NX-5 1.0.1

A topology-based visual encoding system that represents text as nested squares with binary edge notches

NX-5

A first-of-its-kind visual encoding algorithm that uses spatial containment and edge geometry to represent text as nested squares

Unlike every encoding system before it — Braille, QR codes, Morse — NX-5 does not use a flat grid of binary states. It encodes meaning through topology: the relationship between shapes, their edges and the space they contain.

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Table of Contents

• Concept

• How It Works

  - The Base Unit

  - The Notch System

  - Side Encoding

  - Word Encoding — Nesting

  - Sentence Encoding — Clusters

• Full Character Map

  - Letters

  - Digits

  - Symbols

• Visual Color Guide

• Installation

• Usage

  - As a Python Library

  - CLI — Encoder

  - CLI — Decoder

• Configuration

• Project Structure

• Design Philosophy

• What Makes NX-5 Different

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Concept

NX-5 was born from iterative geometric art, the observation that a shape drawn inside itself, repeated, creates a natural rhythm. The insight was simple: what if each iteration represented a letter?

The result is an encoding system where:

• A word is a single cluster of nested squares

• Each square layer is one character

• The edge of the square carries the encoded data as a notch pattern

• Reading goes from the inside out, the innermost square is the first character

Encoded text looks like abstract architectural diagrams or arcane sigils, nothing about the output hints at its content to an untrained eye.

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How It Works

The Base Unit

Every character is a square with a notch pattern cut into one of its sides. The square has four sides but only three are used in NX-5:

Side	Encodes
Left	Capital letters A–Z
Right	Lowercase letters a–z
Top	Digits 0–9 + symbols
Bottom	Reserved

The side tells you what type of character it is, the notch pattern tells you which character.

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The Notch System

Each active side is divided into 5 equal segments. Each segment is either:

• Notched: sticks outward from the square edge => 1

• Flat: stays flush with the square edge => 0

5 segments × 2 states = 2⁵ = 32 unique codes.

Side of square (5 segments, top to bottom):

  ┌─ seg 0 ─┐
  ├─ seg 1 ─┤        ◄── flat   (0)
  ├─ seg 2 ──────┐   ◄── notched (1)  ← one full notch, one bit
  ├─ seg 3 ─┤    │   ◄── flat   (0)
  ├─ seg 4 ─┤    │   ◄── flat   (0)
  └─────────┘    │
                 └── notch sticks outward

  Code read top → bottom: 0 0 1 0 0 = 00100

Segments are read top to bottom for left/right sides, and left to right for the top side.

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Side Encoding

The side the notch appears on encodes the character class:

LEFT side  (blue)   → Capital letter    e.g. A, B, Z

RIGHT side (red)    → Lowercase letter  e.g. a, b, z

TOP side   (green)  → Digit             e.g. 0, 1, 9

TOP side   (purple) → Symbol            e.g. (, !, @, +

So A and a have the same notch pattern — they differ only by which side the notch is on.

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Word Encoding - Nesting

Characters within a single word are stacked as concentric nested squares:

• Innermost square → first character

• Outermost square → last character

• Each layer expands outward by a fixed gap

Word: "abc"

  

┌─────────────────────────────────┐  ← c  (outermost, 3rd)

│                                 │

│  ┌───────────────────────────┐  │

│  │                           ├─┐│  ← b (middle, 2nd)
|
│  │  ┌─────────────────────┐  │ ││
|
│  │  │                     ├─┐│ ││  ← a (innermost, 1st)
|
│  │  │                     │ ││ ││
|
│  │  └─────────────────────┘ ││ ││
|
│  │                          ├─┘│
|
│  └──────────────────────────┘  │
|
│                                │
|
└────────────────────────────────┘

Reading order: inside → out, which mirrors how the shapes are drawn.

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Sentence Encoding — Clusters

Each word is its own independent nested cluster. Words are placed left to right with a gap between them — exactly like normal writing.

"hello world"

  

[  nested cluster  ]     [  nested cluster  ]

      hello                    world

There is no special character for spaces — the physical gap between clusters is the separator.

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Full Character Map

Letters

Letters A–Z are mapped to binary codes 00001–11010 (skipping 00000).

The same code appears on the left for capitals and right for lowercase.

Letter	Code	Letter	Code	Letter	Code
A / a	00001	J / j	01010	S / s	10011
B / b	00010	K / k	01011	T / t	10100
C / c	00011	L / l	01100	U / u	10101
D / d	00100	M / m	01101	V / v	10110
E / e	00101	N / n	01110	W / w	10111
F / f	00110	O / o	01111	X / x	11000
G / g	00111	P / p	10000	Y / y	11001
H / h	01000	Q / q	10001	Z / z	11010
I / i	01001	R / r	10010

Digits

Digits use the top side (green). 0 is assigned 00000 — the only character that uses the all-flat code.

Digit	Code	Digit	Code
0	00000	5	00101
1	00001	6	00110
2	00010	7	00111
3	00011	8	01000
4	00100	9	01001

Symbols

Symbols use the top side (purple). Paired brackets are assigned consecutive codes.

Symbol	Code	Symbol	Code
(	01010	)	01011
[	01100	]	01101
{	01110	}	01111
<	10000	>	10001
!	10010	@	10011
#	10100	$	10101
%	10110	/	10111
&	11000	*	11001
'	11010	"	11011
-	11100	_	11101
=	11110	+	11111

The bottom side is reserved for future expansion — punctuation, extended character sets, or alternative scripts.

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Visual Color Guide

Colors are the only non-geometric hint in the output. An observer needs to know the color mapping to begin decoding.

Color	Hex	Encodes
Blue	#2a6db5	Capital letters A–Z
Red	#c0392b	Lowercase letters a–z
Green	#27ae60	Digits 0–9
Purple	#9b59b6	Symbols

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Installation

pip install nx-5

Requirements: Python 3.8+, Pillow (for PNG export)

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Usage

As a Python Library

from NX_5 import encode_text, decode_svg

  

# Encode text to SVG

encode_text("Hello World", "output.svg")

  

# Encode and also export PNG

encode_text("Hello World", "output.svg", export_png=True)

  

# Decode an SVG back to text

text = decode_svg("output.svg")

print(text)  # → "Hello World"

CLI — Encoder

# Interactive mode

python -m NX_5.encoder

  

# One-shot

python -m NX_5.encoder Hello World

  

# With PNG export

python -m NX_5.encoder Hello World --png

        ||============================================||

        ||               NX-5 Encoder v1.0            ||

        ||  left=CAP - right=lower - top=0-9+symbols  ||

        ||============================================||

  

Enter text to encode: Hello World

  Also export PNG? (y/N): y

Encoded 'Hello World' → Hello_World.svg

  PNG: Hello_World.png

  Words : 2

  Canvas: 3218 × 1660 px

CLI — Decoder

# Interactive mode

python -m NX_5.decoder

  

# One-shot

python -m NX_5.decoder Hello_World.svg

        ||============================================||

        ||               NX-5 Decoder v1.0            ||

        ||      reads svg files from the encoder      ||

        ||============================================||
Decoding: Hello_World.svg

  

  Word 1: 'Hello'

  Word 2: 'World'

  

Decoded: 'Hello World'

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Configuration

All visual parameters live in NX_5/constants.py. Tune them to control the output appearance:

Constant	Default	Effect
INNER_W	160	Width of the innermost square (minimum size for first letter)
INNER_H	160	Height of the innermost square
LAYER_GAP	150	Space between each nested layer — increase for more breathing room
NOTCH_DEPTH	40	How far notches protrude from the square edge
SEGMENTS	5	Number of notch segments per side — do not change
PADDING	50	Outer padding around each word cluster
WORD_GAP	50	Horizontal gap between word clusters
BG_PAD	80	Canvas margin around the entire output
STROKE_WIDTH	7	Line thickness of the squares

Rule of thumb: LAYER_GAP should be at least NOTCH_DEPTH × 3 to keep notches from looking cramped between layers.

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Project Structure

NX-5/

├── NX_5/

│   ├── __init__.py      ← exposes encode_text, decode_svg

│   ├── constants.py     ← all mappings, colors, layout values

│   ├── encoder.py       ← SVG + PNG generation

│   └── decoder.py       ← geometry-based SVG decoding

├── tests/

│   └── test_encoder.py  ← roundtrip encode → decode tests

├── pyproject.toml

├── LICENSE

└── README.md

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Design Philosophy

Topology over grid. Every encoding system before NX-5 encodes data in a flat matrix of binary states - dots on a grid, pits on a disc, pixels in a QR code. NX-5 encodes data through containment and edge features. The meaning lives in the relationship between shapes, not in a flat matrix.

Reading order is spatial. You read from the inside out, which mirrors the natural visual pull of nested shapes. The eye is drawn to the center first.

Case is positional. There is no separate symbol for uppercase versus lowercase. The same notch pattern on the left means capital; on the right means lowercase. One rule, zero ambiguity.

The output is art. A rendered NX-5 message looks like a technical diagram or a geometric sigil. It does not look like ciphertext. This is intentional — the best encoding is one that doesn't announce itself.

Zero metadata. The SVG output contains nothing but raw path coordinates and stroke colors. No labels, no attributes, no hints. Decoding requires knowing the system.

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What Makes NX-5 Different

Property	QR Code	Braille	Morse	NX-5
Grid-based	✓	✓	✗	✗
Requires special reader	✓	✗	✗	✗
Encodes case	✓	✓	✗	✓
Visually artistic	✗	✗	✗	✓
Topology-based	✗	✗	✗	✓
Readable without tools	✗	✗	✓	✓*
Scalable vector output	✗	✗	✗	✓

*with knowledge of the system

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License

MIT — see LICENSE