View source: R/profoundSegim.R
profoundSegimGroup | R Documentation |
Given an input segmentation map, returns a map of groups of touching segments as well as the IDs of segments within each group.
profoundSegimGroup(segim = NULL)
segim |
Integer matrix; required, the segmentation map. |
profoundSegimGroup
uses the label
function from imager, so to use this function you will need to have imager installed. Since this can be a bit cumbersome on some platforms (given its dependencies) this is only listed as a suggested package.
A list containting the following structures:
groupim |
An map of the unique groups identified in the input segim, where the groupID is the same as the lowest valued segID in the group. |
groupsegID |
A data.frame of lists giving the segIDs of segments in each group. |
The data.frame returned by groupsegID is a slightly unusal structure to see in R, but it allows for a compact manner of storing uneven vectors of grouped segments. E.g. you might have a massive group containing 30 other segments and many groups containing a single segment. Padding a normal matrix out to accommodate the larger figure would be quite inefficient. It contains the following:
groupID |
Group ID, which can be matched against values in groupim |
segID |
An embedded list of segmentation IDs for segments in the group. I.e. each list element of segID is a vector (see Examples for clarity). |
Ngroup |
The total number of segments that are in the group. |
Npix |
The total number of pixels that are in the group. |
Aaron Robotham
profoundSegimNear
, ~~~
## Not run:
image = Rfits_read_image(system.file("extdata", 'VIKING/mystery_VIKING_Z.fits',
package="ProFound"))
profound=profoundProFound(image, skycut=1.5, magzero=30, verbose=TRUE)
#Look for nearby (in this case touching) neighbours
group=profoundSegimGroup(profound$segim)
#Look at the first few rows (groups 1:5):
group$groupsegID[1:5,]
#To access the embedded vectors you have to use unlist:
unlist(group$groupsegID[1,2])
#We can check to see which segments are in group number 1:
profoundSegimPlot(image$imDat, profound$segim)
magimage(group$groupim==1, col=c(NA,'red'), add=TRUE)
## End(Not run)
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