fluidsim
Framework for high-performance computational fluid dynamics (CFD) simulations, supporting Navier-Stokes, shallow water, and stratified flows using pseudospectral methods and MPI parallelization.
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Framework for high-performance computational fluid dynamics (CFD) simulations, supporting Navier-Stokes, shallow water, and stratified flows using pseudospectral methods and MPI parallelization.
Structured, template-driven workflow for end-to-end feature development including coding, automated testing, verification, and session-based improvement.
Physical hardware synthesis bridge for PAI. Generates blueprints, 3D printing code, SVG paths for laser cutting, and G-Code for CNC machining to bring agentic designs into the physical world.
BLS periodogram tool for detecting transiting exoplanets and eclipsing binaries in photometric light curves. An astropy-based implementation for period, duration, and depth analysis.
Best practices and code patterns for ManimGL (3Blue1Brown's OpenGL animation engine). Provides templates, rules for 3D/interactive scenes, camera control, and LaTeX math visualization for technical creators.
Generates data cleaning pipelines for pandas/polars/PySpark, handling missing values, duplicates, outliers, type conversions, and validation.
Your personal AI coding tutor that creates customized tutorials based on your actual codebase, tracks your learning progress, and uses spaced repetition to ensure mastery.
Analyze periodic signals in unevenly sampled astronomical time series data using the Lomb-Scargle periodogram method with the lightkurve library.
Pragmatic AI-assisted coding standards focused on clean code, simplicity, and maintainability. Enforces best practices like SRP, DRY, and KISS to prevent over-engineering.
Generate publication-quality figures, charts, and LaTeX tables from experiment data for academic papers.
Linear issue management and synchronization for LobeHub, featuring automated PR referencing, sub-issue tree decomposition, and status tracking.
Nonlinear optimization toolkit using CasADi and IPOPT. Ideal for building complex NLP models, defining symbolic variables, constraints, and solvers, with specialized support for power systems optimization patterns.