These are the tools used to generate the stats. See Engines for information on script ripping for particular engines.

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 Generates the main frequency lists for each script in workspace/, placing the lists under count/. These lists exclude grammatical lexemes. Above, but with altcount/, and not excluding grammatical lexemes. Calculates the hayashi score, coverages, and other stats from every frequency list and script. Generates/regenerates the frequency list in count/ and the frequency list in altcount/ for a single script in workspace/. Runs,, and Might be preferable the first time, but for adding single scripts, you're going to want to use and manually.

Making stats (last edited 2017-08-28 05:06:55 by weh)