This release is a pre-release and may not be stable for production use.
neuromotifs
Python tools to load neuronal microcircuit geometry, generate geometry-aware null models, and quantify over/under-expression of 3-node motifs.
Paper: Neuron Morphological Asymmetry Explains Fundamental Network Stereotypy Across Neocortex (Gal et al.)
Install
pip install neuromotifs
# or, for dev
pip install -e .[dev]
Highlights
- Motif counting for directed triplets (#1-#13)
- Geometry-driven random graph generators (1st-5th order) mirroring the paper’s models
- Reproducibility notebooks for Figures 1-4
- Simple CLI:
neuromotifs motifs,neuromotifs generate,neuromotifs fit
Quickstart
# TBD
Data
data/nmc/contains tiny demonstrators only.- For full datasets, see
data/README.mdfor scripted download instructions.
Citing
Please cite the paper and this package (see CITATION.cff).
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
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 neuromotifs-0.1.0a2.tar.gz.
File metadata
- Download URL: neuromotifs-0.1.0a2.tar.gz
- Upload date:
- Size: 856.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/6.1.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9b501f826f7738e1c816a145adaf3f8892f40729856db25295725289a166d589
|
|
| MD5 |
666de2f39537596ec461f630cad8f5ac
|
|
| BLAKE2b-256 |
329cd7e99054a1be76afdaa7f87b02505f4ad5c83f045cd5b6ae0e30f341ef82
|
File details
Details for the file neuromotifs-0.1.0a2-py3-none-any.whl.
File metadata
- Download URL: neuromotifs-0.1.0a2-py3-none-any.whl
- Upload date:
- Size: 853.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/6.1.0 CPython/3.10.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ef9e738402a989e798199a27cbc4d4ef990116ae7342305be95ff7a6c2db9b95
|
|
| MD5 |
9d26b62696b42f1ac1ee14cf17656dc2
|
|
| BLAKE2b-256 |
2edb2a1e2bde2646804a524988ac622d10b6ab3108a3c1ca6766e70b531f867e
|
