m

R/plot_2rasters.R

@@ -13,7 +13,7 @@
 	nly <- nlyr(y)
 
 	maxnl <- max(1, round(maxnl))
-	nl <- max(nlx, nly)
+	nl <- min(max(nlx, nly), maxnl)
 	if (nl > maxnl) {
 		nl <- maxnl
 		if (nlx > maxnl) {
@@ -26,6 +26,14 @@
 		}
 	}
 
+	if (nlx < nly) {
+		x <- x[[rep_len(1:nlx, nly)]]
+		nlx <- nly
+	} else if (nly < nlx) {
+		y <- y[[rep_len(1:nly, nlx)]]	
+		nly <- nlx
+	}
+
 
 	if (missing(main)) {
 		main <- ""

man/princomp.Rd

@@ -40,11 +40,15 @@ x <- predict(r, pca)
 # use "index" to get a subset of the components
 p <- predict(r, pca, index=1:2)
 
-### use princomp directly (or use prcomp instead)
-pca <- princomp(r)
-# may need to use sampling with a large raster 
+### use princomp directly
+pca2 <- princomp(values(r),  fix_sign = TRUE)
+p2 <- predict(r, pca2)
+
+### may need to use sampling with a large raster 
+### here with prcomp instead of princomp
 sr <- spatSample(r, 100000, "regular")
-pca <- prcomp(sr)
+pca3 <- prcomp(sr)
+p3 <- predict(r, pca3)
 }
 
 \keyword{spatial}