DNF: Discrete Normalizing Flows for Single Cell Omics
Discreate normalizing flows.
Installation
- Create a virtual environment and activate it
conda create -n DNF python=3.10 scipy numpy pandas scikit-learn && conda activate DNF
- Install PyTorch following the official instruction.
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126
- Install DNF
pip3 install DNF-tool
Reproducibility
See the Github repository for materials and tutorials required to reproduce the results.
1 maintainer
Metadata
1 maintainer
Release files for DNF-tool 0.3.4
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 | |
|---|---|---|---|---|
| dnf_tool-0.3.4.tar.gz | 27.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dnf_tool-0.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 56.4 kB
Release files / dnf_tool-0.3.4.tar.gz
| Download URL | dnf_tool-0.3.4.tar.gz |
|---|---|
| Size | 27.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
484dd57be173ccb6557e1817d41432f6decda0b834a73d630ffc0870a3aed895
|
|
BLAKE2b-256 checksum How to use checksums |
7733dda667e2ea66d30272c64429211ea4e436264adb262f0406ff1e5f2f9d5f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.18
|
Release files / dnf_tool-0.3.4-py3-none-any.whl
| Download URL | dnf_tool-0.3.4-py3-none-any.whl |
|---|---|
| Size | 29.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
202a1dd977960e46860c23ddbe75819e8e3b0a6e71b7e09f5d5be2a08c351959
|
|
BLAKE2b-256 checksum How to use checksums |
f6c6c5a3ff8be7b9cec48eaed23087226c9dbd50b3879e0ce9509ec7d749decc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.18
|
Security for DNF-tool 0.3.4
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.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A 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.
