This is a method for the generic function `subset`

.
It extracts the subset of points of `x`

that satisfy the logical expression
`subset`

, and retains only the columns of marks that are
specified by the expression `select`

. The result is always a point
pattern, with the same window as `x`

.

The argument `subset`

determines the subset of points that
will be extracted. It should be a logical expression.
It may involve the variable names
`x`

and `y`

representing the Cartesian coordinates;
the names of other spatial coordinates or local coordinates;
the name `marks`

representing the marks;
and (if there is more than one column of marks)
the names of individual columns of marks.
The default is to keep all points.

The argument `select`

determines which columns of marks
will be retained (if there are several columns of marks).
It should be an expression involving the names of columns of marks
(which will be interpreted as integers representing the positions of
these columns). For example if there are columns of marks named
`A`

to `Z`

, then `select=D:F`

is a valid expression
and means that columns `D`

, `E`

and `F`

will be
retained. Similarly `select=-(A:C)`

is valid and means that columns
`A`

to `C`

will be deleted.
The default is to retain all columns.

Setting `subset=FALSE`

will produce an empty point pattern
(i.e. containing zero points) in the same window as `x`

.
Setting `select=FALSE`

or `select= -marks`

will
remove all the marks from `x`

.

The argument `drop`

determines whether to remove
unused levels of a factor, if the resulting point pattern is multitype
(i.e. the marks are a factor) or if the marks are a data frame
in which some of the columns are factors.

The result is always a point pattern, of the same class as `x`

.
Spatial coordinates (and local
coordinates) are always retained. To extract only some
columns of marks or coordinates as a data frame,
use `subset(as.data.frame(x), ...)`