Downstream and Export Provenance Workflow#

This is a V0.29 recipe page over existing public APIs; it adds no runtime surface.

Use this path when handing canonical data, orbit batches, or discovery outputs to sparse discovery or ML workflows.

FieldBatch / orbit batch / bridge output / backend-native result
-> JSON-compatible summaries
-> workflow report
-> optional split provenance diagnostics

Recipe#

  1. Convert downstream bridge arrays with to_pysindy_trajectories(...) only after the source FieldBatch is ready.

  2. Summarize bridge outputs before calling a backend.

  3. Summarize backend-native results without copying full coefficient matrices into report artifacts.

  4. Attach orbit-batch provenance when materialized translations are used.

  5. Report user-supplied partitions with summarize_split_leakage_provenance(...).

Primary APIs#

  • pdelie.discovery.to_pysindy_trajectories(...)

  • pdelie.discovery.summarize_discovery_bridge_output(...)

  • pdelie.discovery.summarize_discovery_result(...)

  • pdelie.reporting.summarize_downstream_discovery_workflow(...)

  • pdelie.reporting.summarize_split_leakage_provenance(...)

Defensible Claim#

The downstream workflow reports provenance, shape, finite-value, recovery, and traceability evidence. PDELie does not choose benchmark thresholds, create train/test splits, prevent leakage, or certify downstream scientific success.

Next Step#

Use end_to_end_dataset_to_downstream.md for a full Dataset-to-downstream recipe, or candidate_to_split_provenance.md when the starting point is a supplied generator candidate.