onescience_manifest_version: "0.1"
resource_type: dataset

resource:
  id: OneScience/cylinder_flow
  name: cylinder_flow
  domain: cfd
  domain_tags:
    - cfd
    - vortex_shedding
    - cylinder_flow
    - unstructured_mesh
  task: transient_cylinder_flow_dataset
  task_tags:
    - train_data
    - eval_data
    - inference_input
    - dataset_validation
  modalities:
    - unstructured_mesh
    - graph
    - transient_flow_field
  input_formats:
    - tfrecord
    - json
  output_formats:
    - tfrecord
    - json
  summary: DeepMind CylinderFlow 圆柱绕流数据集，包含 train/valid/test TFRecord、meta.json 和 MeshGraphNet 归一化统计量。

platform_resource:
  primary:
    platform: modelscope
    repo_id: OneScience/cylinder_flow
    repo_type: dataset
    url: https://modelscope.cn/datasets/OneScience/cylinder_flow
    revision: main
    readme_path: README.md
    manifest_path: onescience_run_manifest.yaml
  mirrors: []
  access:
    visibility: public
    license: unknown

website_integration:
  enabled: true
  click_target:
    platform: modelscope
    resource_url: https://modelscope.cn/datasets/OneScience/cylinder_flow
  llm_handoff:
    readme_required: true
    manifest_required: true
    download_readme_first: true
    resolve_related_models: true
    default_run_goal: dataset_validation
    cwd_note: 如果使用 modelscope download --cache_dir 下载数据集，请先 cd 到实际下载后的数据集仓库根目录；模型侧默认读取 data/cylinder_flow。

runtime:
  enabled: true
  onescience_domain: cfd
  min_onescience_version: null
  supported_execution:
    - local_dataset_validation
    - model_training_input
    - model_inference_input
  environment:
    exported_env:
      ONESCIENCE_CYLINDER_FLOW_DATA_DIR: <dataset_repo_root>/data/cylinder_flow
  dependencies:
    python: ">=3.10"
    python_packages:
      - tensorflow
      - numpy
      - pyyaml

onescience:
  repo: https://gitee.com/onescience-ai/onescience
  official_links:
    gitee:
      doc: https://gitee.com/onescience-ai/onescience-doc
      onescience: https://gitee.com/onescience-ai/onescience
      skills: https://gitee.com/onescience-ai/oneskills
    github:
      doc: https://github.com/onescience-ai/OneScience-doc
      onescience: https://github.com/onescience-ai/OneScience
      skills: https://github.com/onescience-ai/oneskills
  install:
    required_by_default: false
    command: bash install.sh cfd
  source_paths:
    - onescience/src/onescience/datapipes/cfd/deepmind_cylinderflow.py
  compatibility:
    examples_path: onescience/examples/cfd/Vortex_shedding_mgn
    status: examples_compatible
  datapipe: onescience.datapipes.cfd.DeepMind_CylinderFlowDatapipe

runtime_package:
  kind: standard_runtime_package
  package_root: .
  standard_layout:
    workdir: .
    data_dir: data/cylinder_flow
    metadata_dir: metadata
    output_dir: validation_outputs
  apply_policy:
    mode: direct_use
    target: session_workdir
    overwrite: false
    protect_installed_onescience: true
  entry_files:
    - data/cylinder_flow/meta.json
    - data/cylinder_flow/train.tfrecord
    - data/cylinder_flow/valid.tfrecord
    - data/cylinder_flow/test.tfrecord
    - data/cylinder_flow/stats/edge_stats.json
    - data/cylinder_flow/stats/node_stats.json
    - metadata/cylinder_flow_schema.json
    - scripts/validate_cylinder_flow_dataset.py
    - files_sha256.jsonl
  entrypoints:
    preflight: scripts/validate_cylinder_flow_dataset.py
    validate: scripts/validate_cylinder_flow_dataset.py
    inference: null
    train: null
    finetune: null
    evaluate: null
    visualize: null
    deploy: null

files:
  model_files: []
  dataset_files:
    - path: data/cylinder_flow/train.tfrecord
      role: train_split
      description_zh: CylinderFlow 训练轨迹 TFRecord，供 MeshGraphNet 训练使用。
      required: true
      required_for: [dataset_validation, train]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/train.tfrecord
    - path: data/cylinder_flow/valid.tfrecord
      role: validation_split
      description_zh: CylinderFlow 验证轨迹 TFRecord，供训练过程验证使用。
      required: true
      required_for: [dataset_validation, train, evaluate]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/valid.tfrecord
    - path: data/cylinder_flow/test.tfrecord
      role: test_split
      description_zh: CylinderFlow 测试轨迹 TFRecord，供推理、评测和可视化使用。
      required: true
      required_for: [dataset_validation, inference, evaluate, visualize]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/test.tfrecord
    - path: data/cylinder_flow/meta.json
      role: tfrecord_schema_metadata
      description_zh: TFRecord 字段、shape、dtype、轨迹长度和仿真步长元数据。
      required: true
      required_for: [dataset_validation, train, inference, evaluate]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/meta.json
    - path: data/cylinder_flow/stats/edge_stats.json
      role: edge_normalization_stats
      description_zh: MeshGraphNet 边特征归一化均值和标准差。
      required: true
      required_for: [dataset_validation, train, inference, evaluate]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/stats/edge_stats.json
    - path: data/cylinder_flow/stats/node_stats.json
      role: node_normalization_stats
      description_zh: MeshGraphNet 节点速度、速度差和压力归一化均值与标准差。
      required: true
      required_for: [dataset_validation, train, inference, evaluate]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data/cylinder_flow/stats/node_stats.json
    - path: files_sha256.jsonl
      role: file_size_sha256_inventory
      description_zh: 整理后数据文件的大小和 SHA256 清单，用于完整性校验。
      required: true
      required_for: [dataset_validation]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: files_sha256.jsonl
    - path: data_integrity_summary.json
      role: source_to_standardized_integrity_summary
      description_zh: 原始数据与整理后数据的文件名、大小、SHA256 对照摘要。
      required: true
      required_for: [dataset_validation]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: data_integrity_summary.json
  config_files:
    - path: metadata/cylinder_flow_schema.json
      role: dataset_schema
      description_zh: 描述 CylinderFlow TFRecord 字段、shape、dtype、split、metadata 和 stats。
      required: true
      required_for: [dataset_validation, train, inference]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: metadata/cylinder_flow_schema.json
  sample_files:
    - path: scripts/validate_cylinder_flow_dataset.py
      role: dataset_validation_entry
      description_zh: 数据集读取验证脚本，检查文件结构、shape、dtype、stats、可读性和 SHA256。
      required: true
      required_for: [dataset_validation]
      source:
        platform: modelscope
        repo_id: OneScience/cylinder_flow
        repo_type: dataset
        download_method: command_ref
        command_ref: commands.download.download_dataset
      local_path: scripts/validate_cylinder_flow_dataset.py

relations:
  required_datasets: []
  optional_datasets: []
  compatible_models:
    - id: OneScience/Vortex_shedding_mgn
      role: train_eval_inference_model
      required_for: [train, inference, evaluate, visualize]
      resource_ref:
        platform: modelscope
        repo_id: OneScience/Vortex_shedding_mgn
        repo_type: model
        url: https://modelscope.cn/models/OneScience/Vortex_shedding_mgn
        revision: main
        readme_path: README.md
        manifest_path: onescience_run_manifest.yaml
      expected_local_path: data/cylinder_flow
      expected_env: ONESCIENCE_CYLINDER_FLOW_DATA_DIR

run_matrix:
  scenarios:
    - name: validate_structure
      capability: dataset_validation
      default: true
      required_datasets:
        - id: OneScience/cylinder_flow
          role: train_eval_inference_data
          local_path: data/cylinder_flow
      required_model_files: []
      required_dataset_files:
        - data/cylinder_flow/meta.json
        - data/cylinder_flow/train.tfrecord
        - data/cylinder_flow/valid.tfrecord
        - data/cylinder_flow/test.tfrecord
        - metadata/cylinder_flow_schema.json
      preconditions:
        - 当前工作目录为数据集仓库根目录。
      command_refs:
        - commands.preflight.validate_dataset
      outputs:
        - 控制台输出 [OK] CylinderFlow dataset validation passed
    - name: validate_integrity_full_hash
      capability: dataset_validation
      default: false
      required_datasets:
        - id: OneScience/cylinder_flow
          role: train_eval_inference_data
          local_path: data/cylinder_flow
      required_model_files: []
      required_dataset_files:
        - files_sha256.jsonl
        - data/cylinder_flow/train.tfrecord
        - data/cylinder_flow/valid.tfrecord
        - data/cylinder_flow/test.tfrecord
      preconditions:
        - 当前工作目录为数据集仓库根目录。
      command_refs:
        - commands.preflight.validate_dataset_full_hash
      outputs:
        - 控制台输出 [OK] CylinderFlow dataset validation passed
    - name: provide_to_vortex_shedding_mgn_model
      capability: train
      default: true
      required_datasets:
        - id: OneScience/cylinder_flow
          role: train_data
          local_path: data/cylinder_flow
      required_model_files:
        - OneScience/Vortex_shedding_mgn:conf/mgn_cylinderflow.yaml
      required_dataset_files:
        - data/cylinder_flow/train.tfrecord
        - data/cylinder_flow/valid.tfrecord
        - data/cylinder_flow/test.tfrecord
      preconditions:
        - 模型仓库 OneScience/Vortex_shedding_mgn 已下载。
        - 将本仓库 data/cylinder_flow 放到模型包根目录 data/cylinder_flow，或设置 ONESCIENCE_CYLINDER_FLOW_DATA_DIR 指向本目录用于预检。
      command_refs:
        - commands.prepare.export_dataset_env
      outputs:
        - 模型侧 scripts/preflight_vortex_shedding_mgn.py 可以读取数据集。

capabilities:
  dataset_validation: true
  train_input: true
  inference_input: true
  evaluation_input: true
  visualization_input: true
  preflight: true
  inference: false
  train: false
  finetune: false
  evaluate: false
  visualize: false
  deploy: false

commands:
  download:
    - name: download_dataset
      command: modelscope download --dataset OneScience/cylinder_flow
      cwd: session_workdir
    - name: download_model
      command: modelscope download --model OneScience/Vortex_shedding_mgn
      cwd: session_workdir
  prepare:
    - name: export_dataset_env
      command: export ONESCIENCE_CYLINDER_FLOW_DATA_DIR=/path/to/OneScience_cylinder_flow/data/cylinder_flow
      cwd: .
  preflight:
    - name: validate_dataset
      command: python scripts/validate_cylinder_flow_dataset.py --dataset-root . --skip-tfrecord-read
      cwd: .
    - name: validate_dataset_full_hash
      command: python scripts/validate_cylinder_flow_dataset.py --dataset-root . --verify-sha256 --skip-tfrecord-read
      cwd: .
    - name: validate_dataset_read_first_record
      command: python scripts/validate_cylinder_flow_dataset.py --dataset-root .
      cwd: .
  inference: []
  train: []
  finetune: []
  evaluate: []
  visualize: []
  deploy: []

expected_outputs:
  - name: validate_dataset
    paths: []
    success_criteria:
      - 控制台输出 [OK] CylinderFlow dataset validation passed
  - name: validate_dataset_full_hash
    paths:
      - files_sha256.jsonl
    success_criteria:
      - SHA256 与 files_sha256.jsonl 完全一致。
  - name: model_consumption
    paths: []
    success_criteria:
      - 模型包 scripts/preflight_vortex_shedding_mgn.py 通过数据路径和 schema 检查。

diagnostics:
  - name: missing_data_root
    symptom: missing required file 或 missing data directory
    action: 确认当前目录为 OneScience/cylinder_flow 数据集仓库根目录，且 data/cylinder_flow 存在。
  - name: missing_tfrecord
    symptom: "missing required file: data/cylinder_flow/*.tfrecord"
    action: 对照 files_sha256.jsonl 重新上传或重新下载缺失 TFRecord。
  - name: schema_mismatch
    symptom: meta.json feature shape mismatch 或 dtype mismatch
    action: 确认没有用其他 CylinderFlow 数据覆盖当前文件。
  - name: checksum_mismatch
    symptom: sha256 mismatch
    action: 删除损坏文件后重新下载 OneScience/cylinder_flow。
  - name: model_cannot_find_data
    symptom: 模型侧报告 data/cylinder_flow 不存在
    action: 将本仓库 data/cylinder_flow 复制到模型包根目录 data/cylinder_flow，或修改模型包配置副本中的 data_dir 与 stats_dir。

domain_extension:
  cfd:
    dataset_family: DeepMind CylinderFlow
    physics: transient incompressible cylinder wake / vortex shedding
    simulator: comsol
    file_count: 6
    trajectory_length: 600
    dt: 0.01
    schema:
      cells:
        shape: [1, -1, 3]
        dtype: int32
      mesh_pos:
        shape: [1, -1, 2]
        dtype: float32
      node_type:
        shape: [1, -1, 1]
        dtype: int32
      velocity:
        shape: [600, -1, 2]
        dtype: float32
      pressure:
        shape: [600, -1, 1]
        dtype: float32