dsfb-robotics 0.1.0

DSFB Structural Semiotics Engine for Robotics Health Monitoring — a deterministic, non-intrusive observer layer that reads the residuals existing robot control, kinematic identification, and whole-body balance observers already compute, and structures them into a human-readable grammar of typed episodes. Read-only augmentation, not replacement, of incumbent PHM / FDD / MPC / observer pipelines.
Documentation 
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//! mobile_aloha adapter — see crate's docs for provenance.
//!
//! Real data flows through `scripts/preprocess_datasets.py` to
//! `data/processed/mobile_aloha.csv`; the canonical entry point is
//! `paper-lock mobile_aloha` which loads that CSV via
//! `crate::paper_lock::run_real_data`.

/// Placeholder fixture — real-data path is authoritative for this dataset.
pub const FIXTURE_PLACEHOLDER: [f64; 5] = [0.01, 0.05, 0.10, 0.06, 0.02];

/// Fixture entry point retained for CLI / smoke-test symmetry across all datasets.
pub fn fixture_residuals(out: &mut [f64]) -> usize {
    debug_assert!(!out.is_empty(), "fixture buffer must be non-empty");
    let n = out.len().min(FIXTURE_PLACEHOLDER.len());
    debug_assert!(n <= out.len() && n <= FIXTURE_PLACEHOLDER.len(), "n must respect both source and dest bounds");
    out[..n].copy_from_slice(&FIXTURE_PLACEHOLDER[..n]);
    debug_assert!(n > 0, "fixture must emit at least one sample");
    n
}