Course Outline

Introduction to MATLAB for Geophysics

  • MATLAB environment and workflow
  • Basic scripting and data visualization
  • Loading and working with geophysical datasets

Foundations of Object-Oriented Programming

  • OOP concepts: classes, objects, and encapsulation
  • Benefits of OOP in scientific computing
  • MATLAB syntax for defining classes

Creating and Managing Classes in MATLAB

  • Defining properties and methods
  • Public, private, and protected access
  • Constructors and object instantiation

Inheritance and Class Hierarchies

  • Subclassing and method overriding
  • Abstract classes and interfaces
  • Polymorphism in MATLAB OOP

Applying OOP to Geophysical Data Analysis

  • Designing classes for seismic, gravity, and magnetic data
  • Data preprocessing and filtering methods
  • Visualization and plotting functions within classes

Case Study: Geophysical Modeling Workflow

  • Building a modular OOP framework for modeling
  • Integrating modeling algorithms as class methods
  • Exporting and documenting analysis results

Best Practices and Optimization

  • Improving code readability and maintainability
  • Performance tips for large geophysical datasets
  • Version control and collaborative development

Summary and Next Steps

Requirements

  • Basic understanding of programming concepts
  • Familiarity with fundamental geophysics principles
  • Some exposure to MATLAB or another scientific computing environment

Audience

  • Beginner MATLAB users working in geophysics
  • Geophysics researchers transitioning to object-oriented programming
  • Professionals seeking to organize geophysical data processing workflows
 35 Hours

Delivery Options

Private Group Training

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  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from €11400 online delivery, based on a group of 2 delegates, €3600 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

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