Supplement to "A free, open-source method for automated mapping of quantitative mineralogy from energy-dispersive X-ray spectroscopy scans of rock thin sections" submitted to Geoscientific Instrumentation, Methods, and Data Systems

This is a supplement package for the journal article "A free, open-source method for automated mapping of quantitative mineralogy from energy-dispersive spectroscopy scans of rock thin sections" submitted to Geoscientific Instrumentation, Methods, and Data Systems. This supplement package includes three example datasets with each containing six smooted elemenal intensity rasters (Ca, Na, Mg, K, Fe, and Ti) derived from energy-dispersive spectroscopy of rock thin sections, training polygons, and sample boundary polygons. The package also includes a step-by-step guide for our method detailed in the paper. Also, the package contains Python code, a README, and an environment.yml to run a similar random forest image classification using the package scikit-learn for comparison.