cielab-gamut-tools 0.5.3

Calculate and visualize CIELab colour gamuts of displays

cielab-gamut-tools

Calculate and visualize CIELab colour gamuts of displays.

Implements the gamut volume algorithm from the gamut-volume-m MATLAB library. Results are normative under IDMS v1.3, IEC 62977-3-5, and IEC 62906-6-1.

Installation

Pick the section for your operating system. Each path installs Python automatically if you don't already have it.

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Windows

1 — Open PowerShell

Press Win+R, type powershell, press Enter.

2 — Install Scoop

Scoop is a command-line package manager for Windows. Paste these two lines one at a time:

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
Invoke-RestMethod -Uri https://get.scoop.sh | Invoke-Expression

No administrator rights are needed. If you already have Scoop, skip this step.

3 — Install pipx

scoop install pipx

Scoop will install Python automatically if not already present.

4 — Install cielab-gamut-tools

pipx install cielab-gamut-tools

5 — Verify

cgt about

If you see the version and standards information, installation is complete. If cgt is not found, close PowerShell and reopen it, then try again.

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macOS

1 — Open Terminal

Press Cmd+Space, type Terminal, press Enter.

2 — Install Homebrew

Homebrew is a package manager for macOS. Paste this line (or get it from brew.sh):

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

Follow the on-screen prompts. If you already have Homebrew, skip this step.

3 — Install pipx

brew install pipx
pipx ensurepath

Close and reopen Terminal after running pipx ensurepath.

4 — Install cielab-gamut-tools

pipx install cielab-gamut-tools

5 — Verify

cgt about

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Linux (Ubuntu / Debian)

Ubuntu 23.04+ and Debian 12+ include pipx in their package repositories:

sudo apt install pipx
pipx ensurepath
pipx install cielab-gamut-tools

On older releases, replace the first line with sudo apt install python3-pip python3-venv && pip install --user pipx.

After running pipx ensurepath, reopen the terminal before running cgt about to verify.

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Updating

pipx upgrade cielab-gamut-tools

cgt about will tell you if a newer version is available.

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Install from source (developers)

git clone https://github.com/CIELab-gamut-tools/cielab-gamut-tools-py.git
cd cielab-gamut-tools-py
pip install -e ".[dev]"

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Command-line usage

After installation, three equivalent commands are available:

cielab-gamut-tools   # canonical name used in standards citations
cielab-tools         # short alias
cgt                  # shortest alias for everyday use

Standards and citation information

cgt about

Calculate gamut volume

# From a CGATS measurement file
cgt calculate volume display.txt

# Named reference gamut
cgt calculate volume srgb

# Multiple gamuts — tabulated output
cgt calculate volume display1.txt display2.txt srgb bt.2020

# Machine-readable output
cgt calculate volume display.txt -f json
cgt calculate volume display.txt -f csv

# Standards-traceable output (appends algorithm metadata)
cgt calculate volume display.txt -s IDMS -f json

# Value only, for scripting
cgt calculate volume srgb -q

Named gamuts: srgb, bt.2020, dci-p3, display-p3, adobe-rgb.

Calculate gamut coverage

# Coverage against a single reference
cgt calculate coverage display.txt -r srgb

# Multiple references in one pass
cgt calculate coverage display.txt -r srgb,bt.2020,dci-p3

# CSV for spreadsheet import
cgt calculate coverage display.txt -r srgb,bt.2020 -f csv

Compare multiple gamuts

# Volume comparison — delta vs first gamut
cgt calculate compare display1.txt display2.txt display3.txt

# Coverage of each against a single reference
cgt calculate compare display1.txt display2.txt -r srgb

# Full pairwise intersection matrix (entry (i,j) = % of gamut j covered by gamut i)
cgt calculate compare srgb bt.2020 dci-p3 display-p3 -m
cgt calculate compare srgb bt.2020 dci-p3 -m -f csv

Visualise gamut diagrams

Rings diagram	3D surface
sRGB ∩ BT.2020	sRGB solid + BT.2020 wireframe

# 2D ring diagram (a*-b* plane, L* encoded as ring radii)
cgt plot rings display.txt
cgt plot rings display.txt -r srgb          # with reference overlay
cgt plot rings display.txt -r srgb -i       # intersection view
cgt plot rings display.txt -r srgb -o rings.png --dpi 200

# 3D surface in CIELab space
cgt plot surface display.txt
cgt plot surface srgb bt.2020 --alpha 0.4   # overlay, see-through
cgt plot surface srgb bt.2020 --style ",wireframe+grey+lw:0.5"  # mixed solid/wireframe
cgt plot surface display.txt srgb -o comparison.png

Both commands have many more options — see the detailed references: Rings diagram options · Surface plot options

Generate reference files

# RGB test signal list for measurement (normative 602-point set, m=11)
cgt generate rgb-signals                     # CGATS to stdout
cgt generate rgb-signals -o signals.txt
cgt generate rgb-signals -g 9 -b 10         # reduced grid, 10-bit

# Synthetic reference gamut as CGATS file
cgt generate synthetic srgb -o srgb_envelope.txt
cgt generate synthetic bt.2020 -m measurement -o bt2020_meas.txt

# Custom primaries
cgt generate synthetic \
    --primaries 0.64,0.33,0.21,0.71,0.15,0.06 \
    --white 0.3127,0.3290 --gamma 2.2 -o custom.txt

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Numerical precision

All three computation paths give the same volume result:

Path	sRGB example
calculate volume srgb	830,807
CGATS measurement file	830,807
CGATS envelope file	830,807

The MATLAB reference value for sRGB is 830,766 (~0.005% difference). The standards specify a tolerance of ±1%.

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Using as a Python library

The CLI covers most workflows. If you need to integrate gamut calculations into a Python script or pipeline:

from cielab_gamut_tools import Gamut, SyntheticGamut

# Load measured display gamut
display = Gamut.from_cgats("measurements.txt")

# Reference gamuts
srgb   = SyntheticGamut.srgb()
bt2020 = SyntheticGamut.bt2020()

# Volume and coverage
print(f"Display volume: {display.volume():.0f}")
intersection = display.intersect(srgb)
print(f"sRGB coverage: {intersection.volume() / srgb.volume() * 100:.1f}%")

# Visualize (returns a matplotlib Figure)
fig = display.plot_rings(reference=srgb)
fig.savefig("rings.png", dpi=150)

Available reference gamuts: srgb(), bt2020(), dci_p3(), display_p3(), adobe_rgb(), or construct a custom gamut from CIE xy primaries and white point:

custom = SyntheticGamut(
    primaries_xy=[[0.68, 0.32], [0.265, 0.69], [0.15, 0.06]],
    white_xy=[0.3127, 0.329],
    gamma=2.2,
)

Test signal generation and CGATS export are also available via the API — see the module docstrings for details.

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Troubleshooting

CLI command not found after installation
Close the terminal and reopen it — PATH changes from pipx and Scoop take effect in new sessions. If still missing, run pipx ensurepath (macOS/Linux) or check that Scoop completed without errors (Windows).

File not found errors
Pass an absolute path to your measurement file. On Windows you can Shift+right-click the file and choose "Copy as path"; on macOS hold Option when right-clicking and choose "Copy … as Pathname".

Plot window doesn't appear when using the Python API
Call import matplotlib.pyplot as plt; plt.show() after plotting, or use --output via the CLI to save directly to a file.

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Interactive UI

cgt ui launches a local web application for interactive gamut exploration.

cgt ui              # opens browser at http://localhost:8000
cgt ui --port 8080  # custom port
cgt ui --no-browser # server only

Features: drag-and-drop CGATS file loading, rings diagram and 3D surface views, pairwise coverage matrix, PNG/PDF export.

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Development

git clone https://github.com/CIELab-gamut-tools/cielab-gamut-tools-py.git
cd cielab-gamut-tools-py
pip install -e ".[dev]"
pytest

To work on the UI frontend (requires Node.js):

# Build the frontend once (output goes to ui/dist/, served by cgt ui)
make ui

# Run frontend dev server with hot-reload (proxies /api to the Python server)
cd src/cielab_gamut_tools/ui/frontend
npm install
npm run dev   # Vite on :5173, Python API on :8000

Citations

If you use this software in academic work, please cite:

Gamut volume calculation:

E. Smith, R. L. Heckaman, K. Lang, J. Penczek, J. Bergquist (2020). "Measuring the color capability of modern display systems." Journal of the Society for Information Display, 28(6), 548–556. https://doi.org/10.1002/jsid.918

Gamut rings concept:

K. Masaoka, F. Jiang, M. D. Fairchild, R. L. Heckaman (2020). "Analysis of color volume of multi-chromatic displays using gamut rings." Journal of the Society for Information Display, 28(3), 273–286. https://doi.org/10.1002/jsid.852

Gamut ring intersection:

K. Masaoka, E. Smith, K. Lang, B. Berkeley, J. Bergquist, J. Penczek (2025). "Visualization of reproducible object colors in standard color spaces using the gamut ring intersection." Journal of the Society for Information Display, 33(4), 231–245. https://doi.org/10.1002/jsid.2031

License

MIT — see LICENSE for details.