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| [[Category:R tool]]
| | #REDIRECT [[OpasnetUtils/Interpret]] |
| {{method|moderator=Jouni|stub=Yes}}
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| '''input.interp''' is an R function that interprets model inputs from a user-friendly format into explicit and exact mathematical format. The purpose is to make it easy for a user to give input without a need to worry about technical modelling details.
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| ==Question==
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| What should be a list of important user input formats, and how should they be interpreted?
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| ==Answer==
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| The basic feature is that if a text string can be converted to a meaningful numeric object, it will be. This function can be used when data is downloaded from [[Opasnet Base]]: if Result.Text contains this kind of numeric information, it is converted to numbers and fused with Result.
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| n is the number of iterations in the model. # is any numeric character in the text string.
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| {| {{prettytable}}
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| !Example!!Regular expression!!Interpretation !! Output in R
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| |----
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| | 12 000 ||# # || 12000. Text is interpreted as number if space removal makes it a number. || as.numeric(gsub(" ", "", Result.text))
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| |----
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| | 12,345 ||#,# || 12.345. Commas are interpreted as decimal points. || as.numeric(gsub(",", ".", Result.text)) # Note! Do not use comma as a thousand separator!
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| |----
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| | -14,23 || -# || -14.23. Minus in the beginning of entry is interpreted as minus, not a sign for a range. ||
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| |----
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| | 50 - 125 ||# - # ||Uniform distribution between 50 and 125 || data.frame(iter=1:n, result=runif(n,50,125))
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| |----
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| | -12 345 - -23,56 || || Uniform distribution between -12345 and -23.56. ||
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| |----
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| | 1 - 50 ||# - # || Loguniform distribution between 1 and 50 (Lognormality is assumed if the ratio of upper to lower is => 30) ||
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| |----
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| | 3.1 ± 1.2 or 3.1 +- 1.2||# ± # or # +- # ||Normal distribution with mean 3.1 and SD 1.2 || data.frame(iter=1:n, result=rnorm(n,3.1,1.2))
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| |----
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| | 2.4 (1.8 - 3.0) || # (# - #) ||Normal distribution with mean 2.4 and 95 % confidence interval from 1.8 to 3.0 || data.frame(iter=1:n, result=rnorm(n,2.4,(3.0-1.8)/2/1.96))
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| |----
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| | 2.4 (2.0 - 3.2) || # (# - #) ||Lognormal distribution with mean 2.4 and 95 % confidence interval from 2.0 to 3.0. Lognormality is assumed if the difference from mean to upper limit is => 50 % greater than from mean to lower limit.||
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| |----
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| | 24 - 35 (odds 5:1) || # - # (odds #:#) || Odds is five to one that the truth is between 24 and 35. How to calculate this, I don't know yet, but there must be a prior.|| {{attack|# |I am not sure whether this is actually needed. Who expresses uncertainties in this way?|--[[User:Jouni|Jouni]] 14:00, 28 December 2011 (EET)}}
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| |----
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| | 2;4;7 || || Each entry (2, 4, and 7 in this case) are equally likely to occur. Entries can also be text.||
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| |----
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| | * (in index, or explanatory, columns) || || The result applies to all locations of this index.|| With merge() function, this column is not used as a criterion when these rows are merged.
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| |}
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| How to actually make this happen in R?
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| # Make a temporary result ''temp'' by removing all spaces from Result.Text. Columns: ''Indices,Result.Result.Text,temp'' (Indices contains all explanatory columns.)
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| # Replace all "," with "."
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| # Check if there are parentheses "()". If yes, assume that they contain 95 % CI.
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| # Check if there are ranges "#-#".
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| # Divide the rows of the data.frame into two new data.frames with the same list of columns (''Indices,Result'').
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| #* If temp is a syntactically correct distribution, take the row to data.frame A and replace ''Result'' with ''temp''.
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| #* Otherwise, take the row to data.frame B and replace ''Result'' with ''Result.Text'' if that is not NA.
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| # Create a new data.frame with index Iter = 1:n.
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| # Make a random sample from each probability distribution in data.frame A using Iter.
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| # Merge the data.frame B with Iter.
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| # Join data.frames A and B with rbind(). Columns: ''Iter,Index,Result''.
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| <rcode>
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| lmean <- function(parmean, parsd) {return(log(parmean)-log(1+(parsd^2)/(parmean^2))/2)}
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| lsd <- function(parmean, parsd) {return(log(1+(parsd^2)/(parmean^2)))}
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| input.interp <- function(res.char, n = 1000) {
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| res.char <- gsub(" ", "", res.char)
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| res.char <- gsub(",", ".", res.char)
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| plusminus <- gregexpr(paste("\\+-|", rawToChar(as.raw(177)), sep = ""), res.char) # saattaa osoittautua ongelmaksi enkoodauksen vuoksi
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| plusminus.length <- sapply(plusminus, length)
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| plusminus.exists <- unlist(plusminus)[cumsum(c(0, plusminus.length[-length(plusminus.length)])) + 1] > 0
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| minus <- gregexpr("-", res.char)
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| minus.length <- sapply(minus, length)
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| minus.exists <- unlist(minus)[cumsum(c(0, minus.length[-length(minus.length)])) + 1] > 0
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| brackets <- gregexpr("\\(.*\\)", res.char) # matches for brackets "(...)"
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| brackets.length <- as.numeric(unlist(lapply(brackets, attributes)))
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| brackets.pos <- unlist(brackets)
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| out <- list()
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| for(i in 1:length(res.char)) {
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| if(brackets.pos[i] >= 0) {
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| minus.relevant <- unlist(minus)[(cumsum(c(0, minus.length)) + 1)[i]:cumsum(minus.length)[i]] # Meni hieman monimutkaiseksi ylla olevan vektorisoinnin vuoksi
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| n.minus.inside.brackets <- sum(minus.relevant > brackets.pos[i] & minus.relevant < brackets.pos[i] + brackets.length[i])
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| imean <- as.numeric(substr(res.char[i], 1, brackets.pos[i] - 1))
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| if(n.minus.inside.brackets == 1) {
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| ici <- c(as.numeric(substr(res.char[i], brackets.pos[i] + 1, minus.relevant[minus.relevant > brackets.pos[i]] - 1)), as.numeric(substr(res.char[i],
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| minus.relevant[minus.relevant > brackets.pos[i]] + 1, brackets.pos[i] + brackets.length[i] - 2)))
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| isd <- sum(abs(ici - imean) / 2) / qnorm(0.975)
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| if((ici[2] - imean) / (ici[1] - imean) < 1.5) {
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| out[[i]] <- rnorm(n, imean, isd)
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| } else {
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| out[[i]] <- rlnorm(n, lmean(imean, isd), lsd(imean, isd)) # menee vaarin koska isd on laskettu normaalijakaumalle
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| }
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| } else
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| if(n.minus.inside.brackets == 2|n.minus.inside.brackets == 3) {
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| # consecutive.minuses <- minus.relevant + 1 == c(minus.relevant[2:length(minus.relevant)], 0) # turha jos oletetaan etta ensimmainen luku sulkujen sisalla on aina pienempi
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| ici <- c(as.numeric(substr(res.char[i], brackets.pos[i] + 1, minus.relevant[minus.relevant > brackets.pos[i]][2] - 1)), as.numeric(substr(res.char[i],
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| minus.relevant[minus.relevant > brackets.pos[i]][2] + 1, brackets.pos[i] + brackets.length[i] - 2)))
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| isd <- sum(abs(ici - imean) / 2) / qnorm(0.975)
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| out[[i]] <- rnorm(n, imean, isd)
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| } else out[[i]] <- paste("Unable to interpret \"", res.char[i], "\"", sep = "")
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| } else {
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| if(minus.exists[i]) {
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| minus.relevant <- unlist(minus)[(cumsum(c(0, minus.length)) + 1)[i]:cumsum(minus.length)[i]]
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| if(length(minus.relevant)==1) {if(as.numeric(substr(res.char[i], 1, minus.relevant - 1)) / as.numeric(substr(res.char[i], minus.relevant + 1, nchar(res.char[i]))) >= 1/100) {
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| out[[i]] <- runif(n, as.numeric(substr(res.char[i], 1, minus.relevant - 1)), as.numeric(substr(res.char[i], minus.relevant + 1, nchar(res.char[i]))))} else {
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| out[[i]] <- exp(runif(n, log(as.numeric(substr(res.char[i], 1, minus.relevant - 1))), log(as.numeric(substr(res.char[i], minus.relevant + 1, nchar(res.char[i]))))))}
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| } else {out[[i]] <- runif(n, as.numeric(substr(res.char[i], 1, minus.relevant[2] - 1)), as.numeric(substr(res.char[i], minus.relevant[2] + 1, nchar(res.char[i]))))}
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| } else {
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| if(plusminus.exists[i]) {
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| out[[i]] <- rnorm(n, as.numeric(substr(res.char[i], 1, plusminus[[i]][1] - 1)), as.numeric(substr(res.char[i], plusminus[[i]][1] + 1, nchar(res.char[i]))))
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| }
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| }
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| }
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| }
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| out
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| }
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| iter.f <- function(x) {
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| 1:x
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| }
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| input.interp.df <- function(data, rescol = "Result.text", N = 1000) {
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| temp <- input.interp(data[, rescol], N)
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| temp.lengths <- sapply(temp, length)
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| out <- data[rep(1:nrow(data), each = temp.lengths),]
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| out$Interp.Result <- unlist(temp)
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| dim(temp.lengths) <- length(temp.lengths)
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| out$Iteration <- unlist(apply(temp.lengths, 1, iter.f))
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| out
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| }
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| </rcode>
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| {{comment|# |Koodi on vielä vaiheessa, ottaa character vectorin alkiot ja antaa tulkinnat listana. Virhetoleranssi hyvin huono.|--[[User:Teemu R|Teemu R]] 03:09, 24 January 2012 (EET)}}
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| {{comment|# |Data.framelle oma wrapperi. Testaamaton, ottaa ja antaa data.framen.|--[[User:Teemu R|Teemu R]] 14:15, 24 January 2012 (EET)}}
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