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Save, share, and export

VIPP offers several outputs that solve different problems. They are not interchangeable.

Artifact Use it for Does not contain
Workflow JSON (schema 3) Reopen/edit the validated scientific graph in VIPP 0.12; optionally restore an attached versioned Batch workspace configuration Cached pixels/tables, Python environment, source bytes
Exported Python Execute immutable validated workflow JSON through VIPP's shared headless executor Interactive UI, caches, a portable runtime environment
Saved image/table Analysis result or QC artifact The graph and parameter rationale
OME analysis dataset Reference image plus associated graph label outputs A complete project/archive or arbitrary standalone table provenance
Batch config Recreate source bindings, output declarations, naming, collision policy, and workflow association Input bytes, environment, finalized run outcome
Batch manifest/archive/sidecars Audit planned inputs/outputs, identities, hashes, versions, errors, and per-item/output status One atomic transaction or proof of biological validity

Save a workflow

Choose Save workflow…. Use .json and include a meaningful analysis name. If a Batch workspace is active, VIPP asks what to save:

  • Yes attaches the current versioned batch configuration to the same workflow JSON. This includes source bindings, local input/output paths, patterns, formats, and run policies. It does not include input pixels, computed arrays, or output files.
  • No writes the ordinary graph-only workflow. Use Save config… in Batch workspace if a separate configuration is required.
  • Cancel writes nothing.

Loading a workflow with a valid attachment restores and opens Batch workspace with those settings. It does not scan the collection, build a preview, load a representative, or run the graph for the batch setup. Preview batch remains optional, and Run batch performs a fresh preflight. If the attachment is unsupported or does not match the workflow, VIPP loads the scientific workflow but reports that its Batch workspace could not be restored rather than silently applying the settings.

Before sharing:

  1. Reopen the file in the same VIPP release.
  2. Confirm every Image Source intentionally references a sample, layer, file, or store.
  3. Review graph notes, paths, source names, and metadata for sensitive text.
  4. Recalculate manual nodes and compare expected outputs.

Workflow compatibility can change between alpha releases. Keep an unmodified copy of the original and record the version that created it.

0.12.0a3 still writes schema 3 and rejects versions 1 and 2. Valid 0.12.0a1 and 0.12.0a2 schema-3 workflows load structurally, but cached pixels and tables are not serialized in the workflow. Recalculate and revalidate after upgrading. For a 0.12.0a2 workflow, follow the 0.12.0a2 to 0.12.0a3 procedure. The earlier 0.12.0a1 to 0.12.0a2 procedure remains available for older workflows. Recreate schema-1/2 graphs deliberately; do not edit only the JSON version. See the separate schema-1/2 rebuild procedure.

Save a selected output

Select the desired output and choose Save selected output…. The available format depends on the data type and dimensionality. For tables use CSV or TSV; for scientific images prefer a format that can represent the axes, dtype, and calibration you need.

Read the input/output reference before using a display-oriented raster format or ImageJ TIFF for label IDs.

Export Python

Choose Export Python… when a graph needs a reviewable headless program. The script embeds validated immutable workflow JSON, constructs a fresh pipeline per call, and uses the same headless executor as VIPP. It carries supported ImageState, accepts explicit multi-source bindings, and fails on missing, duplicate, or unknown sources.

The script records the exact VIPP version that created it and refuses another runtime. Regenerate and revalidate it after every upgrade, including alpha updates. UI caches, pinned layers, and graph layout are presentation state and are intentionally absent.

Save a batch configuration and evidence

Use Batch workspace... → Save config... to write vipp_batch_config.json. Keep it with its required workflow companion. After a run, retain the latest manifest, run-id archive, and item sidecars. The optional vipp_batch_pipeline.py is only a thin launcher for that config; it is not a substitute for the workflow/config pair.

The standalone config remains the appropriate form for the supplied headless batch runner and for workflows/configs managed as separate automation artifacts. An attached config is convenient for reopening the interactive setup as one file; it does not replace the finalized manifests and sidecars that document an actual run.

Inspect partial, skipped, and failed records as well as successful outputs. Sidecars help reconstruct an interrupted run, but outputs and provenance files are not one multi-file transaction.

Share an analysis package

At minimum include:

  • workflow JSON;
  • VIPP version and environment record;
  • input identifiers/checksums or an accessible dataset citation;
  • output tables/images and a description of how they were selected;
  • validation/QC evidence;
  • method notes for manual decisions, exclusions, source/grid assumptions, and batch pairing;
  • for batch work: the attached or standalone config, manifest archives, sidecars, and the workflow/config hashes reported by the finalized run.

For publication, follow the reporting checklist.