算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
data-and-download【设计与创意】Safely inspect PDEBench dataset metadata and local HDF5 data, visualize downloaded files, and convert 3D CFD velocity fields to vorticity with verified CPU NumPy/JAX paths.
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Use this sub-skill for metadata-first, local-data workflows: identify a PDEBench shard, inspect its expected HDF5 names and shapes, visualize a file that is already local, or convert a local 3D CFD velocity field to vorticity. Do not begin a multi-gigabyte download, upload, simulation, training run, or benchmark evaluation without an explicit user request and a storage/network/credential check.
--help; these have no network side effect.--overwrite only when replacement is intentional. Its default backend is
NumPy/CPU; JAX is an opt-in acceleration path.pdebench.data_download.download_direct,
pdebench.data_download.visualize_pdes, and
pdebench.data_gen.velocity2vorticity establish native names, dispatch, and
schemas. Their source artifacts are not copied into this runtime tree. The
native downloader must never be treated as a harmless default action.data-generation. Model
training, evaluation, and metrics route to models-and-evaluation.Recorded inspection evidence verified Python 3.10, pdebench 0.1.0, NumPy
1.26.4, JAX 0.4.38 on CPU, and PyTorch 1.13.1 on CPU. NumPy and JAX spectral
vorticity APIs and the CPU path were verified in that recorded environment. The
current review shell used Python 3.13 and did not have JAX installed, so those
facts are not current-shell verification. CUDA may be useful for acceleration,
but is optional and unverified; do not claim GPU verification.