Here are the commands required to reproduce the environment for running solutions on a Linux system
The editor and language options available are:
VS code
Python, Julia, R
Jupyter Lab
Python, Julia, R, Octave, gnu plot
Pluto notebook
Julia
Octave
Octave
These commands were entered on an M1 Mac running Ubuntu 20.04.2 in a Virtual Machine in Parallels but the commands should apply to other Ubuntu systems
uname -a shows 5.13.0-25-generic
mkdir tmp
cd tmp
wget https://mirror.ctan.org/systems/texlive/tlnet/install-tl-unx.tar.gz
zcat install-tl-*
sudo perl ./install-tl –no-interaction
add to .bashrc
export MANPATH=”/usr/local/texlive/2022/texmf-dist/doc/man:$MANPATH”
export INFOPATH=”/usr/local/texlive/2022/texmf-dist/doc/info:$INFOPATH”
export PATH=”/usr/local/texlive/2022/bin/aarch64-linux:$PATH”
mkdir Developer
cd Developer
sudo apt update
From https://github.com/conda-forge/miniforge downloaded Miniforge3-Linux-aarch64 (x86 if not on ARM)
In terminal in Downaloads bash Miniforge3-Linux-aarch64.sh (x86 if not on arm)
Chose to Initialise miniforge3
Restart Terminal
Environment structure is u-ubuntu 3105 – python version
conda create -n u3105 python=3.10.5
conda activate u3105
which python shows /home/parallels/miniforge3/envs/u3105/bin/python (Note where yours is)
python -V shows Python 3.10.5
which pip shows /home/parallels/miniforge3/envs/u3105/bin/pip
conda install -c conda-forge jupyterlab
conda install -c conda-forge numpy
conda install -c conda-forge sympy
conda install -c conda-forge matplotlib
conda install -c conda-forge pandas
conda install -c conda-forge plotly
conda install -c conda-forge bokeh
conda install -c conda-forge scipy
conda install -c conda-forge seaborn
conda install -c conda-forge ipympl
conda install -c conda-forge watermark
conda install -c conda-forge r-base
From julialang.org/downloads downloaded 64bit AArch64 of v1.8.0-rc1
cd Downloads
gunzip julia-1.8.0-rc1-linux-aarch64.tar.gz
sudo mkdir /usr/local/bin/julia18
sudo tar -xvf julia-1.8.0-rc1.linux-aarch64.tar -C /usr/local/bin/julia18
Change /home/parallels for where yours is
ln -s /usr/local/bin/julia18/julia-1.8.0-rc1/bin/julia /home/parallels/miniforge3/envs/u3105/bin/julia18
julia18
using Pkg
Pkg.add(“IJulia”)
exit()
In your chosen environment folder structure:
julia18 -e ‘using Pkg;Pkg.generate(“learn”)
cd learn
julia18 –project=.
add environment specific Julia packages
From https://nodes.org/en/downloads/current downloaded Linux binaries ARMv8
sudo mkdir /usr/local/bin/node
sudo tar -xvf node-v16.15.1-linux-arm64.tar.xz -C /usr/local/bin/node
Extract files from node-v16.15.1-linux-arm64.tar.xz to /home/parallels/node-v16.8.0
ln -s /usr/local/bin/node/node-v16.15.1-linux-arm64/bin/node /home/parallels/miniforge3/envs/u3105/bin/node
R
install.packages(‘IRkernel’)
Selected Bristol mirror
install.packages(‘plotly’)
IRkernel::installspec()
quit()
pip install octave-kernel
sudo apt-get install octave
pip install gnuplot_kernel
python -m gnuplot_kernel install –user
jupyter-lab build
jupyter labextension list
jupyter kernelspec list
jupyter nbextension list
jupyter-lab Verify working with test notebook Then shutdown
sudo apt install fortran-language-server
From quarto.org download Quarto CLI amd64 package
From code.visualstudio.com/download download 64 bit .deb package (arm64 if on Apple Silicon)
sudo apt install ./code_1.68.1…
code
Install Python, Julia, Fortran Xavier Hahn, Fortan IntelliSense, Fortran Breakpoint Support ekibun LaTex Workshop, Quarto, Wolfram Research extensions
In the relevant extension settings add the path to the language servers
Julia: Executable Path /usr/local/bin/julia18
Fortran-ls: Executable Path /usr/local/bin/fortls
Wolfram: Kernel Path /Applications/Wolfram Engine.app/Contents/MacOS/WolframKernel
From quarto.org download and install the program to install the Quarto CLI