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# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received A copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA 02111-1307 USA
################################################################################
# FUNCTION: DESCRIPTION:
# akimaInterp Interpolates irregularly spaced points
# akimaInterpp Interpolates and smoothes pointwise
################################################################################
akimaInterp <-
function(x, y = NULL, z = NULL, gridPoints = 21,
xo = seq(min(x), max(x), length = gridPoints),
yo = seq(min(y), max(y), length = gridPoints), extrap = FALSE)
{
# A function implemented by Diethelm Wuertz
### ==> ../man/stats-interpAkima.Rd
### ~~~~~~~~~~~~~~~~~~~~
# Description:
# Interpolates and Smoothes Irregularly Distributed Data Points
# Arguments:
# x, y, z - either three numeric vectors of equal length or if
# y and z are NULL, a list with entries x, y, a, or named
# data.frame with x in the first, y in the second, and z in
# the third column.
# gridPoints - number of grid points in x and y direction.
# xo, yo, a sequence of data points spanning the grid
# extrap - a logical, if TRUE then the data points are extrapolated.\
# Value:
# A list with three elements, $x and $y which are vectors of length
# 'gridPoints' and $z which is a matrix of size 'gridPoints^2'.
# Example:
# set.seed(1953)
# x = runif(999)-0.5; y = runif(999)-0.5; z = cos(2*pi*(x^2+y^2))
# ans = akimaInterp(x, y, z, extrap = FALSE)
# persp(ans, theta = -50, phi = 30, col = "steelblue")
# ans = akimaInterp(x, y, z, extrap = TRUE)
# persp(ans, theta = -50, phi = 30, col = "steelblue")
# FUNCTION:
if (!requireNamespace("interp", quietly = TRUE))
stop("Needs Package 'interp' which is not installed")
# Arguments:
if (is.data.frame(x))
x <- as.matrix.data.frame(x)
else if (is.list(x))
x <- matrix(unlist(x), ncol = 3)
if (is.matrix(x)) {
z = x[, 3]
y = x[, 2]
x = x[, 1]
}
# Interpolation:
ans <- interp::interp(x, y, z, xo, yo, linear = FALSE,
extrap = extrap, duplicate = "median", dupfun = NULL)
colnames(ans$z) <- as.character(signif(ans$x, round(log(gridPoints), 0)))
rownames(ans$z) <- as.character(signif(ans$y, round(log(gridPoints), 0)))
class(ans) <- "gridData"
# Return Value:
ans
}
# ------------------------------------------------------------------------------
akimaInterpp <-
function(x, y = NULL, z = NULL, xo, yo, extrap = FALSE)
{
# A function implemented by Diethelm Wuertz
# Description:
# Interpolates and Smoothes Irregularly Distributed Data Points
# Arguments:
# x, y, z - either three numeric vectors of equal length or if
# y and z are NULL, a list with entries x, y, a, or named
# data.frame with x in the first, y in the second, and z in
# the third column.
# gridPoints - number of grid points in x and y direction.
# xo, yo, a sequence of data points for pointwise interpolation
# Note:
# Extrapolation is not possible in the case of linear interpolation.
# Value:
# A list with three elements, $x and $y which are vectors of length
# 'gridPoints' and $z which is a matrix of size 'gridPoints^2'.
# Example:
# set.seed(1953)
# x = runif(999)-0.5; y = runif(999)-0.5; z = cos(2*pi*(x^2+y^2))
# ans = akimaInterpp(x, y, z, c(mean(x), 0, 100), c(mean(y), 0, 100))
# persp(ans, theta = -50, phi = 30, col = "steelblue")
# FUNCTION:
if (!requireNamespace("interp", quietly = TRUE))
stop("Needs package 'interp' which is not installed")
# Arguments:
if (is.data.frame(x))
x <- as.matrix.data.frame(x)
else if (is.list(x))
x <- matrix(unlist(x), ncol = 3)
if (is.matrix(x)) {
z = x[, 3]
y = x[, 2]
x = x[, 1]
}
# Settings:
duplicate = "median"
dupfun = NULL
linear = TRUE
# Interpolation:
interpp <- eval(parse(text=paste0("interp",":::","interpp")))
ans <- interpp(x, y, z, xo, yo, linear = FALSE,
extrap = extrap, duplicate = "median", dupfun = NULL)
ans <- data.frame(matrix(unlist(t(ans)), 3))
colnames(ans) = c("x", "y", "z")
# Return Value:
ans
}
################################################################################
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