knitr::opts_chunk$set(echo = TRUE)
To use the (optional but recommended) Python speed-up, you need Python 3.6+ (and conda if on Windows).
Install spmle
directly from this repository:
devtools::install_github("hunzikp/spmle")
In case you don't have scipy and numpy installed (or don't know what these are) and you want to use the Python speed-up, run the following in an R console:
spmle::install_pydep()
This command installs the Python dependencies in the r-reticulate
virtual environment.
To use the Python speed-up you need to specify a python binary or virtual environment where scipy and numpy are installed. If you ran the install_pydep()
command above, then you can use the following:
library(reticulate) library(spmle) reticulate::use_virtualenv("r-reticulate") # In Unix reticulate::use_condaenv("r-reticulate") # In Windows
See here.
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