
The R package dgpsi provides R interface to Python
package dgpsi
for deep and linked Gaussian process emulations using stochastic
imputation (SI).
Hassle-free Python Setup
You don’t need prior knowledge of Python to start using the package, all you need is a single click in R (see Installation section below) that automatically installs and activates the required Python environment for you!
dgpsi currently has following features:
You can install the package from CRAN:
install.packages('dgpsi')or its development version from GitHub:
devtools::install_github('mingdeyu/dgpsi-R')After the installation, run
library(dgpsi)to load the package. To install or activate the required Python
environment automatically, you can either run
dgpsi::init_py() explicitly or simply call any function
from the package. That’s it - the package is ready to use!
Note
After loadingdgpsi, the package may take some time to compile and initiate the underlying Python environment the first time a function fromdgpsiis executed. Any subsequent function calls won’t require re-compiling or re-activation of the Python environment, and will be faster.If you experience Python related issues while using the package, please try to reinstall the Python environment:
dgpsi::init_py(reinstall = T)Or uninstall completely the Python environment:
dgpsi::init_py(uninstall = T)and then reinstall:
dgpsi::init_py()
This package is part of an ongoing research initiative. For detailed information about the research aspects and guidelines for use, please refer to our Research Notice.