Scientific Computing with Python
MCNAcourses ▸ NUMA01/ ÄMAD01 – autumn 2018

Getting Started

It is preferable that you get python with it's scientific libraries installed on your home computer. You will find some help for the installation on our python page. You will also find there some material and links on python for scientific computing.

Training

The training exercises are directly after the lectures and serve to experiment with the material taught so far. The training exercises are supervised. You will use preferably your own Laptops (Linux, Windows, Mac OS). Alternatively you can work with the department's computers (Linux/Windows).

DateTraining
2018-11-05Exercise01.pdf - lists, loops, simple plots
2018-11-08Exercise02.pdf - lists, loops, conditionals
2018-11-11Exercise03.pdf - lists, sets, functions
2018-11-15Exercise04.pdf - functions, zeros, complex
2018-11-18Exercise05.pdf - functions, zeros, integrals
2018-11-26Exercise06.pdf - arrays as vectors
2018-11-29Exercise07.pdf - more on arrays
2018-12-03Exercise09.pdf - Classes training
2018-12-06Exercise10.pdf - More on classes
2018-12-10Exercise11.pdf

Homework

Mandatory homeworks are done in groups of maximum two people and presented for evaluation and grading during an exercise session.

Upload your homework file by using this link.

  1. Homework2.pdf
  2. Homework1.pdf

Final Project

All teams will be constructed during the lecture on Thursday, Dec 13. Be sure to attend that lecture!

  1. ProjectTeachers.pdf

PhD students and external students may define own projects from their research/work after consultation with one of the teachers.

Additional Files and other material

DateTopicpdf-file
Dec. 3, 2018

HaarWavelet: Kvinna.jpg

Kvinna.jpg
Dec. 10, 2018

Data for Training Exercise 11

kwh.dat