Difference between revisions of "OpasnetUtils/Interpret"

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==Description==
 
==Description==
  
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Interpret takes a vector or data.frame as argument. And returns a data.frame with certain textual inputs interpreted as probability distributions. More info on usage [[input.interp|here]](could be moved here).  
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Interpret takes a vector or data.frame as argument. And returns a data.frame with certain textual inputs interpreted as probability distributions.  
 +
 
 +
{| {{prettytable}}
 +
!Example!!Regular expression!!Interpretation
 +
|----
 +
| 12 000 ||# # || 12000. Text is interpreted as number if space removal makes it a number.
 +
|----
 +
| -14,23 || -# || -14.23. Minus in the beginning of entry is interpreted as minus, not a sign for a range.
 +
|----
 +
| 50 - 125 ||# - # ||Uniform distribution between 50 and 125
 +
|----
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| -12 345 - -23.56 || -# - -#|| Uniform distribution between -12345 and -23.56.
 +
|----
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| 1 - 50 ||# - # || Loguniform distribution between 1 and 50 (Loguniformity is assumed if the ratio of upper to lower is > 100)
 +
|----
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| 3.1 ± 1.2 or 3.1 +- 1.2||# ± # or # +- # ||Normal distribution with mean 3.1 and SD 1.2
 +
|----
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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
 +
|----
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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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| 0:0.5:1 || #:#:# ||Triangular distribution. Inputs are always sorted so order of arguments doesn't matter.
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|}
  
 
==Code==
 
==Code==

Revision as of 08:05, 2 July 2012



Description

Interpret takes a vector or data.frame as argument. And returns a data.frame with certain textual inputs interpreted as probability distributions.

Example Regular expression Interpretation
12 000 # # 12000. Text is interpreted as number if space removal makes it a number.
-14,23 -# -14.23. Minus in the beginning of entry is interpreted as minus, not a sign for a range.
50 - 125 # - # Uniform distribution between 50 and 125
-12 345 - -23.56 -# - -# Uniform distribution between -12345 and -23.56.
1 - 50 # - # Loguniform distribution between 1 and 50 (Loguniformity is assumed if the ratio of upper to lower is > 100)
3.1 ± 1.2 or 3.1 +- 1.2 # ± # or # +- # Normal distribution with mean 3.1 and SD 1.2
2.4 (1.8 - 3.0) # (# - #) Normal distribution with mean 2.4 and 95 % confidence interval from 1.8 to 3.0
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.
0:0.5:1 #:#:# Triangular distribution. Inputs are always sorted so order of arguments doesn't matter.

Code

- Hide code

# Lognormal distribution parametrization functions
lmean <- function(parmean, parsd) {return(log(parmean)-log(1+(parsd^2)/(parmean^2))/2)}
lsd <- function(parmean, parsd) {return(log(1+(parsd^2)/(parmean^2)))}

# Actual interpretation function. Takes already pre-processed information and returns a distribution.
interpf <- function(
	n, 
	res.char, 
	brackets.pos, 
	brackets.length, 
	minus, 
	minus.length, 
	minus.exists, 
	plusminus, 
	plusminus.length, 
	plusminus.exists,
	doublePoint
	) {

	if(doublePoint[1] > 0) {
		tempArgs <- sort(as.numeric(unlist(strsplit(res.char, "\\:"))))
		return(rtriangle(n,tempArgs[1],tempArgs[3],tempArgs[2]))
	}
	if(brackets.pos >= 0) {
		minus.relevant <- unlist(minus)[(cumsum(c(0, minus.length)) + 1):cumsum(minus.length)]
		n.minus.inside.brackets <- sum(minus.relevant > brackets.pos & minus.relevant < brackets.pos + brackets.length)
		imean <- as.numeric(substr(res.char, 1, brackets.pos - 1))
		if(n.minus.inside.brackets == 1) {
			ici <- c(as.numeric(substr(res.char, brackets.pos + 1, minus.relevant[minus.relevant > brackets.pos] - 1)), as.numeric(substr(res.char, 
				minus.relevant[minus.relevant > brackets.pos] + 1, brackets.pos + brackets.length - 2)))
			isd <- sum(abs(ici - imean) / 2) / qnorm(0.975)
			if((ici[2] - imean) / (ici[1] - imean) < 1.5) {
				return(rnorm(n, imean, isd))
			} else {
				return(out[[i]] <- rlnorm(n, lmean(imean, isd), lsd(imean, isd))) # menee vaarin koska isd on laskettu normaalijakaumalle
			}
		} else 
		if(n.minus.inside.brackets %in% c(2,3)) {
			ici <- c(as.numeric(substr(res.char, brackets.pos + 1, minus.relevant[minus.relevant > brackets.pos][2] - 1)), as.numeric(substr(res.char, 
				minus.relevant[minus.relevant > brackets.pos][2] + 1, brackets.pos + brackets.length - 2)))
			isd <- sum(abs(ici - imean) / 2) / qnorm(0.975)
			return(rnorm(n, imean, isd))
		}
		warning(paste("Unable to interpret \"", res.char, "\"", sep = ""))
		return(NA)
	}
	if(minus.exists) {
		minus.relevant <- unlist(minus)[(cumsum(c(0, minus.length)) + 1):cumsum(minus.length)]
		if(length(minus.relevant) == 1) {
			if(as.numeric(substr(res.char, 1, minus.relevant - 1)) / as.numeric(substr(res.char, minus.relevant + 1, nchar(res.char))) >= 1/100) {
				return(runif(n, as.numeric(substr(res.char, 1, minus.relevant - 1)), as.numeric(substr(res.char, minus.relevant + 1, nchar(res.char[i])))))
			} else {
				return(exp(runif(n, log(as.numeric(substr(res.char, 1, minus.relevant - 1))), log(as.numeric(substr(res.char, minus.relevant + 1, nchar(res.char)))))))
			}
		}
		if(length(minus.relevant) %in% c(2,3)) {
			return(runif(n, as.numeric(substr(res.char, 1, minus.relevant[2] - 1)), as.numeric(substr(res.char, minus.relevant[2] + 1, nchar(res.char)))))
		}
	}
	if(plusminus.exists) {
		return(rnorm(n, as.numeric(substr(res.char, 1, plusminus[1] - 1)), as.numeric(substr(res.char, plusminus[1] + 1, nchar(res.char)))))
	}
	if(sum(unlist(strsplit(res.char, ""))==";") > 0) {
		return(sample(sapply(strsplit(res.char, ";"), as.numeric), N, replace = TRUE))
	}
	warning(paste("Unable to interpret \"", res.char, "\"", sep = ""))
	return(NA)
}

# The next function processes character strings and loops the interpretation function.
input.interp <- function(res.char, n = 1000) {
	res.char <- gsub(" ", "", res.char)
	res.char <- gsub(",", ".", res.char)
	plusminus <- gregexpr(paste("\\+-|", rawToChar(as.raw(177)), sep = ""), res.char) # saattaa osoittautua ongelmaksi enkoodauksen vuoksi
	plusminus.length <- sapply(plusminus, length)
	plusminus.exists <- unlist(plusminus)[cumsum(c(0, plusminus.length[-length(plusminus.length)])) + 1] > 0
	minus <- gregexpr("-", res.char)
	minus.length <- sapply(minus, length)
	minus.exists <- unlist(minus)[cumsum(c(0, minus.length[-length(minus.length)])) + 1] > 0
	brackets <- gregexpr("\\(.*\\)", res.char) # matches for brackets "(...)"
	brackets.length <- as.numeric(unlist(sapply(brackets, attributes)[1,]))
	brackets.pos <- unlist(brackets)
	doublePoint <- gregexpr(":", res.char)
	out <- list()
	for(i in 1:length(res.char)) {
		out[[i]] <- interpf(n, res.char[i], brackets.pos[i], brackets.length[i], minus[i], minus.length[i], minus.exists[i], plusminus[[i]], 
	plusminus.length[i], plusminus.exists[i],doublePoint[[i]])
	}
	out
}

# Assisting function for data.frame wrapper.
iter.f <- function(x) {
	1:x
}

# Data.frame wrapper for the functions.
interpret <- function(idata, rescol = "Result", N = 1000) {

	temp <- input.interp(idata[, rescol], N)
	temp.lengths <- sapply(temp, length)
	out <- idata[rep(1:nrow(idata), times = temp.lengths),]
	out$Interp.Result <- unlist(temp)
	dim(temp.lengths) <- length(temp.lengths)
	out$Iter<- c(apply(temp.lengths, 1, iter.f))
	out
}

setGeneric("interpret")

setMethod(
	f = "interpret",
	signature = signature(idata = "character"),
	definition = function(idata) {
		if(!is.data.frame){
			callGeneric(data.frame(Result = idata))
			}
			callGeneric(idata)
	}
)

See also

Retrieved from "http://www.opasnet.org/testiwiki/index.php?title=OpasnetUtils/Interpret&oldid=25753"