multi.focal.function {RSAGA}R Documentation

Focal Grid Function with Multiple Grids as Inputs

Description

multi.focal.function cuts out square or circular moving windows from a stack of grids (matrices) and applies a user-defined matrix function that takes multiple arguments to this data. This is especially useful for applying predict methods of statistical models to a stack of grids containing the explanatory variables (see Examples and grid.predict). The function is suitable for large grid files as it can process them row by row; but it may be slow because one call to the focal function is generated for each grid cell.

Usage

multi.focal.function(in.grids, in.grid.prefix, in.factor.grid, 
    out.grid.prefix, path = NULL, in.path = path, out.path = path,
    fun, in.varnames, out.varnames, radius = 0, is.pixel.radius = TRUE,
    na.strings = "NA",
    valid.ranges, nodata.values = c(), out.nodata.value, 
    search.mode = c("circle","square"),  digits = 4, 
    dec = ".", quiet = TRUE, nlines = Inf, mw.to.vector = FALSE, 
    mw.na.rm = FALSE, pass.location = FALSE, ... )

Arguments

in.grids character vector: file names of input ASCII grids, relative to in.path; in.grid.prefix will be used as a prefix to the file name if specified; default file extension: .asc
in.factor.grid optional file name giving a gridded categorical variables defining zones; zone boundaries are used as breaklines for the moving window (see Details)
in.grid.prefix character string (optional), defining a file name prefix to be used for the input file names; a dash (-) will separate the prefix and the in.varnames
out.grid.prefix character string (optional), defining a file name prefix to be used for the output file names; a dash (-) will separate the prefix and the out.varnames
path path in which to look for in.grids and write output grid files; see also in.path and out.path, which overwrite path if they are specified
in.path path in which to look for in.grids (defaults to path)
out.path path in which to write output grid files; defaults to path
fun a function, or name of a function, to be applied on the moving window; see Details; fun is expected to accept named arguments with the names given by in.varnames; grid.predict is a wrapper function that can be used for applying a model's predict method to a stack of grids; see Details
in.varnames character vector: names of the variables corresponding to the in.grids; if missing, same as in.grids; if specified, must have the same length and order as in.grids
out.varnames character vector specifying the name(s) of the variable(s) returned by fun; if missing, multi.focal.function will try to determine the varnames from fun itself, or or from a call to fun if this is a function (see Details)
radius numeric value specifying the (circular or square) radius of the moving window; see is.pixel.radius and search.mode; note that all data within distance <=radius will be included in the moving window, not <radius.
is.pixel.radius logical: if TRUE (default), the radius will be interpreted as a (possibly non-integer) number of pixels; if FALSE, it is interpreted as a radius measured in the grid (map) units.
valid.ranges optional list of length length(in.grids) with numeric vector of length 2, specifying minimum and maximum valid values read from input file; all values <valid.ranges[[i]][1] or >valid.ranges[[i]][1] will be converted to NA.
nodata.values numeric vector: any values from the input grid file that should be converted to NA, in addition to the nodata value specified in the grid header
out.nodata.value numeric: value used for storing NAs in the output file(s); if missing, use the same nodata value as specified in the header of the input grid file
search.mode character, either "circle" (default) for a circular search window, or "square" for a squared one.
digits numeric, specifying the number of digits to be used for output grid file.
dec character, specifying the decimal mark to be used for input and output.
quiet If TRUE, gives some output ("*") after every 10th line of the grid file and when the job is done.
nlines Number of lines to be processed; useful for testing purposes.
mw.to.vector logical: Should the content of the moving window be coerced (from a matrix) to a vector?
mw.na.rm logical: Should NAs be removed from moving window prior to passing the data to fun? Only applicable when mw.to.vector=TRUE.
pass.location logical: Should the x,y coordinates of grid points (center of grid cells) be passed to fun? If TRUE, two additional arguments named arguments x and y are passed to fun; NOTE: This currently only works for radius=0, otherwise a warning is produced and pass.location is reset to FALSE.
na.strings passed on to scan
... Arguments to be passed to fun; local.function: arguments to be passed to focal.function.

Details

multi.focal.function is probably most useful for applying the predict method of a fitted model to a grids representing the predictor variables. An example is given below and in more detail in Brenning (2008); see also grid.predict.

multi.focal.function extends focal.function by allowing multiple input grids to be passed to the focal function fun operating on moving windows. It passes square matrices of size 2*radius+1 to the function fun if mw.to.vector=FALSE (default), or a vector of length <=(2*radius+1)^2 if mw.to.vector=TRUE; one such matrix or vector per input grid will be passed to fun as an argument whose name is specified by in.varnames.

These matrices or vectors will contain the content of the moving window, which may possibly contain NAs even if the in.grid has no nodata values, e.g. due to edge effects. If search.mode="circle", values more than radius units (pixels or grid units, depending on is.pixel.radius) away from the center pixel / matrix entry will be set to NA. In addition, valid.range, nodata.values, and the nodata values specified in the in.grid are checked to assign further NAs to pixels in the moving window. Finally, if in.factor.grid specifies zones, all pixels in the moving window that belong to a different zone than the center pixel are set to NA, or, in other words, zone boundaries are used as breaklines.

The function fun should return a single numeric value or a numeric vector, such as a regression result or a vector of class probabilities returned by a soft classifier. In addition to the named arguments receiving the moving window data, fun may have additional arguments; the ... argument of focal.function is passed on to fun. grid.predict uses this feature.

Optionally, fun should support the following feature: If no argument is passed to it, then it should return a character vector giving variable names to be used for naming the output grids.

For the input files, .asc is used as the default file extension, if it is not specified by the user.

See focal.function for details.

Value

multi.focal.function returns the character vector of output file names.

Note

multi.focal.function can do all the things focal.function can do.

Author(s)

Alexander Brenning

References

Brenning, A. (2008): Statistical geocomputing combining R and SAGA: The example of landslide susceptibility analysis with generalized additive models. In: J. Boehner, T. Blaschke, L. Montanarella (eds.), SAGA - Seconds Out (= Hamburger Beitraege zur Physischen Geographie und Landschaftsoekologie, 19), 23-32. http://www.environment.uwaterloo.ca/u/brenning/Brenning-2008-RSAGA.pdf

See Also

focal.function, grid.predict

Examples

## Not run: 
# Assume that d is a data.frame with point observations
# of a numerical response variable y and predictor variables
# a, b, and c.
# Fit a generalized additive model to y,a,b,c.
# We want to model b and c as nonlinear terms:
require(gam)
fit <- gam(y ~ a + s(b) + s(c), data = d)
multi.focal.function(in.grids = c("a", "b", "c"),
    out.varnames = "pred",
    fun = grid.predict, fit = fit )
    # Note that the 'grid.predict' uses by default the
    # predict method of 'fit'.
# Model predictions are written to a file named pred.asc
## End(Not run)

## Not run: 
# A fake example of a logistic additive model:
require(gam)
fit <- gam(cl ~ a + s(b) + s(c), data = d, family = binomial)
multi.focal.function(in.grids = c("a", "b", "c"),
    out.varnames = "pred",
    fun = grid.predict, fit = fit,
    control.predict = list(type = "response") )
    # 'control.predict' is passed on to 'grid.predict', which
    # dumps its contents into the arguments for 'fit''s
    # 'predict' method.
# Model predictions are written to a file named pred.asc
## End(Not run)

[Package RSAGA version 0.9-4 Index]