itis-sumo

Headless core of the SuMo (Surrogate Model) meta-modeling tools: build, evaluate, cross-validate, and interrogate surrogate models — UQ (Sobol indices, uncertainty propagation, correlation), sampling (LHS / grid / manual-UQ), and MOGA optimization — as a standalone, importable Python package.

Aggregates the computational core of the mmux/vite flaskapi Dakota modules plus recycled utilities from earlier MetaModeling trials. No Flask, no oSPARC, no UI: pure computation on top of the Dakota wheel.

Engine

• Runtime engine = the PyPI wheel itis-dakota==1.5.9 (Dakota 6.20), pinned for exact parity with the mmux/vite flaskapi engine, on Python 3.11.
• The in-repo itis-dakota/ checkout is the IT'IS Dakota fork, kept for reference only — this package consumes the pre-built wheels published to PyPI and does not build the fork.
• Engine calls happen through dakota.environment.study(input_string=...) executed inside a ProcessPoolExecutor; the package never shells out to a dakota binary.
• Engine caveats, the wheel-build process, and the 6.23+ Interface::interface_cache regression (why we stay on 1.5.9) are documented in DAKOTA-STUBS.md, including the T16mo upgrade ladder.

Provenance

Every module in this package was either ported from an earlier mmux repo or deliberately written new. The port source is mmux_vite's flaskapi (branch jgo/sobol-indices @ 22685f7); utilities were recycled from itis_dakota_projects / itis_dakota_projects_clean; the lineage reaches back to mmux_python (mmux_gui). The in-repo itis-dakota/ fork checkout is reference-only.

Full per-repo / per-branch / per-commit inventory — what was ported, what was deliberately not ported, and what remains as porting candidates — is in PORTING.md.

Install & verify

uv sync                          # Python 3.11, resolves itis-dakota==1.5.9
uv run itis-sumo validate        # engine probe (expect: Version 1.5.9)
uv run pytest                    # 123 tests, standalone
uv run python examples/headless_smoke.py   # surrogate -> CV -> Sobol

Package layout

src/itis_sumo/
  core/       Dakota execution primitives (DakotaObject, wiofiles)
  config/     NIDR string composers (surrogate/MOGA/UQ confs)
  data/       data processing (healing, bounds, correlation, dominance)
  sampling/   LHS / manual-UQ / grid sampling
  evaluate/   end-to-end runs (sumo eval, CV+metrics, MOGA, Sobol, UQ)
  preprocess/ DataPreprocessor + function-jobs pydantic models
  utils/      engine validation + NIDR config guard

Docs

• Published docs: https://itisfoundation.github.io/itis-sumo/
• SPEC.md — living spec (goals, constraints, invariants, research, tasks)
• PORTING.md — port provenance per source repo/branch/commit
• DAKOTA-STUBS.md — engine stubs, wheel build, regressions