This repo's codes provide a simple data smoother based penalized least squares, known as Whittaker smoother as well. This smoother is extremely fast, gives continuous control over smoothness, interpolates automatically.
Python 3Scipy,Numpy
Class SIGSMOOTH in signal_smooth.py provides two methods for differenet situation.
PLS_expect: a general situation as interval of x-coordinate is equalPLS_interpolation: used as if interval of x-coordinate is not equal
A website data smoother based on PLS_expect with the equal weight of each data point.
After loading a .csv file and click smooth, the preliminary result is displayed via bokeh.
online tool: vercel
Following the steps in test.py to find a most probable distribution line for data in test.txt, you might have a glance at our method.
This repository is licensed under the GNU GPLv3.