SURE: SUccinct REpresentation of cells
SURE implements a discrete latent state model with normalizing flow encoder for exact estimation of cellular populations.
Installation
- Create a virtual environment
conda create -n SURE python=3.10 scipy numpy pandas scikit-learn && conda activate SURE
- Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
- Install SURE
pip3 install SURE-tools
Metadata
Release files for SURE-tools 4.18.34
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sure_tools-4.18.34.tar.gz | 111.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sure_tools-4.18.34-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 240.7 kB
Release files / sure_tools-4.18.34.tar.gz
| Download URL | sure_tools-4.18.34.tar.gz |
|---|---|
| Size | 111.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.10.18
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Release files / sure_tools-4.18.34-py3-none-any.whl
| Download URL | sure_tools-4.18.34-py3-none-any.whl |
|---|---|
| Size | 129.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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