rasterImage
. It is also possible to copy
a 2D depiction to the system clipboard, which can then be pasted into
various external applications.view.molecule.2d(molecule, ncol = 4, cellx = 200, celly = 200)
view.image.2d(molecule, width = 200, height = 200)
copy.image.to.clipboard(molecule, width = 200, height = 200)
IAtomContainer
object. If multiple molecules
are to be viewed this should be a list
of such objects. If a
character is specified then it is taken asview.molecule.2d
and copy.image.to.ckipboard
do not return anything.
view.image.2d
returns
an array of the dimensions height x width x channels, from the original
PNG version of the 2D depiction.view.molecule.2d
, if a jobjRef
is passed it should be a reference to an
IAtomContainer
object. In case the first argument is of class
character it is assumed to be a file and is loaded by the function.
This function can be used to view a single molecule or multiple
molecules. If a list
of molecule objects is supplied the
molecules are displayed as a grid of 2D viewers. In case a file is
specified, it will display a single molecule or multiple molecules
depending on how many molecules are loaded. For view.image.2d
, the image can be viewed via rasterImage
.
copy.image.to.clipboard
copies the 2D depiction to the system clipboard in
PNG format. You can then paste into other applications.
Due to event handling issues, the depiction will show on OS X, but
the window will be unresponsive. Also copying images to the clipboard will not work.
As a result, on OS X we make use of a standalone
helper that is run via the system
command. Currently, this is supported
for the view.molecule.2d
method (for a single molecule) and the
copy.image.to.clipboard
method. In the future, other view methods will also
be accessible via this mechanism. While this allows OS X users to view molecules, it is
slow due to invoking a new process.
The depictions will work fine (i.e., no need to shell out) on Linux and Windows.
view.table
, rasterImage
, link{readPNG}
m <- parse.smiles('c1ccccc1C(=O)NC')[[1]]
img <- view.image.2d(m, 100,100)
plot(1:10, 1:10, pch=19)
rasterImage(img, 0,8, 2,10)
Run the code above in your browser using DataLab