I wrote a simple Python script to finally present the transitions from glyph to glyph (including word boundaries, denoted with { and }). You can find it at the same GitHub repository, please fork, modify, correct, extend it if you want.

Without further ado, here are the tables of transitions from glyph to glyph. I will discuss them in a future post, possibly with some graphical representation.

The first table indicates the occurrences of glyphs in the first column when following by those in the second one:

Symbol Transition from Occurrences/Total (percentage)
1/14 (7.14%)
1/14 (7.14%)
1/14 (7.14%)
1/14 (7.14%)
{ 10/14 (71.43%)
2/9 (22.22%)
1/9 (11.11%)
1/9 (11.11%)
1/9 (11.11%)
1/9 (11.11%)
{ 3/9 (33.33%)
1/7 (14.29%)
1/7 (14.29%)
2/7 (28.57%)
1/7 (14.29%)
1/7 (14.29%)
{ 1/7 (14.29%)
1/8 (12.50%)
2/8 (25.00%)
1/8 (12.50%)
1/8 (12.50%)
{ 3/8 (37.50%)
2/3 (66.67%)
1/3 (33.33%)
1/5 (20.00%)
1/5 (20.00%)
2/5 (40.00%)
1/5 (20.00%)
1/18 (5.56%)
1/18 (5.56%)
, 1/18 (5.56%)
2/18 (11.11%)
3/18 (16.67%)
1/18 (5.56%)
2/18 (11.11%)
4/18 (22.22%)
{ 3/18 (16.67%)
1/6 (16.67%)
1/6 (16.67%)
{ 4/6 (66.67%)
1/12 (8.33%)
1/12 (8.33%)
3/12 (25.00%)
3/12 (25.00%)
1/12 (8.33%)
{ 3/12 (25.00%)
1/11 (9.09%)
1/11 (9.09%)
1/11 (9.09%)
1/11 (9.09%)
1/11 (9.09%)
2/11 (18.18%)
1/11 (9.09%)
1/11 (9.09%)
{ 2/11 (18.18%)
2/9 (22.22%)
1/9 (11.11%)
1/9 (11.11%)
5/9 (55.56%)
{ 5/5 (100.00%)
1/13 (7.69%)
3/13 (23.08%)
1/13 (7.69%)
2/13 (15.38%)
1/13 (7.69%)
2/13 (15.38%)
1/13 (7.69%)
1/13 (7.69%)
{ 1/13 (7.69%)
, 1/7 (14.29%)
1/7 (14.29%)
1/7 (14.29%)
2/7 (28.57%)
1/7 (14.29%)
1/7 (14.29%)
1/8 (12.50%)
1/8 (12.50%)
1/8 (12.50%)
2/8 (25.00%)
1/8 (12.50%)
{ 2/8 (25.00%)
? { 1/1 (100.00%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
2/17 (11.76%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
{ 8/17 (47.06%)
2/8 (25.00%)
1/8 (12.50%)
2/8 (25.00%)
? 1/8 (12.50%)
2/8 (25.00%)
1/3 (33.33%)
1/3 (33.33%)
{ 1/3 (33.33%)
4/17 (23.53%)
2/17 (11.76%)
2/17 (11.76%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
1/17 (5.88%)
2/17 (11.76%)
1/17 (5.88%)
1/3 (33.33%)
{ 2/3 (66.67%)
1/5 (20.00%)
1/5 (20.00%)
1/5 (20.00%)
1/5 (20.00%)
{ 1/5 (20.00%)
1/11 (9.09%)
1/11 (9.09%)
2/11 (18.18%)
1/11 (9.09%)
1/11 (9.09%)
1/11 (9.09%)
1/11 (9.09%)
2/11 (18.18%)
{ 1/11 (9.09%)
1/9 (11.11%)
2/9 (22.22%)
3/9 (33.33%)
1/9 (11.11%)
1/9 (11.11%)
{ 1/9 (11.11%)
2/16 (12.50%)
5/16 (31.25%)
1/16 (6.25%)
{ 8/16 (50.00%)
1/1 (100.00%)
1/1 (100.00%)
} 1/60 (1.67%)
2/60 (3.33%)
2/60 (3.33%)
2/60 (3.33%)
3/60 (5.00%)
7/60 (11.67%)
2/60 (3.33%)
2/60 (3.33%)
2/60 (3.33%)
4/60 (6.67%)
5/60 (8.33%)
, 6/60 (10.00%)
3/60 (5.00%)
3/60 (5.00%)
4/60 (6.67%)
4/60 (6.67%)
1/60 (1.67%)
2/60 (3.33%)
3/60 (5.00%)
1/60 (1.67%)
1/60 (1.67%)

It is clear that some glyphs are far more promiscuous than others, but its even clearer that our corpus is too limited for any general assumption.

The following table is as important as the previous: while the first gives us the transitions of glyphs towards others, this one gives us the transitions of glyph from others (in other words, it indicates the occurrences of glyphs in the second column when following those in the first one):

(Sorry, the table was wrong — I’ll fix and post it later)

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