This release is a pre-release and may not be stable for production use.
cellshape-cluster
Cellshape-cluster is an easy-to-use tool to analyse the cluster cells by their shape using deep learning and, in particular, deep-embedded-clustering. The tool provides the ability to train popular graph-based or convolutional autoencoders on point cloud or voxel data of 3D single cell masks as well as providing pre-trained networks for inference.
To install
pip install cellshape-cluster
Usage
import torch
from cellshape_cloud import CloudAutoEncoder
from cellshape_cluster import DeepEmbeddedClustering
autoencoder = CloudAutoEncoder(
num_features=128,
k=20,
encoder_type="dgcnn"
)
model = DeepEmbeddedClustering(autoencoder=autoencoder,
num_clusters=10,
alpha=1.0)
points = torch.randn(1, 2048, 3)
recon, features, clusters = model(points)
Parameters
autoencoder: CloudAutoEncoder or VoxelAutoEncoder.
Instance of autoencoder class from cellshape-cloud or cellshape-voxelnum_clusters: int.
The number of clusters to use in deep embedded clustering algorithm.alpha: float.
Degrees of freedom for the Student's t-distribution. Xie et al. (ICML, 2016) let alpha=1 for all experiments.
For developers
- Fork the repository
- Clone your fork
git clone https://github.com/USERNAME/cellshape-cluster
- Install an editable version (
-e) with the development requirements (dev)
cd cellshape-cluster
pip install -e .[dev]
- To install pre-commit hooks to ensure formatting is correct:
pre-commit install
- To release a new version:
Firstly, update the version with bump2version (bump2version patch,
bump2version minor or bump2version major). This will increment the
package version (to a release candidate - e.g. 0.0.1rc0) and tag the
commit. Push this tag to GitHub to run the deployment workflow:
git push --follow-tags
Once the release candidate has been tested, the release version can be created with:
bump2version release
Metadata
Release files for cellshape-cluster 0.0.3rc0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cellshape-cluster-0.0.3rc0.tar.gz | 5.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cellshape_cluster-0.0.3rc0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.0 kB
Release files / cellshape-cluster-0.0.3rc0.tar.gz
| Download URL | cellshape-cluster-0.0.3rc0.tar.gz |
|---|---|
| Size | 5.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fe234406ceed979a715ed763e5519d83913b3daa96723bb18f946806792f5bdc
|
|
BLAKE2b-256 checksum How to use checksums |
8787237bd94623f697364794a5946533958f24e50b945cc2d8548b010a1a866f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.5
|
Release files / cellshape_cluster-0.0.3rc0-py3-none-any.whl
| Download URL | cellshape_cluster-0.0.3rc0-py3-none-any.whl |
|---|---|
| Size | 5.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2c5a11d9a355936810c8dd0b002cf825af1a02dca571bb77cde6d750102de780
|
|
BLAKE2b-256 checksum How to use checksums |
ca59123763741cf6e9269d4e4ee7049947fc5a19cf50232b0b3e851221eb812d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.5
|