add last changes from Martin Maechler

ready for release as 0.5-1

INDEX

@@ -3,5 +3,5 @@ akima                   Waveform Distortion Data for Bivariate
 aspline                 Univariate Akima interpolation
 interp                  Gridded Bivariate Interpolation for Irregular
                         Data
-interpp                 Pointwise Bivariate Interpolation for Irregular
-                        Data
+interpp                 Pointwise Bivariate Interpolation for
+                        Irregular Data

R/interp.new.R

@@ -7,18 +7,14 @@ interp.new <-
   if(!(all(is.finite(x)) && all(is.finite(y)) && all(is.finite(z))))
     stop("missing values and Infs not allowed")
   if(!is.null(ncp)) {
-    if(ncp != 0) {
-      cat("ncp not supported, it is automatically choosen by Fortran code\n")
-    }
-    else {
-      cat("linear interpolation not yet implemented with interp.new().\n")
-      stop("use interp.old().")
-    }
-  }
-  if(linear) {
-    cat("linear interpolation not yet implemented with interp.new().\n")
-    stop("use interp.old().")
+    if(ncp != 0)
+	warning("'ncp' not supported, it is automatically choosen by Fortran code\n")
+    else
+	linear <- TRUE
   }
+  if(linear)
+    stop("linear interpolation not implemented in interp.new().\n",
+	 "use 'interp()' (or 'interp.old()').")
 
   drx <- diff(range(x))
   dry <- diff(range(y))

man/interp.Rd

@@ -107,8 +107,9 @@ interp.new(x, y, z, xo = seq(min(x), max(x), length = 40),
   possible, but is deprecated.
 
   The resulting structure is suitable for input to the
-  functions \code{contour} and \code{image}.  Check the requirements of
-  these functions when choosing values  for \code{xo} and \code{yo}.
+  functions \code{\link{contour}} and \code{\link{image}}.  Check
+  the requirements of these functions when choosing values  for
+  \code{xo} and \code{yo}.
 }
 \details{
   If \code{linear} is \code{TRUE} (default), linear
@@ -125,26 +126,23 @@ interp.new(x, y, z, xo = seq(min(x), max(x), length = 40),
   user defined function).
 
   The triangulation scheme used by \code{interp} works well if \code{x}
-  and \code{y} have
-  similar scales but will appear stretched if they have very different
-  scales.  The spreads of \code{x} and \code{y} must be within four
-  orders of magnitude of each other for \code{interp} to work.
+  and \code{y} have similar scales but will appear stretched if they have
+  very different scales.  The spreads of \code{x} and \code{y} must be
+  within four orders of magnitude of each other for \code{interp} to work.
 }
 \references{
   Akima, H. (1978). A Method of Bivariate Interpolation and
   Smooth Surface Fitting for Irregularly Distributed Data Points.
-  ACM Transactions on Mathematical Software,
-  \bold{4}, 148-164.
+  ACM Transactions on Mathematical Software \bold{4}, 148-164.
 
   Akima, H. (1996). Algorithm 761: scattered-data surface fitting that has
   the accuracy of a cubic polynomial.
-  ACM Transactions on Mathematical Software,
-  \bold{22}, 362--371
-
+  ACM Transactions on Mathematical Software \bold{22}, 362--371.
 }
 \seealso{
   \code{\link{contour}}, \code{\link{image}},
   \code{\link{approx}}, \code{\link{spline}},
+  \code{\link{aspline}},
   \code{\link{outer}}, \code{\link{expand.grid}}.
 }
 \examples{
@@ -162,8 +160,8 @@ points (akima, pch = 3)
 akima.smooth <-
  with(akima, interp(x, y, z, xo=seq(0,25, length=100),
                     yo=seq(0,20, length=100)))
-image  (akima.smooth)
-contour(akima.smooth, add=TRUE)
+image  (akima.smooth, main = "interp(<akima data>, *) on finer grid")
+contour(akima.smooth, add = TRUE, col = "thistle")
 points(akima, pch = 3, cex = 2, col = "blue")
 # use triangulation package to show underlying triangulation:
 if(library(tripack, logical.return=TRUE))
@@ -171,9 +169,9 @@ if(library(tripack, logical.return=TRUE))
 
 # use only 15 points (interpolation only within convex hull!)
 akima.part <- with(akima, interp(x[1:15], y[1:15], z[1:15]))
-image  (akima.part)
+image  (akima.part, "interp() on subset of only 15 points")
 contour(akima.part, add=TRUE)
-points(akima$x[1:15],akima$y[1:15])
+points(akima$x[1:15],akima$y[1:15], col = "blue")
 
 ## spline interpolation, two variants (AMS 526 "Old", AMS 761 "New")
 ## -----------------------------------------------------------------
@@ -184,7 +182,7 @@ table(is.na(akima.sO$z)) ## 3990 NA's; = 40 \%
 akima.sO <- with(akima,
    interp.old(x,y,z, xo=seq(0,25, length=100), yo=seq(0,20, len=100), ncp = 4))
 sum(is.na(akima.sO$z)) ## still 3429
-image  (akima.sO) # almost useless
+image  (akima.sO, main = "interp.old(*, ncp = 4) [almost useless]")
 contour(akima.sO, add = TRUE)
 
 ## "New:"
@@ -195,7 +193,8 @@ akima.spl <- with(akima, interp(x,y,z, xo=seq(0,25, length=100),
                                        yo=seq(0,20, length=100),
                                 linear=FALSE))
 
-contour(akima.spl) ; points(akima)
+contour(akima.spl, main = "smooth  interp(*, linear = FALSE)")
+points(akima)
 
 full.pal <- function(n) hcl(h = seq(340, 20, length = n))
 cool.pal <- function(n) hcl(h = seq(120, 0, length = n) + 150)
@@ -203,6 +202,7 @@ warm.pal <- function(n) hcl(h = seq(120, 0, length = n) - 30)
 
 filled.contour(akima.spl, color.palette = full.pal,
         plot.axes = { axis(1); axis(2);
+                      title("smooth  interp(*, linear = FALSE");
                       points(akima, pch = 3, col= hcl(c=100, l = 20))})
 # no extrapolation!
 

man/interpp.Rd

@@ -120,7 +120,10 @@ dupfun = NULL, ncp)
   \bold{22}, 362-371.
 }
 \seealso{
-  \code{\link[base]{contour}}, \code{\link[base]{image}}, \code{\link[base]{approx}}, \code{\link[base]{spline}}, \code{\link[base]{outer}}, \code{\link[base]{expand.grid}},\code{\link{interp}}.
+  \code{\link[base]{contour}}, \code{\link[base]{image}}, 
+  \code{\link[base]{approx}}, \code{\link[base]{spline}}, 
+  \code{\link[base]{outer}}, \code{\link[base]{expand.grid}},
+  \code{\link{interp}}, \code{\link{aspline}}.
 }
 \examples{
 data(akima)