TSS versus f1-measure
The above movie shows how accuracy, TSS, and f1-measure change under the assumption that a classifier has no false positives until it has classified all of a class correctly. The vertical grey line shows the actual percentage of the features having a given class versus the horizontal axis what percentage of the class is identified by the model. For example, if the true class percentage is 0.1 as shown below we see that an aggressive classifier, one that prefers creating false positives, is punished much less by accuracy and TSS than by the f1-measure.
Generate Thematic Maps from Heliophysics Event Knowledgebase
The below script will allow you to generate thematic maps from the valuable Heliophysics Event Knowledgebase (HEK). I have written it to take a SUVI thematic map as input and output only Spatial Possibilistic Clustering Algorithm (SPoCA) coronal hole and bright region patches in HEK but would be willing to help assist others to modify the script as needed. Expert labeled map SPoCA map from HEK The script can be found below and bundled with smachy, my solar image segmentation toolkit.