acid

The AutoCorrelation Integral Drill (ACID) Test Set

https://github.com/molmod/acid

Science Score: 67.0%

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    Found 4 DOI reference(s) in README
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    Links to: arxiv.org
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    Low similarity (15.1%) to scientific vocabulary

Keywords

acf autocorrelation-function autocorrelation-integral dataset exponential-correlation-time integrated-correlation-time power-spectral-distribution psd python stacie stepup systematic-validation typst worfklow
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Repository

The AutoCorrelation Integral Drill (ACID) Test Set

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  • Host: GitHub
  • Owner: molmod
  • Language: Python
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acf autocorrelation-function autocorrelation-integral dataset exponential-correlation-time integrated-correlation-time power-spectral-distribution psd python stacie stepup systematic-validation typst worfklow
Created 8 months ago · Last pushed 8 months ago
Metadata Files
Readme Changelog Citation

README.md

The AutoCorrelation Integral Drill (ACID) Test Set

This repository contains the scripts and StepUp workflows to regenerate the "AutoCorrelation Integral Drill" (ACID) test set. The ACID test set comprises a diverse collection of algorithmically generated time series designed to evaluate the performance of algorithms that compute the autocorrelation integral. The set contains in total 15360 test cases, and each case consists of one or more time series. The cases differ in the kernel characterizing the time correlations, the number of time series, and the length of the time series. For each combination of kernel, number of sequences and sequence length, 64 test cases are generated with different random seeds to allow for a systematic validation of uncertainty estimates. The total dataset, once generated, is about 80 GB in size.

In addition to the ACID test set, this repository also contains scripts and workflows to validate STACIE, a software package for the computation of the autocorrelation integral.

A description of the dataset, a summary of the validation results, and an archived version of this repository can be found on Zenodo: 10.5281/zenodo.15722903.

License

All files in this dataset are licensed under a Creative Commons Attribution Non Commercial Share Alike 4.0 International.

Citation

If you use this dataset in your research, please cite the following priprint:

Gözdenur, T.; Fauconnier, D.; Verstraelen, T. "STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations" arXiv 2025, arXiv:2506.20438

bibtex @article{Toraman2025, title = {STable AutoCorrelation Integral Estimator (STACIE): Robust and accurate transport properties from molecular dynamics simulations}, url = {https://arxiv.org/abs/2506.20438}, doi = {10.48550/arXiv.2506.20438} publisher = {arXiv}, author = {G\"{o}zdenur Toraman and Dieter Fauconnier and Toon Verstraelen}, year = {2025}, month = jun }

Overview

This repository contains three smaller projects:

  1. acid-dataset/: A workflow to generate the ACID test set.
  2. validation-staciei-calc/: A workflow to recompute the validation of STACIE with the ACID test set.
  3. validation-stacie-report/: A workflow with post-processing scripts of the validation results to regenerate the figures and tables used in the STACIE paper.

The README.md files in these directories provide more details about each project.

Setup of the Python Virtual Environment

The script setup-venv-pip.sh in the root directory of this repository sets up a Python virtual environment with the required dependencies. In order to run this script, you need to have Python 3.11 or later installed on your system. The script is primarily tested on Linux, but may also work on other operating systems.

It is recommended to install and setup direnv to automatically activate the virtual environment when you enter the repository directory.

Owner

  • Name: Center for Molecular Modeling (CMM), Ghent University
  • Login: molmod
  • Kind: organization
  • Location: Belgium

Technologiepark 46, 9052 Zwijnaarde, Belgium

Citation (CITATION.cff)

cff-version: 1.2.0
message: If you use this software, please cite it using these metadata.
title: The AutoCorrelation Integral Drill (ACID) Test Set
abstract: >-
  This repository contains the scripts and StepUp workflows to regenerate
  the "AutoCorrelation Integral Drill" (ACID) test set.
  The ACID test set comprises a diverse collection of algorithmically generated time series
  designed to evaluate the performance of algorithms that compute the autocorrelation integral.
  The set contains in total 15360 test cases, and each case consists of one or more time series.
  The cases differ in the kernel characterizing the time correlations, the number of time series,
  and the length of the time series.
  For each combination of kernel, number of sequences and sequence length,
  64 test cases are generated with different random seeds
  to allow for a systematic validation of uncertainty estimates.
  The total dataset, once generated, is about 80 GB in size.
authors:
  - family-names: Toraman
    given-names: Gözdenur
    orcid: https://orcid.org/0000-0001-6785-333X
    affiliation: >-
      Labo Soete,
      Ghent University,
      Technologiepark-Zwijnaarde 46,
      B-9052,
      Ghent,
      Belgium
  - family-names: Fauconnier
    given-names: Dieter
    orcid: https://orcid.org/0000-0002-0257-4687
    affiliation: >-
      Labo Soete,
      Ghent University,
      Technologiepark-Zwijnaarde 46,
      B-9052,
      Ghent,
      Belgium
  - family-names: Verstraelen
    given-names: Toon
    orcid: https://orcid.org/0000-0001-9288-5608
    affiliation: >-
      Center for Molecular Modeling (CMM),
      Ghent University,
      Technologiepark-Zwijnaarde 46,
      B-9052,
      Zwijnaarde, Belgium
identifiers:
  - type: doi
    value: 10.5281/zenodo.15722903
    description: The concept DOI of the work.
preferred-citation:
  authors:
    - family-names: Toraman
      given-names: Gözdenur
    - family-names: Fauconnier
      given-names: Dieter
    - family-names: Verstraelen
      given-names: Toon
  title: >-
    STable AutoCorrelation Integral Estimator (STACIE):
    Robust and accurate transport properties from molecular dynamics simulations
  doi: 10.48550/arXiv.2506.20438
  type: article
  identifiers:
    - description: arXiv preprint describing STACIE
      type: doi
      value: 10.48550/arXiv.2506.20438
license: LGPL-3.0-or-later
repository-code: https://github.com/molmod/acid

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Dependencies

requirements.in pypi
  • emcee ==3.1.6
  • matplotlib ==3.10.1
  • numpy ==2.2.3
  • path ==17.0.0
  • pre-commit ==4.1.0
  • pytest ==8.3.5
  • scipy ==1.15.2
  • stepup ==3.0.3
  • stepup-queue ==1.0.5
  • stepup-reprep ==3.1.0
  • zarr ==3.0.8
requirements.txt pypi
  • 116 dependencies