Question: What if the words in the VMS have been shortened or expanded with fill characters (here X) so that they end up corresponding to a binomial distribution (with whatever system)?
Here is a line from a comparative text ( regimen sanitatis ):
Input example:
Capitulum primum De regulis sumptis ex parte elementorum nostro corpori occurrentium ab extra
Output example:
Ca primum DeXXXXX regul sump exXXXX parteX elemento nost corpo occu abXXXX extra
Distribution in the entire, modified text ( regimen sanitatis ):
Here is a line from a comparative text ( regimen sanitatis ):
Input example:
Capitulum primum De regulis sumptis ex parte elementorum nostro corpori occurrentium ab extra
Output example:
Ca primum DeXXXXX regul sump exXXXX parteX elemento nost corpo occu abXXXX extra
Distribution in the entire, modified text ( regimen sanitatis ):
Code:
import sys
import numpy as np
from scipy.special import comb
def calculate_binomial_distribution(n, max_length):
"""Berechnet eine Binomialverteilung für Wortlängen."""
k_values = np.arange(1, max_length + 1)
# Berechne die Binomialverteilung für die Formel choose(9, k-1) / 2^9
probabilities = [comb(n, k-1) / (2 ** n) for k in k_values]
# Normiere die Verteilung
probabilities /= np.sum(probabilities)
return probabilities
def adjust_word_lengths(words, target_distribution):
"""Passt die Wortlängen an die Zielverteilung an, indem Wörter gekürzt oder verlängert werden."""
adjusted_words = []
max_word_length = len(target_distribution)
length_bins = np.arange(1, max_word_length + 1)
length_probs = np.array(target_distribution)
for word in words:
current_length = len(word)
target_length = np.random.choice(length_bins, p=length_probs)
# Falls die Zielwortlänge kleiner ist, kürze das Wort
if target_length < current_length:
adjusted_words.append(word[:target_length])
# Falls die Zielwortlänge größer ist, verlängere das Wort mit 'X'
elif target_length > current_length:
adjusted_words.append(word + 'X' * (target_length - current_length))
else:
adjusted_words.append(word) # Wenn die Länge passt, bleibt das Wort unverändert
return adjusted_words
def process_text(file_path):
"""Liest den Text aus der Datei, passt die Wortlängen an und gibt den neuen Text zurück."""
try:
with open(file_path, 'r', encoding='utf-8') as file:
lines = file.readlines()
except FileNotFoundError:
print(f"Error: The file {file_path} was not found.")
sys.exit(1)
except IOError as e:
print(f"Error: An error occurred while reading the file: {e}")
sys.exit(1)
max_word_length = 15 # Maximale Wortlänge festlegen
n = 9 # Anzahl der Würfe für die Binomialverteilung
# Berechne die Binomialverteilung
target_distribution = calculate_binomial_distribution(n, max_word_length)
adjusted_lines = []
for line in lines:
words = line.split()
adjusted_words = adjust_word_lengths(words, target_distribution)
adjusted_lines.append(' '.join(adjusted_words))
return '\n'.join(adjusted_lines)
def main():
if len(sys.argv) != 2:
print("Usage: python adjust_word_length.py <filename>")
sys.exit(1)
file_path = sys.argv[1]
new_text = process_text(file_path)
print("Modified text:")
print(new_text)
if __name__ == "__main__":
main()Quote:ChatGPT
One could design a volvelle that aims to change the word lengths of a text according to a specific distribution. This could be done through the use of rotating disks, each giving specific instructions on how words should be edited.
Example of a volvelle for word length manipulation
Here is a hypothetical description of what a volvelle could look like for this task:
Circle 1: Defines the possible word lengths from 1 to 15 (depending on the maximum word length).
Circle 2: Gives the probability for each word length based on a certain distribution (e.g. binomial distribution).
Circle 3: Instructions for shortening or expanding words to achieve the target distribution.
Use of a volvelle
1. user enters the text.
2. volvelle is rotated to obtain the rules for shortening or expanding words.
3. instructions are applied to the text.
![[+]](https://www.voynich.ninja/images/collapse_collapsed.png)