Hi Ahmet,
My apologies, the final for loop should read:
for(run in 1:length(sm.rle$lengths)) {
if(sm.rle$values[run]) {
cat("Day",day_of_year,"-",day_of_year+sm.rle$lengths[run],
"-",sm.rle$lengths[run],"days\n")
}
day_of_year<-day_of_year+sm.rle$lengths[run]
}
Jim
On Fri, Aug 7, 2020 at
Hi Ahmet,
Here is a way to get the result you ask for for one geographic grid
cell. You may want more detail or something, but this is a
"reproducible example".
# retrieved from
ftp://ftp2.psi.noaa.gov/Datasets/ncep.renalysis.dailyavgs/surface_gauss/soilw.1-10cm.gauss.1949.nc
library(ncdf4)
soilm<
Hi Ahmet,
I think what you are looking for can be done using run length encoding (rle).
# make up some data
soil_moisture<-sin(seq(0,4*pi,length.out=730))+1.1
dates<-as.Date(as.Date("2018-01-01"):as.Date("2019-12-31"),
origin=as.Date("1970-01-01"))
# get a logical vector for your condition
under.
You need to make a small fake dataset that illustrates what you have and what
you want out of it. Telling us you are not getting what you want is simply not
useful.
On August 6, 2020 8:58:09 AM PDT, "ahmet varlı" wrote:
>Hi all,
>
>
>There are 365 days of soil moisture NC files and I am trying
Hi all,
There are 365 days of soil moisture NC files and I am trying to find out how
many days the values are below and above this certain threshold are repeated by
R. However, I couldn't reach exactly what I wanted. For example, Daily soil
moisture is below 0.3 without interrupting how many d
Hi Jim,
Many thanks for your help, I will try a 2D plot and then pass to 3D.
I am trying something like this:
tus.datos<-read.table("datayield.csv",sep=";",header=TRUE)
data_types<-c("PY_1Y","PY_2Y","PY_3Y","PY_4Y","PY_5Y","PY_6Y","PY_7Y")
row_subset<-tus.datos$DATA_TYPE %in% data_types
x<-tu
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