Hi,
I appologise if this is a rudimentary question and long winded but I just
wanted to let ye know where I'm comming from. I'm new to R and I'm trying to
use the 'randomForest' package to classify and predict. The Error message
that is troubling me is:
> pr<-predict(predictors,rf1, ext=ext)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
In addition: Warning message:
'newdata' had 153595 rows but variable(s) found have 109 rows
My steps are outlinded below which hopefully will give you insight into
where I'm going horribly wrong.
Step 1
I've sampled the environmental raster layers in ArcGIS giving me a csv file
as follows.
>Samples<-read.csv(("F:/R/Rst_points_10.csv"),head=TRUE,sep=",")
>head (Samples)
>attach(Samples)
POINTID GRID_CODE X Y Slope Aspect Curvature Rugosity
Plan_Curv Prof_Curv BS_BPI BS_BPI_S FS_BPI
1 1 74 420420.1 5572854 6.379370 116.5650 5 1.014847
2.80 -2.20 3 118 2
2 2 96 420460.1 5572834 5.051153 135.0000 0 1.007454
0.25 0.25 -1 -68 0
3 3 75 420510.1 5572834 0.000000 -1.0000 0 1.000000
0.00 0.00 -1 -68 0
4 4 76 420610.1 5572804 5.885129 194.0362 -4 1.012384
-2.00 2.00 3 118 0
5 5 97 429970.1 5572024 1.432096 270.0000 -3 1.004987
-2.00 1.00 -1 -68 0
6 6 98 429960.1 5571904 1.012750 315.0000 0 1.001247
0.00 0.00 0 -21 0
FS_BPI_S Bathy GROUP G1 G2 G3 G4 G5 G6 G7 G8 G9
1 441 -19 8 0 0 0 0 0 0 0 1 0
2 -27 -24 9 0 0 0 0 0 0 0 0 1
3 -27 -24 8 0 0 0 0 0 0 0 1 0
4 -27 -19 8 0 0 0 0 0 0 0 1 0
5 -27 -18 9 0 0 0 0 0 0 0 0 1
6 -27 -18 9 0 0 0 0 0 0 0 0 1
Step 2
I then uploaded the environemtal raster layers and stacked them.
>files <-list.files(("C:/Users/GIS-Modeller/Documents/10m/ASCII"), pattern=
'asc', full.names=TRUE)
>predictors <-stack(files)
> predictors
class : RasterStack
dimensions : 1745, 3909, 6821205, 10 (nrow, ncol, ncell, nlayers)
resolution : 10, 10 (x, y)
extent : 417085.1, 456175.1, 5556329, 5573779 (xmin, xmax, ymin, ymax)
coord. ref. : NA
min values : NA -2.1e+09 -2.1e+09 -2.1e+09 -2.1e+09 -2.1e+09 -2.1e+09
NA NA NA
max values : NA 2.1e+09 2.1e+09 2.1e+09 2.1e+09 2.1e+09 2.1e+09
NA NA NA
Step 3
I then provided the projection.
projection(predictors)<- "+proj=utm +zone=30 +ellps=WGS84 +datum=WGS84
+units=m +no_defs"
Step 4
I've tried numerous ways to get rid of /relace the NA values.
#na.action<-
#predictors<-predictors[na.rm=FALSE]
#99999->predictors[predictors==NA, ]
#predictors<-predictors[predictors, na.action=na.omit ]
#na.exclude->predictors=NA
#na.omit(predictors)
multiple combinations of these.
(#99999->predictors[predictors==NA, ]) returned the expected max and min
values for 'predictors' had the NA values not been taken into account
(except for the fact that 99999 was neither a max or min value).
> predictors
class : RasterBrick
dimensions : 1745, 3909, 6821205, 10 (nrow, ncol, ncell, nlayers)
resolution : 10, 10 (x, y)
extent : 417085.1, 456175.1, 5556329, 5573779 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=utm +zone=30 +ellps=WGS84 +datum=WGS84 +units=m +no_defs
+towgs84=0,0,0
values : in memory
min values : -1 -59 -10 -487 -26 -5 -1199 -14 -16 0
max values : 358 0 19 863 32 11 2551 16 14 34
Step 5
create the 'model'/rf.
model<-factor(G1)~ Slope+Aspect+Curvature+Rugosity+ Plan_Curv+ Prof_Curv+
BS_BPI+ BS_BPI_S+ FS_BPI
rf<- randomForest(model)
> rf
Call:
randomForest(formula = model)
Type of random forest: classification
Number of trees: 500
No. of variables tried at each split: 3
OOB estimate of error rate: 8.26%
Confusion matrix:
0 1 class.error
0 88 6 0.06382979
1 3 12 0.20000000
Step 6
Begin prediction
>ext = extent(417085.1, 456175.1, 5556329, 5573779)
pr<-predict(predictors,rf1, ext=ext)
Error in x[...] <- m : NAs are not allowed in subscripted assignments
In addition: Warning message:
'newdata' had 153595 rows but variable(s) found have 109 rows
I thank those that have read this. All help is extreemly apprecieated.
Cheers
Fionn
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