Skip to main content

simnibs-analyze

Cohort-level analysis and visualisation of SimNIBS e-field simulations, driven by YAML config.

simnibs-analyze turns SimNIBS outputs into ROI statistics and publication figures across subjects and conditions, for non-invasive brain stimulation studies (TMS/tDCS).

PyPI version Docs License: MIT

📖 Full documentation → ICM-Frontlab-CDPR.github.io/simnibs-analyze


Install & run

pip install simnibs-analyze

Two config-driven commands:

simnibs-analyze --config config-analyze.yaml   # features + statistics
simnibs-viz     --config config-viz.yaml       # figures + cohort montages

Ready-made configs in docs/examples/config/, full key reference in the configuration guide.


Ecosystem

simnibs-analyze is built on:

It consumes results produced by:


Metadata

Release files for simnibs-analyze 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for simnibs-analyze 0.1.0
File Size Uploaded Provenance Actions
simnibs_analyze-0.1.0.tar.gz 29.8 kB Without provenance Details for simnibs_analyze-0.1.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for simnibs-analyze 0.1.0
File Interpreter ABI Platform Actions
simnibs_analyze-0.1.0-py3-none-any.whl Python 3 none any Details for simnibs_analyze-0.1.0-py3-none-any.whl

Total release size: 63.2 kB

Release files / simnibs_analyze-0.1.0.tar.gz

Download URL simnibs_analyze-0.1.0.tar.gz
Size 29.8 kB
Tags Source
SHA-256 checksum
How to use checksums
4b89b246e19d2dc9ac41eaba29525c8c0133572eaf88888af888e9a2c3a14d3a
BLAKE2b-256 checksum
How to use checksums
79e6111833bba4f8e1aacc6b0b81fab569c1befb44fbac70112122023cd486f0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.12

Release files / simnibs_analyze-0.1.0-py3-none-any.whl

Download URL simnibs_analyze-0.1.0-py3-none-any.whl
Size 33.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
d94b05ca8c34d62f93960625a56bcf65a6fc7e1d44238393b885f04e926b0ded
BLAKE2b-256 checksum
How to use checksums
74acfb6289f051e1b2990450e6109a8ce2c968d8c2071ff4cc3593d943dea1b3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.12

Security for simnibs-analyze 0.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page