PX1224: Computational Skills for Problem Solving
School | Cardiff School of Physics & Astronomy |
Department Code | PHYSX |
Module Code | PX1224 |
External Subject Code | 101071 |
Number of Credits | 10 |
Level | L4 |
Language of Delivery | English |
Module Leader | Professor Stephen Fairhurst |
Semester | Spring Semester |
Academic Year | 2013/4 |
Outline Description of Module
To give instruction on and provide practice in the use of to develop the basic data handling (i.e. graphing and data analysis skills) required by physical scientists
To give instruction on and provide practice in the use of to develop the basic numerical computing skills required by physical scientists
To develop proficiency by working through a series of examples which relate to the experimental and taught physics modules.
On completion of the module a student should be able to
Enter or read in data from files (in standard formats); plot and export graphs suitable for inclusion in a report.
Perform statistical analysis of data of the form y = mx +c; best fit and error determinations.
Use and manipulate simple mathematical functions in Python.
Express mathematical integration and differentiation problems such that they may be solved numerically.
Use numerical techniques with Python to solve a number of mathematical and physical problems.
How the module will be delivered
Computing laboratory 11 x 2 hr. Marked exercises and assignments.
Skills that will be practised and developed
Problem solving. Mathematics. Analytical skills. Computational skills.
How the module will be assessed
Continuous assessment 100%.
Assessment Breakdown
Type | % | Title | Duration(hrs) |
---|---|---|---|
Written Assessment | 100 | Computational Skills For Problem Solving | N/A |
Syllabus content
Introduction: To data analysis and numerical techniques via computing with Python.
Graphing skills: Reading in and entering x-y data, data plotting, fitting with straight line (including error determination), and incorporating into reports (Word). Animation.
Random numbers: Generation. Application to the generation of distributions (including plotting histograms).
Using mathematical functions: Use of basic mathematical functions (sine, exp etc) introduction to more advanced functions (i.e. Fast Fourier Transforms FFTs following generation of a F series). Generation and plotting of 3D functions.
Simple numerical integration and differentiation: Numerical techniques and the importance of step size. Practiced (and tested) mainly by application to basic mathematical functions.
Application of Numerical Methods: The approach to solving 2nd order differential equations. Solving physics problems e.g.: modelling the simple pendulum, projectile motion through a viscous medium, analysing real experimental data.
Essential Reading and Resource List
Principles of Physics (Extended Version), Halliday, Resnick and Walker (Wiley)