %>%
>>
>> mutate(field_rep = paste(field_rep, "lp", sep = ".")) %>%
>>
>> spread(key = field_rep, value = lp) %>% mutate_at(.vars =
>> grep("_",
>>
>> names(.)), funs(norm = round(scale(.), 3)))
>>
>> dat2$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$norm_sd >= 1))) {
>>
>> df1 <- dat1
>>
>> return(df1)
>>
>> }
>>
>> else {
>>
>> df2 <- recursive_funlp()
>>
>> return(df2)
>>
>> }
>>
>> }
>>
>> df3 <- recursive_funlp(dataset = dat1, func = funlp2)
>>
>> df3
>>
>> }
>>
>>
>>
>>
>>
>> *From:* Eric Berger [mailto:ericjberger at gmail.com <ericjberger at gmail.com>]
>>
>> *Sent:* Thursday, December 14, 2017 8:17 AM
>> *To:* DIGHE, NILESH [AG/2362] <nilesh.dighe at monsanto.com>
>> *Cc:* r-help <r-help at r-project.org>
>> *Subject:* Re: [R] help with recursive function
>>
>>
>>
>> My own typo ... whoops ...
>>
>>
>>
>> !( any(dat2$norm_sd >= 1 ))
>>
>>
>>
>>
>>
>>
>>
>> On Thu, Dec 14, 2017 at 3:43 PM, Eric Berger <ericjberger at 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.dighe at 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$norm_max <- round(apply(dat2[, grep("lp_norm", names(dat2))],
>>
>> 1, function(x) {
>>
>> max(abs(x), na.rm = TRUE)
>>
>> }), 3)
>>
>> data1 <- dat2 %>% gather(key, value, -uniqueid, -norm_max,
>>
>> -norm_sd) %>% separate(key, c("field_rep", "treatment"),
>>
>> "\\.") %>% spread(treatment, value) %>% mutate(outlier = NA)
>>
>> df_clean <- with(data1, data1[norm_sd < 1, ])
>>
>> datD <- with(data1, data1[norm_sd >= 1, ])
>>
>> s <- split(datD, datD$uniqueid)
>>
>> sdf <- lapply(s, function(x) {
>>
>> data.frame(x, x$outlier <- ifelse(is.na(x$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$outlier <- ifelse(is.na(x$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",
>> "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01",
>> "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01",
>> "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "LM01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01",
>> "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "OL01", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1",
>> "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "SGI1", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS",
>> "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "O2LS", "B2NW", "B2NW",
>> "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "B2NW", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3",
>> "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "17C3", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1",
>> "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "WCI1", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "NY01",
>> "NY01", "NY01", "NY01", "NY01", "NY01", "NY01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND", "MAND",
>> "MAND", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP", "28EP",
>> "28EP", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01", "EX01",
>> "EX01", "EX01", "EX01", "EX01", "EX01", "EX01"), set = c("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", "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", "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",
>> "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", "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", "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
>>
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