[R-sig-Geo] [R-sig-eco] raster::predict example doesn't work?

[Bede-Fazekas Ákos]

Dear Genoveva,

All the examples in the help file of package 'party' 
(https://cran.r-project.org/web/packages/party/party.pdf) use the 
function predict() from package 'stats' instead of package 'raster'.
But converting the RasterStack to data.frame, changing the column 'red' 
from numeric to factor, using stats::predict(..., newdata), and create a 
new layer of the RasterStack can solve the problem.
logo_df <- as.data.frame(logo)
logo_df$red <- factor(logo_df$red, levels = levels(v$red))
pc <- stats::predict(m, OOB = TRUE, newdata = logo_df)
logo$pc <- pc

HTH,
Ákos Bede-Fazekas
Hungarian Academy of Sciences


2018.12.04. 15:52 keltezéssel, Gonzalez-Mirelis, Genoveva írta:
> Dear list,
>
> I posted this question recently on another list so I apologize for any cross-posting. Still no solution.
>
>
> I would like to use the 'predict' function in the 'raster' package in an implementation of species distribution modelling with a couple of factor variables. Furthermore, I would like to set this up exactly as the cforest example listed in the help file. Unfortunately, I cannot get the example to work!
>
>
>
> # create a RasterStack or RasterBrick with with a set of predictor layers
>
>
>
> logo <- brick(system.file("external/rlogo.grd", package="raster"))
>
> names(logo)
>
>
>
> # known presence and absence points
>
> p <- matrix(c(48, 48, 48, 53, 50, 46, 54, 70, 84, 85, 74, 84, 95, 85,
>
>                66, 42, 26, 4, 19, 17, 7, 14, 26, 29, 39, 45, 51, 56, 46, 38, 31,
>
>                22, 34, 60, 70, 73, 63, 46, 43, 28), ncol=2)
>
>
>
> a <- matrix(c(22, 33, 64, 85, 92, 94, 59, 27, 30, 64, 60, 33, 31, 9,
>
>                99, 67, 15, 5, 4, 30, 8, 37, 42, 27, 19, 69, 60, 73, 3, 5, 21,
>
>                37, 52, 70, 74, 9, 13, 4, 17, 47), ncol=2)
>
>
>
> # extract values for points
>
> xy <- rbind(cbind(1, p), cbind(0, a))
>
> v <- data.frame(cbind(pa=xy[,1], extract(logo, xy[,2:3])))
>
>
>
> # cforest (other Random Forest implementation) example with factors argument
>
>
>
> v$red <- as.factor(round(v$red/100))
>
> logo$red <- round(logo[[1]]/100)
>
>
>
> library(party)
>
> m <- cforest(pa~., control=cforest_unbiased(mtry=3), data=v) f <- list(levels(v$red))
>
> names(f) <- 'red'
>
> pc <- predict(logo, m, OOB=TRUE, factors=f)
>
>
>
> # Error in v[cells, ] <- predv :
>
> # number of items to replace is not a multiple of replacement length
>
>
>
> # If you change the order of the first two arguments (I read this somewhere) then the error changes, like this:
>
>
>
> pc <- predict(m, logo, OOB=TRUE, factors=f)
>
>
>
> # Error in RET using prediction_weights(newdata = newdata, mincriterion = mincriterion,  :
>
> # unused argument (factors = f)
>
>
>
> # Lastly, if I run the line without the 'factors' argument
>
> pc <- predict(m, logo, OOB=TRUE)
>
>
>
> # Then I get no errors, but I don't understand the result. It's a vector of 40 values (predictions?)
>
>
>
> I am using Package 'raster' version 2.6-7 in RStudio 1.1.453, running off a server. I have tried the on several other computers, though, and the error persisted.
>
>
>
> Many thanks for any help,
>
>
>
> Genoveva
>
> Genoveva Gonzalez Mirelis, Scientist
> Institute of Marine Research
> Nordnesgaten 50
> 5005 Bergen, Norway
> Phone number +47 55238510
>
>
> Genoveva Gonzalez Mirelis, Scientist
> Institute of Marine Research
> Nordnesgaten 50
> 5005 Bergen, Norway
> Phone number +47 55238510
>
>
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>
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