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 | 2014/5 |
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)
Background Reading and Resource List
Not applicable.