---

name: stumpy description: "Use the STUMPY time-series matrix-profile package for exact, approximate, streaming, multidimensional, motif, segmentation, distributed, and optional GPU workflows." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

STUMPY repo skill

Use this skill when a task asks for STUMPY, matrix profiles, motif/discord discovery, MPdist, snippets, time-series chains, semantic segmentation, streaming matrix profiles, pan matrix profiles, or STUMPY Dask/GPU execution.

STUMPY is a Python package for time-series data mining around the matrix profile. It exposes CPU, distributed, and optional CUDA APIs for exact and approximate matrix profiles plus downstream analysis workflows.

First checks

Install the public package in the target environment when it is absent:

python -m pip install stumpy
# or: conda install -c conda-forge stumpy

For distributed Dask workflows, also install Dask Distributed if the environment did not include it:

python -m pip install dask distributed

Run the bundled environment check before relying on optional backends:

python scripts/stumpy_check_env.py --check all

Route by task

• Exact 1-D matrix profile, distance profile, self-join, AB-join, dtype/window issues: read sub-skills/matrix-profile-basics/SKILL.md.
• Multidimensional input, row-as-dimension layout, mstump, maamp, subspace, mdl, multidimensional motifs: read sub-skills/multidimensional-profiles/SKILL.md.
• Motifs, query matching, discords/anomalies, consensus motifs, MPdist, snippets, chains, FLUSS/FLOSS segmentation, shapelets: read sub-skills/motifs-anomalies-segmentation/SKILL.md.
• Approximate/anytime profiles, streaming updates, online segmentation, pan matrix profile/window-size exploration: read sub-skills/approximate-streaming-pan/SKILL.md.
• Dask, Ray, CUDA, GPU-STUMP, multi-GPU, backend diagnostics, or acceleration fallbacks: read sub-skills/distributed-gpu-acceleration/SKILL.md.

Common decisions

1. Normalize or not: use normalized APIs (stump, mstump, scrump, stumpi, stimp, motifs, match) for shape similarity after z-normalization. Use non-normalized families (aamp, maamp, scraamp, aampi, aamp_stimp, aamp_motifs, aamp_match) when absolute amplitudes and offsets matter.
2. Self-join or AB-join: self-joins search within one time series and should keep ignore_trivial=True. AB-joins compare two series and should use ignore_trivial=False.
3. One-dimensional or multidimensional: one-dimensional APIs accept shape (n,); multidimensional workflows expect rows as dimensions and columns as time, shape (d, n).
4. Exact, approximate, streaming, or accelerated: exact CPU APIs are the clearest baseline. Use approximate/streaming objects for latency or online data. Add Dask/Ray/CUDA only after the owner workflow is selected.
5. Matrix-profile output: distance and index columns may share an object-dtype array. Cast distance columns to float before numeric validation.

Shared references and scripts

• references/package-overview.md summarizes package capabilities, data assumptions, and dependency choices.
• references/troubleshooting.md covers cross-cutting install/import, dependency, Numba, data, and routing failures.
• references/repo-provenance.md records the source snapshot for refresh decisions.
• references/repo-routing-metadata.json contains structured router import metadata.
• scripts/stumpy_check_env.py checks imports, versions, Dask, and optional CUDA visibility.
• scripts/stumpy_quickstart.py runs a short synthetic no-network tour across core STUMPY workflows.

Do not do these

• Do not tell future users to open this source checkout's original docs, tests, notebooks, or scripts. Use the bundled references/scripts in this skill.
• Do not claim CUDA support from import stumpy alone; require numba.cuda.is_available() and a backend smoke in the target runtime.
• Do not flatten multidimensional data silently. Preserve the STUMPY convention that rows are dimensions and columns are time.
• Do not mix normalized and non-normalized API families without explaining the distance-model change.
• Do not import this skill into the live repo-skills library for this run; production was requested as non-imported output.