scipy-optimization-toolkit
SciPy scientific computing skill for numerical optimization, integration, and signal processing in physics
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技能内容
SciPy Optimization Toolkit
Purpose
Provides expert guidance on SciPy for scientific computing in physics, including optimization, integration, and signal processing.
Capabilities
- Nonlinear least squares fitting
- Global optimization methods
- Numerical integration (quadrature)
- ODE/PDE solvers
- Signal processing (FFT, filtering)
- Sparse matrix operations
Usage Guidelines
- Optimization: Use appropriate optimizer for the problem type
- Fitting: Apply nonlinear least squares for data fitting
- Integration: Choose proper quadrature methods
- ODEs: Solve differential equations with adaptive solvers
- Signal Processing: Apply FFT and filtering techniques
Tools/Libraries
- SciPy
- NumPy
- lmfit
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原文件路径
library/specializations/domains/science/physics/skills/scipy-optimization-toolkit/SKILL.md