midas-suite

A meta-package that installs the MIDAS Python pipeline in a single command.

pip install midas-suite

This pulls in the currently published MIDAS sub-packages — the FF/NF HEDM analysis chain, calibration, peak fitting, radial integration, forward model, indexing, transforms, grain processing, and stress/strain analysis.

midas-suite itself contains no scientific code. It's a thin meta-package whose only job is to declare the sub-packages as dependencies so users don't have to install them one at a time.

What you get

pip install midas-suite installs 19 sub-packages (as of v0.3.1):

Top-level orchestrators (the entry points most users want):

Sub-package Role
midas-pipeline Unified FF + PF orchestrator (--scan-mode {ff,pf,auto}). End-to-end from raw data through grain reconstruction; single source for both scan modes.
midas-ff-pipeline Independent FF-HEDM workflow orchestrator (1-N detectors). Co-exists with midas-pipeline; same kernels under the hood.
midas-nf-pipeline Pure-Python NF-HEDM pipeline orchestrator (single + multi-resolution, multi-layer). Drop-in for nf_MIDAS.py / nf_MIDAS_Multiple_Resolutions.py.
midas-parsl-configs Bundled + user-extensible Parsl configs for running MIDAS pipelines on laptops, workstations, clusters.

FF-HEDM building blocks:

Sub-package Role
midas-peakfit Differentiable PyTorch peak fitting for FF-HEDM Zarr
midas-transforms FF-HEDM peak transforms (merge / radius / fit-setup / save-bin)
midas-index Pure-Python/PyTorch FF-HEDM indexer (drop-in for IndexerOMP)
midas-fit-grain Single/multi-grain refiner
midas-process-grains FF-HEDM grain-determination + strain pipeline

NF-HEDM building blocks:

Sub-package Role
midas-nf-preprocess NF-HEDM preprocessing (hex grid, tomo filter, spot prediction)
midas-nf-fitorientation NF-HEDM orientation/calibration fitter

Shared foundations:

Sub-package Role
midas-stress Crystallographic stress/strain analysis (Voigt-Mandel, Cij inversion, slip/Schmid/Taylor)
midas-params Parameter-file registry, validator, wizard for FF/NF/PF/RI
midas-hkls Pure-Python crystallography & HKL list generator (sginfo-equivalent)
midas-diffract End-to-end differentiable HEDM forward model (FF + NF + pf-HEDM)
midas-integrate Pure-Python radial integration (DetectorMapper + CSR + streaming server)
midas-integrate-v2 Differentiable, autograd-clean integration kernels (torch); companion to v1
midas-calibrate Native Python/Torch detector geometry calibration (LM-based)
midas-calibrate-v2 Torch-native Bayesian/Laplace calibration (LM + L-BFGS); companion to v1

You then import midas_stress, import midas_diffract, etc. directly — each sub-package retains its own API. midas-suite does not re-export them.

To check what was installed:

import midas_suite
print(midas_suite.installed())

Modality bundles

If you don't want everything, the optional extras let you pick a workflow:

pip install "midas-suite[ff]"        # FF-HEDM stack
pip install "midas-suite[pf]"        # PF-HEDM stack (scanning / point-focus)
pip install "midas-suite[nf]"        # NF-HEDM stack
pip install "midas-suite[calib]"     # v1 calibration + integration
pip install "midas-suite[calib-v2]"  # v2 (torch differentiable) calibration + integration
pip install "midas-suite[ff,plots]"
Extra What it pulls
ff midas-ff-pipeline (transitively pulls hkls, peakfit, transforms, index, fit-grain, process-grains, diffract, parsl-configs) + stress, params, calibrate, integrate
pf midas-pipeline[fast] (numba) + stress, params, calibrate, integrate (scan-mode pf pulls index + fit-grain + transforms + stress transitively)
nf midas-nf-pipeline (transitively pulls hkls, stress, nf-preprocess, nf-fitorientation) + params
calib hkls, integrate, peakfit, calibrate (v1 C-backed stack)
calib-v2 hkls, calibrate-v2, integrate-v2, peakfit (torch differentiable stack)
plots matplotlib (for sub-package plotting helpers)

What pip install midas-suite does NOT include

Be aware:

  • The MIDAS C executables (IndexerOMP, ProcessGrains, MakeDiffrSpots, …) still need to be built from source via cmake --build . from the MIDAS monorepo. The pure-Python pipeline (calibration → integration → indexing → grain processing) is now end-to-end in PyTorch and does not require them.
  • The PyQt FF viewer GUI needs PyQt5 or PySide6 installed separately. Not declared here because it's optional and platform-sensitive.
  • Optional crystallography backends for midas-hkls: install gemmi or pycifrw separately for CIF I/O via pip install midas-hkls[cif].
  • GPU acceleration is a runtime backend selected by PyTorch device string. CUDA/MPS just work if your torch install supports them; no separate *-gpu package needed.
  • In-tree-only packages (midas-grain-odf, midas-joint-ff-calibrate, midas-pf-odf, midas-pink, midas-propagate, midas-uq) are intentionally not published to PyPI — they live in the monorepo for ongoing research and only build / install from a local checkout.

Cross-platform

All MIDAS Python sub-packages are pure Python or PyTorch and ship as py3-none-any wheels. Tested install paths: Linux, macOS, Windows. See packages/RELEASE_READINESS.md for the detailed cross-platform readiness matrix.

Versioning

midas-suite versions are independent of the sub-package versions. The rule:

Change Bump
Floors tightened (no new sub-package added) patch (0.1.0 → 0.1.1)
New sub-package added to the dep list minor (0.1.0 → 0.2.0)
Backwards-incompatible reorganisation of bundles major (0.x.y → 1.0.0)

Floors are pinned with >=, never ==, so a sub-package patch release doesn't break midas-suite.

Releasing a new version

See RELEASING.md for the full release flow. TL;DR:

cd packages/midas_suite
./release.sh 0.3.2 --publish

License

BSD-3-Clause, same as the sub-packages.

Project links

Data verified by PyPI on Aug 10, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (0.10.2)

1 maintainer

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Avatar for marinerhemant from gravatar.com marinerhemant

Credits

Author: Hemant Sharma

GitHub Statistics

Data verified by PyPI on Aug 10, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

BSD-3-Clause

Requires

Python >=3.9

Provides Extra

ff nf pf calib calib-v2 pdf defect dfxm xaf ultrafast grain-odf pf-odf pink plots all dev

Tags

MIDAS HEDM 3DXRD powder diffraction tomography DCT Laue synchrotron crystallography PyTorch

Classifiers

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