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The Naibbe cipher

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• The Naibbe cipher

• RE: The Naibbe cipher

  quimqu > 14-08-2025, 10:17 AM

  (14-08-2025, 12:25 AM)davidma Wrote: You are not allowed to view links. Register or Login to view.As i recall from your post quimqu no other cipher had that distinctive bump that the VM has, but the naibbe one does. 

  
  No, syllabic substitution made the trick of the bump also.

• RE: The Naibbe cipher

  bi3mw > 14-08-2025, 04:47 PM

  Addendum to You are not allowed to view links. Register or Login to view.:
  
  You can also create a heat map in which the labels are displayed in Voynichese. This requires that the font (usually “eva1.ttf”) be installed on your PC. In the following line in the Python script, the path to the font must be adjusted (line 59):
  
  custom_font_path = "/home/me/.local/share/fonts/eva1.ttf"
  
  
  The call is made as already described, where 25 is the variable number of listed pairs:
  
  python heatmap_prefix_suffix.py parsed.txt 25
  
  
  

  Code:

  #!/usr/bin/env python3
import sys
from collections import Counter
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import font_manager as fm

def extract_prefix_suffix(word):
    parts = word.split('/')
    if len(parts) < 3:
        return [], [], None
    stem_index = len(parts) // 2
    prefix = parts[:stem_index]
    suffix = parts[stem_index+1:]
    return prefix, suffix, parts[stem_index]

def main():
    if len(sys.argv) < 2:
        print("Usage: python heatmap_prefix_suffix.py output_segmented.txt [N]")
        sys.exit(1)

    filename = sys.argv[1]
    top_n = 20  # default number of top prefixes and suffixes
    if len(sys.argv) >= 3:
        try:
            top_n = int(sys.argv[2])
        except ValueError:
            print("Parameter N must be an integer.")
            sys.exit(1)

    prefix_suffix_counts = Counter()

    with open(filename, 'r', encoding='utf-8') as f:
        for line in f:
            words = line.strip().split()
            for w in words:
                prefix, suffix, stem = extract_prefix_suffix(w)
                for pre in prefix:
                    for suf in suffix:
                        prefix_suffix_counts[(pre, suf)] += 1

    if not prefix_suffix_counts:
        print("No prefix-suffix combinations found.")
        sys.exit(1)

    data = [{"prefix": pre, "suffix": suf, "count": count}
            for (pre, suf), count in prefix_suffix_counts.items()]
    df = pd.DataFrame(data)

    # Select top N prefixes and suffixes by total count
    top_prefixes = df.groupby('prefix')['count'].sum().nlargest(top_n).index
    top_suffixes = df.groupby('suffix')['count'].sum().nlargest(top_n).index

    pivot = df.pivot(index='prefix', columns='suffix', values='count').fillna(0)
    pivot_top = pivot.loc[top_prefixes, top_suffixes]

    # Lade lokalen Font
    custom_font_path = "/home/me/.local/share/fonts/eva1.ttf"
    custom_font = fm.FontProperties(fname=custom_font_path, size=12)

    # Plot
    plt.figure(figsize=(18, 12))
    ax = sns.heatmap(
        pivot_top,
        annot=True,
        fmt=".0f",
        cmap="YlGnBu",
        cbar_kws={"shrink": 0.5}
    )

    plt.title(f"Top {top_n} Prefix-Suffix Combinations")
    plt.xlabel("Suffix")
    plt.ylabel("Prefix")

    # Achsenbeschriftungen (Tick-Labels) mit lokalem Font
    ax.set_xticklabels(ax.get_xticklabels(), fontproperties=custom_font, rotation=45, ha='right')
    ax.set_yticklabels(ax.get_yticklabels(), fontproperties=custom_font, rotation=0)

    plt.subplots_adjust(bottom=0.2)
    plt.show()

if __name__ == "__main__":
    main()

  
     
     
  
  Here are the text files for parsing:
  
    naibbe.txt (Size: 142 KB / Downloads: 2)
  
    ZL3a-n_B.txt (Size: 143.11 KB / Downloads: 2)
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