Diameter synthesis
This code aims at generating synthetic diameters for neurons, with parameters learned from a set of biological neurons.
Installation
Use pip:
pip install diameter-synthesis
Main usage
Step 1: Building models
In folder example, you first have to modify create_jsons.py to suit your needs.
You have the following important parameters for the dict extract_models_params:
morph_path: path to morphology filesmtypes_sort: how to learn distributions:allto use all together,mtypesto use by mtypes ,super_mtypesto use home made cells types (seediameter_typesbelow)models: to create several models (for now they are all the same, just different realisation of random numbers)neurite_types: types of neurite to learn parameters forextra_params: dict of additional model parameters
Step 2: Building diameters
Then simply run ./run_models.sh to create the models (saved in a json file).
In create_jsons.py, the dict generate_diameters_params needs to be updated, too, with entries matching the previous dict.
The path in new_morph_path will be where the new morphologies will be saved.
Then run ./run_diamters.sh to generate diameters.
Additional scripts
Several additional scripts in folder scripts:
diameter-checks: run the diameter-check code (bluepymm) on the biological and sampled cellsdiameter_types: cluster mtypes using distributions of surface areas (uses two privates repositories a the moment)extract_morphometrics: from bio and sample cells, extracts and plot distribution of surface area and diameter as a function of branch order and path lengthsextract_morphologies: from a cell release, find the ones that can be run through diameter-checkplot_morphologies: plot all morphologies in mtype folders
Examples
The examples folder contains a simple example that will fetch morphologies from neuromorpho.org, learn a diameter model, rediametrize these morphologies, and perform some analysis of the results to compare original and diametrized morphologies.
This example can simply be run using the following command:
./run.sh
Funding & Acknowledgment
The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
For license and authors, see LICENSE.txt and AUTHORS.md respectively.
Copyright © 2021-2022 Blue Brain Project/EPFL
Metadata
Release files for diameter-synthesis 0.7.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| diameter_synthesis-0.7.1.tar.gz | 416.3 kB | With provenance | Details for diameter_synthesis-0.7.1.tar.gz |
Release files / diameter_synthesis-0.7.1.tar.gz
| Download URL | diameter_synthesis-0.7.1.tar.gz |
|---|---|
| Size | 416.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
626924c9118da2b05e346b09a5dadd58e47eb5b472b812113a9e3d4ba867726d
|
|
BLAKE2b-256 checksum How to use checksums |
9e66be8a62bb24c75f4242fff8778b77160081cd83c6f2b3b1e5e18aef9f1673
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logSecurity for diameter-synthesis 0.7.1
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.
Full provenance
All 1 file in this release has been uploaded with provenance metadata.
Attestation for diameter_synthesis-0.7.1.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logA 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.