recipe sparse-neighbors-search

Approximate k-nearest neighbors search on sparse datasets

Homepage:

https://github.com/joachimwolff/sparse-neighbors-search

License:

MIT

Recipe:

/sparse-neighbors-search/meta.yaml

package sparse-neighbors-search

versions:

0.7-2,  0.7-1,  0.7-0,  0.6-1,  0.6-0,  0.5-0,  0.4-1,  0.4-0,  0.3-1, 

0.7-2,  0.7-1,  0.7-0,  0.6-1,  0.6-0,  0.5-0,  0.4-1,  0.4-0,  0.3-1,  0.3-0,  0.2.3-0

depends libgcc-ng:

>=12

depends libstdcxx-ng:

>=12

depends numpy:

>=1.17

depends numpy:

>=1.23.3,<2.0a0

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

depends scikit-learn:

>=0.21

depends scipy:

>=1.3

depends umap-learn:

requirements:

additional platforms:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install sparse-neighbors-search

and update with::

   mamba update sparse-neighbors-search

To create a new environment, run:

mamba create --name myenvname sparse-neighbors-search

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/sparse-neighbors-search:<tag>

(see `sparse-neighbors-search/tags`_ for valid values for ``<tag>``)

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Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/sparse-neighbors-search/README.html)