colour.models.log_encoding_CanonLog¶

colour.models.log_encoding_CanonLog(x: FloatingOrArrayLike, bit_depth: int = 10, out_normalised_code_value: bool = True, in_reflection: bool = True) → FloatingOrNDArray[source]¶

Define the Canon Log log encoding curve / opto-electronic transfer function.

Parameters

x (FloatingOrArrayLike) – Linear data \(x\).
bit_depth (int) – Bit depth used for conversion.
out_normalised_code_value (bool) – Whether the Canon Log non-linear data is encoded as normalised code values.
in_reflection (bool) – Whether the light level \(x\) to a camera is reflection.

Returns

Canon Log non-linear data.

Return type

numpy.floating or numpy.ndarray

References

[Tho12]

Notes

Domain	Scale - Reference	Scale - 1
`x`	[0, 1]	[0, 1]

Range	Scale - Reference	Scale - 1
`clog`	[0, 1]	[0, 1]

Examples

>>> log_encoding_CanonLog(0.18) * 100  
34.3389651...

The values of Table 2 Canon-Log Code Values table in [Tho12] are obtained as follows:

>>> x = np.array([0, 2, 18, 90, 720]) / 100
>>> np.around(log_encoding_CanonLog(x) * (2 ** 10 - 1)).astype(np.int)
array([ 128,  169,  351,  614, 1016])
>>> np.around(log_encoding_CanonLog(x, 10, False) * 100, 1)
array([   7.3,   12. ,   32.8,   62.7,  108.7])

colour.models.log_decoding_CanonLog3

colour.models.log_decoding_CanonLog