Module Information | Study information

MODULE TITLE	Scientific Programming in Python	CREDIT VALUE	15
MODULE CODE	PHY2035	MODULE CONVENER	Unknown

DURATION: TERM	1	2	3
DURATION: WEEKS	11

Number of Students Taking Module (anticipated)	120

DESCRIPTION - summary of the module content

A knowledge of a computing language and how to write programs to solve physics related problems is a valuable transferable skill. It is taught though a series of practical sessions in which the student will initially learn to understand the logic of the source code and are required to modify the code for a number of prepared projects. This module teaches the Python programming language, but the principles involved are applicable to almost every procedural programming language.

AIMS - intentions of the module

This module aims to build on the introduction to programming in Python given in the IT Skills training in Stage 1 (e.g. PHY1027) in order to develop students' ability to write clear, structured, debuggable and maintainable computer programs in Python and to understand such programs written by others.

INTENDED LEARNING OUTCOMES (ILOs) (see assessment section below for how ILOs will be assessed)

A student who has passed this module should be able to:

Module Specific Skills and Knowledge:

1. explain and use standard features of the Python programming language including assignments, statements, iterators and objects;

2. write and modify simple programs in Python;

3. find errors and debug code;

4. write structured code based on short routines with a clear purpose and interfaces that are simple and unambiguous;

5. write self-documenting code using docstrings and comments;

6. select and apply existing tools for scientific programming from modules including NumPy, SciPy, Matplotlib and Astropy, based on the documentation;

Discipline Specific Skills and Knowledge:

7. apply logic to the solution of problems;

8. keep proper records of work;

9. apply the Python programming language to simple physical problems including calculations, modelling and data analysis;

10. produce publication-quality plots;

11. present a portfolio of work;

Personal and Key Transferable / Employment Skills and Knowledge:

12. deal with the practicalities of writing a computer program;

13. think and plan in a logical manner;

14. apply a structured approach to problem solving.

SYLLABUS PLAN - summary of the structure and academic content of the module

I. Introduction to Python 3 and Revision

Running Python and Jupyter notebook
Loading modules and packages
Using Python as a graphical calculator; simple calculations, maths, functions and plotting

II. Core Python.

Objects, assignments and variables, dynamic typing
Numbers, comparisons and logic
Strings and print statements
Lists and tuples
Sets and dictionaries
Control flow: loops and if-statements
File I/O
Functions

III. Program Design and Practice

Python scripts
Self-documenting code with comments, docstrings and markdown cells
Testing and debugging
Handling errors and exceptions

IV. Modules/Packages and Applications

NumPy
Matplotlib
SciPy
Astropy

V. Advanced Python

Creating a Python module
Introduction to classes and Object Oriented Programming

VI. Projects

A number of projects based upon the Stage 2 physics course. The background physics required for each project is provided for the student in the project description.

LEARNING AND TEACHING

LEARNING ACTIVITIES AND TEACHING METHODS (given in hours of study time)

Scheduled Learning & Teaching Activities	33	Guided Independent Study	117	Placement / Study Abroad

DETAILS OF LEARNING ACTIVITIES AND TEACHING METHODS

Category	Hours of study time	Description
Scheduled learning & teaching activities	11 hours	11×1-hour lectures
Scheduled learning & teaching activities	22 hours	11×2-hour supervised computer labs
Guided independent study	56 hours	Directed self-study and project work
Guided independent study	61 hours	Reading to support own learning requirements

ASSESSMENT

FORMATIVE ASSESSMENT - for feedback and development purposes; does not count towards module grade

SUMMATIVE ASSESSMENT (% of credit)

Coursework	70	Written Exams	0	Practical Exams	30

DETAILS OF SUMMATIVE ASSESSMENT

Form of Assessment	% of Credit	Size of Assessment (e.g. duration/length)	ILOs Assessed	Feedback Method
Homework assignment	13%	8 hours (Deadline Monday, Week 4, Term 1)	1-16	Written and verbal
Homework assignment	13%	8 hours (Deadline Monday, Week 6, Term 1)	1-16	Written and verbal
Programming Knowledge and Skills Test	30%	1 hour 30 (Term 1, Week 6)	1-9, 11, 13-16	Written and verbal
Homework assignment	13%	8 hours (Deadline Monday, Week 9, Term 1)	1-16	Written and verbal
Programming Project	31%	32 hours (Deadline Friday, Week 12, Term 1)	1-16	Written and verbal

DETAILS OF RE-ASSESSMENT (where required by referral or deferral)

Original Form of Assessment	Form of Re-assessment	ILOs Re-assessed	Time Scale for Re-assessment
Programming Knowledge and Skills Test	Test (1hr 30min) 30% wt	1-9, 11, 13-16	August/September assessment period
Programming Project and Homework Assignments	Programming Project (32 hours) 70% wt	1-16	August/September assessment period

RE-ASSESSMENT NOTES

RESOURCES

INDICATIVE LEARNING RESOURCES - The following list is offered as an indication of the type & level of
information that you are expected to consult. Further guidance will be provided by the Module Convener

ELE:

http://newton.ex.ac.uk/redirects/ELE/phy2035

Reading list for this module:

Type	Author	Title	Edition	Publisher	Year	ISBN
Set	Hill, C.	Learning Scientific Programming with Python		Cambridge	2020	978-1-108-74591-8

CREDIT VALUE	15	ECTS VALUE	7.5

PRE-REQUISITE MODULES	PHY1025, PHY2021
CO-REQUISITE MODULES

NQF LEVEL (FHEQ)	5	AVAILABLE AS DISTANCE LEARNING	No
ORIGIN DATE	Wednesday 13th March 2024	LAST REVISION DATE	Wednesday 13th March 2024

KEY WORDS SEARCH	Physics; Program; Structures; Function; Codes; Project; Data; Computing; Arrays; Designing.

Scientific Programming in Python - 2024 entry