colour.recovery.PCA_Jiang2013#
- colour.recovery.PCA_Jiang2013(msds_camera_sensitivities: Mapping[str, MultiSpectralDistributions], eigen_w_v_count: Optional[int] = None, additional_data: bool = False) Union[Tuple[Tuple[NDArrayFloat, NDArrayFloat, NDArrayFloat], Tuple[NDArrayFloat, NDArrayFloat, NDArrayFloat]], Tuple[NDArrayFloat, NDArrayFloat, NDArrayFloat]] [source]#
Perform the Principal Component Analysis (PCA) on given camera RGB sensitivities.
- Parameters:
- Returns:
Tuple of camera RGB sensitivities eigen-values \(w\) and eigen-vectors \(v\) or tuple of camera RGB sensitivities eigen-vectors \(v\).
- Return type:
Examples
>>> from colour.colorimetry import SpectralShape >>> from colour.characterisation import MSDS_CAMERA_SENSITIVITIES >>> shape = SpectralShape(400, 700, 10) >>> camera_sensitivities = { ... camera: msds.copy().align(shape) ... for camera, msds in MSDS_CAMERA_SENSITIVITIES.items() ... } >>> np.array(PCA_Jiang2013(camera_sensitivities)).shape (3, 31, 31)