The Voynich Ninja

Gallows positional distribution

In response to another post I found these 2 nice blog posts by Julian Bunn.

The Page Positional Distribution of the Gallows glyphs.

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I liked the idea so much i replicated it (sort of).
ZL transcription : uncertain spaces as spaces, words containg uncertain chars removed.
Each pixel represents a voynich glyph in the ZL transcription.
The 4 Gallows glyphs have their own unique color,
all other glyphs are colored black.
Spaces are not represented.
If a word starts with a gallows glyph the rest of that word is colored with a shade of the initial glyph.

yellow : folio separator
black  : all chars except gallows
orange : EVA-f
green  : EVA-p
pink  : EVA-t
blue  : EVA-k

Problem: if a line of text contains more than 100 glyphs the line wraps around.



[attachment=5390]

It would be nice if you could make a page a little bigger. Then the distribution would be easier to understand.
Preferably a page with a lot of text.
Thank you

Hi Aga,
The resolution of the above image is enough so that if you save the image locally,
you can open it with Gimp, PaintDotNet, MS Paint or any other image editor with a strong zoom.
Then you can zoom down to the pixel level.
Web browsers dont have a strong enough zoom to really see the detail.

Here you go Aga , f114r.

[attachment=5391]

Heres the text for f114v:

Hi, Rob:

Thanks for the work and the direction toward Gimp in order to zoom in more effectively.

So, what do you think about the positional patterns being responsible for the chaotic behavior of EVA <f> (orange) and EVA <p> (green) in the time series data?  I'm inserting the relevant table below from Matlach et al. for reference.

 [attachment=5392]

I think it’s possible, and it’s certainly takes more than just showing up at certain positions within words -  otherwise EVA <q> and EVA <y> would have been “chaotic” and that doesn’t seem to be the case.

I mean, if time sequence analysis measures the interval between one use of a "glyph" and the next use of the same "glyph" and these two show different behavior than the rest (arguably EVA <t> (pink) is on the edge and EVA <k> (blue) is the same as the rest) doesn't that support trying to determine what the basis for this is?  This is data to show that these two glyphs were utilized differently than the others in construction of the text and figuring out why could help understand how it was done.

Although I understand the ligature arguments, I need some convincing that this unusual behavior can be explained by combining otherwise individual glyphs together.

Do you (particularly after putting together the graphics) or anyone else have thoughts about what this data might mean?

Just as a quick reminder -- "chaotic" = normal behavior for symbols in natural speech and the non-chaotic behavior of almost all the VM glyphs is not normal.  In other words, two of the glyphs that look most outwardly "unusual" are actually behaving in this data set closer to a normal "letter" than any of the other glyphs.

These plots ignore spaces, do they?

@Anton , for input spaces are used to define the words, for the output i.e the above graphic, yes, spaces are ignored.

@MichellL11, I haven't read the Matlach et al paper thoroughly yet so i cannot really comment,
except to say EVA <f> (orange) is far less frequent than the other gallows glyphs so in that sense it has fewer opportunities to misbehave.

When I created my concordance, I made a distinction between p with a curled crossbar and without a curl because I had noticed, early on, that the ones at the beginnings of lines/paragraphs were more likely to have a curl.




This kind of distinction would, of course, change the statistics.