Benchmark Builder / 基准构建器

Choose a benchmark slice, generate the dataset code, and attach a quality report covering every selected PDE family. 选择配置后自动生成数据与质量检查代码。

7 PDE losses Local + Linux SeaWulf Slurm Deep-linkable choices
Scientific status / 科学状态: bundled compact solvers are for development and CI. They can produce complete quality reports, but their outputs are not paper-ready ground truth until numerical validation and the publication-candidate quality gate pass. Even then, publication_ready remains false until the canonical full-factor expected plan/checksums and independent release evidence pass. 内置紧凑求解器可以生成完整质量报告,但通过数值验证、完整因子计划、校验和及独立发布证据前,不应作为论文级真值数据。

Choose a factor slice or the complete 7 x 4 x 10 benchmark. The page creates a reproducible YAML configuration and copy-ready commands; it never sends your selections or paths to a server. 选择需要的 PDE、边界、数据规模和运行环境后,页面会自动生成配置与命令;所有选择均只在浏览器本地处理。

1. Choose the benchmark / 选择基准

Advanced paths and resources

2. Training per observation type / 按观测类型分别训练

Primary matched-mask comparison: every normal learned baseline gets an independent checkpoint for each PDE and each of the nine observation masks. The model trained on random 3% is reused only for the separate mask-transfer/OOD table; it never replaces matched-mask training in the primary IID table.

主要 matched-mask 对比:每个普通学习基线都按 PDE 与观测掩码分别训练。random 3% 检查点只用于单独的 mask-transfer/OOD 表,不能替代主要 IID 表中的同掩码训练。

Open the complete observation-training protocol / 查看完整观测训练协议

Execution boundary: this planner counts the complete paper matrix, including methods that are not integrated in PDE-OBS. Its campaign manifest is planning-only. It never invents commands for Gappy POD, DeepONet, PINN/PINO, Transolver/GNOT, DiffusionPDE, or FunDPS.

Campaign preset / 计划预设

Planning status
    Method rowFit policySeedsObservationsPreparationEvaluationsBuilder status

    3. Copy the generated code / 复制生成代码

    The dataset YAML is the executable source of truth. The campaign tab is a non-executable planning record and lists every missing adapter explicitly.

    Loading benchmark contract...

    4. Quality management for every PDE / 全 PDE 数据质量管理

    Every generated sample receives finite-value, geometry, initial/boundary, and family-specific physics diagnostics. Dataset aggregation reports each selected PDE separately; the complete benchmark reports all seven losses together. 每个样本都保存数值、几何、初边值和对应 PDE 物理残差;完整基准会在同一份报告中分别汇总七类 PDE loss。

    PDEReported normalized lossInterpretation

    Always produced

      Gate levels

      1. Report: report scientific losses without applying an unfrozen PDE threshold; malformed array/geometry contracts are still quarantined.
      2. Strict: reject structural/BC/IC failures, log them to *.quality-failures.jsonl, and apply a PDE limit only when calibrated.
      3. Publication candidate: expert-only and intentionally blocked by this Builder until validated solver evidence and a per-stratum threshold table exist. It does not by itself set publication_ready.
      Important interpretation: saved-frame residuals are not the same as integrator replay error. Helmholtz nominal residual and legacy regularized transfer defect stay separate. Bounded Navier-Stokes uses a versioned vorticity/streamfunction residual plus divergence and boundary diagnostics.