Code, raw episode data and figures for "An Axiomatic Resilience Functional for Fault-Tolerant Control of Redundant Manipulators"

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Code, raw episode data and figures for C. Urrea, "An Axiomatic Resilience Functional for Fault-Tolerant Control of Redundant Manipulators: Representation, Rank Invariance, and Sample Complexity", Mathematics (MDPI), 2026.Six axioms on the aggregation of performance criteria reduce the admissible resilience scores to the weighted geometric mean alone, excluding the weighted arithmetic mean the field currently uses. The exact distance from the nominal weights to the set of weights that reverse a pairwise comparison admits a closed form, and distribution-free bounds give the episode budgets: 738 for an absolute score accurate to 0.05 at 95% confidence, 343 for a paired comparison.This record archives release v1.0.0 of the code and the raw episode-level criteria of all 32,000 evaluation episodes, over five plants, eight fault classes and eight control laws, together with the calibrated detection thresholds, the reference constants, the published figures and the generated LaTeX tables.Contents: rsp-resilience-v1.0.0-code.zip, rsp-resilience-v1.0.0-data.zip, rsp-resilience-v1.0.0-figures.zip, CHECKSUMS.sha256, ENVIRONMENT.txt, README_FIGSHARE.md.Reproducing takes about 26 minutes on a single core from the seed 20260811. Python 3.10 or later, NumPy, SciPy, Matplotlib. No GPU and no hardware. Development repository: https://github.com/ClaudioUrrea/rsp-resilienceThe study is entirely computational; no human subjects, personal data or animal experimentation are involved.