v1.1.0

[thiebes]

News

• This software was developed alongside a paper¹ which has now been published in The Journal of Chemical Physics here: https://doi.org/10.1063/5.0190347
• Calculate the CNR of your noisy Gaussian profile with this online calculator. No Python installation is necessary.

Updates in version 1.1.0

The following changes have been included in this version of DICE:

• A requirements.txt file has been added to facilitate installation.
• Contrast-to-noise ratio (CNR) estimates are now rounded to two decimal places, as there is no reason to believe the CNR estimates will be more accurate than that.
• A web app for calculating contrast-to-noise estimates for 1D noisy Gaussian profiles has been added to the repository. The web app is being served here.
• A new gradient colormap, dice_gradient, has been added to colordefs().
  • dice_gradient is a colorblind-accessible, gradient color map that transitions from light lavender to dark forest green, optimized for clarity in both color and grayscale printing. This gradient is generated with cubehelix^2,3.
  • 
• A new section on interpreting the results of simulations has been added to the README.md file.
• Citation of the paper has been added in the documentation.
• The README.md file has been reorganized and updated.

References

[1] Joseph J. Thiebes, Erik M. Grumstrup; Quantifying noise effects in optical measures of excited state transport. J. Chem. Phys. 28 March 2024; 160 (12): 124201. doi:10.1063/5.0190347
[2] Green, D. A.; A colour scheme for the display of astronomical intensity images. Bulletin of the Astronomical Society of India 2011; 39: 289–295. doi:10.48550/arXiv.1108.5083.
[3] Davenport, J. R. Cubehelix, or How I Learned to Love Black & White Printers. If We Assume. Retrieved March 15, 2024, from https://ifweassume.blogspot.com/2013/05/cubehelix-or-how-i-learned-to-love.html

---

This discussion was created from the release v1.1.0.