colour

If you are interested in this topic, we have a fully feature colour science Python package that can of course render the visible spectrum: https://github.com/colour-science/colour?tab=readme-ov-file#...

Quite enjoying the idea as I have been looking for something like this for a while but it is reallllllly slow for our medium sized codebase, I have like 2 or 3 fps on my M1: https://github.com/colour-science/colour/tree/develop/colour

I haven’t seen the math for the conversion of the article but typically the conversion from CCT to xy/uv are given for a particular domain. One of the conversion with the largest domain, i.e. Ohno m, covers domain [1000K, 100000K]: https://github.com/colour-science/colour/blob/develop/colour... Infinity is very much in extrapolation territory.

Negative numbers are not really an issue, quite the opposite because they are necessary for invertibility of most of the computations. We almost never ever clip values in Colour (https://github.com/colour-science/colour) and leave that responsibility to the user. One exception is conversion to Hexadecimal where if you don't do ensure the values are in the range [0, 1], you will induce the user in error: https://github.com/colour-science/colour/issues/584#issuecom...

Has anyone here used the Python "Colour" library? They've got pretty extensive and awesome documentation. I discovered it a couple of months ago. https://github.com/colour-science/colour

Would be very easy to fix using the above numbers and adding proper encoding, even a naive gamma 2.2 would help :) Here is a Gist for the spectral computations: https://gist.github.com/KelSolaar/fb1e09b56b54d37d90e1886aef... (It uses Colour: https://github.com/colour-science/colour)

Colour 0.3.14 (https://github.com/colour-science/colour/releases/tag/v0.3.1...) has also been released over the weekend along with Colour - Datasets 0.1.0 (https://github.com/colour-science/colour-datasets/releases/t...), a new Python package dedicated to colour science datasets management.

I would like to add that the problem with the codedrome.com implementation is that it is relying on an approximation to convert wavelengths to RGB, it is a shame because you really just need the Colour Matching Functions (CMFs) data for the Standard Observer of interest, i.e. 2deg or 10deg (https://github.com/colour-science/colour/blob/develop/colour...) and a 3x3 matrix to convert from CIE XYZ to the RGB colourspace of interest, e.g. sRGB (https://github.com/colour-science/colour/blob/develop/colour...).

We do have support for quite a few chromatic adaptation transforms to cones space (https://github.com/colour-science/colour/blob/develop/colour...) some cones space transformation are directly tied to the various chromatic adaptation models (https://github.com/colour-science/colour/tree/develop/colour...) or colour appearance models (https://github.com/colour-science/colour/tree/develop/colour...) we have implemented. We also have the Stockman & Sharpe Cone Fundamentals for 2 and 10 degree observers (https://github.com/colour-science/colour/blob/develop/colour...) and the code to convert those cone fundamentals cmfs to the corresponding XYZ cmfs (https://github.com/colour-science/colour/blob/develop/colour...) although it is more educational than anything else because often, the resulting cmfs are manually adjusted (I would have to check