Voynich Manuscript Parser and Resources
Pure Python parser for the IVTFF formatted ZL transliteration of the Voynich Manuscript.
Intended for NLP/ML/DL use on the Voynich Manuscript.
voynich.VoynichManuscript is what you'll likely mostly be using, it contains voynich.Pages, which contain voynich.Lines.
Example usage (subject to change):
>>> from voynich import VoynichManuscript
>>> vm = VoynichManuscript(path_to_txt, inline_comments=False)
>>> print(vm)
VoynichManuscript(num_pages=227, inline_comments=False)
>>> print(vm.pages["f1r"])
Page(page_name=f1r, quire_num=None, folio_num=None, num_lines=31, illust_type=None)
>>> print(vm.pages["f1r"][0])
Line(<%>fachys.ykal.ar.ataiin.shol.shory.[cth:oto]res.y.kor.sholdy)
>>> print(vm.pages["f1r"][0].text)
<%>fachys.ykal.ar.ataiin.shol.shory.[cth:oto]res.y.kor.sholdy
>>> print(vm.get_paragraphs()[0])
'fachys.ykal.ar.ataiin.shol.shory.cthres.y.kor.sholdy.sory.ckhar.or,y.kair.chtaiin.shar.ase.cthar.cthar,dansyaiir.sheky.or.ykaiin.shod.cthoary.cthes.daraiin.sysoiin.oteey.oteos,roloty.cthiar,daiin.okaiin.or.okansair,y.chear.cthaiin.cphar.cfhaiinydaraishy'Each Page object also contains a list of paragraphs Page.paragraphs. These paragraphs have some additional processing on them, removing paragraph markers (<%> and <$>), gap indicators (<->), and (currently) chooses the first possible interpretation of ambiguous characters (i.e. [o:a] -> o). For future work, will update paragraph parser to produce one paragraph for every possible combination of ambiguous characters.
