further changes for _R_CHECK_DEPENDS_ONLY_=true; #117

Author: edzer

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: sp
-Version: 1.5-0
+Version: 1.5-1
 Title: Classes and Methods for Spatial Data
 Authors@R: c(person("Edzer", "Pebesma", role = c("aut", "cre"),
 				email = "[email protected]"),

inst/include/sp.h

@@ -8,7 +8,7 @@
 #endif
 /* remember to touch local_stubs.c */
 
-#define SP_VERSION "1.5-0"
+#define SP_VERSION "1.5-1"
 
 #include <R.h>
 /* RSB 091203 */

man/disaggregate.Rd

@@ -24,6 +24,7 @@ per \link{Polygons}, respectively.
 
 \author{ Robert Hijmans, Edzer Pebesma }
 \examples{
+if (require(rgeos, quietly = TRUE)) {
 Sr1 = Polygon(cbind(c(2,4,4,1,2),c(2,3,5,4,2)), hole = FALSE)
 Sr2 = Polygon(cbind(c(5,4,2,5),c(2,3,2,2)), hole = FALSE)
 Sr3 = Polygon(cbind(c(4,4,5,10,4),c(5,3,2,5,5)), hole = FALSE)
@@ -47,4 +48,5 @@ sl = SpatialLines(list(S1,S2))
 length(sl)
 length(disaggregate(sl))
 }
+}
 \keyword{methods}

man/over.Rd

@@ -138,6 +138,7 @@ and use \link[rgeos:pred-binary-gIntersects]{gIntersects}.}
 \code{vignette("over")} for examples and figures;
 \link{point.in.polygon}, package \link[rgeos:pred-binary-gIntersects]{gIntersects}}
 \examples{
+if (require(rgeos, quietly = TRUE)) {
 r1 = cbind(c(180114, 180553, 181127, 181477, 181294, 181007, 180409, 
 180162, 180114), c(332349, 332057, 332342, 333250, 333558, 333676, 
 332618, 332413, 332349))
@@ -195,4 +196,5 @@ over(meuse.grid, srdf, fn = mean)
 over(as(meuse.grid, "SpatialPoints"), sr)
 over(as(meuse.grid, "SpatialPoints"), srdf)
 }
+}
 \keyword{methods}

src/sp.h

@@ -8,7 +8,7 @@
 #endif
 /* remember to touch local_stubs.c */
 
-#define SP_VERSION "1.5-0"
+#define SP_VERSION "1.5-1"
 
 #include <R.h>
 /* RSB 091203 */

tests/agg.R

@@ -1,5 +1,6 @@
 options("rgdal_show_exportToProj4_warnings"="none")
 library(sp)
+if (require(rgeos, quietly = TRUE)) {
 g = SpatialGrid(GridTopology(c(5,5), c(10,10), c(3,3)))
 p = as(g, "SpatialPolygons")
 p$z = c(1,0,1,0,1,0,1,0,1)
@@ -31,3 +32,4 @@ rnd2(c(aggregate(p, sq, mean)[[1]],
   aggregate(p, sq, mean, minDimension = 1)[[1]],
   aggregate(p, sq, mean, minDimension = 2)[[1]],
   aggregate(p, sq, mean, areaWeighted=TRUE)[[1]]))
+}

tests/over2.R

@@ -1,6 +1,7 @@
 options("rgdal_show_exportToProj4_warnings"="none")
 library(sp)
 
+if (require(rgeos, quietly = TRUE)) {
 g = SpatialGrid(GridTopology(c(0,0), c(1,1), c(3,3)))
 p = as(g, "SpatialPolygons")
 over(g,g)
@@ -39,3 +40,4 @@ rgeos::overGeomGeom(pt,sp,returnList=TRUE, minDimension = 0)
 rgeos::overGeomGeom(pt,pt,minDimension=2)
 rgeos::overGeomGeom(pt,pt,minDimension=1)
 rgeos::overGeomGeom(pt,pt,minDimension=0)
+}

vignettes/csdacm.Rnw

@@ -961,12 +961,13 @@ Let us first generate, as an example, a set of 100 conditional Gaussian
 simulations for the zinc variable in the meuse data set:
 \begin{footnotesize}
 <<eval=TRUE,echo=TRUE>>= 
-library(gstat)
 data(meuse)
 coordinates(meuse) <- ~x+y
-v <- vgm(.5, "Sph", 800, .05)
-sim <- krige(log(zinc)~1, meuse, meuse.grid, v, nsim=100, nmax=30)
-sim@data <- exp(sim@data)
+if (require(gstat, quietly = TRUE)) {
+ v <- vgm(.5, "Sph", 800, .05)
+ sim <- krige(log(zinc)~1, meuse, meuse.grid, v, nsim=100, nmax=30)
+ sim@data <- exp(sim@data)
+}
 @
 \end{footnotesize}
 
@@ -985,16 +986,20 @@ after which we can find the sample lower and upper 95\%
 confidence limits by
 \begin{footnotesize}
 << >>=
+if (require(gstat, quietly = TRUE)) {
 sim$lower <- quantile.Spatial(sim[1:100], probs = 0.025)
 sim$upper <- quantile.Spatial(sim[1:100], probs = 0.975)
+}
 @
 \end{footnotesize}
 
 To get the sample distribution of the areal median, we can aggregate over
 layers:
 \begin{footnotesize}
 << >>=
+if (require(gstat, quietly = TRUE)) {
 medians <- quantile.Spatial(sim[1:100], probs = 0.5, byLayer = TRUE)
+}
 @
 <<eval=FALSE>>=
 hist(medians)
@@ -1025,9 +1030,11 @@ fractionBelow <- function(x, q, byLayer = FALSE) {
 options("width"=70)
 @
 << >>=
+if (require(gstat, quietly = TRUE)) {
 over500 <- 1 - fractionBelow(sim[1:100], 200, byLayer = TRUE)
 summary(over500)
 quantile(over500, c(0.025, 0.975))
+}
 @
 \end{footnotesize}
 
@@ -1072,12 +1079,8 @@ if (run) {
 library(rgdal)
 x <- GDAL.open(fn)
 class(x)
-}
-if (run) {
 x.subs <- x[1:100, 1:100, 1]
 class(x.subs)
-}
-if (run) {
 gridparameters(x.subs)
 }
 @

vignettes/over.Rnw

@@ -144,10 +144,14 @@ and shown in figure \ref{fig:toy}.
 
 \begin{figure}[htb]
 <<fig=TRUE,echo=FALSE>>=
-library(RColorBrewer)
-pal = brewer.pal(5, "Set2")
-plot(pol, xlim = c(-1.1, 2.1), ylim = c(-1.1, 1.6), border=pal, axes=TRUE,
-	col = paste0(pal, "4D"))
+if (require(RColorBrewer, quietly = TRUE)) {
+ pal = brewer.pal(5, "Set2")
+ col = paste0(pal, "4D")
+} else {
+ pal = 1:5
+ col = pal
+}
+plot(pol, xlim = c(-1.1, 2.1), ylim = c(-1.1, 1.6), border=pal, axes=TRUE, col = col)
 points(pts, col='red')
 text(c(-1,0.1,0.1,1.9,0.45), c(0.05,0.05,-.95,0.05,0.15), 
 	c("x1", "x2", "x3", "x4", "x5"))
@@ -188,7 +192,9 @@ row.names(pol[pts])
 \code{over} can also be used to query polygons in a single object overlay each other:
 
 <<>>=
-over(pol, pol, returnList = TRUE)
+if (require(rgeos, quietly = TRUE)) {
+ over(pol, pol, returnList = TRUE)
+}
 @
 
 \noindent
@@ -300,7 +306,7 @@ text(c(0.52, 1.52), c(1.5, 1.5), c("L1", "L2"))
 The set of \code{over} operations on the polygons, lines and points 
 is shown below (note that lists and vectors are named in this case):
 <<>>=
-library(rgeos)
+if (require(rgeos, quietly = TRUE)) {
 over(pol, pol)
 over(pol, pol,returnList = TRUE)
 over(pol, L)
@@ -309,6 +315,7 @@ over(L, pol, returnList = TRUE)
 over(L, L)
 over(pts, L)
 over(L, pts)
+}
 @
 
 Another example overlays a line with a grid, shown in figure \ref{fig:grid}.
@@ -319,9 +326,11 @@ gridded(meuse.grid) = ~x+y
 Pt = list(x = c(178274.9,181639.6), y = c(329760.4,333343.7))
 sl = SpatialLines(list(Lines(Line(cbind(Pt$x,Pt$y)), "L1")))
 image(meuse.grid)
-xo = over(sl, geometry(meuse.grid), returnList = TRUE)
-image(meuse.grid[xo[[1]], ],col=grey(0.5),add=T)
-lines(sl)
+if (require(rgeos, quietly = TRUE)) {
+ xo = over(sl, geometry(meuse.grid), returnList = TRUE)
+ image(meuse.grid[xo[[1]], ],col=grey(0.5),add=T)
+ lines(sl)
+}
 @
 \caption{ Overlay of line with grid, identifying cells crossed (or touched)
 by the line }
@@ -342,17 +351,21 @@ text(coordinates(g), labels = 1:9)
 
 We can match these geometries with themselves by
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(g,g)
 over(p,p)
 over(p,g)
 over(g,p)
+}
 @
 and see that most give a 1:1 match, except for polygons-polygons \code{(p,p)}.
 
 When we ask for the full set of matches, we see
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(px[5], g, returnList = TRUE)
 over(p[c(1,5)], p, returnList = TRUE)
+}
 @
 and note that the implementation lets grids/pixels not match
 (intersect) with neighbour grid cells, but that polygons do. 
@@ -369,8 +382,10 @@ By default, polygon-polygon features are matched by
 {\em any} order (feature order, it seems). Although it is slower,
 we  can however improve on this by switching to \code{rgeos::gRelate}, and see
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(px[5], g, returnList = TRUE, minDimension = 0)
 over(p[c(1,5)], p, returnList = TRUE, minDimension = 0)
+}
 @
 When \code{minDimension = 0} is specified, the matching geometries
 are being returned based on a nested ordering. First, ordering
@@ -391,7 +406,9 @@ Note that the ordering also determines which feature is matched
 when \code{returnList=FALSE}, as in this case the first element of
 the ordered set is taken:
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(p, p, minDimension = 0)
+}
 @
 
 Consider the following example where a point is {\em on} \code{x1} and {\em in} \code{x2}: 
@@ -413,12 +430,14 @@ When matching the point \code{pt} with the two polygons, the
 sp method (default) gives no preference of the second polygon
 that (fully) contains the point; the rgeos method however does:
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(pt,sp)
 over(pt,sp,minDimension=0)
 over(pt,sp,returnList=TRUE)
 rgeos::overGeomGeom(pt,sp)
 rgeos::overGeomGeom(pt,sp,returnList=TRUE)
 rgeos::overGeomGeom(pt,sp,returnList=TRUE,minDimension=0)
+}
 @
 
 % #    x1     x2 
@@ -435,12 +454,14 @@ area overlap {\em or} line in common. This can be done using the
 parameter \code{minDimension}:
 
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 over(p[5], p, returnList=TRUE, minDimension=0)
 over(p[5], p, returnList=TRUE, minDimension=1)
 over(p[5], p, returnList=TRUE, minDimension=2)
 rgeos::overGeomGeom(pt, pt, minDimension=2) # empty
 rgeos::overGeomGeom(pt, pt, minDimension=1) # empty
 rgeos::overGeomGeom(pt, pt, minDimension=0)
+}
 @
 
 \section{Aggregation}
@@ -474,9 +495,11 @@ x 400 m grid}
 An example of the aggregated values of \code{meuse.grid} along
 (or under) the line shown in Figure \ref{fig:lines} are
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 sl.agg = aggregate(meuse.grid[,1:3], sl, mean)
 class(sl.agg)
 as.data.frame(sl.agg)
+}
 @
 Function \code{aggregate} returns a spatial object of the same
 class of \code{sl} (\code{SpatialLines}), and \code{as.data.frame}
@@ -490,6 +513,7 @@ specifying {\em how} polygons intersect\footnote{sp versions
 in Figure \ref{fig:agg}.
 
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 g = SpatialGrid(GridTopology(c(5,5), c(10,10), c(3,3)))
 p = as(g, "SpatialPolygons")
 p$z = c(1,0,1,0,1,0,1,0,1)
@@ -499,10 +523,12 @@ p$ag1a = aggregate(p, p, mean, minDimension = 0)[[1]]
 p$ag2 = aggregate(p, p, mean, minDimension = 1)[[1]]
 p$ag3 = aggregate(p, p, mean, minDimension = 2)[[1]]
 p$ag4 = aggregate(p, p, areaWeighted=TRUE)[[1]]
+}
 @
 
 \begin{figure}[ht]
 <<echo=FALSE,fig=TRUE>>=
+if (require(rgeos, quietly = TRUE)) {
 pts = cbind(c(9,21,21,9,9),c(9,9,21,21,9))
 sq = SpatialPolygons(list(Polygons(list(Polygon(pts)), "ID")))
 rnd2 = function(x) round(x, 2)
@@ -519,6 +545,8 @@ spplot(p, names.attr = c("source", "default aggregate", "minDimension=0",
 	"minDimension=1", "minDimension=2", "areaWeighted=TRUE"), layout = c(3,2), 
 	as.table=TRUE, col.regions=bpy.colors(151)[50:151], cuts=100, 
 	sp.layout = l, scales = list(draw = TRUE))
+} else
+	plot(1)
 @
 \caption{Effect of aggregating checker board {\tt SpatialPolygons} by themselves, for
 different values of {\tt minDimension} and {\tt areaWeighted}; the green square example
@@ -536,12 +564,14 @@ using {\tt minDimension}, and area weighting for aggregating the 0-1 checker
 board of figure \ref{fig:agg} by the green square polygon ({\tt sq}) 
 shown in the last panel of that figure:
 <<>>=
+if (require(rgeos, quietly = TRUE)) {
 round(c(
   aggDefault = aggregate(p, sq, mean)[[1]],
   aggMinDim0 = aggregate(p, sq, mean, minDimension = 0)[[1]],
   aggMinDim1 = aggregate(p, sq, mean, minDimension = 1)[[1]],
   aggMinDim2 = aggregate(p, sq, mean, minDimension = 2)[[1]],
   areaWeighted = aggregate(p, sq, areaWeighted=TRUE)[[1]]), 3)
+}
 @