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name: motifs-anomalies-segmentation description: "Route matrix-profile results into motif discovery, query matching, discords/anomalies, consensus motifs, MPdist, snippets, chains, shapelets, and semantic segmentation." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Motifs, anomalies, and segmentation

Use this sub-skill when the matrix profile already exists, or when you already know the query or comparison series and need analysis rather than profile construction.

Route here for

• motif extraction from a 1-D profile
• query matching against a raw series
• discords / anomalies from profile peaks
• consensus motifs across a list of series
• MPdist and snippets for similarity and summarization
• chains from left / right nearest-neighbor indices
• FLUSS / FLOSS semantic segmentation
• shapelet candidate ranking from class-vs-class profile contrasts

Route away when

• you still need the base 1-D profile computation -> matrix-profile-basics
• you need multidimensional profile construction or subspace choice -> multidimensional-profiles
• you need online, anytime, or pan updates -> approximate-streaming-pan
• you need Dask / GPU / Ray acceleration setup -> distributed-gpu-acceleration

What the APIs consume

• raw series + 1-D profile -> motifs
• raw query + raw series -> match
• list of raw series -> ostinato
• precomputed multidimensional profile / index arrays -> mmotifs handoff only
• raw pair of series -> mpdist
• raw series -> snippets
• left / right index columns -> atsc, allc
• nearest-neighbor index column -> fluss
• full 4-column matrix profile + raw series -> floss

Workflow

1. Start from the smallest stable input you already have.
2. Use references/workflows.md for the exact path.
3. Use scripts/motif_segmentation_smoke.py --help for the bundled no-network smoke path.
4. If the failure is really about profile creation, dimensionality, or acceleration, hand off to the owning sub-skill.

Validation cues

• low profile values are motif candidates
• high profile values are discord / anomaly candidates
• normalize=False must stay consistent across the upstream profile and the downstream analysis call
• atsc, allc, and fluss are index-driven; do not pass profile distances where indices are required

Bundled references

• references/api-reference.md
• references/workflows.md
• references/troubleshooting.md