Re: [R-sig-Geo] Error running Mann-Kendall trend test on a raster stack
Hi Tim and Loïc,
Thanks for your suggestions.
I was able to run the analysis using the following function (which also
accounts for NA values in the raster object):
library(raster)
library(rkt)
# Create the date sequence
idx <- seq.Date(as.Date("2011-01-01"), as.Date("2099-01-01"), by='year')
# Create raster stack and apply the date
r <- raster(ncol=23, nrow=19)
s <- stack(lapply(1:length(idx), function(x) setValues(r, runif(ncell(r), 0,
1200
s <- setZ(s, idx)
s
year <- as.numeric(substr(getZ(s), 1, 4))
# Now I define a function
tsfun <- function(x) {
if(all(is.na(x))){
c(NA, NA)
} else {
r.kenn <- rkt(year, x)
a <- r.kenn$B
b <- r.kenn$sl
return(cbind(a, b))
}
# I then apply the function - takes a while to run!
raster.kenn <- calc(s, fun=tsfun)
raster.kenn
Greetings,
-- Thiago V. dos Santos
PhD student
Land and Atmospheric Science
University of Minnesota
On Saturday, February 27, 2016 5:19 AM, Loïc Dutrieux
wrote:
Hi Thiago,
A few calc tips inline that you can use together with Tim's suggestion.
On 02/27/2016 07:47 AM, Tim Appelhans wrote:
> Dear Thiago,
> have a look at the gimms package, available on CRAN. The function of
> interest is significantTau().
>
> https://github.com/environmentalinformatics-marburg/gimms/blob/master/R/significantTau.R
>
>
> Hope this helps,
> Tim
>
> On 27.02.2016 09:49, Thiago V. dos Santos wrote:
>> Dear colleagues,
>>
>> I have a raster stack with 89 layers, each layer representing yearly
>> precipitation.
>>
>> I am trying to use the function rkt (from package "rkt") to detect a
>> possible trend in my precipitation time series.
>>
>> Its usage is pretty simple, and this is how it runs on a data frame:
>>
>>
>> library(rkt)
>>
>> # generate some random data
>> myDF <- data.frame(Date = seq.Date(as.Date("2011-01-01"),
>> as.Date("2099-01-01"), by='year'),
>> value = runif(89,0,1200))
>>
>> # extract year from date, as numeric
>> myDF$year <- as.numeric(format(myDF$Date, "%Y"))
>>
>> # run mann-kendall test
>> kenn <- rkt(myDF$year, myDF$value)
>> kenn
>>
>>
>>
>> Now, this is my attempt to apply this test on a raster stack, using a
>> calc function:
>>
>>
>> library(raster)
>>
>> # Create the date sequence
>> idx <- myDF$Date
>>
>> # Create raster stack and apply the date
>> r <- raster(ncol=50, nrow=50)
>> s <- stack(lapply(1:length(idx), function(x) setValues(r,
>> runif(ncell(r), 0, 1200
>> s <- setZ(s, idx)
>> s
>>
>> # Now I define a function
>> tsfun <- function(x) {
>> year <- as.numeric(substr(getZ(x), 1, 4))
>> r.kenn <- rkt(year, x)
>> return(r.kenn)
>> }
You can't call getZ() on x. Within the calc function environment x is a
numeric vector not a RasterBrick.
If you do it outside of the function and refer to it within the function
it should work.
dates <- getZ(s) # then use the dates variable in the function.
You can only store numerics in raster cells, and r.kenn is a full
object. You need to choose which numerics contained in that object you
want the function to return and subset the object accordingly.
Functions passed to calc should work on numeric vectors and ideally they
should also be vectorized. It's not always easy to vectorize a function
though; so in such case you can set the forceapply= argument to TRUE. I
believe that may cost a bit of speed though.
Cheers,
Loïc
>>
>> # I apply the function
>> raster.kenn <- calc(s, fun=tsfun)
>>
>>
>>
>>
>> And the error message I get is:
>>
>> Error in .calcTest(x[1:5], fun, na.rm, forcefun, forceapply) :
>> cannot use this function
Always loved that very informative error message from calc :)
>>
>> What am I doing wrong here?
>> Greetings,
>> -- Thiago V. dos Santos
>>
>> PhD student
>> Land and Atmospheric Science
>> University of Minnesota
>>
>> ___
>> R-sig-Geo mailing list
>> R-sig-Geo@r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
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Re: [R-sig-Geo] Error running Mann-Kendall trend test on a raster stack
Hi Thiago,
A few calc tips inline that you can use together with Tim's suggestion.
On 02/27/2016 07:47 AM, Tim Appelhans wrote:
Dear Thiago,
have a look at the gimms package, available on CRAN. The function of
interest is significantTau().
https://github.com/environmentalinformatics-marburg/gimms/blob/master/R/significantTau.R
Hope this helps,
Tim
On 27.02.2016 09:49, Thiago V. dos Santos wrote:
Dear colleagues,
I have a raster stack with 89 layers, each layer representing yearly
precipitation.
I am trying to use the function rkt (from package "rkt") to detect a
possible trend in my precipitation time series.
Its usage is pretty simple, and this is how it runs on a data frame:
library(rkt)
# generate some random data
myDF <- data.frame(Date = seq.Date(as.Date("2011-01-01"),
as.Date("2099-01-01"), by='year'),
value = runif(89,0,1200))
# extract year from date, as numeric
myDF$year <- as.numeric(format(myDF$Date, "%Y"))
# run mann-kendall test
kenn <- rkt(myDF$year, myDF$value)
kenn
Now, this is my attempt to apply this test on a raster stack, using a
calc function:
library(raster)
# Create the date sequence
idx <- myDF$Date
# Create raster stack and apply the date
r <- raster(ncol=50, nrow=50)
s <- stack(lapply(1:length(idx), function(x) setValues(r,
runif(ncell(r), 0, 1200
s <- setZ(s, idx)
s
# Now I define a function
tsfun <- function(x) {
year <- as.numeric(substr(getZ(x), 1, 4))
r.kenn <- rkt(year, x)
return(r.kenn)
}
You can't call getZ() on x. Within the calc function environment x is a
numeric vector not a RasterBrick.
If you do it outside of the function and refer to it within the function
it should work.
dates <- getZ(s) # then use the dates variable in the function.
You can only store numerics in raster cells, and r.kenn is a full
object. You need to choose which numerics contained in that object you
want the function to return and subset the object accordingly.
Functions passed to calc should work on numeric vectors and ideally they
should also be vectorized. It's not always easy to vectorize a function
though; so in such case you can set the forceapply= argument to TRUE. I
believe that may cost a bit of speed though.
Cheers,
Loïc
# I apply the function
raster.kenn <- calc(s, fun=tsfun)
And the error message I get is:
Error in .calcTest(x[1:5], fun, na.rm, forcefun, forceapply) :
cannot use this function
Always loved that very informative error message from calc :)
What am I doing wrong here?
Greetings,
-- Thiago V. dos Santos
PhD student
Land and Atmospheric Science
University of Minnesota
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Re: [R-sig-Geo] Error running Mann-Kendall trend test on a raster stack
Dear Thiago,
have a look at the gimms package, available on CRAN. The function of
interest is significantTau().
https://github.com/environmentalinformatics-marburg/gimms/blob/master/R/significantTau.R
Hope this helps,
Tim
On 27.02.2016 09:49, Thiago V. dos Santos wrote:
Dear colleagues,
I have a raster stack with 89 layers, each layer representing yearly
precipitation.
I am trying to use the function rkt (from package "rkt") to detect a possible
trend in my precipitation time series.
Its usage is pretty simple, and this is how it runs on a data frame:
library(rkt)
# generate some random data
myDF <- data.frame(Date = seq.Date(as.Date("2011-01-01"),
as.Date("2099-01-01"), by='year'),
value = runif(89,0,1200))
# extract year from date, as numeric
myDF$year <- as.numeric(format(myDF$Date, "%Y"))
# run mann-kendall test
kenn <- rkt(myDF$year, myDF$value)
kenn
Now, this is my attempt to apply this test on a raster stack, using a calc
function:
library(raster)
# Create the date sequence
idx <- myDF$Date
# Create raster stack and apply the date
r <- raster(ncol=50, nrow=50)
s <- stack(lapply(1:length(idx), function(x) setValues(r, runif(ncell(r), 0,
1200
s <- setZ(s, idx)
s
# Now I define a function
tsfun <- function(x) {
year <- as.numeric(substr(getZ(x), 1, 4))
r.kenn <- rkt(year, x)
return(r.kenn)
}
# I apply the function
raster.kenn <- calc(s, fun=tsfun)
And the error message I get is:
Error in .calcTest(x[1:5], fun, na.rm, forcefun, forceapply) :
cannot use this function
What am I doing wrong here?
Greetings,
-- Thiago V. dos Santos
PhD student
Land and Atmospheric Science
University of Minnesota
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--
#
Tim Appelhans
Department of Geography
Environmental Informatics
Philipps Universität Marburg
Deutschhausstraße 12
Raum 00A08
35032 Marburg (Paketpost: 35037 Marburg)
Germany
Tel +49 (0) 6421 28-25957
http://environmentalinformatics-marburg.de/
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