R/sim_ld.R

In canalcheng/ChinSimi: Measuring the Similarity between Chinese Strings

#' Compute levenstein edit similarity between strings, accounting for ambiguous characters and potentially aggregating similarity over multiple transformations (e.g. pinyin for phonetic similarity and four corner code for visual similarity)
#'
#' @param s_1 A vector or matrix of characters representing one set of original strings
#' @param s_2 A vector or matrix of characters representing a second set of original strings (must be the same length as s_1)
#' @param aggr A character function name or function object indicating how similarities calculated over multiple transformations should be aggregated
#' @return A vector of edit similarities corresponding to the pairwise comparisons of elements of s_1 and s_2

sim_ld <- function(s_1, s_2,aggr='mean'){ #inputs may be string vectors
    
    if(any(c('data.frame','matrix') %in% class(s_1))){
      temp = lapply(1:ncol(s_1), function(c){
        sim_ld(s_1[,c],s_2[,c])
      })
      temp = do.call(cbind,temp)
      return(apply(temp,1,match.fun(aggr)))
    } 
    
    hominds = which(pmax(grepl('\\[',s_1),grepl('\\[',s_2))==1)
    if(length(hominds)==0){
      return(stringsim(s_1,s_2,'lv'))
    } 
    res = rep(0,length(s_1))
    
    res[-hominds] = stringsim(s_1[-hominds],s_2[-hominds],'lv')
    
    torun = do.call(rbind,lapply(hominds,function(i){
      
      v1 = s_1[i]
      v2 = s_2[i]
      s1 = if(grepl('\\[',v1)){
        homonym(v1)
      }else v1 
      s2 = if(grepl('\\[',v2)){
        homonym(v2)
      }else v2 
      
      matrix(c(rep(s1,each=length(s2)),rep(s2,length(s1)),rep(i,length(s1)*length(s2))),ncol=3)
    }))
    
    simtemp = stringsim(torun[,1],torun[,2],'lv')
    
    
    res[hominds] = tapply(simtemp,torun[,3],max)
      
    return(res)  
  }