# cut.lpp

##### 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.

##### 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.

##### See Also

##### 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 1.52-1, License: GPL (>= 2)*