Linux Scientific Computing - ryzendew/Linux-Tips-and-Tricks GitHub Wiki

Linux Scientific Computing Guide

Complete beginner-friendly guide to scientific computing on Linux, covering Arch Linux, CachyOS, and other distributions including Python scientific libraries, R, MATLAB alternatives, and data analysis tools.

Table of Contents

  1. Python Scientific Libraries
  2. R Statistical Computing
  3. MATLAB Alternatives
  4. Data Analysis Tools
  5. Troubleshooting

Python Scientific Libraries

NumPy

Install NumPy:

# Install NumPy
pip install numpy

# Or system package
sudo pacman -S python-numpy

SciPy

Install SciPy:

# Install SciPy
pip install scipy

# Or system package
sudo pacman -S python-scipy

Matplotlib

Install Matplotlib:

# Install Matplotlib
pip install matplotlib

# Or system package
sudo pacman -S python-matplotlib

Pandas

Install Pandas:

# Install Pandas
pip install pandas

# Or system package
sudo pacman -S python-pandas

R Statistical Computing

Install R

Arch/CachyOS:

# Install R
sudo pacman -S r

# Install RStudio (optional)
yay -S rstudio-desktop-bin

Debian/Ubuntu:

sudo apt install r-base

Fedora:

sudo dnf install R

Use R

Launch R:

# Launch R
R

# Or RStudio
rstudio

MATLAB Alternatives

Octave

Install Octave:

# Install Octave
sudo pacman -S octave

# Launch
octave

Scilab

Install Scilab:

# Install Scilab
yay -S scilab-bin

Data Analysis Tools

Jupyter

Install Jupyter:

# Install Jupyter
pip install jupyter

# Launch
jupyter notebook

Spyder

Install Spyder:

# Install Spyder
sudo pacman -S spyder

# Launch
spyder

Troubleshooting

Library Import Errors

Check installation:

# Check Python
python -c "import numpy; print(numpy.__version__)"

# Reinstall if needed
pip install --upgrade numpy

Summary

This guide covered scientific computing tools for Arch Linux, CachyOS, and other distributions.

Next Steps

This guide covers Arch Linux, CachyOS, and other Linux distributions. For distribution-specific details, refer to your distribution's documentation.