Description Usage Arguments Value Author(s) See Also Examples
Assign a shared "dupGroup" number to each duplicated interaction, here defined as A.canonical, type, B.canonical. All other information about the interaction is ignored. An A-B interaction is treated the same as a B-A interaction. This assessment prepares a possibly large interaction set for scrutiny by eye, or programmatically, for filtering, in which a single preferred interaction can be selected, out of each dupGroup, for further use.
Note that preferred.interaction.types elements may be substrings of the full (and often unwieldy) interaction type names used in the underlying data.
1 2 | pickBestFromDupGroup(dupGrp, tbl.dups,
preferred.interaction.types)
|
dupGrp |
an integer |
tbl.dups |
data.frame, returned by detectDuplicateInteractions. |
preferred.interaction.types |
list of character strings |
The row name (or names, for dupGroup 0) of the tbl.dups row which is the best match to the ordered list of preferred.interaction.types.
Paul Shannon
RefNet, providerClasses, interactions, addStandardNames, detectDuplicateInteractions
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | filename <- system.file(package="RefNet", "extdata", "tbl.dups.RData")
load(filename)
preferred.types <- c("direct", "physical", "aggregation")
# get the best from dupGroup 1
best.1 <- pickBestFromDupGroup(1, tbl.dups, preferred.types)
tbl.dups[best.1, c("A.common", "B.common", "type", "provider", "publicationID")]
# get all of the best. not every dupGroup will pass muster
dupGroups <- sort(unique(tbl.dups$dupGroup))
bestOfDups <- unlist(lapply(dupGroups, function(dupGroup)
pickBestFromDupGroup(dupGroup, tbl.dups, preferred.types)))
deleters <- which(is.na(bestOfDups))
if(length(deleters) > 0)
bestOfDups <- bestOfDups[-deleters]
length(bestOfDups)
tbl.dups[bestOfDups, c("A.common", "B.common", "type", "provider", "publicationID")]
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