Image data is analyzed after the aging test with a Python script (shared in the code repository). Due to the consistent shape of the samples, the script is designed to crop the images to the sample holder only, slice them to single sample sub-images, average the color over the sample, and color calibrate them (a result from the script analysis is shown in Figure ). The color calibration is performed by the aid of XRite ColorChecker Passport (Figure ). It is photographed in the chamber in the place of the sample holder as the first image of each aging test, and used as a reference. The difference between how the color of each color patch is known to appear under a D60 reference illuminant and how they are observed by the camera in the aging chamber is used as a basis for calibrating the colors of the samples. The color calibration is implemented via a 3-dimensional thin plate spline transformation from the color space of the chamber to the reference color space, first transforming the colors from RGB color space to LAB color space, then applying the spline transformation, and transforming back to LAB color space. The approach is described in detail in the Supplementary Material of our previous work and the code implementation is integrated into our analysis script (shared in the code repository). The Python script applies the color calibration automatically to all but the first picture in the aging test data folder and produces graphs on the average color-calibrated sample color as a function of the aging test duration (Figure ).