Hello everyone,
I am working for a few days already on a basic algorithm, very common in
applied agronomy, that aims to determine the degree-days necessary for a
given individual to reach a given growth stade. The algorithm (and context)
is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and
so I implemented my function in R as follows:
DD <- function(Tmin, Tmax, Tseuil, meanT, method = "DDsin")
### function that calculates the degree-days based on
### minimum and maximum recorded temperatures and the
### minimal threshold temperature (lower growth temperature)
{
### method arcsin
if(method == "DDsin"){
cond1 <- (Tmax <= Tseuil)
cond2 <- (Tmin >= Tseuil)
amp <- ((Tmax - Tmin) / 2)
print((Tseuil-meanT)/amp)
alpha <- asin((Tseuil - meanT) / amp)
DD_ifelse3 <- ((1 / pi) * ((meanT - Tseuil) * ((pi/2) - alpha)) +
amp*cos(alpha))
DD <- ifelse(cond1, 0, ifelse(cond2, (meanT - Tseuil), DD_ifelse3))
}
### method (Tmin + Tmax) / 2
else if(method == "DDt2"){
cond1 <- (meanT > Tseuil)
DD <- ifelse(cond1,(meanT - Tseuil),0)
}
else{
stop("\nMethod name is invalid.\nMethods available = DDsin (sinus) or
DDt2
(mean)\n")
}
return(DD)
}
BUT! When I try to process random data:
library(reshape2)
library(plyr)
station <-
rep(c("station1","station2","station3"), 20)
values_min <- sample(-5:20, size = 60, replace = T)
values_max <- sample(20:40, size = 60, replace = T)
meanT <- ((values_min+values_max)/2)
d <- data.frame(station,values_min,values_max,meanT)
names(d) <- c("station",
"values_min","values_max","meanT")
x<-ddply(d, .(station), transform, t1
cumsum(DD(values_min,values_max,0,meanT)))
I get a warning on my alpha calculation (NaN produced); indeed, the values I
give as argument to asin() are out of the range [-1:1], as the print()
reveals. I can't figure out how to solve this issue, because the same
algorithm works in Excel (visual basic).
It is very annoying, especially because it seems that no occurence of such
error using that algorithm can be found on Internet.
Any help is welcome :) Thanks for your time
P.
--
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On 12-03-19 7:42 AM, Letnichev wrote:> Hello everyone, > > I am working for a few days already on a basic algorithm, very common in > applied agronomy, that aims to determine the degree-days necessary for a > given individual to reach a given growth stade. The algorithm (and context) > is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and > so I implemented my function in R as follows: > > DD<- function(Tmin, Tmax, Tseuil, meanT, method = "DDsin") > ### function that calculates the degree-days based on > ### minimum and maximum recorded temperatures and the > ### minimal threshold temperature (lower growth temperature) > { > ### method arcsin > if(method == "DDsin"){ > cond1<- (Tmax<= Tseuil) > cond2<- (Tmin>= Tseuil)These look like useful diagnostics of out-of-range values, but you don't use them before the arcsin transformation.> amp<- ((Tmax - Tmin) / 2) > print((Tseuil-meanT)/amp) > alpha<- asin((Tseuil - meanT) / amp)> DD_ifelse3<- ((1 / pi) * ((meanT - Tseuil) * ((pi/2) - alpha)) + > amp*cos(alpha)) > > DD<- ifelse(cond1, 0, ifelse(cond2, (meanT - Tseuil), DD_ifelse3)) > } > > ### method (Tmin + Tmax) / 2 > else if(method == "DDt2"){ > cond1<- (meanT> Tseuil) > DD<- ifelse(cond1,(meanT - Tseuil),0) > } > > else{ > stop("\nMethod name is invalid.\nMethods available = DDsin (sinus) or DDt2 > (mean)\n") > } > return(DD) > } > > BUT! When I try to process random data:It's a good idea to use set.seed when trying to debug problems like this. Then you can construct a reproducible example. I'd also suggest getting rid of ddply at least for debugging; it makes it harder to see what's going on. Duncan Murdoch> > library(reshape2) > library(plyr) > > station<- rep(c("station1","station2","station3"), 20) > values_min<- sample(-5:20, size = 60, replace = T) > values_max<- sample(20:40, size = 60, replace = T) > meanT<- ((values_min+values_max)/2) > d<- data.frame(station,values_min,values_max,meanT) > names(d)<- c("station", "values_min","values_max","meanT") > > x<-ddply(d, .(station), transform, t1 > cumsum(DD(values_min,values_max,0,meanT))) > > I get a warning on my alpha calculation (NaN produced); indeed, the values I > give as argument to asin() are out of the range [-1:1], as the print() > reveals. I can't figure out how to solve this issue, because the same > algorithm works in Excel (visual basic). > It is very annoying, especially because it seems that no occurence of such > error using that algorithm can be found on Internet. > Any help is welcome :) Thanks for your time > > P. > > -- > View this message in context: http://r.789695.n4.nabble.com/Issue-with-asin-tp4484462p4484462.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > 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.
On 19-03-2012, at 12:42, Letnichev wrote:> Hello everyone, > > I am working for a few days already on a basic algorithm, very common in > applied agronomy, that aims to determine the degree-days necessary for a > given individual to reach a given growth stade. The algorithm (and context) > is explained here: http://www.oardc.ohio-state.edu/gdd/glossary.htm , and > so I implemented my function in R as follows: > > DD <- function(Tmin, Tmax, Tseuil, meanT, method = "DDsin") > ### function that calculates the degree-days based on > ### minimum and maximum recorded temperatures and the > ### minimal threshold temperature (lower growth temperature) > { > ### method arcsin > if(method == "DDsin"){ > cond1 <- (Tmax <= Tseuil) > cond2 <- (Tmin >= Tseuil) > amp <- ((Tmax - Tmin) / 2) > print((Tseuil-meanT)/amp) > alpha <- asin((Tseuil - meanT) / amp) > DD_ifelse3 <- ((1 / pi) * ((meanT - Tseuil) * ((pi/2) - alpha)) + > amp*cos(alpha)) > > DD <- ifelse(cond1, 0, ifelse(cond2, (meanT - Tseuil), DD_ifelse3)) > } > > ### method (Tmin + Tmax) / 2 > else if(method == "DDt2"){ > cond1 <- (meanT > Tseuil) > DD <- ifelse(cond1,(meanT - Tseuil),0) > } > > else{ > stop("\nMethod name is invalid.\nMethods available = DDsin (sinus) or DDt2 > (mean)\n") > } > return(DD) > } > > BUT! When I try to process random data: > > library(reshape2) > library(plyr) > > station <- rep(c("station1","station2","station3"), 20) > values_min <- sample(-5:20, size = 60, replace = T) > values_max <- sample(20:40, size = 60, replace = T) > meanT <- ((values_min+values_max)/2) > d <- data.frame(station,values_min,values_max,meanT) > names(d) <- c("station", "values_min","values_max","meanT") > > x<-ddply(d, .(station), transform, t1 > cumsum(DD(values_min,values_max,0,meanT))) > > I get a warning on my alpha calculation (NaN produced); indeed, the values I > give as argument to asin() are out of the range [-1:1], as the print() > reveals. I can't figure out how to solve this issue, because the same > algorithm works in Excel (visual basic).That doesn't mean that Excel and/or Visual Basic gives correct answers. With the same input? Then what does Excel say that asin(-7.4) evaluates to? I tried asin(-1.2) and asin(-7.4) in LibreOffice Calc (3.5.0) and got #VALUE! (Error: wrong data type) twice. You'll have to present correct input to asin() if you want to avoid the NaN's. Berend> It is very annoying, especially because it seems that no occurence of such > error using that algorithm can be found on Internet. > Any help is welcome :) Thanks for your time > > P. > > -- > View this message in context: http://r.789695.n4.nabble.com/Issue-with-asin-tp4484462p4484462.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > 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.
Hi, You're not following the algorithm as given. The asin step shouldn't be done for all values, but only for the ones that don't meet the previous conditions. You're trying to calculate that step for ALL values, then only use certain ones. You must instead subset the values, THEN calculate that step. I would guess that your "working" Excel version does follow the correct algorithm, but it's hard to know for certain. Here's a version that more closely follows the given reference: MaxDailyTemp <- values_max MinDailyTemp <- values_min k <- 0 GDD <- rep(0, length(Tmin)) AvgDailyTemp <- (MaxDailyTemp + MinDailyTemp)/2 # if MaxDailyTemp < k # GDD = GDD + 0 # - add 0 # if MaxDailyTemp > k & MinDailyTemp > k # GDD = GDD + AvgDailyTemp - k GDD[MaxDailyTemp > k & MinDailyTemp > k] <- AvgDailyTemp[MaxDailyTemp> k & MinDailyTemp > k] - k# if MaxDailyTemp > k & MinDailyTemp < k # GDD = GDD + (1/pi) * [ (AvgDailyTemp ? k) * ( ( pi/2 ) ? arcsine( theta ) ) + ( a * cos( arcsine( theta ) ) ) ] a <- (MaxDailyTemp - MinDailyTemp)/2 theta <- ((k - AvgDailyTemp)/a) GDD[MaxDailyTemp > k & MinDailyTemp < k] <- (1/pi) * ( (AvgDailyTemp[MaxDailyTemp > k & MinDailyTemp < k] - k) * ( ( pi/2 ) - asin( theta[MaxDailyTemp > k & MinDailyTemp < k] ) ) + ( a[MaxDailyTemp > k & MinDailyTemp < k] * cos( asin( theta[MaxDailyTemp> k & MinDailyTemp < k] ) ) ) )sum(GDD) Sarah On Mon, Mar 19, 2012 at 7:42 AM, Letnichev <chatelain.phil at gmail.com> wrote:> Hello everyone, > > I am working for a few days already on a basic algorithm, very common in > applied agronomy, that aims to determine the degree-days necessary for a > given individual to reach a given growth stade. The algorithm (and context) > is explained here: ?http://www.oardc.ohio-state.edu/gdd/glossary.htm , and > so I implemented my function in R as follows: > > DD <- function(Tmin, Tmax, Tseuil, meanT, method = "DDsin") > ### function that calculates the degree-days based on > ### minimum and maximum recorded temperatures and the > ### minimal threshold temperature (lower growth temperature) > ? ? ? ?{ > ? ? ? ?### method arcsin > ? ? ? ?if(method == "DDsin"){ > ? ? ? ? ? ? ? ?cond1 <- (Tmax <= Tseuil) > ? ? ? ? ? ? ? ?cond2 <- (Tmin >= Tseuil) > ? ? ? ? ? ? ? ?amp <- ((Tmax - Tmin) / 2) > ? ? ? ? ? ? ? ?print((Tseuil-meanT)/amp) > ? ? ? ? ? ? ? ?alpha <- asin((Tseuil - meanT) / amp) > ? ? ? ? ? ? ? ?DD_ifelse3 <- ((1 / pi) * ((meanT - Tseuil) * ((pi/2) - alpha)) + > amp*cos(alpha)) > > ? ? ? ? ? ? ? ?DD <- ifelse(cond1, 0, ifelse(cond2, (meanT - Tseuil), DD_ifelse3)) > ? ? ? ?} > > ? ? ? ?### method (Tmin + Tmax) / 2 > ? ? ? ?else if(method == "DDt2"){ > ? ? ? ? ? ? ? ?cond1 <- (meanT > Tseuil) > ? ? ? ? ? ? ? ?DD <- ifelse(cond1,(meanT - Tseuil),0) > ? ? ? ? ? ? ? ?} > > ? ? ? ?else{ > ? ? ? ? ? ? ? ?stop("\nMethod name is invalid.\nMethods available = DDsin (sinus) or DDt2 > (mean)\n") > ? ? ? ? ? ? ? ?} > ? ? ? ?return(DD) > } > > BUT! When I try to process random data: > > library(reshape2) > library(plyr) > > station <- rep(c("station1","station2","station3"), 20) > values_min <- sample(-5:20, size = 60, replace = T) > values_max <- sample(20:40, size = 60, replace = T) > meanT <- ((values_min+values_max)/2) > d <- data.frame(station,values_min,values_max,meanT) > names(d) <- c("station", "values_min","values_max","meanT") > > x<-ddply(d, .(station), transform, t1 > cumsum(DD(values_min,values_max,0,meanT))) > > I get a warning on my alpha calculation (NaN produced); indeed, the values I > give as argument to asin() are out of the range [-1:1], as the print() > reveals. I can't figure out how to solve this issue, because the same > algorithm works in Excel (visual basic). > It is very annoying, especially because it seems that no occurence of such > error using that algorithm can be found on Internet. > Any help is welcome :) Thanks for your time > > P. >-- Sarah Goslee http://www.functionaldiversity.org