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numerical-integration

Maintainer FreedomIntelligence · Last updated April 1, 2026

Select and configure time integration methods for ODE/PDE simulations. Use when choosing explicit/implicit schemes, setting error tolerances, adapting time steps, diagnosing integration accuracy, planning IMEX splitting, or handling stiff/non-stiff coupled systems.

OpenClawNanoClawAnalysisWritingnumerical-integration📊 data science & toolscomputational simulation & ontologyselect

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/numerical-integration

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

Provide a reliable workflow to select integrators, set tolerances, and manage adaptive time stepping for time-dependent simulations.
python3 scripts/integrator_selector.py --stiff --jacobian-available --accuracy high --json.

Source Doc

Excerpt From SKILL.md

Requirements

Python 3.8+
NumPy (for some scripts)
No heavy dependencies for core functionality

Inputs to Gather

Input	Description	Example
Problem type	ODE/PDE, stiff/non-stiff	`stiff PDE`
Jacobian available	Can compute ∂f/∂u?	`yes`
Target accuracy	Desired error level	`1e-6`
Constraints	Memory, implicit allowed?	`implicit OK`
Time scale	Characteristic time	`1e-3 s`

Stiff vs Non-Stiff Detection

Symptom	Likely Stiff	Action
dt shrinks to tiny values	Yes	Switch to implicit
Eigenvalues span many decades	Yes	Use BDF/Radau
Smooth solution, reasonable dt	No	Stay explicit

Use cases

Use when choosing explicit/implicit schemes, setting error tolerances, adapting time steps, diagnosing integration accuracy, planning IMEX splitting, or handling stiff/non-stiff coupled systems.

Not for

Do not rely on this catalog entry alone for installation or maintenance details.

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