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differentiation-schemes

@HeshamFS/materials-simulation-skills
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Select and apply numerical differentiation schemes for PDE/ODE discretization. Use when choosing finite difference/volume/spectral schemes, building stencils, handling boundaries, estimating truncation error, or analyzing dispersion and dissipation.

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SKILL.md

name differentiation-schemes
description Select and apply numerical differentiation schemes for PDE/ODE discretization. Use when choosing finite difference/volume/spectral schemes, building stencils, handling boundaries, estimating truncation error, or analyzing dispersion and dissipation.
allowed-tools Read, Bash, Write, Grep, Glob

Differentiation Schemes

Goal

Provide a reliable workflow to select a differentiation scheme, generate stencils, and assess accuracy for simulation discretization.

Requirements

  • Python 3.8+
  • NumPy (for stencil computations)
  • No heavy dependencies

Inputs to Gather

Input Description Example
Derivative order First, second, etc. 1 or 2
Target accuracy Order of truncation error 2 or 4
Grid type Uniform, nonuniform uniform
Boundary type Periodic, Dirichlet, Neumann periodic
Smoothness Smooth or discontinuous smooth

Decision Guidance

Scheme Selection Flowchart

Is the field smooth?
├── YES → Is domain periodic?
│   ├── YES → Use central differences or spectral
│   └── NO → Use central interior + one-sided at boundaries
└── NO → Are there shocks/discontinuities?
    ├── YES → Use upwind, TVD, or WENO
    └── NO → Use central with limiters

Quick Reference

Situation Recommended Scheme
Smooth, periodic Central, spectral
Smooth, bounded Central + one-sided BCs
Advection-dominated Upwind
Shocks/fronts TVD, WENO
High accuracy needed Compact (Padé), spectral

Script Outputs (JSON Fields)

Script Key Outputs
scripts/stencil_generator.py offsets, coefficients, order, accuracy
scripts/scheme_selector.py recommended, alternatives, notes
scripts/truncation_error.py error_scale, order, notes

Workflow

  1. Identify requirements - derivative order, accuracy, smoothness
  2. Select scheme - Run scripts/scheme_selector.py
  3. Generate stencils - Run scripts/stencil_generator.py
  4. Estimate error - Run scripts/truncation_error.py
  5. Validate - Test with manufactured solutions or grid refinement

Conversational Workflow Example

User: I need to discretize a second derivative for a diffusion equation on a uniform grid. I want 4th-order accuracy.

Agent workflow:

  1. Select appropriate scheme:
    python3 scripts/scheme_selector.py --smooth --periodic --order 2 --accuracy 4 --json
  2. Generate the stencil:
    python3 scripts/stencil_generator.py --order 2 --accuracy 4 --scheme central --json
  3. Result: 5-point stencil with coefficients [-1/12, 4/3, -5/2, 4/3, -1/12] / dx².

Pre-Discretization Checklist

  • Confirm derivative order and target accuracy
  • Choose scheme appropriate to smoothness and boundaries
  • Generate and inspect stencils at boundaries
  • Estimate truncation error vs physics scales
  • Verify with grid refinement study

CLI Examples

# Select scheme for smooth periodic problem
python3 scripts/scheme_selector.py --smooth --periodic --order 1 --accuracy 4 --json

# Generate central difference stencil for first derivative
python3 scripts/stencil_generator.py --order 1 --accuracy 2 --scheme central --json

# Generate 4th-order second derivative stencil
python3 scripts/stencil_generator.py --order 2 --accuracy 4 --scheme central --json

# Estimate truncation error
python3 scripts/truncation_error.py --dx 0.01 --order 2 --accuracy 2 --scale 1.0 --json

Error Handling

Error Cause Resolution
order must be positive Invalid derivative order Use 1, 2, 3, ...
accuracy must be even for central Odd accuracy requested Use 2, 4, 6, ...
Unknown scheme Invalid scheme type Use central, upwind, compact

Interpretation Guidance

Stencil Properties

Property Meaning
Symmetric offsets Central scheme (no directional bias)
Asymmetric offsets One-sided or upwind scheme
More points Higher accuracy but wider stencil

Truncation Error Scaling

Accuracy Order Error Scales As Refinement Factor
2nd order O(dx²) 2× refinement → 4× error reduction
4th order O(dx⁴) 2× refinement → 16× error reduction
6th order O(dx⁶) 2× refinement → 64× error reduction

Common Stencils

Derivative Accuracy Points Coefficients (× 1/dx or 1/dx²)
1st 2 3 [-1/2, 0, 1/2]
1st 4 5 [1/12, -2/3, 0, 2/3, -1/12]
2nd 2 3 [1, -2, 1]
2nd 4 5 [-1/12, 4/3, -5/2, 4/3, -1/12]

Limitations

  • Boundary handling: Stencil generator provides interior stencils; boundaries need special treatment
  • Nonuniform grids: Standard stencils assume uniform spacing
  • Spectral: Not covered by stencil generator

References

  • references/stencil_catalog.md - Common stencils
  • references/boundary_handling.md - One-sided schemes
  • references/scheme_selection.md - FD/FV/spectral comparison
  • references/error_guidance.md - Truncation error scaling

Version History

  • v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, examples
  • v1.0.0: Initial release with 3 differentiation scripts