Phelma Formation 2022

Scientific programming - VPMDSPR1

  • Number of hours

    • Lectures 7.0
    • Projects 0
    • Tutorials 7.0
    • Internship 0
    • Laboratory works 16.0
    • Written tests 0

    ECTS

    ECTS 6.0

Goal(s)

Using a scientific programming language (e.g., Python) as a tool for modelling and numerical analysis.

Contact Ronald PHLYPO

Content(s)

This course covers the basics of scientific programming

  • number representation systems and their precision
  • data in Python
    • basic data structures: scalars, strings, lists, dictionaries, sets, tuples
    • matrix representations of numbers: the numpy ndarray (vs matrix), pandas data tables
    • read and write data according to the data type (CSV, JSON, pickle, ...)
  • array operations
    • unitary operators MX0 --> MX1
    • n-ary operators (MX0, ..., MXn-1) --> MXn
  • solving equations
    • linear matrix equations with applications to interpolation and regression
    • differential equations with applications to interpolation and prediction
  • probability and statistics in Python
    • probability laws: distribution families, random variables, realisations
    • statistical tests


Prerequisites

mathematical background on

  • probability and statistics
  • linear algebra
  • differential equations

Test

Semester 7 - The exam is given in english only 

  • CC1: lab reports and report on final problem
  • CC2: short quizzes to test your comprehension of the course basics
  • ORAL: oral exam for second sit (if applicable)
  • DS : written exam for second sit (if applicable)

N1 : first sit
N2 : second sit



Under regular conditions

N1 = 70%CC1 + 30%CC2
N2 = 70%CC1 + 30%ORAL

When students have no longer access to the school

N1 = 70%CC1 + 30%CC2
N2 = 70%CC1 + 30%DS

Additional Information

Semester 7 - This course is given in english only EN

Course list
Curriculum->Master->Semester 7

Bibliography

https://www.scipy.org/

E. Bashier, Practical scientific and numerical computing with MATLAB and Python. Boca Raton: CRC Press, 2020.

H. P. Langtangen, A Primer on Scientific Programming with Python. Springer Berlin Heidelberg, 2016.

P. O. J. Scherer, Computational Physics. Springer International Publishing, 2017.

B. A. Stickler and E. Schachinger, Basic Concepts in Computational Physics. Springer International Publishing, 2016.