Making your scientific plots more accessible and visually useful is a great general goal when publishing results, both online and in print. Matplotlib offers a few perceptually uniform colormaps that accurately represent data even in grayscale (useful for print copies or people with color vision deficiency) without introducing visual artifacts that emphasize non-existent features (since the human eye perceives some colors with more intensity than others). CMasher offers many more of these colormaps, but, in both cases, the maps are pre-generated. sandman is different because it allows you to generate perceptually uniform colormaps from a palette you like and use them wherever you would use a Matplotlib/CMasher colormap.
A C++20 template header library for computing arbitrary derivatives of unknown functions, intended to facilitate the solving of partial differential equations.
Mathematica function definitions for predicting the variances and covariances of the binned light curve model parameters of Price & Rogers (2014).
Python functions for predicting the variances and covariances of the binned light curve model parameters of Price & Rogers (2014); depends on the NumPy scientific computing package.
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