dkibalnikov / simplefuzzymatchr

Simple vectorised Fuzzy Matching function in R based on Levenshtein distance

Simple Fuzzy Match R

Simple vectorised Fuzzy Matching function in R based on Levenshtein distance

Problem

Base R function agrep() has several limitation in case vectorize matching:

1. Returns all matches:
   1.1 Either with number of match (1)
   1.2 Either the match case (2)

fruits <- c("apple", "apples", "aple", "melone", "applejuice", "peanapple", "pear")

agrep("apple", fruits) #(1)
#>[1] 1 2 3 5 6

agrep("apple", fruits, value = TRUE) #(2)
#>[1] "apple"      "apples"     "aple"       "applejuice" "peanapple" 

2. Returns "matches substrings of each element of x" (see documentation agrep()).
   But someone is likely to like strict matching: "apple", "apples", "aple", "applejuice", "peanapple"
3. Enythere someone also likes vectorize form where in f(x, y): x, y are vectors for matching and f(x, y) returns vector of best matches from y in sequance of x
4. f(x, y) should return NA if Levenshtein distance of matching is more than some max value

Solution

Simple function get_match() based on adist():

library("purrr")

get_match <- function(x, y, max = 3, cost = 1) {
  dist_mtrx <- adist(x, y, partial = FALSE, costs = cost) 
  dimnames(dist_mtrx) <- list(x, y)
  
  get_best <- function(n, dist_mtrx, max){
    min_dist <- dist_mtrx[n, ] %>% min()
    if(min_dist < max) res <- dist_mtrx[n, ] %>% which.min() %>% names()
    else res <- NA
    return(res)
  }
  
  1:nrow(dist_mtrx) %>% 
    map_chr(~get_best(., dist_mtrx, max = max))
}

#test result
fruits1 <- stringr::fruit
fruits2 <- c("pears","apples", "melone", "per", "apple", "orange")
get_match(fruits2, fruits1)

#>[1] "pear"   "apple"  NA       "pear"   "apple"  "orange"  

Same result but a little bit faster using only base R

get_match <- function(x, y, max = 3, cost = 1) {
  dist_mtrx <- adist(x, y, partial = FALSE, costs = cost) 
  dimnames(dist_mtrx) <- list(x, y)
  
  get_best <- function(n, dist_mtrx, max){
    min_dist <- min(dist_mtrx[n, ])
    if(min_dist < max) res <- names(which.min(dist_mtrx[n, ])) 
    else res <- NA
    return(res)
  }
  
  sapply(X = 1:nrow(dist_mtrx), FUN = function(x) get_best(x, dist_mtrx, max = max))
}

#test result
fruits1 <- stringr::fruit
fruits1

fruits2 <- c("pears","apples", "melone", "per", "apple", "orange")
get_match(fruits2, fruits1)

#>[1] "pear"   "apple"  NA       "pear"   "apple"  "orange"

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