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tcfuse-preprocess

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업데이트2026년 6월 9일 12:02

TC-Fuse dataset preprocessing pipeline — Stage 0 IBTrACS prep + ATCF→SID translation table, Stage 1 per-source HDF5 snapshots, Stage 2 assembled per-storm HDF5 + concatenated index, Stage 3A season splits, Stage 3B window index building, normalization statistics, the I/O API in `src/tcfuse/data/sources/`. Use when preparing any dataset (TC-PRIMED, CyclObs, dropsondes, Argo), running `prepare_ibtracs.py` / `assemble.py` / `build_splits.py` / `build_windows.py` / `compute_normalization.py`, working with `Source` or `StormData`, or extending the per-source HDF5 / assembled formats.

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Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

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dauvillc

dauvillc/tcfuse

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Manus에서 실행

관련 직업SOC

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소프트웨어 개발자컴퓨터 및 수학직·SOC 15-1252

SKILL.md

readonly

name

tcfuse-preprocess

description

Content has moved. The full skill documentation is in .agents/preprocess.md. Read that file for pipeline stages, dataset inventory, HDF5 schemas, running instructions, and the I/O API reference.

이 저장소의 다른 Skills

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2026-06-300

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TC-Fuse evaluation pipeline — computing metrics and building figures from saved predictions with `scripts/evaluation/evaluate.py` (Hydra, `conf/evaluation.yaml`). Plugin-based: each `Evaluation` (`src/tcfuse/evaluation/`) is enabled via the `conf/evaluation/` config group and writes into its own subfolder under `paths.results/<run_id>/<experiment_name>/`. The base contract imposes no data shape (flattening is plugin-dependent); the `quantitative_metrics` plugin computes RMSE/MAE/R2/MAPE per source/channel with numpy/scikit-learn, independent of torchmetrics. Use when evaluating a prediction run, adding a new evaluation plugin, or changing the results layout.

2026-06-290

tcfuse-inference

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Drive the CLEPS (Inria Paris) cluster from the local machine — rsync sync, preflight, SLURM submission via submitit, job monitoring, checkpoint resume, and storage quota. Use whenever a task involves `ssh cleps`, $SCRATCH, CLEPS SLURM partitions (cpu_devel / gpu / arches), pixi on the cluster, `submitit`, `setup=cleps_*`, `paths=cleps`, or running jobs on CLEPS. CLEPS uses pixi (no modules) and W&B online (no offline sync), and its scratch is persistent (no archive step).

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Fix basedpyright diagnostics with clean, minimal Python typing changes. Use when the user mentions Pyright, basedpyright, type errors, typing fixes, type checking, or Python typing diagnostics.

2026-06-090

name

tcfuse-preprocess

description

Content has moved. The full skill documentation is in .agents/preprocess.md. Read that file for pipeline stages, dataset inventory, HDF5 schemas, running instructions, and the I/O API reference.