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'Miniconda' environment

Source: R/install.R
conda-env.Rd

These functions/variables are used to configure 'Miniconda' environment.

Usage

CONDAENV_NAME(env_name)

conda_path()

conda_bin()

env_path()

list_pkgs(...)

configure_matlab(matlab, python_ver = "auto")

configure_conda(
  python_ver = "auto",
  packages = NULL,
  matlab = NULL,
  update = FALSE,
  force = FALSE,
  standalone = FALSE
)

remove_conda(ask = TRUE)

add_packages(packages = NULL, python_ver = "auto", ...)

ensure_rpymat(verbose = TRUE, cache = TRUE)

matlab_engine()

call_matlab(
  fun,
  ...,
  .options = getOption("rpymat.matlab_opt", "-nodesktop -nojvm"),
  .debug = getOption("rpymat.debug", FALSE)
)

Arguments

env_name

alternative environment name to use; default is "rpymat-conda-env"

...

for add_packages, these are additional parameters passing to conda_install; for call_matlab, ... are the parameters passing to fun

matlab

'Matlab' path to add to the configuration path; see 'Details'

python_ver

python version to use; see 'Configuration'

packages

additional python or conda packages to install

update

whether to update conda; default is false

force

whether to force install the 'Miniconda' even a previous version exists; default is false. Setting false=TRUE rarely works. Please see 'Configuration'.

standalone

whether to install conda regardless of existing conda environment

ask

whether to ask for user's agreement to remove the repository. This parameter should be true if your functions depend on remove_conda (see 'CRAN Repository Policy'). This argument might be removed and force to be interactive in the future.

verbose

whether to print messages

cache

whether to use cached configurations; default is true

fun

'Matlab' function name, character (experimental)

.options

'Matlab' compiler options

.debug

whether to enable debug mode

Value

None

Background & Objectives

Package reticulate provides sophisticated tool-sets that allow us to call python functions within R. However, the installation of 'Miniconda' and python can be tricky on many platforms, for example, the 'M1' chip, or some other 'ARM' machines. The package rpymat provides easier approach to configure on these machines with totally isolated environments. Any modifications to this environment will not affect your other set ups.

Since 2014, 'Matlab' has introduced its official compiler for python. The package rpymat provides a simple approach to link the compiler, provided that you have proper versions of 'Matlab' installed. Here is a list of 'Matlab' versions with official compilers and their corresponding python versions.

Configuration

If 'Matlab' compiler is not to be installed, In most of the cases, function configure_conda with default arguments automatically downloads the latest 'Miniconda' and configures the latest python. If any other versions of 'Miniconda' is ought to be installed, please set options "reticulate.miniconda.url" to change the source location.

If 'Matlab' is to be installed, please specify the 'Matlab' path when running configure_conda. If the environment has been setup, configure_matlab can link the 'Matlab' compilers without removing the existing environment. For 'ARM' users, unfortunately, there will be no 'Matlab' support as the compilers are written for the 'Intel' chips.

Initialization

Once conda and python environment has been installed, make sure you run ensure_rpymat() before running any python code. This function will make sure correct compiler is linked to your current R session.

Examples


# The script will interactively install \code{conda} to `R_user_dir`
if (FALSE) {

# Install conda and python 3.9

configure_conda(python_ver = '3.9')


# Add packages h5py, pandas, jupyter

add_packages(c('h5py', 'pandas', 'jupyter'))

# Add pip packages

add_packages("itk", pip = TRUE)

# Initialize the isolated environment

ensure_rpymat()


# Remove the environment

remove_conda()

}