Course Outline
Getting Started with MATLAB in Geophysics
- Navigating the MATLAB environment and typical workflows
- Essential scripting techniques and data visualization
- Importing and managing geophysical datasets
Core Concepts of Object-Oriented Programming
- Key OOP elements: classes, objects, and encapsulation
- The advantages of OOP in scientific computing contexts
- MATLAB syntax for class definition
Developing and Managing Classes in MATLAB
- Specifying properties and methods
- Understanding public, private, and protected access levels
- Implementing constructors and object creation
Inheritance and Class Structures
- Techniques for subclassing and overriding methods
- Using abstract classes and interfaces
- Applying polymorphism in MATLAB OOP
Implementing OOP in Geophysical Data Analysis
- Designing classes to handle seismic, gravity, and magnetic data
- Methods for data preprocessing and filtering
- Integrating visualization and plotting functions within classes
Case Study: Geophysical Modeling Workflow
- Constructing a modular OOP framework for modeling tasks
- Incorporating modeling algorithms as class methods
- Exporting and documenting analysis outcomes
Best Practices and Performance Optimization
- Strategies for enhancing code readability and maintainability
- Tips for optimizing performance with large geophysical datasets
- Managing version control and collaborative development
Conclusion and Future Directions
Requirements
- A foundational understanding of general programming concepts
- Acquaintance with basic principles of geophysics
- Prior exposure to MATLAB or other scientific computing platforms
Target Audience
- Beginners in MATLAB operating within the geophysics sector
- Geophysics researchers aiming to adopt object-oriented programming paradigms
- Professionals looking to streamline and organize geophysical data processing workflows
Testimonials (3)
Concrete, hands-on exercises that were relevant to our core business. Having a trainer with a scientific background was a real asset because we could delve into deeper discussions, not just about programming but also about science and how to combine the two. The practical sessions in Jupyter Notebook format were interesting.
Victor - Vermon
Course - Python for Matlab Users
Machine Translated
The many examples and the building of the code from start to finish.
Toon - Draka Comteq Fibre B.V.
Course - Introduction to Image Processing using Matlab
The practical exercises and the trainer's availability to answer questions.
Sebastien Botte - SDECCI
Course - MATLAB Programming
Machine Translated
