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# Chromatic Adaptation
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Comprehensive chromatic adaptation functionality for adapting stimuli between different viewing conditions and illuminants using various chromatic adaptation models and transforms.
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## Capabilities
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### Main Chromatic Adaptation Function
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The primary function for chromatic adaptation with multiple method support.
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```python { .api }
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def chromatic_adaptation(
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    XYZ: ArrayLike, 
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    XYZ_w: ArrayLike, 
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    XYZ_wr: ArrayLike, 
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    method: Literal["CIE 1994", "CMCCAT2000", "Fairchild 1990", "Von Kries", "Zhai 2018", "vK20"] = "Von Kries",
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    **kwargs: Any
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus from test viewing conditions to reference viewing conditions.
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    Parameters:
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    - XYZ: CIE XYZ tristimulus values of stimulus to adapt
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    - XYZ_w: test viewing condition CIE XYZ tristimulus values of the whitepoint
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    - XYZ_wr: reference viewing condition CIE XYZ tristimulus values of the whitepoint
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    - method: chromatic adaptation method to use
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    - **kwargs: method-specific parameters (see individual methods for details)
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    Returns:
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    CIE XYZ_c tristimulus values of the stimulus corresponding colour
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    Supported Methods:
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    - "Von Kries": Classical Von Kries chromatic adaptation
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    - "CIE 1994": CIE 1994 chromatic adaptation model 
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    - "CMCCAT2000": CMC CAT2000 chromatic adaptation transform
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    - "Fairchild 1990": Fairchild's 1990 incomplete chromatic adaptation model
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    - "Zhai 2018": Zhai and Luo 2018 two-step chromatic adaptation
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    - "vK20": Von Kries 2020 evolution with degree of adaptation
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    Domain/Range: [0, 1] for all XYZ parameters in Scale - 1 mode
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    """
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```
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### Von Kries Chromatic Adaptation
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Classical Von Kries chromatic adaptation model implementation.
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```python { .api }
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def matrix_chromatic_adaptation_VonKries(
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    XYZ_w: ArrayLike,
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    XYZ_wr: ArrayLike, 
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    transform: LiteralChromaticAdaptationTransform = "CAT02"
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) -> NDArrayFloat:
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    """
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    Compute the chromatic adaptation matrix from test viewing conditions to reference viewing conditions.
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    Parameters:
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    - XYZ_w: test viewing conditions CIE XYZ tristimulus values of whitepoint
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    - XYZ_wr: reference viewing conditions CIE XYZ tristimulus values of whitepoint
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    - transform: chromatic adaptation transform matrix to use
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    Returns:
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    Chromatic adaptation matrix M_cat
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    Available transforms: "XYZ Scaling", "Von Kries", "Bradford", "Sharp", 
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    "Fairchild", "CMCCAT97", "CMCCAT2000", "CAT02", "CAT02 Brill 2008", 
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    "CAT16", "Bianco 2010", "Bianco PC 2010"
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    """
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def chromatic_adaptation_VonKries(
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    XYZ: ArrayLike,
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    XYZ_w: ArrayLike,
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    XYZ_wr: ArrayLike,
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    transform: LiteralChromaticAdaptationTransform = "CAT02"
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus CIE XYZ tristimulus values from test viewing conditions 
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    to reference viewing conditions using Von Kries chromatic adaptation model.
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    Parameters:
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    - XYZ: CIE XYZ tristimulus values of stimulus to adapt
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    - XYZ_w: test viewing condition CIE XYZ tristimulus values of whitepoint
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    - XYZ_wr: reference viewing condition CIE XYZ tristimulus values of whitepoint  
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    - transform: chromatic adaptation transform matrix to use
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    Returns:
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    CIE XYZ_c tristimulus values of the stimulus corresponding colour
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    """
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```
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### CMCCAT2000 Chromatic Adaptation
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CMC CAT2000 chromatic adaptation transform with viewing condition support.
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```python { .api }
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class InductionFactors_CMCCAT2000:
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    """
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    CMCCAT2000 chromatic adaptation model induction factors.
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    Attributes:
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    - F: surround condition factor
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    """
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    F: float
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def chromatic_adaptation_CMCCAT2000(
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    XYZ: ArrayLike,
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    XYZ_w: ArrayLike,
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    XYZ_wr: ArrayLike,
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    L_A1: ArrayLike,
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    L_A2: ArrayLike,
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    surround: InductionFactors_CMCCAT2000 = None,
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    direction: Literal["Forward", "Inverse"] = "Forward"
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus CIE XYZ tristimulus values from test viewing conditions 
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    to reference viewing conditions using CMCCAT2000 chromatic adaptation model.
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    Parameters:
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    - XYZ: CIE XYZ tristimulus values of the stimulus to adapt
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    - XYZ_w: test viewing condition CIE XYZ tristimulus values of whitepoint
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    - XYZ_wr: reference viewing condition CIE XYZ tristimulus values of whitepoint
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    - L_A1: luminance of test adapting field in cd/m²
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    - L_A2: luminance of reference adapting field in cd/m²
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    - surround: surround viewing conditions induction factors
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    - direction: chromatic adaptation direction ("Forward" or "Inverse")
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    Returns:
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    CIE XYZ_c tristimulus values of the stimulus corresponding colour
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    Domain/Range: [0, 100] for XYZ in reference scale, [0, 1] in scale-1 mode
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    """
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def chromatic_adaptation_forward_CMCCAT2000(
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    XYZ: ArrayLike,
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    XYZ_w: ArrayLike,
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    XYZ_wr: ArrayLike,
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    L_A1: ArrayLike,
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    L_A2: ArrayLike,
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    surround: InductionFactors_CMCCAT2000 = None
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) -> NDArrayFloat:
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    """
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    Forward CMCCAT2000 chromatic adaptation from test to reference conditions.
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    Parameters same as chromatic_adaptation_CMCCAT2000 with direction="Forward"
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    """
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def chromatic_adaptation_inverse_CMCCAT2000(
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    XYZ: ArrayLike,
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    XYZ_w: ArrayLike,
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    XYZ_wr: ArrayLike,
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    L_A1: ArrayLike,
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    L_A2: ArrayLike,
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    surround: InductionFactors_CMCCAT2000 = None
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) -> NDArrayFloat:
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    """
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    Inverse CMCCAT2000 chromatic adaptation from reference to test conditions.
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    Parameters same as chromatic_adaptation_CMCCAT2000 with direction="Inverse"
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    """
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```
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### CIE 1994 Chromatic Adaptation
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CIE 1994 chromatic adaptation model with illuminance considerations.
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```python { .api }
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def chromatic_adaptation_CIE1994(
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    XYZ_1: ArrayLike,
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    xy_o1: ArrayLike,
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    xy_o2: ArrayLike,
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    Y_o: ArrayLike,
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    E_o1: ArrayLike,
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    E_o2: ArrayLike,
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    n: ArrayLike = 1
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus CIE XYZ tristimulus values from test viewing conditions 
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    to reference viewing conditions using CIE 1994 chromatic adaptation model.
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    Parameters:
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    - XYZ_1: CIE XYZ tristimulus values of test sample/stimulus
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    - xy_o1: chromaticity coordinates of test illuminant and background
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    - xy_o2: chromaticity coordinates of reference illuminant and background
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    - Y_o: luminance factor of achromatic background as percentage [18, 100]
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    - E_o1: test illuminance in cd/m²
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    - E_o2: reference illuminance in cd/m²
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    - n: noise component in fundamental primary system
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    Returns:
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    Adapted CIE XYZ tristimulus values of stimulus
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    Domain/Range: [0, 100] for XYZ and Y_o in reference scale
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    """
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```
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### Fairchild 1990 Chromatic Adaptation
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Fairchild's 1990 incomplete chromatic adaptation model.
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```python { .api }
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def chromatic_adaptation_Fairchild1990(
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    XYZ_1: ArrayLike,
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    XYZ_n: ArrayLike,
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    XYZ_r: ArrayLike,
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    Y_n: ArrayLike,
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    discount_illuminant: bool = False
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus CIE XYZ tristimulus values from test viewing conditions 
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    to reference viewing conditions using Fairchild (1990) chromatic adaptation model.
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    Parameters:
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    - XYZ_1: CIE XYZ tristimulus values of test sample/stimulus
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    - XYZ_n: test viewing condition CIE XYZ tristimulus values of whitepoint
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    - XYZ_r: reference viewing condition CIE XYZ tristimulus values of whitepoint
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    - Y_n: luminance of test adapting stimulus in cd/m²
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    - discount_illuminant: whether the illuminant should be discounted
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    Returns:
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    Adapted CIE XYZ tristimulus values of stimulus
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    Domain/Range: [0, 100] for XYZ in reference scale, [0, 1] in scale-1 mode
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    """
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```
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### Von Kries 2020 (vK20) Chromatic Adaptation
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Modern evolution of Von Kries adaptation with degree of adaptation coefficients.
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```python { .api }
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class Coefficients_DegreeOfAdaptation_vK20:
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    """
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    Von Kries 2020 (vK20) degree of adaptation coefficients.
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    Attributes:
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    - D_n: degree of adaptation for the adapting illuminant
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    - D_r: degree of adaptation for the reference illuminant  
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    - D_p: degree of adaptation for the previous illuminant
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    """
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    D_n: float
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    D_r: float
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    D_p: float
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def matrix_chromatic_adaptation_vk20(
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    XYZ_p: ArrayLike,
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    XYZ_n: ArrayLike,
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    XYZ_r: ArrayLike = None,
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    coefficients: Coefficients_DegreeOfAdaptation_vK20 = None,
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    transform: LiteralChromaticAdaptationTransform = "CAT02"
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) -> NDArrayFloat:
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    """
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    Compute the vK20 chromatic adaptation matrix.
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    Parameters:
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    - XYZ_p: previous/test viewing conditions XYZ tristimulus values of whitepoint
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    - XYZ_n: current viewing conditions XYZ tristimulus values of whitepoint
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    - XYZ_r: reference viewing conditions XYZ tristimulus values of whitepoint
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    - coefficients: vK20 degree of adaptation coefficients
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    - transform: chromatic adaptation transform matrix to use
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    Returns:
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    vK20 chromatic adaptation matrix
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    """
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def chromatic_adaptation_vK20(
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    XYZ: ArrayLike,
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    XYZ_p: ArrayLike,
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    XYZ_n: ArrayLike,
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    XYZ_r: ArrayLike = None,
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    coefficients: Coefficients_DegreeOfAdaptation_vK20 = None,
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    transform: LiteralChromaticAdaptationTransform = "CAT02"
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) -> NDArrayFloat:
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    """
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    Adapt given stimulus CIE XYZ tristimulus values using Von Kries 2020 (vK20) 
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    chromatic adaptation model.
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    Parameters:
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    - XYZ: CIE XYZ tristimulus values of stimulus to adapt
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    - XYZ_p: previous/test viewing conditions XYZ tristimulus values of whitepoint
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    - XYZ_n: current viewing conditions XYZ tristimulus values of whitepoint
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    - XYZ_r: reference viewing conditions XYZ tristimulus values of whitepoint
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    - coefficients: vK20 degree of adaptation coefficients
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    - transform: chromatic adaptation transform matrix to use
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    Returns:
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    CIE XYZ_c tristimulus values of the stimulus corresponding colour
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    """
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```
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### Zhai and Luo 2018 Chromatic Adaptation
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Two-step chromatic adaptation model with baseline illuminant concept.
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```python { .api }
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def chromatic_adaptation_Zhai2018(
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    XYZ_b: ArrayLike,
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    XYZ_wb: ArrayLike,
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    XYZ_wd: ArrayLike,
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    D_b: ArrayLike = 1,
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    D_d: ArrayLike = 1,
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    XYZ_wo: ArrayLike = None,
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    transform: Literal["CAT02", "CAT16"] = "CAT02"
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) -> NDArrayFloat:
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    """
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    Adapt given sample colour from input viewing conditions to output viewing conditions 
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    using Zhai and Luo (2018) two-step chromatic adaptation model.
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    This model uses a baseline illuminant (BI) concept where adaptation is calculated
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    relative to an intrinsic property of the human vision system, allowing for 
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    incomplete-to-incomplete adaptation scenarios.
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    Parameters:
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    - XYZ_b: sample colour under input illuminant β
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    - XYZ_wb: input illuminant β tristimulus values
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    - XYZ_wd: output illuminant δ tristimulus values  
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    - D_b: degree of adaptation of input illuminant β
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    - D_d: degree of adaptation of output illuminant δ
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    - XYZ_wo: baseline illuminant (BI) tristimulus values
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    - transform: chromatic adaptation transform ("CAT02" or "CAT16")
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    Returns:
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    Sample corresponding colour XYZ tristimulus values under output illuminant
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    Domain/Range: [0, 100] for XYZ in reference scale, [0, 1] in scale-1 mode
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    """
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```
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## Chromatic Adaptation Transform Matrices
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Pre-defined chromatic adaptation transform matrices for various CAT models.
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```python { .api }
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# Primary CAT Matrices (3x3 NDArrayFloat)
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CAT_XYZ_SCALING: NDArrayFloat
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"""XYZ Scaling chromatic adaptation transform (identity matrix)."""
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CAT_VON_KRIES: NDArrayFloat  
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"""Von Kries chromatic adaptation transform."""
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CAT_BRADFORD: NDArrayFloat
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"""Bradford chromatic adaptation transform."""
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CAT_SHARP: NDArrayFloat
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"""Sharp chromatic adaptation transform."""
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CAT_FAIRCHILD: NDArrayFloat
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"""Fairchild chromatic adaptation transform."""
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CAT_CMCCAT97: NDArrayFloat
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"""CMCCAT97 chromatic adaptation transform."""
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CAT_CMCCAT2000: NDArrayFloat
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"""CMCCAT2000 chromatic adaptation transform."""
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CAT_CAT02: NDArrayFloat
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"""CAT02 chromatic adaptation transform."""
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CAT_CAT02_BRILL2008: NDArrayFloat
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"""Brill and Susstrunk (2008) corrected CAT02 chromatic adaptation transform."""
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CAT_CAT16: NDArrayFloat
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"""CAT16 chromatic adaptation transform."""
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CAT_BIANCO2010: NDArrayFloat
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"""Bianco and Schettini (2010) chromatic adaptation transform."""
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CAT_PC_BIANCO2010: NDArrayFloat
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"""Bianco and Schettini PC (2010) chromatic adaptation transform (no negative lobes)."""
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```
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## Viewing Conditions and Constants
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Standard viewing conditions and adaptation coefficients for chromatic adaptation models.
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```python { .api }
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# CMCCAT2000 Viewing Conditions
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VIEWING_CONDITIONS_CMCCAT2000: Dict[str, InductionFactors_CMCCAT2000]
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"""
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Reference CMCCAT2000 chromatic adaptation model viewing conditions.
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Available conditions:
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- "Average": F = 1.0
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- "Dim": F = 0.8  
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- "Dark": F = 0.8
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"""
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# vK20 Degree of Adaptation Conditions  
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CONDITIONS_DEGREE_OF_ADAPTATION_VK20: Dict[str, Coefficients_DegreeOfAdaptation_vK20]
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"""
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Conditions for the Von Kries 2020 (vK20) degree of adaptation coefficients.
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Available conditions:
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- "Fairchild": (D_n=0.7, D_r=0.3, D_p=0)
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- "Hands": (D_n=0.95, D_r=0.05, D_p=0)
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- "No Hands": (D_n=0.85, D_r=0.15, D_p=0)
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- "Ordinal 1st": (D_n=0.9, D_r=0.1, D_p=0)
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- "Ordinal 2nd": (D_n=0.8, D_r=0.1, D_p=0.1)
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- "Reversibility Trial 1st": (D_n=0.7, D_r=0.3, D_p=0.1)
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- "Reversibility Trial 2nd": (D_n=0.6, D_r=0.3, D_p=0.1)
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- "Ma et al.": (D_n=1/3, D_r=1/3, D_p=1/3)
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- "Hunt & Winter": (D_n=0.6, D_r=0.2, D_p=0.2)  
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- "Hurvich & Jameson": (D_n=0.7, D_r=0.3, D_p=0)
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- "Simple von Kries": (D_n=1, D_r=0, D_p=0)
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"""
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TVS_XYZ_R_VK20: NDArrayFloat
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"""
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Von Kries 2020 (vK20) reference illuminant tristimulus values.
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Approximately 15000K sky blue (u'=0.185, v'=0.425).
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"""
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# Transform Collections
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CHROMATIC_ADAPTATION_TRANSFORMS: Dict[str, NDArrayFloat]
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"""
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Available chromatic adaptation transforms mapping method names to matrices.
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Keys: "XYZ Scaling", "Von Kries", "Bradford", "Sharp", "Fairchild", 
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"CMCCAT97", "CMCCAT2000", "CAT02", "CAT02 Brill 2008", "CAT16", 
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"Bianco 2010", "Bianco PC 2010"
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"""
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CHROMATIC_ADAPTATION_METHODS: Dict[str, Callable]
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"""
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Supported chromatic adaptation methods mapping method names to functions.
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Keys: "CIE 1994", "CMCCAT2000", "Fairchild 1990", "Von Kries", 
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"Zhai 2018", "vK20"
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"""
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```
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## Usage Examples
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### Basic Von Kries Adaptation
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```python
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import numpy as np
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437
# Basic Von Kries chromatic adaptation
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XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
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XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])  # D65
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XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])  # D50
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# Adapt from D65 to D50 using Von Kries (default)
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XYZ_adapted = chromatic_adaptation(XYZ, XYZ_w, XYZ_wr)
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# array([0.21638817, 0.1257, 0.03847493])
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# Using Bradford transform explicitly
447
XYZ_adapted_bradford = chromatic_adaptation_VonKries(
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    XYZ, XYZ_w, XYZ_wr, transform="Bradford"
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)
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```
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### CMCCAT2000 Adaptation with Viewing Conditions
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```python
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# CMCCAT2000 adaptation with specific viewing conditions
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XYZ = np.array([0.2248, 0.2274, 0.0854])
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XYZ_w = np.array([1.1115, 1.0000, 0.3520])
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XYZ_wr = np.array([0.9481, 1.0000, 1.0730])
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L_A = 200
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461
XYZ_adapted = chromatic_adaptation(
462
    XYZ, XYZ_w, XYZ_wr, 
463
    method="CMCCAT2000",
464
    L_A1=L_A, 
465
    L_A2=L_A,
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    surround=VIEWING_CONDITIONS_CMCCAT2000["Average"]
467
)
468
```
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### vK20 Adaptation with Custom Coefficients  
471

472
```python
473
# Von Kries 2020 adaptation with specific coefficients
474
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
475
XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
476
XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
477

478
# Using predefined coefficients
479
XYZ_adapted = chromatic_adaptation(
480
    XYZ, XYZ_w, XYZ_wr,
481
    method="vK20",
482
    coefficients=CONDITIONS_DEGREE_OF_ADAPTATION_VK20["Fairchild"]
483
)
484

485
# Using custom coefficients
486
custom_coeffs = Coefficients_DegreeOfAdaptation_vK20(D_n=0.8, D_r=0.2, D_p=0)
487
XYZ_adapted_custom = chromatic_adaptation_vK20(
488
    XYZ, XYZ_w, XYZ_wr, coefficients=custom_coeffs
489
)
490
```
491

492
### Two-Step Zhai 2018 Adaptation
493

494
```python
495
# Zhai 2018 two-step adaptation with baseline illuminant
496
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
497
XYZ_wb = np.array([0.95045593, 1.00000000, 1.08905775])  # Input illuminant
498
XYZ_wd = np.array([0.96429568, 1.00000000, 0.82510460])  # Output illuminant
499
XYZ_wo = np.array([100, 100, 100])  # Baseline illuminant
500

501
XYZ_adapted = chromatic_adaptation(
502
    XYZ, XYZ_wb, XYZ_wd,
503
    method="Zhai 2018",
504
    D_b=0.9,      # Degree of adaptation for input
505
    D_d=0.95,     # Degree of adaptation for output  
506
    XYZ_wo=XYZ_wo
507
)
508
```
509

510
### Computing Adaptation Matrices
511

512
```python
513
# Compute Von Kries adaptation matrix
514
XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
515
XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
516

517
# Using CAT02 transform
518
M_cat = matrix_chromatic_adaptation_VonKries(XYZ_w, XYZ_wr, transform="CAT02")
519

520
# Apply matrix directly to adapt colors
521
XYZ_adapted_manual = XYZ @ M_cat.T
522

523
# vK20 adaptation matrix
524
M_vk20 = matrix_chromatic_adaptation_vk20(
525
    XYZ_w, XYZ_wr, 
526
    coefficients=CONDITIONS_DEGREE_OF_ADAPTATION_VK20["Fairchild"]
527
)
528
```
529

530
## Type Definitions
531

532
```python
533
from typing import Literal, Union
534
from numpy.typing import NDArray
535

536
# Type aliases for chromatic adaptation
537
ArrayLike = Union[list, tuple, NDArray]
538
NDArrayFloat = NDArray[float]
539

540
LiteralChromaticAdaptationTransform = Literal[
541
    "XYZ Scaling", "Von Kries", "Bradford", "Sharp", "Fairchild",
542
    "CMCCAT97", "CMCCAT2000", "CAT02", "CAT02 Brill 2008", "CAT16", 
543
    "Bianco 2010", "Bianco PC 2010"
544
]
545

546
LiteralChromaticAdaptationMethod = Literal[
547
    "CIE 1994", "CMCCAT2000", "Fairchild 1990", 
548
    "Von Kries", "Zhai 2018", "vK20"
549
]
550
```
551

552
## Notes
553

554
### Domain and Range Scaling
555

556
Most chromatic adaptation functions support dual domain/range scaling:
557
- **Reference Scale**: XYZ values in [0, 100], Y_o in [0, 100]
558
- **Scale-1**: XYZ values in [0, 1], Y_o in [0, 1]
559

560
The scaling mode is controlled by the global domain-range scale setting.
561

562
### Transform Selection Guidelines
563

564
- **CAT02**: Default for most applications, good balance of accuracy and stability
565
- **Bradford**: Widely used, excellent for D-series illuminants
566
- **Von Kries**: Classical choice, simple and robust
567
- **CAT16**: Modern choice, designed for CAM16 color appearance model
568
- **Sharp/Bianco**: Optimized transforms for specific applications
569
- **CMCCAT2000**: Specialized for CMCCAT2000 model usage
570

571
### Method Selection Guidelines
572

573
- **Von Kries**: Fast, simple, suitable for most applications
574
- **CMCCAT2000**: When viewing conditions (luminance, surround) are important
575
- **CIE 1994**: When illuminance levels affect adaptation
576
- **Fairchild 1990**: For incomplete adaptation scenarios
577
- **vK20**: Modern approach with adaptation history consideration
578
- **Zhai 2018**: For complex incomplete-to-incomplete adaptation scenarios
579

580
### Performance Considerations
581

582
- Von Kries methods are fastest (simple matrix operations)
583
- CMCCAT2000 and CIE 1994 have moderate computational overhead
584
- Zhai 2018 is most complex (two-step process with baseline illuminant)
585
- Matrix pre-computation recommended for batch processing