Tritanopia Simulation Matrix

Apply Machado et al. 2009 full-severity tritan matrix in linear sRGB then encode, reporting clipping. Model visualization only, not diagnosis, an exact individual view or accessibility certification.

Description

A tritanopia visualization can transform linear-light RGB with a published full-severity matrix.

A tritanopia visualization can transform linear-light RGB with a published full-severity matrix. It represents a model rather than an individual view.^{[1, 2]}

Enter three encoded normalized sRGB channels 0–1. Decode the sRGB transfer, apply the Machado 2009 tritan matrix, clip linear channels 0–1 and encode. Return RGB and indexes of strict linear excursions.

When to use Tritanopia Simulation Matrix

Use Tritanopia Simulation Matrix when you need to evaluate the supplied records under the calculation and evidence rules below. No diagnosis, exact individual simulation or accessibility certification is provided.

Prepare colors in the stated color space and scale. Use encoded RGB fractions, linear RGB, Lab, xy, byte values or ink percentages exactly as requested; supply caller tolerances and reference conditions.

How to use Tritanopia Simulation Matrix and understand its results

Prepare colors in the stated color space and scale. Use encoded RGB fractions, linear RGB, Lab, xy, byte values or ink percentages exactly as requested; supply caller tolerances and reference conditions.
Enter baseRgb using the field table and calculation rules, then run the tool.
Read simulatedRgb, clippedLinearChannelIndices. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
baseRgb	Base rgb	list of number	Required

encodedRGB → linearRGB → tritan matrix → clamp → encode

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
simulatedRgb	Simulated rgb	list of number
clippedLinearChannelIndices	Clipped linear channel indices	list of number

json

{
  "input": {
    "baseRgb": [
      1,
      0,
      0
    ]
  },
  "output": {
    "simulatedRgb": [
      0.9999999999999999,
      0,
      0.058385974375206574
    ],
    "clippedLinearChannelIndices": [
      0,
      1
    ]
  }
}

Limitations and assumptions

No diagnosis, exact individual simulation or accessibility certification is provided.

Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Numeric lists are limited to 10,000 entries; string lists to 128 strings of at most 128 characters each. The rules above may impose smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Protanopia Simulation Matrix: A protanopia visualization applies a published full-severity model in linear sRGB. Clipping remains visible in the returned evidence. For a complementary task, use Deuteranopia Simulation Matrix: A deuteranopia visualization applies a full-severity model to linear sRGB. Returned clipping evidence shows lost channel excursions.

Further background: A physiologically-based model for simulation of color vision deficiency (2009).

References

Tritanopia Simulation Matrix — tool.io
A physiologically-based model for simulation of color vision deficiency (2009) — Machado, Oliveira and Fernandes

Similar or alternative tools

Protanopia Simulation Matrix
A protanopia visualization applies a published full-severity model in linear sRGB. Clipping remains visible in the returned evidence.
Deuteranopia Simulation Matrix
A deuteranopia visualization applies a full-severity model to linear sRGB. Returned clipping evidence shows lost channel excursions.