alkahest

A lightweight, dependency-free toolbox for pre-processing XY data from experimental methods (i.e. any signal that can be measured along a continuous variable). This package provides methods for baseline estimation and correction, smoothing, normalization, integration and peaks detection. Baseline correction methods includes polynomial fitting as described in Lieber and Mahadevan-Jansen (2003) doi:10.1366/000370203322554518, Rolling Ball algorithm after Kneen and Annegarn (1996) doi:10.1016/0168-583X(95)00908-6, SNIP algorithm after Ryan et al. (1988) doi:10.1016/0168-583X(88)90063-8, 4S Peak Filling after Liland (2015) doi:10.1016/j.mex.2015.02.009 and more.

Last 30 days

This package has been downloaded 357 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,773 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Aug 28, 2024 with 61 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.