MATLAB and Python Recipes for Earth Sciences

John Aitchison spent much of his career addressing the unique challenges of statistics for compositional data. His legacy is being carried on by colleagues who do not always succeed in presenting the material in a way that is understandable to geoscientists. Now in the fourth part of a series of blog posts, I am attempting to address the problems of closed data and possible workarounds using a series of simple MATLAB simulations, without frustrating geoscientists with mathematical formulas.

Continue reading “MATLAB Example to Illustrate John Aitchison’s Log-Ratio Transformation, Part 4”

The popular online course on data analysis in the geosciences will be taught bilingual using the two leading programming languages and development environments MATLAB and Python in parallel on 15–19 September 2025. The course is based on my books MATLAB Recipes for Earth Science (Springer 2025) and Python Recipes for Earth Sciences (Springer 2024).

Continue reading “60th Online Shortcourse on MATLAB & Python Recipes for Earth Sciences”

Continue reading “An Artificial Neural Network with Backpropagation in 6 Steps”

After writing a ~500 pages book in two versions for MATLAB and Python, I would like to offer a comparison from the point of view of a MATLAB user. Comments, corrections and additions via email are as always welcome! Continue reading “MATLAB vs. PYTHON from a MATLABer’s Perspective”

Now that both new editions have been published, the MRES and PRES books can be used as a MATLAB-Python and Python-MATLAB dictionary. Continue reading “Using MRES and PRES as a Dictionary Between MATLAB and Python”

This week, the practical on data acquisition with LEGO Mindstorms, spectral and 3D cameras and smartphone sensors is running again. A lot has changed in the use of smartphone sensors in recent years, both on smartphones with MATLAB Mobile and on MATLAB Desktop – here is the update!
Continue reading “Mobile Phone Sensor Data Collection with MATLAB – Update”

A LEGO vehicle with two motors and an ultrasonic sensor that stops 30 cm in front of an obstacle and then reverses was one of the first programming exercises in the data acquisition practical that we developed in 2017. We used the MATLAB Support Package for LEGO MINDSTORMS EV3 Hardware to connect the LEGO vehicle with MATLAB Desktop on a computer to solve for Exercise #2. While this support continues to be offered for Windows, Linux and macOS (Intel), it is not available for macOS (Apple Silicon). Exercise #15 uses a Python solution for programming the LEGO vehicle – but do not expect too much! Continue reading “Controlling Motors and Read Sensors of LEGO MINDSTORMS with Python”