๐ฌ GRIN Fixture Auto-Calibration Framework¶
xPRIMEray / GD_xPRIMEray โ Engineering Study Architecture¶
๐ง Purpose¶
Establish a repeatable, measurable, and automatable framework for:
- Characterizing
GrinFilmCamerabehavior - Defining valid parameter operating regions
- Enabling Codex-assisted execution
- Progressing toward auto-calibration of GRIN ray paths
This document defines the A / B / C execution model and integrates it into the broader xPRIMEray architecture.
๐งฑ Core Philosophy¶
We are not just rendering.
We are building a:
Controlled optical laboratory inside the renderer
Where: - Scenes = fixtures - Rays = measurable signals - Parameters = controllable inputs - Logs = instrumentation - Codex = execution + analysis agent
๐บ A / B / C Framework¶
A โ Safe Execution Harness (Operations Layer)¶
Goal¶
Enable deterministic, bounded, reproducible test execution.
Requirements¶
- Fixed entrypoint script(s)
- Controlled scenes only
- Non-destructive commands
- Predictable output directory
- Codex-friendly interface
Example Entry Script¶
/scripts/run_fixture_baseline.sh
Responsibilities¶
- Load fixture scene
- Apply parameter set
- Run renderer in bounded mode
- Emit logs to structured location
B โ Measurement & Logging Layer (Signal Layer)¶
Goal¶
Convert ray behavior into quantifiable engineering metrics
Required Metrics (Initial Set)¶
- Hit Success Rate
- Miss / Divergence Rate
- Bend Angle Distribution
- Radial Deviation
- Final Intercept Error
- Path Smoothness (oscillation detection)
- Symmetry Error (if applicable)
Output Format¶
/output/fixture_runs/{timestamp}/
โโโ params.json
โโโ ray_log.txt
โโโ metrics.json
โโโ summary.txt
Key Principle¶
If it cannot be measured, it cannot be calibrated.
C โ Codex Execution Workflow (Integration Layer)¶
Goal¶
Enable Codex to act as a controlled engineering operator
Standard Interaction Pattern¶
- Show command
- Confirm non-destructive
- Execute
- Summarize results
Example Prompt Pattern¶
Run the GRIN fixture baseline.
Show command first, then execute, then summarize metrics.
Responsibilities¶
- Execute harness scripts
- Parse output artifacts
- Compare runs
- Suggest parameter adjustments
๐งช Fixture-Based Characterization¶
Definition¶
A fixture is a controlled scene designed to test specific GRIN behaviors.
Fixture Components¶
- Known emitter position
- Known target surface or region
- Defined GRIN field
- Expected ray behavior
Example Fixture Types¶
- Radial focusing lens
- Symmetric field test
- Wormhole throat proxy
- Flat-to-curved transition field
๐ Phase Plan¶
Phase 1 โ Baseline Harness (A)¶
Deliverables¶
- One fixture scene
- One execution script
- Basic logging
Success Criteria¶
- Codex can run fixture without errors
- Output artifacts generated consistently
Phase 2 โ Metric Instrumentation (B-lite)¶
Deliverables¶
- Core metric extraction
- Structured
metrics.json
Success Criteria¶
- Runs produce comparable numeric outputs
- Basic pass/fail thresholds definable
Phase 3 โ Comparative Analysis (B-full)¶
Deliverables¶
- Run-to-run comparison tooling
- Delta reporting
Success Criteria¶
- Detect parameter sensitivity
- Identify stable vs unstable regions
Phase 4 โ Codex Workflow Integration (C)¶
Deliverables¶
- Codex-compatible script interface
- Standardized prompt templates
Success Criteria¶
- Codex can execute + summarize runs reliably
Phase 5 โ Parameter Sweep Engine¶
Deliverables¶
- Controlled parameter sweeps
- Multi-run aggregation
Success Criteria¶
- Parameter space begins forming stability maps
Phase 6 โ Calibration Engine¶
Deliverables¶
- Optimization loop
- Objective function (error minimization)
Success Criteria¶
- Identify best-fit parameter sets for fixture
Phase 7 โ Auto-Calibration¶
Deliverables¶
- Fully automated loop:
- run โ evaluate โ adjust โ repeat
Success Criteria¶
- System converges to valid GRIN configurations autonomously
๐ง Architectural Integration¶
This framework connects to:
RayBeamRendererโ ray path generationGrinFilmCameraโ parameter control surfaceFieldSource3Dโ GRIN field definition- Future:
ResearchModeConfig
๐ฎ Long-Term Vision¶
A system where:
- Any fixture can be loaded
- Codex executes a test suite
- Metrics are generated automatically
- Optimal parameters are proposed
Resulting in:
A self-characterizing optical simulation engine
โก Immediate Next Step¶
Implement:
- First fixture scene
- Single execution script
- Minimal metrics output
Then validate with Codex execution.
๐งฌ Tagline¶
We are not tuning parameters manually.
We are teaching the system how to understand itself.
๐ End of Document