SolvScout / SolvTune: Examples
Run journeys 01→06 in order. Each page below is a full walkthrough: what the scenario teaches, which APIs matter, the important code pattern, act-by-act narration, and commands to run locally.
Examples source: Journey scripts ship in the product
python/examples/bundle (resonix_prod_solvscout_solvtune). They are not inside thesolvscoutwheel — download the examples package from your account or use the release materials tree. Release note: SolvScout / SolvTune is production (GA) and free for life after registration. Download the release wheel from your Resonix account, activate a machine-locked seat, then run the examples — see Install and Licensing.
What the journeys teach
You have an ODE model and need to know how stiff it is and which integrator to try first. SolvScout probes your RHS (or a recorded trajectory) and returns a ProblemProfile. SolvTune — same package — ranks solver arms with confidence labels using Resonix empirical evidence inside the native library.
Install the release wheel from your Resonix account. SolvScout / SolvTune is free for life after registration; you still activate a machine-locked seat. It does not run solvers locally — use recommend / compare for shortlists, then wire SolvSRK or SciPy in your app.
Journey index
| # | Journey | What you learn |
|---|---|---|
| 01 | First contact | Verify install and license, then make your first classify() call on a trivial decay ODE. You learn that every SolvScout … |
| 02 | Classify an RHS | How classify() turns an RHS callback into a ProblemProfile + FeatureReport, and why you classify once and reuse the prof… |
| 03 | Recommend a solver | Rank solver arms for a fixed ProblemProfile under different objectives (balanced, precision, survival, efficiency) and r… |
| 04 | Compare arms | Use compare() to get a four-objective corpus lookup table without running solvers locally. Understand corpus_match and s… |
| 05 | Product profile token | Mint an opaque rx-... profile token for solvsrk.run_profile() — the production hand-off from SolvTune analysis to SolvSR… |
| 06 | Limits and non-goals | What SolvScout deliberately does not do, where SolvSRK fits, and how to interpret low confidence and dead zones. |
Start with Journey 01 if this is your first install.
Set SOLVSCOUT_QUIET=1 only when you want silent CLI runs (no narration).
Example bundle
Every journey is a domain scenario with narrated acts — run the guided tour first to see what each number means, then copy the production one-liner into your pipeline.
| Resource | Purpose |
|---|---|
PROGRESSION.md | Core runbook — journeys 01→06 with dual commands |
SKU_PROGRESSION.md | Vertical SKU runbook — Grid, Pricing, Control, Climate, Thermal, Specialty |
COVERAGE.md | Capability matrix — which APIs each journey exercises |
APPLICATIONS.md | Where the product applies in real programs |
run_examples.py | Interactive menu for core journeys |
run_sku_examples.py | Interactive menu for vertical SKU walkthroughs |
Guided journeys
| # | Script | Scenario |
|---|---|---|
| 01 | 01_first_contact.py | Version, license, simplest successful call |
| 02 | 02_classify_rhs.py | From dynamics to a ProblemProfile + FeatureReport |
| 03 | 03_recommend.py | One profile, several objectives, ranked arms |
| 04 | 04_compare_arms.py | A corpus-backed work-precision table (no local solve) |
| 05 | 05_product_profile.py | recommend_product() for portable SolvSRK configs |
| 06 | 06_limits.py | What SolvScout / SolvTune is NOT |
Run from the python/ directory after install and license activation.
Set SOLVSCOUT_QUIET=1 only when you want silent CLI runs (no narration).