--- id: tesseract version: "0.1.3" license: UNKNOWN license_treatment: copyleft maintenance: abandoned --- # tesseract — Tesselation based Recovery of Amorphous halo Concentrations License: copyleft · Maintenance: abandoned · Downloads: 82.2K/mo ## What it is and what it does TesseRACt is a specialized astrophysics package for computing concentration parameters of dark matter halos from N-body simulation particle data. It implements a Voronoi tessellation-based method that is non-parametric and does not assume spherical symmetry, allowing it to handle substructure in halos. The package includes a C program (vorovol) that computes Voronoi diagrams from particle data in multiple formats (Gadget-2, Gasoline, binary, ASCII) and halo catalogues, plus Python routines to compile, run, and parse its output. The package also provides routines for computing concentrations using particle volumes, traditional NFW profile fitting, and non-parametric techniques assuming spherical symmetry. It was published alongside a peer-reviewed paper (Lang et al. 2015) and includes test halos and performance benchmarks from that work. However, the package has been abandoned since 2015-07-13 with no subsequent maintenance or updates. Use it for: - Analyze dark matter halo concentration in cosmological N-body simulations using Voronoi tessellation methods. - Compare concentration estimates from non-parametric techniques against traditional NFW profile fitting. - Process particle data from Gadget-2, Gasoline, or other simulation formats to compute halo properties. - Reproduce or verify results from Lang et al. (2015) using the included test halos and benchmarks. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Computes dark matter halo concentration parameters from simulated particle data using Voronoi tessellation, a non-parametric technique that does not assume spherical symmetry. No. The package is abandoned (last release 2015-07-13), has high install friction due to a C compilation requirement, and is unmaintained. While it implements a valid scientific technique, the lack of support for modern environments makes it unsuitable for new projects. Use only if reproducing historical results and you can manage C build issues independently. ## Install pip install tesseract uv add tesseract poetry add tesseract ## Installing tesseract Before you install: High install friction: the package is abandoned (last release 2015-07-13) and includes a compiled C component (vorovol) that must be built during installation. No active maintenance or support. License in practice: Licensed under GPL (copyleft); any derivative work or distribution must also be open-source under compatible terms. The license_raw field is marked UNKNOWN, so verify the exact GPL version before integrating into proprietary code. Quickstart: pip install tesseract==0.1.3 import tesseract # Requires vorovol C program compilation and particle data in supported format Requires a C compiler and build tools to compile the bundled vorovol program; no Python version constraint specified. Verify before relying: - Exact GPL version (GPL v2, v3, or later) not specified in metadata; verify in source before use in proprietary projects. - Whether the bundled vorovol C program has external build dependencies (e.g., Qhull) not listed in the fact sheet. - Current compatibility with modern Python versions and compilers, given the 2015 release date and abandoned status. ## Package facts - License: UNKNOWN (copyleft) - Python support: unspecified - Install friction: high - Maintenance: abandoned - Downloads: 82.2K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags dark matter halo concentration, voronoi tessellation particles, concentration parameter computation, simulated halo analysis, non-parametric concentration estimation, voronoi volume analysis, particle halo properties, cosmology, n-body-simulation, abandoned [View on SkillFed](https://skillfed.io/packages/tesseract) · [View on PyPI](https://pypi.org/project/tesseract/)