Hi AK,
Thanks very much for the updated code.
My simulated results are even more consistent with observations after apply the
updated version of the code.
Cheers,
Atem.
On Wednesday, April 16, 2014 11:31 PM, Zilefac Elvis <zilefacel...@yahoo.com>
wrote:
Hi AK,
Thanks very much.
Atem.
On Wednesday, April 16, 2014 9:32 PM, arun <smartpink...@yahoo.com> wrote:
Hi,
Use this code after `lst2`.
lapply(seq_along(lst2), function(i) {
lstN <- lapply(lst2[[i]], function(x) {
datN <- as.data.frame(matrix(NA, nrow = 101, ncol = length(names1),
dimnames = list(NULL,
names1)))
x1 <- x[, -1]
qt <- numcolwise(function(y) quantile(y, seq(0, 1, by = 0.01), na.rm =
TRUE))(x1)
datN[, match(names(x1), names(datN))] <- qt
datN
})
arr1 <- array(unlist(lstN), dim = c(dim(lstN[[1]]), length(lstN)), dimnames
= list(NULL,
names1))
res <- rowMeans(arr1, dims = 2, na.rm = TRUE)
colnames(res) <- gsub(" ", "_", colnames(res))
res1 <- data.frame(Percentiles = paste0(seq(0, 100, by = 1), "%"), res,
stringsAsFactors = FALSE)
write.csv(res1, paste0(paste(getwd(), "final", paste(names(lst1)[[i]],
"Quantile",
sep = "_"), sep = "/"), ".csv"), row.names = FALSE, quote = FALSE)
})
ReadOut1 <- lapply(list.files(recursive = TRUE)[grep("Quantile",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
sapply(ReadOut1, function(x) dim(x))
lstNew <- simplify2array(ReadOut1)
nrow(lstNew)
#[1] 258
dir.create("Indices")
lapply(2:nrow(lstNew), function(i) {
dat1 <- data.frame(Percentiles = lstNew[1], do.call(cbind,
lstNew[i, ]), stringsAsFactors = FALSE)
colnames(dat1) <- c("Percentiles", paste(names(lst2),
rep(rownames(lstNew)[i],
length(lst2)), sep = "_"))
write.csv(dat1, paste0(paste(getwd(), "Indices", gsub(" ", "_",
rownames(lstNew)[i]),
sep = "/"), ".csv"), row.names = FALSE, quote = FALSE)
})
## Output2:
ReadOut2 <- lapply(list.files(recursive = TRUE)[grep("Indices",
list.files(recursive = TRUE))],
function(x) read.csv(x, header = TRUE, stringsAsFactors = FALSE))
names(ReadOut2) <- gsub(".*\\/(.*)\\.csv","\\1",list.files(recursive =
TRUE)[grep("Indices", list.files(recursive = TRUE))])
ReadOut2$pint_DJF[1:3,1:3]
# Percentiles G100_pint_DJF G101_pint_DJF
#1 0% 0.982001 1.020892
#2 1% 1.005563 1.039288
#3 2% 1.029126 1.057685
any(is.na(ReadOut2$pint_DJF))
[1] FALSE
A.K.
On Wednesday, April 16, 2014 12:34 PM, Zilefac Elvis <zilefacel...@yahoo.com>
wrote:
Hi AK,
I tried the updated "Quantilecode.txt". It works well but when I open the files
in "Indices", I find some columns filled with NAs. This should not be the case
given that I am working with simulations and there are no missing values in the
process. The ##not correct section yielded no NAs. Check for example,
pint_..._DJF in "Indices".
Let be be sure we are in the same page. I removed the ##not correct section of
the code, ran the code from beginning to end; Q1 and then Q2. My results are
found in the "Indices" folder.
Thanks,
Atem.
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