Skip to main content

DimFlux: Force-Based Doubly-Additive Drawings

Project description

DimFlux: Force-Directed Doubly-Additive Line Diagrams

This repository implements a force-directed placement approach for doubly-additive line drawings.

References

This project is based on the theory and methods described in the following works.

Primary Reference

@article{Noehre2026,
  title = {DimFlux: Force-directed additive line diagrams},
  journal = {International Journal of Approximate Reasoning},
  volume = {197},
  pages = {109734},
  year = {2026},
  issn = {0888-613X},
  doi = {https://doi.org/10.1016/j.ijar.2026.109734},
  url = {https://www.sciencedirect.com/science/article/pii/S0888613X2600109X},
  author = {Marcel Nöhre and Dominik Dürrschnabel and Bernhard Ganter and Gerd Stumme},
  keywords = {Formal concept analysis, Force-directed placement, Additive line diagrams, DimDraw, DimFlux},
  abstract = {The visualization of concept lattices is a central problem in the field of Formal Concept Analysis. Force-directed algorithms, as popular in graph drawing, are a promising approach, treating lattice diagrams as physical models, optimizing node positions based on forces derived from the lattice structure. We build on the work of Zschalig, who, however, limited himself to attribute-additive diagrams. We use a more general additivity, in which both the attributes and the objects contribute to the positions of the concept nodes. We replace the planarity enhancer used by Zschalig to obtain a starting diagram for force-directed optimization with the DimDraw algorithm, which generates structured order diagrams on its own. The combination results in DimFlux, an algorithm that leverages the advantages of DimDraw but generates additive diagrams in which readability is increased by maximizing the conflict distance between nodes and non-incident edges.}
}

Supplementary Material

@misc{Noehre2026Supplementary,
  author = {Nöhre, Marcel and Dürrschnabel, Dominik and Ganter, Bernhard and Stumme, Gerd},
  title = {A Visual Benchmark of DimFlux: Comparison of Line Diagrams for Concept Lattices},
  month = mar,
  year = 2026,
  publisher = {Zenodo},
  doi = {10.5281/zenodo.18936106},
  url = {https://doi.org/10.5281/zenodo.18936106}
}

If you use this code in your work, please cite the above references.

Usage

Install via PyPI

Install the package from PyPI using pip.

pip install dim-flux

Execute the layout generation using the dim-flux command.

dim-flux

Install from source

Clone the repository and initialize the environment. uv will automatically create a virtual environment and sync dependencies based on the pyproject.toml. uv will automatically create a virtual environment.

uv sync

Execute the layout generation using uv run to ensure the correct environment context.

uv run dim-flux

The script will prompt you for a path to a .cxt file. To export the node positions add the --export flag.

uv run dim-flux --export

The --export flag also works with the PyPI install:

dim-flux --export

Use as a library

DimFlux can also be called directly from Python via dim_flux.plot.

from dim_flux import plot

# cxt can be a path to a .cxt file, or a pandas DataFrame representing the incidence matrix
positions = plot('path/to/context.cxt')

By default plot returns the computed (x, y) coordinates in lectic order as a numpy array. Pass export=True to instead write the PDF, GraphML and .pos exports to disk.

plot('path/to/context.cxt', export=True)

Configuration

Category Parameter Description
Drawings plot_si_graph Visualize the Supremum-Infimum graph ($f_{max}$ is highlighted)
plot_initial_layout Visualize the initial layout of the concept lattice
plot_optimized_layout Visualize the final optimized layout of the concept lattice
Annotations si_graph_annotations Display annotations in the SI-Graph
initial_layout_annotations Display annotations in the initial drawing
optimized_layout_annotations Display annotations in the final optimized drawing
Forces plot_individual_forces Display force vectors for objects and attributes respectively
plot_combined_forces Display combined force vectors
plot_gradients Display gradient vectors at concepts
Dev plot_origin Display the origin $(0,0)$

License

Shield: CC BY 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License.

CC BY 4.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dim_flux-1.0.4.tar.gz (26.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dim_flux-1.0.4-py3-none-any.whl (32.2 kB view details)

Uploaded Python 3

File details

Details for the file dim_flux-1.0.4.tar.gz.

File metadata

  • Download URL: dim_flux-1.0.4.tar.gz
  • Upload date:
  • Size: 26.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.15 {"installer":{"name":"uv","version":"0.9.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"25.10","id":"questing","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for dim_flux-1.0.4.tar.gz
Algorithm Hash digest
SHA256 6fa8dd13e29f3c3da4fdc3c13586c512b4d7eeb9c2287b70b4d74acb5975f538
MD5 ba6db7745edb6a9bab522e6e54bd05f0
BLAKE2b-256 46c5c95739c7a33652104f986904bd6039060ebb89fefa9e7360090669a8fcf5

See more details on using hashes here.

File details

Details for the file dim_flux-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: dim_flux-1.0.4-py3-none-any.whl
  • Upload date:
  • Size: 32.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.15 {"installer":{"name":"uv","version":"0.9.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"25.10","id":"questing","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for dim_flux-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 695b5c4f0e96d7e35d8d50aed540acd8619bf7fb946dfd7e5ff1a74fe79b38fc
MD5 ccc60e55d52ac0bdb492f146b74eff8f
BLAKE2b-256 e1591008a516250a0fb053470f515cc87702b7210f94665373ffe5c1a8f3fb7a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page