https://github.com/cran/fields
Tip revision: 292e80962d92c497484ad0735f3f13a4b8d3e0ac authored by Doug Nychka on 29 November 2007, 14:39:12 UTC
version 4.1
version 4.1
Tip revision: 292e809
as.image.Rd
\name{as.image}
\alias{as.image}
\title{
Creates image from irregular x,y,z
}
\description{
Discretizes a set of 2-d locations to a grid and produces a image object
with the z values in the right cells. For cells with more than one Z
value the average is used.
}
\usage{
as.image(Z, ind=NULL, grid=NULL, x=NULL, nrow=64, ncol=64,weights=NULL,
na.rm=FALSE, nx=NULL,ny=NULL, boundary.grid=FALSE)
}
\arguments{
\item{Z}{
Values of image
}
\item{ind}{
A matrix giving the row and column subscripts for each image
value in Z. (Not needed if x is specified.)
}
\item{grid}{
A list with components x and y of equally spaced values describing the
centers of the grid points. The default is to use nrow and ncol and the
ranges of the data locations (x) to construct a grid.
}
\item{x}{
Locations of image values. Not needed if ind is specified.
}
\item{nrow}{
Number of rows in image matrix ( x-axis direction)
}
\item{ncol}{
Number of columns in image matrix ( y-axis direction)
}
\item{weights}{
If two or more values fall into the same
pixel a weighted average is used to represent the pixel value. Default is
equal weights.
}
\item{na.rm}{
If true NA's are removed from the Z vector.}
\item{nx}{ Same as nrow}
\item{ny}{ Same as ncol}
\item{boundary.grid} { If FALSE grid points are assumed to be the
midpoints. If TRUE they are the grid box boundaries.}
}
\value{
An list in image format with a few more components. Components x and y are
the grid values , z is a
nrow X ncol matrix
with the Z values. NA's are placed at cell locations where Z data has
not been supplied.
Component ind is a 2 column matrix with subscripts for the locations of
the values in the image matrix.
Component weights is an image matrix with the sum of the
individual weights for each cell. If no weights are specified the
default for each observation is one and so the weights will be the
number of observations in each bin.
}
\details{
The discretization is straightforward once the grid is determined.
If two or more Z values have locations in the same cell the weighted
average value is taken as the value. The weights component that is
returned can be used to account for means that have different numbers
(or precisions) of observations contributing to the grid point averages.
The default weights are taken to be one for each observation.
See the source code to modify this to get more
information about coincident locations. (See the call to fast.1way)
}
\seealso{
image.smooth, image.plot, Krig.discretize, Krig.replicates
}
\examples{
# convert precip data to 50X50 image
look<- as.image( RMprecip$y, x= RMprecip$x, nrow=50, ncol=50)
image.plot( look)
# number of obs in each cell -- in this case equal to the
# aggregated weights because each obs had equal wieght in the call
image.plot( look$x ,look$y, look$weights, col=terrain.colors(50))
# hot spot is around Denver
}
\keyword{manip}
% docclass is function
% Converted by Sd2Rd version 1.21.