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DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Microstructure Modeling and Simulation. Generate microstructures using site-saturation condition, and simulate grain growth using Monte Carlo Potts Model.
GrainStat is a comprehensive Python package for analyzing grain microstructures in materials science. It provides robust tools for image processing, grain segmentation, statistical analysis, and report generation that are essential for materials characterization.
MCP server for XAUUSD: live microstructure, OOS-validated strategy intelligence, macro context, and AI analyst aggregation. Cross-platform (Claude, ChatGPT, Cursor, Windsurf).
Realistic market making backtester with tick-by-tick L2/L3 replay, FIFO queue simulation (iceberg detection + cancel inference), latency modeling, maker/taker execution, multi-asset support, realistic fill simulation and detailed adverse selection metrics. Built for strategy research, focusing on real queue dynamics and fill quality.