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Value Matching

Source: R/utils.R
grr_matches.Rd

Returns a lookup table or list of the positions of ALL matches of its first argument in its second and vice versa. Similar to match, though that function only returns the first match.

Usage

grr_matches(
  x,
  y,
  all.x = TRUE,
  all.y = TRUE,
  list = FALSE,
  indexes = TRUE,
  nomatch = NA
)

Arguments

x

vector. The values to be matched. Long vectors are not currently supported.

y

vector. The values to be matched. Long vectors are not currently supported.

all.x

logical; if TRUE, then each value in x will be included even if it has no matching values in y

all.y

logical; if TRUE, then each value in y will be included even if it has no matching values in x

list

logical. If TRUE, the result will be returned as a list of vectors, each vector being the matching values in y. If FALSE, result is returned as a data.table with repeated values for each match.

indexes

logical. Whether to return the indices of the matches or the actual values.

nomatch

the value to be returned in the case when no match is found. If not provided and indexes=TRUE, items with no match will be represented as NA. If set to NULL, items with no match will be set to an index value of length+1. If indexes=FALSE, they will default to NA.

Value

data.table

Details

This behavior can be imitated by using joins to create lookup tables, but matches is simpler and faster: usually faster than the best joins in other packages and thousands of times faster than the built in merge.

all.x/all.y correspond to the four types of database joins in the following way:

left

all.x=TRUE, all.y=FALSE

right

all.x=FALSE, all.y=TRUE

inner

all.x=FALSE, all.y=FALSE

full

all.x=TRUE, all.y=TRUE

Note that NA values will match other NA values.

Source of the function: https://github.com/cran/grr/blob/master/R/grr.R

Examples

mat_elem <- data.table::data.table(
  DrugName = rep(c("untreated", "drugA", "drugB", "untreated"), 2),
  DrugName_2 = rep(c("untreated", "vehicle", "drugA", "drugB"), 2),
  clid = rep(c("C1", "C2"), each = 4)
)
untreated_tag <- gDRutils::get_env_identifiers("untreated_tag")
ref_idx <- which(
  mat_elem$DrugName %in% untreated_tag |
   mat_elem$DrugName_2 %in% untreated_tag
)
ref <- mat_elem[ref_idx, ]
treated <- mat_elem[-ref_idx, ]
valid <- c("DrugName", "DrugName_2")
trt <- lapply(valid, function(x) {
  colnames <- c("clid", x) 
  treated[, colnames, with = FALSE]
})
trt <- do.call(paste, 
  do.call(rbind, lapply(trt, function(x) setNames(x, names(trt[[1]]))))
)
ref <- lapply(valid, function(x) {
  colnames <- c("clid", x) 
  ref[, colnames, with = FALSE]
})
ref <- do.call(paste, 
  do.call(rbind, lapply(ref, function(x) setNames(x, names(ref[[1]]))))
)
grr_matches(trt, ref, list = FALSE, all.y = FALSE)
#>        x     y
#>    <int> <int>
#> 1:     3     2
#> 2:     1     9
#> 3:     4     5
#> 4:     2    12