In my quest to teach people the science behind light interrupting the circadian rhythm, I found that existing graphics tools produced very ugly visuals.
I am considering turning these into a webapp. Please contact me if you are interested in this.
Written in Python 3, Beautiful Photometry generates Spectral Power Distributions (SPDs), essentially the fingerprints of different light sources.
Beautiful Photometry can display individual SPDs or compare them on the same chart. It can also compute metrics such as: M/P ratio, S/P ratio, and CRI.
Why Beautiful Photometry is Significant
While two white light sources might look similar, the relative intensity of each wavelength may vary substantially. Small changes to the SPD affect color quality, visual acuity, circadian rhythm delay, and ecological pattern disruption. It is important to quantify these factors with metrics and visualizations.
Few, if any, lighting graphics tools can directly compare SPDs. Some lighting engineers resort to building their own tools in Excel or MATLAB, but this is not exactly accessible, nor is it a great use of time.
My hope is that Beautiful Photometry will enable wider understanding of the lighting metrics that impact health, which leads to better lighting products and more consideration given to lighting in the built environment.
Another rarely-understood factor of lighting is flicker. This rapid, often invisible flashing can contribute to headaches, eyestrain, and loss in concentration. The suspected reason for this is the inability of the human eye to move the proper saccade distance under non-constant light.
Beautiful Flicker is a set of Python tools for displaying flicker metrics. Currently, it can display flicker waveforms and the IEEE PAR 1789 graphic. It can also compute conformance to various flicker standards, such as California Title 24 and the WELL Building Standard.