simnibs-analyze
Post-processing and analysis pipeline for SimNIBS e-field outputs. Built to facilitate the analysis of simnibs simulations in the context of non-invasive brain stimulation studies (TMS/tDCS).
What it does
Starting from SimNIBS outputs, the pipeline covers the full analysis workflow:
- Target definition — generate ROI masks in MNI and subject space from MNI coordinates or atlas parcels (sphere, atlas-based)
- E-field preparation — coregister, skull-strip, smooth, and mask NIfTI volumes; intra/extra-ROI decomposition
- E-field analysis — extract scalar features (mean, max, percentiles, focality ratio) per subject and condition
- Single-subject optimisation assessment — evaluate how well a given montage targets the intended ROI
- Simulation robustness — assess sensitivity of the e-field distribution to input variability
- Stimulation method comparison — contrast montages or stimulation parameters across conditions
- Group-level analysis — inter-subject summary statistics, condition comparisons, and effect-size reporting
- Visualisation — 2D slice overlays, 3D surface rendering, histograms, and group bar plots
Installation
# TODO: publication sur PyPI
pip install simnibs-analyze
Prerequisite Data (Input structure from simnibs):
You need to have already run:
- simnibs-simulation or/ andsimnibs-optimization folder
- simnibs-m2m folder
Quick start:
- prepare a config file : use examples from (add link)
- then run: simnibs-analyze --config="pathToYourConfig.yaml"
Click here for a full documentation
| Ressource | Description |
|---|---|
| Documentation API | Classes et fonctions (généré par pdoc) |
| Référence config.yaml | Toutes les clés du fichier de configuration |
| Structure des outputs | Fichiers générés dans simnibs_output/ et results_dir/ |
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
simnibs_analyze-0.0.2.tar.gz
(54.2 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file simnibs_analyze-0.0.2.tar.gz.
File metadata
- Download URL: simnibs_analyze-0.0.2.tar.gz
- Upload date:
- Size: 54.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/6.2.0 CPython/3.11.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3b7cf95e2146380bfd038fa0d2b96104d64ac64072a7e1caf82c82ff466d225c
|
|
| MD5 |
dff3cf3a2ffe3c09cc19a488626ee1f8
|
|
| BLAKE2b-256 |
b328fcdb8ab06c9a348c9850ef733a663ebe3d66fdc2fdf87d345990ed94bd27
|
File details
Details for the file simnibs_analyze-0.0.2-py3-none-any.whl.
File metadata
- Download URL: simnibs_analyze-0.0.2-py3-none-any.whl
- Upload date:
- Size: 65.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/6.2.0 CPython/3.11.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
437e1e7b2cb539d874e1053009cf61063b9661b4458d601d2ad85b5155b93ccf
|
|
| MD5 |
de8dcb54f849f3033579c2c066c6cca2
|
|
| BLAKE2b-256 |
4c1267691f3d07c39ad657bd5371d6829bc41ad57f83eec7e66410da00b58847
|