# cut.lpp

0th

Percentile

##### Classify Points in a Point Pattern on a Network

For a point pattern on a linear network, classify the points into distinct types according to the numerical marks in the pattern, or according to another variable.

Keywords
methods, spatial
##### Usage
# S3 method for lpp
cut(x, z=marks(x), ...)
##### Arguments
x

A point pattern on a linear network (object of class "lpp").

z

Data determining the classification. A numeric vector, a factor, a pixel image on a linear network (class "linim"), a function on a linear network (class "linfun"), a tessellation on a linear network (class "lintess"), a string giving the name of a column of marks, or one of the coordinate names "x", "y", "seg" or "tp".

Arguments passed to cut.default. They determine the breakpoints for the mapping from numerical values in z to factor values in the output. See cut.default.

##### Details

This function has the effect of classifying each point in the point pattern x into one of several possible types. The classification is based on the dataset z, which may be either

• a factor (of length equal to the number of points in z) determining the classification of each point in x. Levels of the factor determine the classification.

• a numeric vector (of length equal to the number of points in z). The range of values of z will be divided into bands (the number of bands is determined by …) and z will be converted to a factor using cut.default.

• a pixel image on a network (object of class "linim"). The value of z at each point of x will be used as the classifying variable.

• a function on a network (object of class "linfun", see linfun). The value of z at each point of x will be used as the classifying variable.

• a tessellation on a network (object of class "lintess", see lintess). Each point of x will be classified according to the tile of the tessellation into which it falls.

• a character string, giving the name of one of the columns of marks(x), if this is a data frame.

• a character string identifying one of the coordinates: the spatial coordinates "x", "y" or the segment identifier "seg" or the fractional coordinate along the segment, "tp".

The default is to take z to be the vector of marks in x (or the first column in the data frame of marks of x, if it is a data frame). If the marks are numeric, then the range of values of the numerical marks is divided into several intervals, and each interval is associated with a level of a factor. The result is a marked point pattern, on the same linear network, with the same point locations as x, but with the numeric mark of each point discretised by replacing it by the factor level. This is a convenient way to transform a marked point pattern which has numeric marks into a multitype point pattern, for example to plot it or analyse it. See the examples.

To select some points from x, use the subset operators [.lpp or subset.lpp instead.

##### Value

A multitype point pattern on the same linear network, that is, a point pattern object (of class "lpp") with a marks vector that is a factor.

cut, lpp, lintess, linfun, linim

• cut.lpp
##### Examples
# NOT RUN {
X <- runiflpp(20, simplenet)
f <- linfun(function(x,y,seg,tp) { x }, simplenet)
plot(cut(X, f, breaks=4))
plot(cut(X, "x", breaks=4))
plot(cut(X, "seg"))
# }

Documentation reproduced from package spatstat, version 1.57-1, License: GPL (>= 2)

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