interp.old: Gridded Bivariate Interpolation for Irregular Data

Description Usage Arguments Details Value Note References See Also

Description

These functions implement bivariate interpolation onto a grid for irregularly spaced input data. These functions are only for backward compatibility, use interp instead.

Usage

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interp.old(x, y, z, xo= seq(min(x), max(x), length = 40),
           yo=seq(min(y), max(y), length = 40), ncp = 0,
           extrap=FALSE, duplicate = "error", dupfun = NULL)
interp.new(x, y, z, xo = seq(min(x), max(x), length = 40),
           yo = seq(min(y), max(y), length = 40), linear = FALSE,
           ncp = NULL, extrap=FALSE, duplicate = "error", dupfun = NULL)

Arguments

x

vector of x-coordinates of data points or a SpatialPointsDataFrame object. Missing values are not accepted.

y

vector of y-coordinates of data points. Missing values are not accepted.

If left as NULL indicates that x should be a SpatialPointsDataFrame and z names the variable of interest in this dataframe.

z

vector of z-coordinates of data points or a character variable naming the variable of interest in the SpatialPointsDataFrame x.

Missing values are not accepted.

x, y, and z must be the same length (execpt if x is a SpatialPointsDataFrame) and may contain no fewer than four points. The points of x and y cannot be collinear, i.e, they cannot fall on the same line (two vectors x and y such that y = ax + b for some a, b will not be accepted). interp is meant for cases in which you have x, y values scattered over a plane and a z value for each. If, instead, you are trying to evaluate a mathematical function, or get a graphical interpretation of relationships that can be described by a polynomial, try outer().

xo

vector of x-coordinates of output grid. The default is 40 points evenly spaced over the range of x. If extrapolation is not being used (extrap=FALSE, the default), xo should have a range that is close to or inside of the range of x for the results to be meaningful.

yo

vector of y-coordinates of output grid; analogous to xo, see above.

linear

logical – indicating wether linear or spline interpolation should be used. supersedes old ncp parameter

ncp

deprecated, use parameter linear. Now only used by interp.old().

old meaning was: number of additional points to be used in computing partial derivatives at each data point. ncp must be either 0 (partial derivatives are not used), or at least 2 but smaller than the number of data points (and smaller than 25).

extrap

logical flag: should extrapolation be used outside of the convex hull determined by the data points?

duplicate

character string indicating how to handle duplicate data points. Possible values are

"error"

produces an error message,

"strip"

remove duplicate z values,

"mean","median","user"

calculate mean , median or user defined function (dupfun) of duplicate z values.

dupfun

a function, applied to duplicate points if duplicate= "user".

Details

see interp

Value

list with 3 components:

x,y

vectors of x- and y- coordinates of output grid, the same as the input argument xo, or yo, if present. Otherwise, their default, a vector 40 points evenly spaced over the range of the input x.

z

matrix of fitted z-values. The value z[i,j] is computed at the x,y point xo[i], yo[j]. z has dimensions length(xo) times length(yo).

If input is a SpatialPointsDataFrame a SpatialPixelssDataFrame is returned.

Note

interp.new is deprecated and interp.old will soon be deprecated.

References

Akima, H. (1978). A Method of Bivariate Interpolation and Smooth Surface Fitting for Irregularly Distributed Data Points. ACM Transactions on Mathematical Software 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 22, 362–371.

See Also

contour, image, approx, spline, aspline, outer, expand.grid.


akima documentation built on May 29, 2017, 6:47 p.m.