version 1.6-2

cran · May 29, 2007 · c9f6e77 · c9f6e77
1 parent fb4b12e
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,5 +1,5 @@
 Package: adehabitat
-Version: 1.6-1
+Version: 1.6-2
 Date: 2007/05/29
 Title: Analysis of habitat selection by animals
 Author: Clement Calenge, contributions from Mathieu Basille, Stephane Dray and Scott Fortmann-Roe
@@ -9,4 +9,4 @@ Suggests: gpclib, sp, spatstat, MASS, tkrplot, shapefiles, CircStats
 Description: A collection of tools for the analysis of habitat selection by animals
 Encoding: latin1
 License: GPL version 2 or newer
-Packaged: Tue May 29 17:17:32 2007; calenge
+Packaged: Fri Aug 17 11:32:58 2007; calenge
diff --git a/R/corrXY.r b/R/corrXY.r
@@ -15,7 +15,7 @@
 ### Correction XY vitesse constante
 .corrXY <- function(x, y, dab, daa)
 {
-    ## Correction éventuelle de x1
+    ## Correction eventuelle de x1
     x1 <- x[1]
     y1 <- y[1]
 
@@ -36,7 +36,7 @@
         }
     }
 
-    ## Correction éventuelle de xn
+    ## Correction eventuelle de xn
     xn <- x[length(y)]
     yn <- y[length(y)]
     if (daa[length(daa)]!=dab[length(dab)]) {
@@ -89,7 +89,7 @@
         yc[daa<dab] <- yc[daa<dab] + sin(alpha[daa<dab] + pi)*r[daa<dab]
     }
 
-    ## Cas 2: t1 après
+    ## Cas 2: t1 apres
     daa <- daat
     dab <- dabt
 

diff --git a/R/cutltraj.r b/R/cutltraj.r
@@ -1,7 +1,7 @@
 ##################################################################
 ##
-## cutltraj coupe une trajectoire en plusieurs bursts après une loc
-## donnée qui remplit les conditions
+## cutltraj coupe une trajectoire en plusieurs bursts apres une loc
+## donnee qui remplit les conditions
 ##
 
 

diff --git a/R/kernelUD.r b/R/kernelUD.r
@@ -1,5 +1,6 @@
 "kernelUD" <- function(xy, id=NULL, h="href", grid=40, same4all=FALSE,
-                      hlim=c(0.1, 1.5), kern = c("bivnorm", "epa"))
+                       hlim=c(0.1, 1.5), kern = c("bivnorm", "epa"),
+                       extent=0.5)
 {
     ## Verifications
     kern <- match.arg(kern)
@@ -37,8 +38,10 @@
                 stop("grid should be an object of class asc or a number")
             xli<-range(xy[,1])
             yli<-range(xy[,2])
-            xli<-c(xli[1]-0.3*abs(xli[2]-xli[1]),xli[2]+0.3*abs(xli[2]-xli[1]))
-            yli<-c(yli[1]-0.3*abs(yli[2]-yli[1]),yli[2]+0.3*abs(yli[2]-yli[1]))
+            xli<-c(xli[1]-extent*abs(xli[2]-xli[1]),
+                   xli[2]+extent*abs(xli[2]-xli[1]))
+            yli<-c(yli[1]-extent*abs(yli[2]-yli[1]),
+                   yli[2]+extent*abs(yli[2]-yli[1]))
             xygg<-data.frame(x=xli, y=yli)
             grid<-ascgen(xygg, nrcol=grid)
             cellsize<-attr(grid, "cellsize")
@@ -121,10 +124,10 @@
                 cellsize<-ref/ncol(grid)
 
                 ## One adds empty rows and columns to the "core" grid
-                xll<-xll-lx/2
-                yll<-yll-ly/2
-                arajlig<-ceiling((lx/2)/cellsize)
-                arajcol<-ceiling((ly/2)/cellsize)
+                xll<-xll-lx*extent
+                yll<-yll-ly*extent
+                arajlig<-ceiling((lx*extent)/cellsize)
+                arajcol<-ceiling((ly*extent)/cellsize)
                 mrajlig<-matrix(0, ncol=ncol(grid), nrow=arajlig)
                 grid<-rbind(mrajlig, grid, mrajlig)
                 mrajcol<-matrix(0, ncol=arajcol, nrow=nrow(grid))

diff --git a/R/sett0.r b/R/sett0.r
@@ -1,4 +1,4 @@
-## Pour poser le t0 en fonction d'une date de référence
+## Pour poser le t0 en fonction d'une date de reference
 sett0 <- function(ltraj, date.ref, dt,
                   correction.xy=c("none", "cs"), tol=dt/10,
                   units=c("sec", "min", "hour", "day"), ...)

diff --git a/R/subsample.r b/R/subsample.r
@@ -1,4 +1,4 @@
-### Rééchantillonner une trajectoire
+### Reechantillonner une trajectoire
 subsample <- function(ltraj, dt, nlo=1,
                       units=c("sec", "min", "hour", "day"), ...)
 {

diff --git a/man/kernelUD.Rd b/man/kernelUD.Rd
@@ -22,7 +22,7 @@
 }
 \usage{
 kernelUD(xy, id = NULL, h = "href", grid = 40, same4all = FALSE,
-         hlim = c(0.1, 1.5), kern = c("bivnorm", "epa"))
+         hlim = c(0.1, 1.5), kern = c("bivnorm", "epa"), extent = 0.5)
 print.khr(x, \dots)
 image.khr(x, axes = FALSE, mar = c(0,0,2,0),
           addcontour = TRUE, addpoints = TRUE, \dots)
@@ -62,6 +62,9 @@ kernelbb(tr, sig1, sig2, grid = 40, same4all = FALSE, byburst = FALSE)
   \item{kern}{a character string.  If \code{"bivnorm"}, a bivariate
     normal kernel is used.  If \code{"epa"}, an Epanechnikov kernel is
     used.}
+  \item{extent}{a value indicating the extent of the grid used for the
+    estimation (the extent of the grid on the abscissa is equal to
+    \code{(min(xy[,1]) + extent * diff(range(xy[,1])))}).}
   \item{x}{an object of class \code{khr} returned by \code{kernelUD}.}
   \item{axes}{logical.  Whether the axes are to be plotted}
   \item{mar}{the margin parameter (see \code{help(par)})}