Python Hyperspectral Analysis Tool (PyHAT) Principal Component Analysis (PCA) Plot Example

This figure shows an example PCA plot generated using PyHAT. The input data were laser induced breakdown spectroscopy (LIBS) spectra. PyHAT was used to apply a baseline correction and normalization to the total intensity for each spectrum. The loading vectors for the first two pricipal components are shown at right, and the corresponding scores plot is shown at left. The points in the scores plot are colored based on Fe2O3T content of the original samples, illustrating that principal component 1 has strong positive loadings correponding to iron emission lines in the spectra.

This figure is one of a series of figures used to demonstrate some of the capabilities of the PyHAT software.