recipe pcst-fast

A fast implementation of the Goemans-Williamson scheme for the PCST (prize-collecting Steiner tree/forest) problem.

Homepage:

https://github.com/fraenkel-lab/pcst_fast

License:

MIT / MIT

Recipe:

/pcst-fast/meta.yaml

package pcst-fast

versions:

1.0.10-0,  1.0.8-1,  1.0.8-0,  1.0.7.1-1,  1.0.7.1-0,  1.0.7-0

depends libgcc-ng:

>=12

depends libstdcxx-ng:

>=12

depends pybind11:

>=2.4

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

requirements:

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 pcst-fast

and update with::

   mamba update pcst-fast

To create a new environment, run:

mamba create --name myenvname pcst-fast

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/pcst-fast:<tag>

(see `pcst-fast/tags`_ for valid values for ``<tag>``)

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Link to this page

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