Find the smallest rectangle containing a given window(s), image(s) or point pattern(s).
boundingbox(…)# S3 method for default
boundingbox(…)
# S3 method for im
boundingbox(…)
# S3 method for owin
boundingbox(…)
# S3 method for ppp
boundingbox(…)
# S3 method for psp
boundingbox(…)
# S3 method for lpp
boundingbox(…)
# S3 method for linnet
boundingbox(…)
# S3 method for solist
boundingbox(…)
One or more windows (objects of class "owin"
),
pixel images (objects of class "im"
) or
point patterns (objects of class "ppp"
or "lpp"
)
or line segment patterns (objects of class "psp"
)
or linear networks (objects of class "linnet"
)
or any combination of such objects.
Alternatively, the argument may be a list of such objects,
of class "solist"
.
This function finds the smallest rectangle (with sides parallel to the coordinate axes) that contains all the given objects.
For a window (object of class "owin"
), the bounding box
is the smallest rectangle that contains all the vertices of the
window (this is generally smaller than the enclosing frame,
which is returned by as.rectangle
).
For a point pattern (object of class "ppp"
or "lpp"
),
the bounding box
is the smallest rectangle that contains all the points of the pattern.
This is usually smaller than the bounding box of the window of the
point pattern.
For a line segment pattern (object of class "psp"
)
or a linear network (object of class "linnet"
), the
bounding box is the smallest rectangle that contains all endpoints
of line segments.
For a pixel image (object of class "im"
), the image will
be converted to a window using as.owin
,
and the bounding box of this window is obtained.
If the argument is a list of several objects, then this function finds the smallest rectangle that contains all the bounding boxes of the objects.
# NOT RUN {
w <- owin(c(0,10),c(0,10), poly=list(x=c(1,2,3,2,1), y=c(2,3,4,6,7)))
r <- boundingbox(w)
# returns rectangle [1,3] x [2,7]
w2 <- unit.square()
r <- boundingbox(w, w2)
# returns rectangle [0,3] x [0,7]
# }
Run the code above in your browser using DataLab