IMPRS

Python for Computational Science - Part 2 (1/5)

by Hans Fangohr (MPSD, SSU Computational Science)), Martin Lang (CFEL-SSUCS (SSU Computational Science))

Europe/Berlin
is yet to be announced

is yet to be announced

Description

 

Python for Computational Science - Part 2

 

Building on “Introduction to Python for Computational Science”, this course covers additional aspects:

  1. advanced Python, 
  2. additional libraries such as numpy, scipy, pandas, sympy,
  3. research software engineering and testing, and 
  4. application examples with focus on physics and engineering problems.

 
Parts (1
) to (3) are covered in the beginning of the course. Part (4) is delivered at the end of the week, and can be omitted if not relevant to the participant.

 

 

Topics include:

 

Ø Higher order functions
Ø programming paradigms
Ø scipy, pandas, sympy
Ø Research software engineering practices, in particular testing
Ø Python installations
Ø interpolation, root finding, curvefitting
Ø Optimisation, computing derivatives
Ø Integration of ordinary differential equations
 
From the same series
2 3 4 5
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