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| Place scripts under workplace/. __All VN scripts must be in utf-8.__ Unix line endings (\n, not \r\n) are preferred. | Place scripts under workplace/. __All VN scripts must be in utf-8.__ '''See [[Ripping]] for information on script formatting.''' Unix line endings (\n, not \r\n) are preferred. |
These are the tools used to generate the stats. See Engines for information on script ripping for particular engines.
http://wareya.moe/extra/workspace.zip
These tools require Python 3, 64-bit Java, and a bash prompt.
Place scripts under workplace/. All VN scripts must be in utf-8. See Ripping for information on script formatting. Unix line endings (\n, not \r\n) are preferred.
analyzer.jar: the core of the stats generation. Creates a lemmatized frequency list from a given VN script. Uses kuromoji-unidic, which uses a viterbi graph and a pre-trained markov model about how what words connect to eachother and how common each lexeme is. VN script must be in utf-8. Invoked by a bash script. Github
normalizer.jar: Merges frequency lists in the format that analyzer.jar outputs. Invoked manually on most of the frequency lists generated under the count/ directory. Used in order to create the frequency list for the 5k columns. Github
dowork.sh: Generates the main frequency lists for each script in workspace/, placing the lists under count/. These lists exclude grammatical lexemes.
altwork.sh: Above, but with altcount/, and not excluding grammatical lexemes.
refresh.sh: Calculates the hayashi score, coverages, and other stats from every frequency list and script.
newscript.sh: Generates/regenerates the frequency list in count/ and the frequency list in altcount/ for a single script in workspace/.
fullredo.sh: Runs dowork.sh, altwork.sh, and refresh.sh. Might be preferable the first time, but for adding single scripts, you're going to want to use newscript.sh and refresh.sh manually.