Procedural Typography Laboratory

A collection of custom fonts, experimental font transformations, degradation sequences, visualization tools, and document-generation utilities built on FontTools.

The project explores the idea that typography can be treated as a dynamic process rather than a fixed object. Fonts become trajectories. Glyphs become evolving structures. Documents become experiments in legibility, decay, distortion, erosion, collapse, and transformation.

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Repository Overview

The repository contains:

• Original fonts
• Styled variants
• Experimental transformations
• Automated sequence generators
• Compound degradation models
• HTML preview tools
• LaTeX degradation-document generators
• Diagnostic and debugging utilities

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Installation

Python Dependencies

pip install fonttools

Optional:

pip install brotli
pip install lxml

For LaTeX generation:

sudo apt install texlive-full

or at minimum:

sudo apt install texlive-luatex

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Repository Layout

Original Fonts

Examples:

Sga-Regular.ttf
Systada-Regular.ttf
NovaMonoStandardGalactic.ttf
Cheiro-Regular.ttf
Clypto-Regular.ttf
shapeform.ttf
dactyl.ttf

These serve as source material for transformations.

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Styled Fonts

styled_fonts/

Contains manually generated style variants:

bold
italic
expand
condense
outline
shadow

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Experimental Variants

experiments/static/

Contains one-off transformed fonts.

Examples:

jitter
wave
quantize
shear
collapse
droop
dropout
asc_evap

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Transformation Sequences

experiments/sequences/

Each directory contains a progressive transformation.

Example:

Sga-Regular_jitter_seq/

    Sga-Regular_jitter_000.ttf
    Sga-Regular_jitter_001.ttf
    ...
    Sga-Regular_jitter_007.ttf

Sequence 000 is closest to the original.

Sequence 007 is the most transformed.

These are intended for animation, visualization, or document degradation experiments.

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Compound Transformations

experiments/compound/

Contains multi-stage degradation models.

Examples:

full_decay
dissolution
wave_erosion
geological

These combine multiple transformations into a single progression.

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Generating Experimental Fonts

Main generator:

python make_experiments.py

This creates:

experiments/static/
experiments/sequences/
experiments/compound/

depending on configuration.

Generated fonts are normalized before saving to prevent coordinate overflow.

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Checking Glyph Integrity

python check-glyphs.py

Used to verify:

• Missing glyphs
• Broken contours
• Coordinate issues
• Encoding problems

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Debugging Font Generation

Logs:

errors.log
detailed-errors.log

Common failure:

Value does not fit in format h

This means transformed coordinates exceeded the TrueType signed 16-bit range.

The generator should normalize coordinates before writing.

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Previewing Fonts

HTML Preview

Generate a visual contact sheet:

python sample_sequence.py \
    --fonts experiments/sequences/Sga-Regular_jitter_seq \
    --out preview.html

Open:

firefox preview.html

or

python -m http.server

then visit:

http://localhost:8000

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Creating Typographic Degradation Documents

The repository includes:

make_degradation_doc.py

This converts a sequence of fonts into a progressively mutating document.

Example:

python make_degradation_doc.py \
    --fonts experiments/sequences/Sga-Regular_jitter_seq \
    --text source.txt \
    --granularity paragraph \
    --out output

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Granularity Modes

Paragraph

Each paragraph receives a different font.

--granularity paragraph

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Sentence

Each sentence receives a different font.

--granularity sentence

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Word

Each word receives a different font.

--granularity word

This often creates striking degradation effects.

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Page

Fonts change every simulated page.

--granularity page

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Compiling Generated Documents

After generation:

cd output
lualatex main.tex

Output:

main.pdf

The PDF gradually transitions through the font sequence.

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Example Experiments

Information Decay

Use:

full_decay

to simulate archival deterioration.

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Geological Drift

Use:

geological

to create slow structural mutation.

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Signal Corruption

Use:

dropout

or

collapse

to model information loss.

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Wave Distortion

Use:

wave

or

wave_erosion

to simulate transmission instability.

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Research Directions

Potential applications include:

• Procedural typography
• Experimental publishing
• Visual cryptography
• Artificial writing systems
• Information decay studies
• Archival aesthetics
• Legibility experiments
• Computational paleography
• Dynamic manuscripts
• Generative art

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Typical Workflow

Generate transformations:

python make_experiments.py

Inspect sequences:

python sample_sequence.py \
    --fonts experiments/sequences/Sga-Regular_jitter_seq

Generate a document:

python make_degradation_doc.py \
    --fonts experiments/sequences/Sga-Regular_jitter_seq \
    --text source.txt

Compile:

cd output
lualatex main.tex

Study the resulting progression from stable typography to transformed typography.

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License

See:

LICENSE

for licensing information.