Diametrize cells.
Project description
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
Project details
Release history Release notifications | RSS feed
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 diameter_synthesis-0.7.0.tar.gz.
File metadata
- Download URL: diameter_synthesis-0.7.0.tar.gz
- Upload date:
- Size: 418.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
082780241d559bc65176c0f720325f8ed8b3b559c33350f06734261ec3f913d0
|
|
| MD5 |
14cf2d2b71746791e04e9f50e84b0539
|
|
| BLAKE2b-256 |
463289c1d2f83c6f108b27237c84f6e84a6b04b983530b7bb208ffbcf30304da
|
File details
Details for the file diameter_synthesis-0.7.0-py3-none-any.whl.
File metadata
- Download URL: diameter_synthesis-0.7.0-py3-none-any.whl
- Upload date:
- Size: 34.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d33fdbe2f76d009daa670d401dc406a812e12702e8686db2b7af165c23422985
|
|
| MD5 |
bad1b7ee034e9387427cfa0256b3e293
|
|
| BLAKE2b-256 |
8869de1d2d2c360744bd8a52cd6841ccb489f9091b5f1e8a363c1f5ca562efb1
|