When working with
APL package please cite:
Association Plots: Visualizing associations in high-dimensional correspondence analysis biplots Elzbieta Gralinska, Martin Vingron bioRxiv 2020.10.23.352096; doi: https://doi.org/10.1101/2020.10.23.352096
library(devtools) install_github(" elagralinska/APL-Rpackage")
In order to speed up the singular value decomposition, we highly recommend the installation of
Users can instead also opt to use the slower R native SVD. For this, please turn the argument
python = FALSE wherever applicable in this vignette.
library(reticulate) install_miniconda() conda_install(envname = "r-reticulate", packages = "numpy") conda_install(envname = "r-reticulate", packages = "pytorch")
Download the appropriate Miniconda installer for your system from the conda website.
Follow the installation instructions on their website and make sure the R package
reticulate is also installed before proceeding.
Once installed, list all available conda environments via
conda info --envs
One of the environments should have
r-reticulate in its name. Depending on where
you installed it and your system, the exact path might be different.
Activate the environment and install pytorch into it.
conda activate ~/.local/share/r-miniconda/envs/r-reticulate # change path accordingly. conda install numpy conda install pytorch
after installation for an introduction into the package.
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