I got this question today from a Drought researcher:
Question:
There a table with 62 years * 12 months of rain data in mm. We
calculated the cumulative distribution using ecdf: empirical
cumulative distribution function. So the table looks like this:
Year Jan Feb Mach (…) each cell contains the cum dist.
We also got the number of months per year with less than X mm of
rain. But he needs to know how many months are between the
drought months, regardless the year. So, I thought that
converting the data into a ts was going to facilitate the task,
but it doesn’t, because now I don’t’ have columns and rows any
longer.
How do I handle a ts object to do for example an ifelse?
I answered:
This looks a lot like the Hutchinson Drought Index which I’ve coded up here
- https://github.com/ivanhanigan/HutchinsonDroughtIndex
- https://github.com/ivanhanigan/HutchinsonDroughtIndex/blob/master/src/HutchinsonDroughtIndex_tools_droughtIndex.r
- Also there is a completely reproducible example with BoM rainfall data at https://github.com/ivanhanigan/SuicideAndDroughtInNSW
This is the key bit for counting consecutive months below a threshold
R Code:
x<-data$index<=-1
xx <- (cumsum(!x) + 1) * x
x2<-(seq_along(x) - match(xx, xx) + 1) * x
data$count<-x2
I got it from https://stat.ethz.ch/pipermail/r-help/2007-June/134594.html and looked in wonder at the structure and am amazed it works.
I also really like the cumulative summing version a lot
R Code:
data$sums<-as.numeric(0)
y <- ifelse(data$index >= -1, 0, data$index)
f <- data$index < -1
f <- (cumsum(!f) + 1) * f
z <- unsplit(lapply(split(y,f),cumsum),f)
data$sums <- z
Several things I’d like to change.
- I like the idea of using a wide dataset and ecdf rather than my loop thru months
- I’d like to look into Joe Wheatley;s approach http://joewheatley.net/20th-century-droughts/
- I was defeated by Mike’s request to make a different threshold for breaking a drought than starting a drought. went back to a for loop
