R
R.scripts
!!!myIndexNICER3
{{outline}}
!ファイル名・スコア・言語指標を取り出す
*NICERのCHATフォーマットのデータの入っているフォルダー内で、
*各種言語指標とファイル名とエッセイのスコアを取り出して、「リスト」として出力する。
{{pre
myIndexNICER3 <- function(){
  result <- list()
  files <- list.files()
  k <- 0
  for (i in files){
    k <- k +1
    Token <- 0
    Type <- 0
    NoS <- 0
    TTR <- 0
    GI <- 0
    AWL <- 0
    ASL <- 0
    wttr <- 0
    ttrsum <- 0
    MATTR <- 0
    
    lines.tmp <- scan(i, what="char", sep="\n", quiet = T)
    #Criterion score
    criterion.tmp <- grep("@Criterion", lines.tmp, value = T)
    Score <- gsub("@Criterion:\t", "", criterion.tmp)
    
    #----NICER
    data.tmp <- grep("\\*(JPN|NS)...:\t", lines.tmp, value=T)
    
    body.tmp <- gsub("\\*(JPN|NS)...:\t", "", data.tmp)
    
    body.tmp <- body.tmp[body.tmp != ""]
    #----
    lines.lower <- tolower(body.tmp)
    
    words.tmp <- unlist(strsplit(lines.lower, "\\W+"))
    
    Token <- length(words.tmp)
    Type <- length(unique(words.tmp))
    NoS <- length(lines.tmp)
    TTR <- Type/Token
    GI <- Type/sqrt(Token)
    AWL <- nchar(paste(words.tmp, collapse=""))/Token
    ASL <- Token/NoS
    words.tmp2 <- c(words.tmp, words.tmp)
    for (j in 1:Token){
      mado <- words.tmp2[j:(99+j)]
      wttr <- length(unique(sort(mado)))/100
      ttrsum <- ttrsum + wttr
    }
    MATTR <- ttrsum/Token
    #cat(i, Score, Token, Type, NoS, TTR, GI, MATTR, AWL, ASL, "\n", file=output.file, append=T)
    #cat(i, Score, Token, Type, NoS, TTR, GI, MATTR, AWL, ASL, "\n")
    #print(i, Score, Token, Type, NoS, TTR, GI, MATTR, AWL, ASL)
    result[[k]] <- list(i, Score, Token, Type, NoS, TTR, GI, MATTR, AWL, ASL)
  }
  return(result)
}

}}
!その後の処理
*unlistして、matrixとして一覧表にする。
 > matrix(unlist(JP_result), nrow=10, ncol=50)
*縦横変換 t()
{{pre
> t(matrix(unlist(JP_result), nrow=10, ncol=50))
      [,1]         [,2] [,3]  [,4]  [,5]  [,6]                [,7]               [,8]                [,9]               [,10]             
 [1,] "JPN501.txt" "4"  "319" "135" "123" "0.423197492163009" "7.55854889790403" "0.592131661442006" "4.30407523510972" "2.59349593495935"
 [2,] "JPN502.txt" "4"  "356" "161" "120" "0.452247191011236" "8.5329829340512"  "0.664915730337079" "4.23314606741573" "2.96666666666667"
 [3,] "JPN503.txt" "3"  "201" "121" "70"  "0.601990049751244" "8.53468195188904" "0.717014925373134" "4.74626865671642" "2.87142857142857"
 [4,] "JPN504.txt" "4"  "260" "140" "114" "0.538461538461538" "8.68243142124459" "0.687769230769229" "4.76153846153846" "2.28070175438596"
 [5,] "JPN505.txt" "4"  "420" "175" "106" "0.416666666666667" "8.53912563829967" "0.634190476190476" "3.9952380952381"  "3.9622641509434" 
 [6,] "JPN506.txt" "3"  "261" "124" "93"  "0.475095785440613" "7.67540731131814" "0.639003831417626" "4.0727969348659"  "2.80645161290323"
}}
*データフレームに
{{pre
> as.data.frame(t(matrix(unlist(JP_result), nrow=10, ncol=50)))
           V1 V2  V3  V4  V5                V6               V7                V8               V9              V10
1  JPN501.txt  4 319 135 123 0.423197492163009 7.55854889790403 0.592131661442006 4.30407523510972 2.59349593495935
2  JPN502.txt  4 356 161 120 0.452247191011236  8.5329829340512 0.664915730337079 4.23314606741573 2.96666666666667
3  JPN503.txt  3 201 121  70 0.601990049751244 8.53468195188904 0.717014925373134 4.74626865671642 2.87142857142857
4  JPN504.txt  4 260 140 114 0.538461538461538 8.68243142124459 0.687769230769229 4.76153846153846 2.28070175438596
5  JPN505.txt  4 420 175 106 0.416666666666667 8.53912563829967 0.634190476190476  3.9952380952381  3.9622641509434
6  JPN506.txt  3 261 124  93 0.475095785440613 7.67540731131814 0.639003831417626  4.0727969348659 2.80645161290323
}}