eelsmapper 0.1.1

Data-driven analysis pipeline for STEM-EELS spectra

eelsmapper

eelsmapper is a data-driven pipeline for analyzing STEM-EELS spectra to perform high-resolution compositional mapping without relying on reference spectra. It integrates PCA, t-SNE, clustering, mutual information, and vector quantization to uncover subtle chemical differences and discover novel material phases.

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Purpose

STEM-EELS data is high-dimensional and noisy, making it challenging to interpret with traditional methods. eelsmapper offers a robust, modular pipeline for:

• Denoising spectra (PCA)
• Visualizing compositional patterns (t-SNE and/or UMAP)
• Clustering spectra (K-Means)
• Identifying correlated elemental regions (Mutual Information)
• Enhancing signal quality (Vector Quantization)
• Discovering new material phases without needing reference spectra