# split.ppp

##### Divide Point Pattern into Sub-patterns

Divides a point pattern into several sub-patterns, according to their marks, or according to any user-specified grouping.

- Keywords
- spatial

##### Usage

```
split.ppp(x, f = x$marks)
split(x, f) <- value
```

##### Arguments

- x
- A two-dimensional point pattern.
An object of class
`"ppp"`

. - f
- Factor determining the grouping.
- value
- List of point patterns.

##### Details

The function `split.ppp`

divides up the points of the point pattern `x`

into several sub-patterns according to the levels of the factor
`f`

. The result is a list of point patterns, one for each
level of `f`

.

If `f`

is present, it must be a factor, and its length
must equal the number of points in `x`

. The levels of `f`

determine the destination of each point in `x`

.
The `i`

th point of `x`

will be placed in the sub-pattern
`split.ppp(x)$l`

where `l = f[i]`

.

If `f`

is missing, then `x`

must be a multitype point pattern
(a marked point pattern whose marks vector is a factor).
Then the effect is that the points of each type
are separated into different point patterns.

The result of `split.ppp`

has class `"splitppp"`

and can be plotted using `plot.splitppp`

.

The assignment function `split<-.ppp`

updates the point pattern `x`

so that
it satisfies `split(x, f) = value`

. The argument `value`

is expected to be a list of point patterns, one for each level of
`f`

. These point patterns are expected to be compatible in the sense
that they all have the same window, and either they are all unmarked
or they all have marks of the same kind.

Splitting can also be undone by the function `superimpose`

.

##### Value

- The value of
`split.ppp`

is a list of point patterns. The components of the list are named by the levels of`f`

.The assignment form

`split<-.ppp`

returns the updated point pattern`x`

.

##### synopsis

split.ppp(x, f = x$marks)

##### See Also

##### Examples

```
# Multitype point pattern: separate into types
data(amacrine)
u <- split(amacrine)
# the following are equivalent:
amon <- amacrine[amacrine$marks == "on"]
amon <- split(amacrine)$on
# plot them
plot(split(amacrine))
# Scramble the locations of the 'on' cells
u <- unmark(split(amacrine))
u$on <- runifpoint(amon$n, amon$window)
split(amacrine) <- u
# Point pattern with continuous marks
data(longleaf)
<testonly># smaller dataset
longleaf <- longleaf[seq(1, longleaf$n, by=80)]</testonly>
# cut the range of tree diameters into three intervals
long3 <- cut.ppp(longleaf, 3)
# now split them
long3split <- split(long3)
# Unmarked point pattern
data(swedishpines)
# cut & split according to nearest neighbour distance
f <- cut(nndist(swedishpines), 3)
u <- split(swedishpines, f)
```

*Documentation reproduced from package spatstat, version 1.5-5, License: GPL version 2 or newer*