Programming help

The most popular programming languages in scientific computing are still Fortran and C due to their speed. However, Python has gained popularity recently due to its simple syntax and large library of tools. Python is slow, but it is possible to call numeric routines coded in C or Fortran from Python combining the flexibility and efficiency of the different languages.

In the provided exercises and project, we will run simulations in a Python environment using the libraries

• ASE
• NumPy
• Pysic
• friction_tools

Those interested may want to explore the documentation of these tools. However, The module friction_tools is a custom collection of simple commands for building a simulation. These tools should be enough for running the simulations. You can of course complement the provided tools with your own programming.

Knowing Python will help, but it is not necessary as instructions and examples are provided and the teachers are willing to help in setting up the simulations. If you do wish to learn more, the best place to start is at the Code Academy, along with the Python tutorials as a more referential source.

• Setting up the simulation environment
  • Instructions for Aalto Linux (and Mac) workstations
  • Instructions for other Linux computers
• Tutorial simulations
  • Visualization
  • Getting started
  • Different atoms
  • About temperature
  • Potential problems
  • Take control
  • Absolute precision
• Tools
  • The FrictionSimulation class
  • Tools functions
  • Module API
• Physical units in simulations
• VMD
• Other resources