Python for Scientific Computations and Control
Code  Completion  Credits  Range  Language 

E375004  KZ  4  2P+2C 
 Lecturer:
 Matouš Cejnek, Cyril Oswald (guarantor)
 Tutor:
 Matouš Cejnek, Cyril Oswald (guarantor), Michal Kuchař, Adam Peichl
 Supervisor:
 Department of Instrumentation and Control Engineering
 Synopsis:

Scientific computations and processing of online measured data in programming environment Python, communication with connected devices, saving and visualization of online measured data into PC using Python in real time, libraries, programming the common tasks of numerical mathematics in Python, programming graphic user interfaces, visualization, demonstration of solved problems. Classification upon the individually solved class projects. The analogies to Matlab will be discussed during the course.
 Requirements:
 Syllabus of lectures:

1.Programming environment Python and its potentials
2.Programming language Python for scientific computations and data processing (NumPy, SciPy)
3.Working with vectors and matrices  matrix operations, solving sets of linear equations in Python
4.Eigenvalues and eigenvectors in Python, data compression by PCA in Python
5.Data visualization (MatplotLib)
6.A simple ODE solver for simulation of a set of differential equations and their sets; computing of a discrete time (difference) equation in Python
7.Graphic User Interface (GUI) designs in Python
8.Recording online measured data into PC and visualization in Python
9.Vizualization and signal processing in Python (statistical markers, correlation analysis, noise analysis, power spectral density)
10.Fundamental algorithms of static function approximation (gradient descent, LevenbergMarquardt algorithm) and their implementation in Python
11.Examples of the gradient descent method for approximation of a dynamic system in Python
12.Example of tuning of controller parameters for a (real) laboratory system
13.Demonstration  options for design of artificial neural network and fuzzy system in Python
14.Further potentials of Python, summary
 Syllabus of tutorials:
 Study Objective:
 Study materials:
 Note:
 Timetable for winter semester 2019/2020:

06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Fri Thu Fri  Timetable for summer semester 2019/2020:
 Timetable is not available yet
 The course is a part of the following study plans: