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Welcome to Horton-Part’s documentation!

HORTON-PART is a computational chemistry package that supports different partition schemes. It is based on the sub-module part of HORTON2, which is written and maintained by Toon Verstraelen (2). In HORTON3, all sub-modules have been rewritten using the pure Python programming language to support Python 3+. See more details on this website. It should be noted that HORTON2 also supports Python 3+ now. The part module has also been rewritten and is now called denspart module. However, the algorithm implemented in denspart only uses one-step optimization, which can be computationally expensive for large systems. Additionally, denspart only supports the MBIS partitioning scheme. Another part module has been rewritten in pure Python programming language by Farnaz Heidar-Zadeh (2). However, the integration grid implemented in this module still uses the old ‘grid’ from Horton2. HORTON-PART with version 0.0.X is based on this module. Starting from version 1.X.X, HORTON-PART only supports the new integration qc-grid. The molecular density can be prepared using IOData (https://github.com/theochem/iodata) and GBasis (https://github.com/theochem/gbasis) packages.

This version contains contributions from YingXing Cheng (1), Toon Verstraelen (2), Pawel Tecmer (3), Farnaz Heidar-Zadeh (3), Cristina E. González-Espinoza (3), Matthew Chan (3), Taewon D. Kim (3), Katharina Boguslawski (3), Stijn Fias (4), Steven Vandenbrande (2), Diego Berrocal (3), and Paul W. Ayers (3)

    1. Numerical Mathematics for High Performance Computing (NMH), University of Stuttgart, Stuttgart, Germany.

    1. Center for Molecular Modeling (CMM), Ghent University, Ghent, Belgium.

    1. The Ayers Group, McMaster University, Hamilton, Ontario, Canada.

    1. General Chemistry (ALGC), Free University of Brussels, Brussels, Belgium.

The Horton-Part source code is hosted on GitHub and is released under the GNU General Public License v3.0. Please report any issues you encounter while using Horton-Part library on GitHub Issues. For further information and inquiries please contact us at yxcheng2buaa@gmail.com.

Functionality

  • Real space partitioning schemes

    • Mulliken partitioning method

  • Density related partitioning schemes

    • Becke partitioning method

    • Stockholder schemes

      • Hirshfeld partitioning method

    • Iterative Stockholder schemes

      • Iterative Hirshfeld (Hirshfeld-I) partitioning method

      • Iterative Stockholder Approach (ISA)

      • Minimal Basis Iterative Stockholder (MBIS)

      • Gaussian iterative stockholder approach (GISA)

      • Alternating Linear approximation of the ISA (aLISA) method

      • Global Linear approximation of the ISA (gLISA) method

      • Generalized Minimal Basis Iterative Stockholder (GMBIS)

      • Non-linear approximation of the ISA (NLIS) method

Citations

Please use the following citations in any publication using horton-part library:

[1] Cheng, Y.; Stamm, B. Approximations of the Iterative Stockholder Analysis scheme using exponential basis functions. arXiv 2024, 2412.05079

[2] Cheng, Y.; Cancès, E.; Ehrlacher, V.; Misquitta, A. J.; Stamm, B. Multi-center decomposition of molecular densities: A numerical perspective. J. Chem. Phys. 2025, 162, 074101. https://doi.org/10.1063/5.0245287

[3] Benda, R.; Cancès, E.; Ehrlacher, V.; Stamm, B. Multi-center decomposition of molecular densities: A mathematical perspective. J. Chem. Phys. 2022, 156, 164107. https://doi.org/10.1063/5.0076630

[4] Chan, M.; Verstraelen, T.; Tehrani, A.; Richer, M.; Yang, X. D.; Kim, T. D.; Vöhringer-Martinez, E.; Heidar-Zadeh, F.; Ayers, P. W. The tale of HORTON: Lessons learned in a decade of scientific software development. J. Chem. Phys. 2024, 160, 162501. https://doi.org/10.1063/5.0196638

[5] Tehrani, A.; Yang, X. D.; Martínez-González, M.; Pujal, L.; Hernández-Esparza, R.; Chan, M.; Vöhringer-Martinez, E.; Verstraelen, T.; Ayers, P. W.; Heidar-Zadeh, F. Grid: A Python library for molecular integration, interpolation, differentiation, and more. J. Chem. Phys. 2024, 160, 172503. https://doi.org/10.1063/5.0202240

[6] Kim, T. D.; Pujal, L.; Richer, M.; van Zyl, M.; Martínez-González, M.; Tehrani, A.; Chuiko, V.; Sánchez-Díaz, G.; Sanchez, W.; Adams, W.; Huang, X.; Kelly, B. D.; Vöhringer-Martinez, E.; Verstraelen, T.; Heidar-Zadeh, F.; Ayers, P. W. GBasis: A Python library for evaluating functions, functionals, and integrals expressed with Gaussian basis functions. J. Chem. Phys. 2024, 161, 042503. https://doi.org/10.1063/5.0216776

[7] Verstraelen, T.; Adams, W.; Pujal, L.; Tehrani, A.; Kelly, B. D.; Macaya, L.; Meng, F.; Richer, M.; Hernández-Esparza, R.; Yang, X. D.; Chan, M.; Kim, T. D.; Cools-Ceuppens, M.; Chuiko, V.; Vöhringer-Martinez, E.; Ayers, P. W.; Heidar-Zadeh, F. IOData: A python library for reading, writing, and converting computational chemistry file formats and generating input files. J. Comput. Chem. 2021, 42, 458–464. https://doi.org/10.1002/jcc.26468

Modules

Modules

Description

Becke

Becke partitioning method

Hirshfeld

Hirshfeld partitioning method

Hirshfeld-I

Iterative Hirshfeld partitioning method

ISA

Iterative Stockholder analysis (ISA) method

MBIS

Minimal Basis Iterative Stockholder (MBIS) method

GISA

Gaussian iterative stockholder approach (GISA)

aLISA

Alternating Linear approximation of the ISA method (aLISA)

gLISA

Global linear approximation of the ISA method (gLISA)

GMBIS

Generalized Minimal Basis Iterative Stockholder (MBIS) method

NLIS

Non-linear approximation of the ISA method (NLIS) method

User Documentation

Quick Start

Example Tutorials

API Documentation

Indices and tables