English

Implementation of the Bin Hierarchy Method for restoring a smooth function from a sampled histogram

Other Statistics 2019-10-23 v1 Other Condensed Matter Data Analysis, Statistics and Probability

Abstract

We present BHM\texttt{BHM}, a tool for restoring a smooth function from a sampled histogram using the bin hierarchy method. The theoretical background of the method is presented in [arXiv:1707.07625]. The code automatically generates a smooth polynomial spline with the minimal acceptable number of knots from the input data. It works universally for any sufficiently regular shaped distribution and any level of data quality, requiring almost no external parameter specification. It is particularly useful for large-scale numerical data analysis. This paper explains the details of the implementation and the use of the program.

Cite

@article{arxiv.1711.04316,
  title  = {Implementation of the Bin Hierarchy Method for restoring a smooth function from a sampled histogram},
  author = {Olga Goulko and Alexander Gaenko and Emanuel Gull and Nikolay Prokof'ev and Boris Svistunov},
  journal= {arXiv preprint arXiv:1711.04316},
  year   = {2019}
}

Comments

Code is available at https://github.com/olgagoulko/BHM/tree/GPLv3

R2 v1 2026-06-22T22:43:28.232Z