Scipy ode simulation starter
A framework for discovering, compiling, and validating reusable skills for scientific agents.
npx -y skills add ma-compbio-lab/SkillFoundry --skill scipy-ode-simulation-starterAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
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SciPy ODE Simulation Starter
Use this skill to integrate a deterministic predator-prey ordinary differential equation with scipy.integrate.solve_ivp and return a compact trajectory summary.
What it does
- Solves a Lotka-Volterra system with fixed parameters and deterministic initial conditions.
- Reports peak times, peak populations, and the final state from the simulated trajectory.
- Produces a small JSON summary that is stable enough for repository smoke tests.
When to use it
- You need a runnable starter for
ODE / SDE simulation workflows. - You want a minimal verified example of
solve_ivpbefore building larger simulation workflows.
Example
slurm/envs/scientific-python/bin/python skills/scientific-computing-and-numerical-methods/scipy-ode-simulation-starter/scripts/run_scipy_ode_simulation.py \
--out scratch/scipy-ode/lotka_volterra_summary.json
Verification
- Skill-local tests:
python3 -m unittest discover -s skills/scientific-computing-and-numerical-methods/scipy-ode-simulation-starter/tests -p 'test_*.py' - Repository smoke:
python3 -m unittest tests.smoke.test_phase30_empty_domain_seed_skills -v