Together with colleagues Bodo Bookhagen, Simon Schneider and Jens Tronicke, I am convening a session on “Classroom-sized earth science experiments” at the European Geosciences Union General Assembly 2018 in Vienna Austria between 8–13 April 2018.
The new release R2017b of MATLAB has a nice way of visualizing data values at specific geographic locations. Here I use the new geobubble function to display the statistics of the MRES blog. Continue reading “Display the MRES Blog Statistics using the new geobubble Function with MATLAB”
According to the Release Notes for R2017b the Live Editor now checks code for errors and warnings using the message bar and message indicator. However, deactivating the warnings in the editor does not seem to affect the Live Editor. Was the possibility of disabling warnings forgotten by the software developers? In my example the message bar is full of warnings marked in orange because I define graphics object handles most of which are not used.
Today the University of Potsdam published an article (in German) by Matthias Zimmermann about the MATLAB/LEGO MINDSTORMS practical, sponsored by MathWorks Inc. The practical, part of the master’s courses “Geosciences” and “Remote Sensing, geoInformation and Visualization“, as well as of the Summer School on Earth Surface Dynamics, aims to improve student’s skills to build efficient teams to solve typical problems in earth sciences in acquiring, processing and analyzing typical multispectral (visible, infrared, thermal), geophysical (seismic, magnetic) and geometric (2D, 3D) data. Photo: Karla Fritze.
At the moment we are very busy with the calculation of recurrence plots in the working group. One of my doctoral students complained that his MATLAB installation often crashes due to Java problems after the calculation has been running for a while. Of course you can try to solve the Java problems. On the other hand, you can also completely avoid the MATLAB user interface. Here is how.
The 2nd edition of the book MATLAB® and Design Recipes for Earth Sciences (MDRES), together with designer Elisabeth Sillmann, was submitted to Springer International Publishing AG today. Different from the first edition shown on the right hand side, the book’s new title is Collecting, Processing and Presenting Geoscientific Information with the subtitle MATLAB® and Design Recipes for Earth Sciences. The book has been thoroughly reworked and includes a 12th chapter on Creating Multimedia Publications.
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 MATLAB function pca, but with the function of eig for the calculation of eigenvectors and eigenvalues. Continue reading “Principal Component Analysis in 5 Steps”