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Babysitter scipy-optimization-toolkit

SciPy scientific computing skill for numerical optimization, integration, and signal processing in physics

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/physics/skills/scipy-optimization-toolkit" ~/.claude/skills/a5c-ai-babysitter-scipy-optimization-toolkit && rm -rf "$T"
manifest: library/specializations/domains/science/physics/skills/scipy-optimization-toolkit/SKILL.md
tags
#scipy-optimization#numerical-integration#signal-processing#nonlinear-fitting#ode-solvers
source content

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

  1. Optimization: Use appropriate optimizer for the problem type
  2. Fitting: Apply nonlinear least squares for data fitting
  3. Integration: Choose proper quadrature methods
  4. ODEs: Solve differential equations with adaptive solvers
  5. Signal Processing: Apply FFT and filtering techniques

Tools/Libraries

  • SciPy
  • NumPy
  • lmfit