Select and configure time integration methods for ODE and PDE simulations — choose among explicit Runge-Kutta, BDF, Rosenbrock, and Adams families, set relative and absolute error tolerances, implement adaptive step-size control with P/PI step-size controllers, plan IMEX operator splitting for mixed stiff and non-stiff terms, and estimate splitting errors. Use when picking an integrator for a new simulation, diagnosing step rejections or tolerance failures, setting up operator splitting for pha…
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Skill metadata
Parsed from SKILL.md frontmatter.
Version1.2.2
Allowed toolsRead, Write, Grep, Glob
Declared agentsclaude-code
More metadata
author
HeshamFS
version
1.2.2
security_tier
medium
security_reviewed
1
tested_with
["claude-code"]
last_evaluated
2026-06-24
eval_cases
4
last_reviewed
2026-06-23
standards
["Hairer, Norsett & Wanner, Solving Ordinary Differential Equations I (Nonstiff): RK45 (Dormand-Prince), DOP853, embedded error estimation","Hairer & Wanner, Solving ODEs II (Stiff and DAE): BDF, Radau IIA, Rosenbrock methods","Gustafsson (1991\/1994), control-theoretic PI step-size control","Strang (1968), operator splitting; with Lie-Trotter and Marchuk-Strang variants","Eyre (1998), unconditionally gradient-stable convex splitting for phase-field (Allen-Cahn \/ Cahn-Hilliard)"]
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md13,326 B
docsSUMMARY.md294 B
History
First seen on skills.sh
First recorded snapshot · 2 installs
SKILL.md
Numerical Integration
Goal
Provide a reliable workflow to select integrators, set tolerances, and manage adaptive time stepping for time-dependent simulations.
Requirements
Python 3.10+
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
Decision Guidance
Choosing an Integrator
Is the problem stiff?
├── YES → Is Jacobian available?
│ ├── YES → Use Rosenbrock or BDF
│ └── NO → Use BDF with numerical Jacobian
└── NO → Is high accuracy needed?
├── YES → Use RK45 or DOP853
└── NO → Use RK4 or Adams-Bashforth
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
Script Outputs (JSON Fields)
Script
Key Outputs
scripts/error_norm.py
errornorm, scalemin, scale_max
scripts/adaptivestepcontroller.py
accept, dt_next, factor
scripts/integrator_selector.py
recommended, alternatives, notes
scripts/imexsplitplanner.py
implicitterms, explicitterms, splitting_strategy
scripts/splittingerrorestimator.py
error_estimate, substeps
Workflow
Classify stiffness - Check eigenvalue spread or use stiffness_detector
Choose tolerances - See references/tolerance_guidelines.md
Select integrator - Run scripts/integrator_selector.py
Compute error norms - Use scripts/error_norm.py for step acceptance
Adapt step size - Use scripts/adaptivestepcontroller.py
Plan IMEX/splitting - If mixed stiff/nonstiff, use scripts/imexsplitplanner.py
Validate convergence - Repeat with tighter tolerances
Conversational Workflow Example
User: I'm solving the Allen-Cahn equation with a stiff double-well potential. What integrator should I use?
Agent workflow:
Check integrator options:
``bash python3 scripts/integrator_selector.py --stiff --jacobian-available --accuracy high --json ``
Plan the IMEX splitting (diffusion implicit, reaction explicit):
Recommend: Use IMEX-BDF2 with diffusion term implicit, double-well reaction explicit.
Pre-Integration Checklist
Identify stiffness and dominant time scales
Set rtol/atol consistent with physics and units
Confirm integrator compatibility with stiffness
Use error norm to accept/reject steps
Verify convergence with tighter tolerance run
CLI Examples
# Select integrator for stiff problem with Jacobian
python3 scripts/integrator_selector.py --stiff --jacobian-available --accuracy high --json
# Compute scaled error norm
python3 scripts/error_norm.py --error 0.01,0.02 --solution 1.0,2.0 --rtol 1e-3 --atol 1e-6 --json
# Adaptive step control with PI controller
python3 scripts/adaptive_step_controller.py --dt 1e-2 --error-norm 0.8 --order 4 --controller pi --json
# Plan IMEX splitting
python3 scripts/imex_split_planner.py --stiff-terms diffusion,elastic --nonstiff-terms reaction --coupling strong --json
# Estimate splitting error
python3 scripts/splitting_error_estimator.py --dt 1e-4 --scheme strang --commutator-norm 50 --target-error 1e-6 --json
Error Handling
Error
Cause
Resolution
rtol must be a non-negative finite number / atol must be a non-negative finite number
Invalid tolerances
Use non-negative finite values
error_norm must be finite and non-negative
Negative or non-finite error norm
Check error computation
`scale must be positive; with min_scale=0 ensure atol>0 or rtol*\
y\
>0`
All scale entries collapsed to 0 (e.g. rtol=0, atol=0, default min_scale=0)
Set atol>0, rtol>0, or --min-scale > 0
argument --controller: invalid choice: ... (choose from p, pi)
Invalid controller type
Use p or pi
Provide at least one stiff or non-stiff term
Empty term list
Specify stiff or nonstiff terms
Interpretation Guidance
Error Norm Values
Error Norm
Meaning
Action
< 1.0
Step acceptable
Accept, maybe increase dt
≈ 1.0
At tolerance boundary
Accept with current dt
> 1.0
Step rejected
Reject, reduce dt
Controller Selection
Controller
CLI value
Properties
Best For
P (elementary / integral)
p (default)
Simple, some overshoot
Non-stiff, moderate accuracy
PI (proportional-integral)
pi
Smooth, robust (requires --prev-error)
General use
PID control is described in references/error_control.md for reference only; the adaptivestepcontroller.py CLI implements p and pi controllers.
IMEX Strategy
Coupling
Strategy
Weak
Simple operator splitting
Moderate
Strang splitting
Strong
Fully coupled IMEX-RK
Verification checklist
Recorded the scaled errornorm (and scalemin/scalemax) from scripts/errornorm.py and confirmed scale_min > 0, so no component reduced to atol-only scaling by accident.
Confirmed each accepted step has errornorm <= acceptthreshold (default 1.0) per scripts/adaptivestepcontroller.py; logged any accept: false steps and the resulting dt_next/factor rather than forcing the step through.
For the PI controller, supplied --prev-error and verified controller_used reported pi (not the silent p fallback that occurs when --prev-error is omitted).
Ran scripts/integrator_selector.py with the actual --stiff/--jacobian-available/--accuracy flags matching the problem and recorded recommended plus the notes (e.g. the "expect smaller dt" warning for stiff-without-implicit).
For operator splitting, recorded errorestimate, substeps, and dteffective from scripts/splittingerrorestimator.py and confirmed error_estimate <= target-error after substepping, using the correct --scheme order (lie=1, strang=2).
Ran the convergence validation (Workflow step 7): repeated with tighter rtol/atol and confirmed the solution change is below the target accuracy, rather than trusting a single tolerance run.
Common pitfalls & rationalizations
Tempting shortcut
Why it's wrong / what to do
"I picked an implicit/BDF method, so any dt is fine."
Unconditional stability is not accuracy; large dt still inflates temporal error. Check error_norm against the accept threshold and run the tighter-tolerance convergence check (Workflow step 7).
"error_norm came back < 1, so the step and the whole run are correct."
The norm only certifies the local step under the chosen rtol/atol. A loose tolerance passes every step while the global solution is wrong — tighten tolerances and confirm convergence before trusting results.
"I'll use the PI controller for smoother stepping" but omit --prev-error.
Without --prev-error the script silently falls back to the P controller (controllerused: p). You get no PI benefit. Pass the previous accepted errornorm and verify controller_used: pi.
"Strang vs Lie splitting won't matter much here."
Splitting error scales as commutatornorm * dt^(order+1) with order 1 (lie) vs 2 (strang). For a nonzero commutator the schemes differ by a full power of dt — run splittingerror_estimator.py with the actual --commutator-norm and --target-error instead of guessing.
"The selector recommended IMEX/RK-Chebyshev, so I'll just run explicitly without a Jacobian."
That branch fires only for stiff problems without implicit solves and the script warns "expect smaller dt." Read the notes: provide a Jacobian/Jv product and use BDF/Radau if implicit solves are feasible.
"It ran to the final time without crashing, so the integration is valid."
Completion is not correctness. Verify step acceptance (errornorm <= threshold), splitting error within target-error, and convergence under tighter tolerances; for conservative problems pass --conservative to imexsplit_planner.py and check conserved quantities.
Security
Input Validation
All numeric inputs (dt, rtol, atol, errornorm, stiffnessratio, commutator_norm, etc.) are validated as finite numbers at the function boundary
imexsplitplanner.py validates term names against [a-zA-Z][a-zA-Z0-9 -]* with length and count limits, preventing injection payloads in user-supplied term lists
Comma-separated value lists are capped at 100,000 entries to prevent resource exhaustion
Numeric bounds enforced: dimension capped at 10 billion, order at 20, stiffness_ratio at 1e30
--controller is validated against a fixed allowlist (p, pi)
--scheme is validated against known splitting schemes (lie, strang)
File Access
Scripts read no external files; all inputs are provided via CLI arguments
Scripts write only to stdout (JSON output); no files are created unless the agent explicitly uses the Write tool
Tool Restrictions
Read: Used to inspect script source, references, and user configuration files
Write: Used to save integrator recommendations or splitting plans; writes are scoped to the user's working directory
Grep/Glob: Used to locate relevant files and search references
The skill's allowed-tools excludes Bash to prevent the agent from executing arbitrary commands when processing user-provided inputs
Safety Measures
No eval(), exec(), or dynamic code generation
All subprocess calls use explicit argument lists (no shell=True)
Reduced tool surface (no Bash) limits the agent to read/write operations only
Term names are sanitized before use, preventing shell metacharacter injection
Limitations
No automatic stiffness detection: Use stiffness_detector from numerical-stability
Splitting assumes separability: Terms must be cleanly separable
Jacobian requirement: Some methods need analytical or numerical Jacobian
References
references/method_catalog.md - Integrator options and properties
references/multiphasefieldpatterns.md - Phase-field specific splits
Version History
v1.2.2 (2026-06-24): Added Verification checklist and Common pitfalls & rationalizations sections grounding step acceptance, PI controller usage, integrator selection, and splitting-error checks in the scripts' actual outputs
v1.2.0 (2026-06-23): Fixed PI controller coefficient/sign to standard form, fixed error_norm scale-collapse crash, corrected error-message and controller documentation to match the scripts