recipe pcasuite

PCAzip compresses a trajectory, recentering the snapshots using a standard RMS or a gaussian version.

Homepage:

https://mmb.irbbarcelona.org/gitlab/andrio/pcasuite

License:

APACHE / Apache Software License

Recipe:

/pcasuite/meta.yaml

PCAunzip recreates the original trajectory from the projection data. PCZdump analyzes the compressed trajectory and gives coefficients and values computed from the stored trajectory.

package pcasuite

(downloads) docker_pcasuite

versions:

1.0.0-3,  1.0.0-2,  1.0.0-1,  1.0.0-0

depends bison:

depends lapack:

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends libgfortran-ng:

depends libgfortran5:

>=12.2.0

depends liblapack:

>=3.9.0,<4.0a0

depends libnetcdf:

>=4.8.1,<4.8.2.0a0

depends libstdcxx-ng:

>=12

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 pcasuite

and update with::

   mamba update pcasuite

To create a new environment, run:

mamba create --name myenvname pcasuite

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/pcasuite:<tag>

(see `pcasuite/tags`_ for valid values for ``<tag>``)

Download stats

Link to this page

Render an install-with-bioconda 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/pcasuite/README.html)