R conda env on RCE including lme4 package

Conda_Env_RCE_lme4.md

Steps for setting up R environment including nloptr and lme4 packages

• Step 1: Request for a powershell terminal.

Using nomachine:

• Select Applications tab
• Select RCE Powered Applications
• Select Anaconda Shell (Python 3.6) 5.2.0
• Select required number of cores and RAM

This will open a terminal.

• Step 2: Make sure that conda is installed. Run:

which conda

If conda is installed, the command should return a path. For example:

/nfs/tools/lib/anaconda/3-5.2.0/bin/conda

• Step 3: Under your user account, create .conda folder. For example, my account name is nak443 and my .conda folder is located in the following path:

nfs/home/N/nak443/shared_space/ci3_nak443/.conda

• Step 4: Under the .conda folder, create pkgs and envs folders.
• Step 5: Export the path of these folders. In my case, it will be:

export CONDA_PKGS_DIRS=/nfs/home/N/nak443/shared_space/ci3_nak443/.conda/pkgs
export CONDA_ENVS_PATH=/nfs/home/N/nak443/shared_space/ci3_nak443/.conda/envs

• Step 6: Take a look at the current environment:

conda env list

If your environment is already exist, move to step xyz.

• Step 7: Create a recipe for environment. For example this is r_env.yaml file content. You can put the library version infront of the library name and make the environment more customized.

name: r_env
channels:
  - conda-forge
  - anaconda
dependencies:
  - r-base=4.1
  - r-tidyverse
  - r-devtools
  - r-xgboost
  - r-superlearner
  - r-earth
  - r-ranger
  - r-gam
  - r-kernsmooth
  - r-gnm
  - r-polycor
  - r-wcorr
  - r-rlang
  - r-glue
  - r-logger
  - r-cli
  - python
  - cmake
  - jupyterlab
  - jupyter_client

• Step 8: Create your environment.

conda env create -n r_env -f r_env.yaml

• Step 9: Activate your environment.

conda activate r_env

• Step 10: Start an R session.

R

• Step 11: Install IRkernel and register kernel in jupyter lab

# In R
library('devtools')
devtools::install_github("IRkernel/IRkernel")
IRkernel::installspec()

• Step 12: Install other packages. For example, I want to install nloptr and lme4 packages.

install.packages('nloptr')
install.packages('lme4')

• Step 13: Now you can either use interactive R or start a Jupyter lab. If you decided to go with jupyter lab, type:

jupyter lab