{"ID":2859660,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.04438","arxiv_id":"2510.04438","title":"spd-metrics-id: A Python Package for SPD-Aware Distance Metrics in Connectome Fingerprinting and Beyond","abstract":"We present spd-metrics-id, a Python package for computing distances and divergences between symmetric positive-definite (SPD) matrices. Unlike traditional toolkits that focus on specific applications, spd-metrics-id provides a unified, extensible, and reproducible framework for SPD distance computation. The package supports a wide variety of geometry-aware metrics, including Alpha-z Bures-Wasserstein, Alpha-Procrustes, affine-invariant Riemannian, log-Euclidean, and others, and is accessible both via a command-line interface and a Python API. Reproducibility is ensured through Docker images and Zenodo archiving. We illustrate usage through a connectome fingerprinting example, but the package is broadly applicable to covariance analysis, diffusion tensor imaging, and other domains requiring SPD matrix comparison. The package is openly available at https://pypi.org/project/spd-metrics-id/.","short_abstract":"We present spd-metrics-id, a Python package for computing distances and divergences between symmetric positive-definite (SPD) matrices. Unlike traditional toolkits that focus on specific applications, spd-metrics-id provides a unified, extensible, and reproducible framework for SPD distance computation. The package sup...","url_abs":"https://arxiv.org/abs/2510.04438","url_pdf":"https://arxiv.org/pdf/2510.04438v1","authors":"[\"Kaosar Uddin\"]","published":"2025-10-06T02:12:55Z","proceeding":"stat.CO","tasks":"[\"stat.CO\",\"cs.LG\",\"stat.ML\"]","methods":"[\"Diffusion Model\"]","project_urls":"[\"https://pypi.org/project/spd-metrics-id/\"]","has_code":false,"code_links":[{"ID":608652,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2859660,"paper_url":"https://arxiv.org/abs/2510.04438","paper_title":"spd-metrics-id: A Python Package for SPD-Aware Distance Metrics in Connectome Fingerprinting and Beyond","repo_url":"https://github.com/yourusername/spd-metrics-id.git","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0},{"ID":608653,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2859660,"paper_url":"https://arxiv.org/abs/2510.04438","paper_title":"spd-metrics-id: A Python Package for SPD-Aware Distance Metrics in Connectome Fingerprinting and Beyond","repo_url":"https://github.com/pypi/warehouse","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}