recipe bioconductor-delayedtensor

R package for sparse and out-of-core arithmetic and decomposition of Tensor






DelayedTensor operates Tensor arithmetic directly on DelayedArray object. DelayedTensor provides some generic function related to Tensor arithmetic/decompotision and dispatches it on the DelayedArray class. DelayedTensor also suppors Tensor contraction by einsum function, which is inspired by numpy einsum.

package bioconductor-delayedtensor

(downloads) docker_bioconductor-delayedtensor



depends bioconductor-biocsingular:


depends bioconductor-delayedarray:


depends bioconductor-delayedrandomarray:


depends bioconductor-hdf5array:


depends r-base:


depends r-einsum:

depends r-irlba:

depends r-matrix:

depends r-rtensor:



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 bioconductor-delayedtensor

and update with::

   mamba update bioconductor-delayedtensor

To create a new environment, run:

mamba create --name myenvname bioconductor-delayedtensor

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<tag>

(see `bioconductor-delayedtensor/tags`_ for valid values for ``<tag>``)

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