Divides a multidimensional point pattern into several sub-patterns, according to their marks, or according to any user-specified grouping.
A multi-dimensional point pattern.
An object of class
Data determining the grouping. Either a factor, or the name of one of the columns of marks.
Logical. Determines whether empty groups will be deleted.
Logical. Determines whether the resulting subpatterns will be unmarked (i.e. whether marks will be removed from the points in each subpattern).
Other arguments are ignored.
The generic command
split allows a dataset to be separated
into subsets according to the value of a grouping variable.
split.ppx is a method for the generic
split for the class
"ppx" of multidimensional
point patterns. It divides up the points of the point pattern
into several sub-patterns according to the values of
The result is a list of point patterns.
f may be
a factor, of length equal to the number of points in
The levels of
determine the destination of each point in
ith point of
x will be placed in the sub-pattern
l = f[i].
a character string, matching the name of one of the columns of
marks(x) is a data frame. This column should
be a factor.
f is missing, then it will be determined by the
marks of the point pattern. The pattern
x can be either
a multitype point pattern
(a marked point pattern whose marks vector is a factor).
f is taken to be the marks vector.
The effect is that the points of each type
are separated into different point patterns.
a marked point pattern with a data frame or hyperframe
of marks, containing at least one
column that is a factor. The first such column will be used to
determine the splitting factor
Some of the sub-patterns created by the split
may be empty. If
drop=TRUE, then empty sub-patterns will
be deleted from the list. If
drop=FALSE then they are retained.
un determines how to handle marks
in the case where
x is a marked point pattern.
un=TRUE then the marks of the
points will be discarded when they are split into groups,
un=FALSE then the marks will be retained.
un are both missing,
then the default is
un=TRUE for multitype point patterns
un=FALSE for marked point patterns with a data frame of
The result of
split.ppx has class
"anylist". There are methods for
A list of point patterns.
The components of the list are named by the levels of
The list also has the class
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