Computer Programming

Prerequisite Knowledge

Numerical analysis, courses on engineering applications, programming principles.

Course Units

#	Title	Description	Hours
1	Introduction to Python	Introduction to the necessary tools, show case of tools' installation, introduction to Python, variables, expressions, scalar types, conditional execution.	1Χ3=3
2	Loops, functions, and array and matrix arithmetic	Loops, generators, flow control commands. Array and matrix arithmetic. Function definitions and calls. Input and output arguments. Default arguments. Variable number of arguments. Applications.	1Χ3=3
3	Complex data types & object oriented programming	Pyzo integrated environment. Variables, tuples, lists, sets, dictionaries. Examples. Classes and objects. Python built-in objects. Methods and members. Inheritance. Polymorphism. Examples.	1Χ3=3
4	Runtime error manipulation and exceptions	Error propagation in nested functions. Error control with exceptions. Exception types. Raising Exceptions. Debugging with Pyzo. Examples.	1Χ3=3
5	Creation and manipulation of numerical data	Matrix computations and numpy. Scientific computation with scipy. Complex graphs with matplotlib. Compatibility with Matlab. Examples.	1Χ3=3
6	Graphical user interface (GUI)	Tkinter graphical user interface. Master window. Widgets. Display and input of text. Fonts. Geometry manager - grid. Menu. Displaying error messages. GUI and object oriented programming. Examples.	1Χ3=3
7	Graphical user interface (GUI) 2	GUI and logic separation. Read and write files with GUI. Drawing of vector graphics, lines, circles etc. Automatic geometry resizing. Multi-line text. Scrollbars. Widget containers. New classes of widgets. Multiple windows.	1Χ3=3
8	Introduction to parallel programming	Serial and parallelizable computations. Parallel system architecture. MPI parallel system. Execution of same code instances in multiple cores. Execution differentiation with Rank. Instance communication with send/recv. Broadcast and Reduce. Examples.	1Χ3=3
9	Generators and paths	Generator expressions. Generators. Nested generators. Built-in generators and generator expressions. File paths. Directory paths. Unified use in Windows, Linux, MacOS. Path methods. Nested paths. Examples.	1Χ3=3
10	Introduction to Internet programming	Internet, WWW, HTTP, URL. Clients and servers. Links. Brief description of HTML. Creation of server with Python bottle. Assigning web pages to functions. Grouping of web pages. Printing HTML from functions. Examples.	1Χ3=3
11	Introduction to Fortran	Interpreters and compilers. Advantages and disadvantages. Fortran variables. User defined and platform independent precision. Flow control commands. Matrices and multidimensional arrays. Matrix operations and matrix functions. Dynamic size matrices. Numerical libraries. Compiled binaries. Examples.	1Χ3=3
12	Object oriented programming in Fortran	Modules. Common variables. Public and private functions. Function overloading. New data types. Class definition. Inheritance and polymorphism. Examples.	1Χ3=3
13	Fortran parallel programming and C interoperability	Multiple instances of single program. Integrated parallel processing with Fortran statements. Communication with co-arrays. Instances synchronization with SYNC and NOTIFY, QUERY. Avoiding side effects with critical regions. Examples. Interoperability with C. Compatible variable types. Calling C functions from Fortran. Calling Fortran functions from C. Interfaces. Calling C functions from Python, calling Fortran functions from Python.	1Χ3=3

Learning Objectives

Upon successful completion of the course, students will be able to:

1. possess deep and pluralistic knowledge on computer programming (interpreted and compiled languages),
2. realize the value of computers to civil engineering,
3. understand how computers work, and the confines and limitations of programs and PCs in general,
4. structure extensive and integrated general-purpose computer programs, and
5. compute through computer programming any civil engineering problem.

Teaching Methods

Teaching methods	Class lectures and workshops.
Teaching media	Theory - Applications and Exercises, teaching using blackboard and slides to one group of students.
Laboratories	Yes. This is a laboratory course. The entire course takes place in a computer lab where each student develops programs and solves engineering problems in a Python and Fortran environment.
Computer and software use	Yes (Python and Fortran computational packages)
Problems - Applications	Yes

Student Assessment

• Final written exam: 80%
• Assignments (projects, reports): 20%

Textbooks - Bibliography

1. Introduction to programming with Python (in Greek), Authors: Manis G., ISBN: 978-960-603-415-2, Type: electronic book - pdf, Publisher: Hellenic Academic Books, www.kallipos.gr, 2015.
2. Introduction to object-oriented programming with Python (in Greek), Authors: Κ. Magkoutis K., Nikolaou X., ISBN: 978-960-603-101-4, Type: electronic book - pdf, Publisher: Hellenic Academic Books, www.kallipos.gr, 2015.
3. A Whirlwind Tour of Python, Authors: Jake VanderPlas, ISBN: 978-1-491-96465-1, Τύπος: electronic book - pdf, Publisher: O' Reilly Media Inc., 2016.
4. Scipy Lecture Notes, Authors: Gael Varoquax et al, Type: electronic book - pdf, Publisher: Gael Varoquax, www.scipy-lectures.org, 2015.
5. Python for Computational Science and Engineering, Authors: Hans Fangohr, Type: electronic book - pdf, Publisher: Hans Fangohr, http://www.southampton.ac.uk/~fangohr/teaching/python/book.html, 2016.
6. Python Scripting for Computational Science, Third Edition, Authors: Hans Petter Langtangen, ISBN: 978-3-540-73915-9, Type: electronic book - pdf, Publisher: Springer, 2007.
7. Python Cookbook, Authors: Alex Martelli et al, Second edition, ISBN: 0-596-00797-3, Type: book, Publisher: O' Reilly, 2005.
8. Lecture notes from the site of the course.

Lecture Time - Place:

• Thursday, 09:45 – 12:30,
  Rooms:
  • Ζωγράφου, Εργαστήριο Κέντρου Η/Υ ΔΕΠΥ Α & Β (ισογ., 1ος όροφος)