boundingbox.list
is designed to be used on objects that
contain 3D point information and for which xyzmatrix
is defined.
boundingbox.shape3d
is designed to be used on objects
that contain 3D point information and inherit from rgl
's
shape3d
class and for which xyzmatrix
is defined. Presently
this applies to mesh3d
objects.
Set the bounding box of an im3d object
boundingbox(x, ...)# S3 method for im3d
boundingbox(x, dims = dim(x), ...)
# S3 method for character
boundingbox(x, ...)
# S3 method for list
boundingbox(x, na.rm = FALSE, ...)
# S3 method for neuron
boundingbox(x, na.rm = FALSE, ...)
# S3 method for shape3d
boundingbox(x, na.rm = FALSE, ...)
# S3 method for default
boundingbox(x, dims, input = c("boundingbox", "bounds"), ...)
boundingbox(x) <- value
a matrix
with 2 rows and 3 columns with
class='boundingbox'
or NULL when missing.
A vector or matrix specifying a bounding box, an im3d
object,
any object with base class list for which xyzmatrix
can
extract 3D points (e.g. neurons, surfaces etc), or, for
boundingbox.character
, a character vector specifying a file.
Additional arguments for methods
The number of voxels in each dimension when x is a BoundingBox matrix.
Whether to ignore NA points (default FALSE
)
Whether x
defines the boundingbox or bounds of the image
(see details).
The object which will provide the new boundingbox information.
This can be be either an im3d object with a boundingbox or a vector or
matrix defined according to boundingbox.default
.
The bounding box is defined as the position of the voxels at the two
opposite corners of the cuboid encompassing an image, when each voxel
is assumed to have a single position (sometimes thought of as its centre)
and no physical extent. When written as a vector it should look
like: c(x0,x1,y0,y1,z0,z1)
. When written as a matrix it should look
like: rbind(c(x0,y0,z0),c(x1,y1,z1))
where x0,y0,z0 is the position
of the origin.
Note that there are two competing definitions for the physical extent of an
image that are discussed e.g.
https://teem.sourceforge.net/nrrd/format.html. The definition that
makes most sense depends largely on whether you think of a pixel as a
little square with some defined area (and therefore a voxel as a cube with
some defined volume) or you take the view that you can only define
with certainty the grid points at which image data was acquired. The first
view implies a physical extent which we call the bounds=dim(x) *
c(dx,dy,dz)
; the second is defined as BoundingBox=dim(x)-1 *
c(dx,dy,dz)
and assumes that the extent of the image is defined by a
cuboid including the sample points at the extreme corner of the grid. Amira
takes this second view and this is the one we favour given our background
in microscopy. If you wish to convert a bounds
type definition into
an im3d BoundingBox, you should pass the argument input='bounds'
.
plot3d.boundingbox
Other im3d:
as.im3d()
,
im3d-coords
,
im3d-io
,
im3d()
,
imexpand.grid()
,
imslice()
,
is.im3d()
,
mask()
,
origin()
,
projection()
,
threshold()
,
unmask()
,
voxdims()
boundingbox(c(x0=0,x1=10,y0=0,y1=20,z0=0,z1=30))
# bounding box for a neuron
boundingbox(Cell07PNs[[1]])
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