Scientific Computing with Python and Fortran
Vetenskaplig programmering i Python och Fortran

FMA320F, 7.5 credits

Valid from: Autumn 2024
Decided by: Maria Sandsten
Date of establishment: 2024-03-19

General Information

Division: Mathematics
Course type: Third-cycle course
Teaching language: English

Aim

The course treats programming in Python and Fortran. The focus is on scientific programming and methods that are useful to doctoral students within technical and scientific subjects.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must Explain current concepts of scientific computing using Python and Fortran.

Competences and Skills

For a passing grade the doctoral student must

• Write basic Python programs for solving problems in scientific computing.
• Implement basic numerical codes in Python and NumPy.
• Visualise data using Python using Matplotlib and ParaView.
• Implement basic user interfaces in Python and Qt.
• Handle different types of data formats in Python
• Combine Python and Fortran code in a single application (mixed language programming)
• Create and manage customized Python environments for scientific applications

Judgement and Approach

For a passing grade the doctoral student must

• Compare the advantages and disadvantages of using Python and Fortran in Scientific Computing.
• Choose the right tools/language for the implementing scientific applications in Python and Fortran

Course Contents

Numerical computing with Python and NumPy. Data handling in Python Visualising data in Python Introduction to Fortran Mixed Language Programming

Course Literature

The literature will be announced to participants before course start.

Instruction Details

Types of instruction: Lectures, exercises. Teaching consists of lectures, tutorials and computer exercises.

Examination Details

Examination formats: Written report, written assignments. Assessment is based on assignments during the course on a final project work.
Grading scale: Failed, pass
Examiner:

Admission Details

Assumed prior knowledge: Basic skills in MATLAB or Python is required to be able to follow the course.

Further Information

Contact: Jonas Lindemann, jonas.lindemann@lunarc.lu.se

Course Occasion Information

Contact and Other Information

Course coordinators: