This is a semi-maintained and developing library for k-nacci words and word curves in python, first developed for research in 2018-2019.
The k-nacci word is a string over the alphabet 
generated recursively via the rules:
The word curves are drawn via turtle-graphics (a non-branching Lindenmyer System, if you like) via a drawing rule:
(1) Initalize: declare the turning angle 
, set the inital drawing angle to 
, and place the turtle on 
. Set the index 
to 1 .
(2) Move the turtle forward one step.
(3) If the th character of the word is a '0', turn the turtle's direction by 
.
(4) Increment the index by one.
(5) If 
, return to step 2.
To generate the fractal, we take each curve and rotate/scale it so that the endpoint of the curve touches 
. Then we take the limit of the modified curve as 
.
Usage examples of the files included in this repo:
With Knacci Utils, you can obtain all types of 
-nacci words easily. Get 
via the command f(k,n). For example,
from WordGen import f
for n in range(1,10):
print(n, f(2,n))You can also get 
via the command t(k,n).
It is easy to test hypotheses about the drawing rule with random_word, which returns a random binary word of any arbitrary length. There are a few other tools.
from Debugging import random_word
w = random_word(100) #makes a random binary word of length 100
is_alphabet_valid(w) #checks to see if the alphabet is a subset of {'0','1'}This gives you 
, draws pictures of the word curves, and lets you have a list of vertices in the word curve.
from math import pi
from WordGen import f
from AngleAndVertex import alpha_coeff, vertices, draw_me, end_position
#gives the coefficient of alpha that the drawer is
# pointing after drawing the word, related to net angle.
alpha_coeff(f(3,5))
#a list of vertices in the word curve given some drawing angle
vertices(f(2,5), pi/3)
#plt.plot(), plt.show() the vertices in the word curve.
draw_me(f(2,11), pi/3)
#gives both the coefficient of alpha after drawing and also the last vertex in the word curve
end_position(f(2,17), pi/3) For discovering word generation patterns. There also exist some word comparison generators, not sure what I was doing with those.
from WordGen import f
from WordSplit import split_to
# outputs all possible word decompositions given the subwords in the dict.
split_to(f(2,7), {"f(2,6)":f(2,6), "f(2,5)":f(2,5), "f(2,4)":f(2,4), "f(2,3)":f(2,3)}) Determine the endpoints of a composition of words. This file uses numpy.
from math import pi
from WordGen import f, t
from HighLevelEndpoints import wordmat, ep_for_words
# z(w) + wordmat(w).z(v) = z(wv)
#gives the translation/rotation matrix for
# drawing another word curve after drawing a word.
wordmat(f(2,7), pi/3)
#gives the endpoint and drawing angle coefficient after drawing all words given.
ep_for_words(pi/2, f(2,7),f(2,8),t(2,5)) Aided validation of the main claim in our research paper, about the fractal dimension of the iterated function system that makes the 2-nacci word fractal. We used combinatorial tools to observe recurring patterns in word-decompositions, translated those into linear algebra mappings, and used traditional tools to compute the Hausdorff dimension.
