# `gps_denied.testing` — E2E Test Harness

Test-only subpackage. Not imported by product code. Runs the full `FlightProcessor` pipeline as a black box on public UAV datasets and compares estimated trajectories against ground truth.

## When to use this

- Adding a new public dataset → implement a `DatasetAdapter` subclass here.
- Debugging the pipeline on real flight-like data → run an e2e test locally with a real dataset in `./datasets/`.
- Guarding a refactor (VO → cuVSLAM, `src/gps_denied/` → `src/`, etc.) → run `pytest tests/e2e/` before and after, compare numbers.

Do **not** put production code here and do not import `gps_denied.testing.*` from `gps_denied.core.*` or `gps_denied.api.*`. The import direction is one-way: tests may see the product, the product must not see tests.

## Package layout

```
src/gps_denied/testing/
  coord.py                   ECEF→WGS84 (Heikkinen closed-form), Euler→quaternion (ZYX aerospace)
  metrics.py                 trajectory_rmse, absolute_trajectory_error, relative_pose_error
  harness.py                 E2EHarness + HarnessResult
  download.py                DATASET_REGISTRY + SHA256-verified download_dataset()
  datasets/
    base.py                  DatasetAdapter ABC, DatasetCapabilities, DatasetFrame/IMU/Pose
    synthetic.py             SyntheticAdapter (harness self-test)
    euroc.py                 EuRoCAdapter (ETHZ ASL MAV format)
    vpair.py                 VPAIRAdapter (AerVisLoc sample — ECEF + Euler)
    mars_lvig.py             MARSLVIGAdapter (pre-extracted ROS bag layout)
```

Tests live at `tests/e2e/`. Real datasets are expected at repo root in `./datasets/<name>/` (gitignored).

## DatasetAdapter contract

Every adapter is a read-only iterator over one dataset sequence. It has a `name`, declared `capabilities`, and three streams: frames, IMU samples, ground-truth poses. Frames carry a timestamp and an image path; IMU carries body-frame accel+gyro; poses are WGS84 lat/lon/alt plus a unit quaternion.

```python
class DatasetAdapter(ABC):
    @property
    def name(self) -> str: ...                      # e.g. "euroc:MH_01"

    @property
    def capabilities(self) -> DatasetCapabilities: ...

    def iter_frames(self) -> Iterator[DatasetFrame]: ...
    def iter_imu(self) -> Iterator[DatasetIMU]: ...
    def iter_ground_truth(self) -> Iterator[DatasetPose]: ...
```

If the dataset is not present on disk (or is incomplete), the adapter's `__init__` raises `DatasetNotAvailableError` with an actionable message. Test fixtures catch that and `pytest.skip` — they never fail.

### Capability flags

`DatasetCapabilities` tells tests what to expect. Tests use these flags to skip paths the adapter can't exercise:

| Flag | What it means | Example false case |
|---|---|---|
| `has_raw_imu` | `iter_imu()` yields raw accel+gyro at ≥100 Hz | VPAIR sample (ships 6-DoF poses only) |
| `has_rtk_gt` | Ground-truth positions are RTK-grade (<0.1 m) | EuRoC (uses Vicon, millimetre-grade but not RTK) |
| `has_loop_closures` | Trajectory revisits locations (affects GPR expected hit rate) | Most open-field fixed-wing flights |
| `platform_class` | `fixed_wing` / `rotary` / `indoor` / `synthetic` — dynamics differ sharply | — |

When a test needs `has_raw_imu=True` but the adapter has it False, the integration test should `pytest.skip` at the top, not assert.

## Writing a new adapter — recipe

1. **Decide capabilities first.** Read the dataset's paper/README. Does it ship raw IMU? RTK? What's the platform class?
2. **Add a failing adapter unit test** in `tests/e2e/test_<name>_adapter.py` using a `tmp_path`-based fabricated fixture. Mirror the real file layout (directory names, CSV headers, value ranges).
3. **Implement the adapter.** Reuse `coord.ecef_to_wgs84` and `coord.euler_to_quaternion` if the dataset ships those. Synthesize timestamps if the dataset doesn't have them (e.g. VPAIR — 5 Hz = 200 000 000 ns period).
4. **Add a session-scoped fixture** in `tests/e2e/conftest.py` that looks for the real dataset under `./datasets/<name>/<subdir>/` and skips with an actionable install hint.
5. **Add an integration test** in `tests/e2e/test_<name>.py` with `@pytest.mark.e2e @pytest.mark.needs_dataset` (add `@pytest.mark.e2e_slow` if >2 min). Compare harness output to GT using `metrics.absolute_trajectory_error`. When the pipeline is not yet tuned for the dataset, use `pytest.xfail()` to document the current gap instead of hard failing.
6. **Register SHA256** of the known-good dataset archive in `DATASET_REGISTRY`. Leave `url=""` if downloads are form-gated — the registry then documents the hash without enabling drive-by fetches.

## Harness data flow

```
adapter.iter_frames()  ─┐
adapter.iter_imu()      ├─▶ E2EHarness.run() ─▶ FlightProcessor.process_frame() ─▶ collected estimates
adapter.iter_ground_truth() ────────────────────▶ HarnessResult.ground_truth (ENU metres)
                                                          │
                                                          ▼
                                             metrics.absolute_trajectory_error()
                                                          │
                                                          ▼
                                         RMSE assert or pytest.xfail()
```

The harness owns a minimal `FlightProcessor` built with `MagicMock` repository and SSE streamer, wires in the real `vo/gpr/metric/graph/chunk_mgr/recovery` components via `attach_components()`, and feeds frames sequentially. GPS estimates (`FrameResult.gps`) are collected; both estimate and GT tracks are converted to a local ENU frame rooted at GT pose 0 so trajectory metrics don't depend on the absolute geodetic origin.

## Running

```bash
# Fast: unit + adapter tests, skip anything needing a real dataset
pytest tests/e2e/ -q

# CI tier: run what has a dataset locally, stay under ~30s
pytest tests/e2e/ -m "e2e and not e2e_slow" -v

# Nightly tier: VPAIR, MARS-LVIG, other long runs
pytest tests/e2e/ -m e2e_slow -v

# Download a dataset registered in DATASET_REGISTRY with a URL
python scripts/download_dataset.py euroc_mh01
```

Markers (`e2e`, `e2e_slow`, `needs_dataset`) are registered in `pyproject.toml`.

## Existing adapters at a glance

| Adapter | Platform | Raw IMU | GT | Real-run status |
|---|---|---|---|---|
| `SyntheticAdapter` | — | yes (zero motion) | exact | smoke test only, always runs |
| `EuRoCAdapter` | indoor MAV | 200 Hz ADIS16448 | Vicon | pending first real run (dataset download in progress) |
| `VPAIRAdapter` | fixed-wing light aircraft | no (pose-only) | GNSS/INS ~1 m | ran once — ATE ~1770 km, xfail documented; VO alone diverges without anchoring |
| `MARSLVIGAdapter` | rotary (DJI M300 RTK) | yes | RTK | pending (requires pre-extracted ROS bag) |

## References

- Dataset-selection rationale: [ADR 0001](../../../_docs/01_solution/decisions/0001-e2e-dataset-strategy.md)
- Roadmap checklist: [next_steps.md](../../../next_steps.md)
- Target system solution: [_docs/01_solution/solution.md](../../../_docs/01_solution/solution.md), §Testing Strategy