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In many projects it is necessary to share the result of programming work with other colleagues – or to work together on these projects. In the MRDAES book, Chapter 2.8.5 describes how to collaborate on MATLAB projects with collaborators with four different levels of MATLAB skills: (1) no software installed and no experience with MATLAB, (2) software installed but only limited MATLAB skills, and (3) software installed and good MATLAB skills. Below you find an update of this chapter, which now also includes using (4) MATLAB Projects to organize and collaborate on large programming projects together with Git, the most popular version control system for programming projects.

Continue reading “Collaborative Coding with Git and MATLAB Projects”

The Principal Component Analysis (PCA) is equivalent to fitting an n-dimensional ellipsoid to the data, where the eigenvectors of the covariance matrix of the data set are the axes of the ellipsoid. The eigenvalues represent the distribution of the variance among each of the eigenvectors. To understand the method, it is helpful to know something about matrix algebra, eigenvectors, and eigenvalues. Here is a n=2 dimensional example to perform a PCA without the use of the NumPy function pca, but with the function of eig for the calculation of eigenvectors and eigenvalues. Continue reading “Principal Component Analysis in 6 Steps – the Python Version”

Soon, the popular book MATLAB Recipes for Earth Sciences (MRES) will be available in a version for Python (PRES). You can then put both books side by side, like a dictionary, MATLAB to Python and back. Continue reading “MATLAB and Python Recipes for Earth Sciences”

Here you find the MATLAB code and data of my paper “TURBO2: A MATLAB simulation to study the effects of bioturbation on paleoceanographic time series” published in the Elsevier journal Computers & Geosciences. Continue reading “MATLAB Code of “TURBO2: A MATLAB simulation to study the effects of bioturbation on paleoceanographic time series” (Trauth, C&G 2013)”

In two earlier posts, I presented templates for a conference poster with dark and white background. Here’s the white template in various formats. Continue reading “Creating Better Scientific Posters, Part 3”

Since I have just finished the PYTHON version of my book MATLAB Recipes for Earth Sciences (Springer 2021), I would like to offer a comparison of the advantages and disadvantages of both programming languages and development environments. Comments, corrections and additions via email are as always welcome! Continue reading “MATLAB vs. PYTHON from a MATLABer’s Perspective”

The popular online course on data analysis in the geosciences will be taught bilingual for the first time, using the two leading programming languages and development environments MATLAB and Python in parallel on 19–23 September 2022. The course is based on the 5th edition of my book MATLAB Recipes for Earth Science (Springer 2021) and on the new book Python Recipes for Earth Sciences (Springer, in press).

Continue reading “55th Online Shortcourse on MATLAB & Python Recipes for Earth Sciences”

The German version of the 5th edition of MATLAB Recipes for Earth Sciences is out today. Thanks to the subject of SpringerSpektrum for the professional support in the realization of the project.

Continue reading “German Translation of MATLAB Recipes for Earth Sciences Published”