semvec/pypi-packages huggingface dataset:
lib4P 1.0.0
Feature library for 4P - Plant Phenotyping Processing Platform developed at INRAE for the PHENOME French national infrastructure
Requires Python: >=3.8
Keywords: 4P, Plant, Phenotyping, Processing, Platform, Phenome, INRAE, INRA, AgroEcoPhen, PHIS, Sixtine, OpenSilex

<h1 align="center">
    <img src="https://4p.pages-forge.inrae.fr/tools/4p-python-library/latest/_images/main-logo-4p.png" />
</h1>

lib4P is a feature package for 4P - Plant Phenotyping Processing Platform developed at INRAE for the PHENOME French national infrastructure.

- **Website:** https://phenome.inrae.fr/4p
- **Documentation:** https://4p.pages-forge.inrae.fr/tools/4p-python-library
- **Contact:** <a href="mailto:4P@inrae.fr">4P@inrae.fr</a>
- **Source code:** https://forge.inrae.fr/4p/tools/4p-python-library/
- **Issues:** https://forge.inrae.fr/4p/tools/4p-python-library/-/issues
- **Funding:** https://4p.pages-forge.inrae.fr/documentation/user-guide/other/faq.html#team-associated-projects

It provides:

- a reader/writer of metadata usually attached to LiDAR, RGB or Multispectral images
- an argparse overlay to improve integration on 4P
- a provider of datasets for testing purposes
- a naming convention validator for modules and variables
- beginnings of functionalities for log standardization
scimilarity 0.4.1
Single cell embedding into latent space that quantifies similarity between expression states.
Requires Python: >=3.10
Keywords: single-cell embedding/retrieval

SCimilarity
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**SCimilarity** is a unifying representation of single cell expression profiles
that quantifies similarity between expression states and generalizes to
represent new studies without additional training.

This enables a novel cell search capability, which sifts through millions of
profiles to find cells similar to a query cell state and allows researchers to
quickly and systematically leverage massive public scRNA-seq atlases to learn
about a cell state of interest.

Documentation
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Tutorials and API documentation can be found at:
https://genentech.github.io/scimilarity/index.html

Download & Install
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The latest API release can be installed from PyPI::

    pip install scimilarity

Pretrained model weights, embeddings, kNN graphs, a single-cell metadata
can be downloaded from:
https://zenodo.org/records/10685499

A docker container with SCimilarity preinstalled can be pulled from:
https://ghcr.io/genentech/scimilarity

Citation
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To cite SCimilarity in publications please use:

**A cell atlas foundation model for scalable search of similar human cells.**
*Graham Heimberg\*, Tony Kuo\*, Daryle J. DePianto, Tobias Heigl,
Nathaniel Diamant, Omar Salem, Gabriele Scalia, Tommaso Biancalani,
Jason R. Rock, Shannon J. Turley, Héctor Corrada Bravo, Josh Kaminker\*\*,
Jason A. Vander Heiden\*\*, Aviv Regev\*\*.*
Nature (2024). https://doi.org/10.1038/s41586-024-08411-y