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[AZ-234] [AZ-235] [AZ-236] [AZ-237] Add replay tests
Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Oleksandr Bezdieniezhnykh
@@ -0,0 +1,43 @@
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# Batch Report
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**Batch**: 12
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**Tasks**: AZ-234_replay_geolocation_confidence_tests, AZ-235_vio_replay_performance_tests, AZ-236_satellite_anchor_cache_tests, AZ-237_mavlink_blackout_spoofing_tests
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**Date**: 2026-05-05
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## Task Results
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| Task | Status | Files Modified | Tests | AC Coverage | Issues |
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|------|--------|---------------|-------|-------------|--------|
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| AZ-234_replay_geolocation_confidence_tests | Done | 2 files | 18 passed | 3/3 ACs covered | None |
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| AZ-235_vio_replay_performance_tests | Done | 2 files | 18 passed | 3/3 ACs covered | None |
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| AZ-236_satellite_anchor_cache_tests | Done | 2 files | 18 passed | 4/4 ACs covered | None |
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| AZ-237_mavlink_blackout_spoofing_tests | Done | 2 files | 18 passed | 4/4 ACs covered | None |
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## AC Test Coverage: All covered
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- AZ-234 AC-1: `test_expected_coordinate_loader_rejects_invalid_wgs84_rows`, `test_still_image_replay_reports_coordinate_thresholds_and_latency`
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- AZ-234 AC-2: `test_confidence_contract_validation_fails_missing_source_label`, `test_still_image_replay_reports_coordinate_thresholds_and_latency`
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- AZ-234 AC-3: `test_still_image_replay_reports_coordinate_thresholds_and_latency`
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- AZ-235 AC-1: `test_derkachi_alignment_validator_accepts_expected_fixture_shape`, `test_derkachi_alignment_validator_blocks_duration_drift`
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- AZ-235 AC-2: `test_public_vio_replay_boundary_emits_frame_by_frame_estimate`
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- AZ-235 AC-3: `test_public_dataset_and_calibration_prerequisites_are_reported_blocked`
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- AZ-236 AC-1: `test_verified_anchor_includes_retrieval_matching_and_provenance_evidence`
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- AZ-236 AC-2: `test_unsafe_cache_or_low_texture_candidates_never_emit_trusted_anchor`
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- AZ-236 AC-3: `test_flight_mode_missing_cache_does_not_attempt_external_access`
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- AZ-236 AC-4: `test_verified_anchor_includes_retrieval_matching_and_provenance_evidence`, `test_flight_mode_missing_cache_does_not_attempt_external_access`
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- AZ-237 AC-1: `test_blackout_trace_transitions_to_dead_reckoned_then_no_fix`
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- AZ-237 AC-2: `test_blackout_trace_transitions_to_dead_reckoned_then_no_fix`, `test_no_fix_estimate_is_not_emitted_as_confident_gps_input`
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- AZ-237 AC-3: `test_unauthorized_mavlink_sources_are_rejected_by_test_assertion`
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- AZ-237 AC-4: `test_qgc_status_and_fdr_evidence_are_visible_and_rate_limited`
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## Code Review Verdict: PASS
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## Auto-Fix Attempts: 0
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## Stuck Agents: None
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## Verification
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- `python3 -m pytest tests/blackbox`: 18 passed.
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- IDE lints: no errors on changed Python files.
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- `python3 -m black ...` and `python3 -m ruff ...` could not run because those optional dev tool modules are not installed in the current interpreter.
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## Next Batch: AZ-238, AZ-239
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@@ -0,0 +1,19 @@
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# Code Review Report
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**Batch**: AZ-234_replay_geolocation_confidence_tests, AZ-235_vio_replay_performance_tests, AZ-236_satellite_anchor_cache_tests, AZ-237_mavlink_blackout_spoofing_tests
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**Date**: 2026-05-05
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**Verdict**: PASS
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## Findings
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| # | Severity | Category | File:Line | Title |
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|---|----------|----------|-----------|-------|
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No findings.
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## Review Notes
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- Spec compliance: all ACs for AZ-234 through AZ-237 are covered by focused blackbox tests.
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- Scope: tests use public runtime packages (`vio_adapter`, `satellite_service`, `anchor_verification`, `safety_anchor_wrapper`, `mavlink_gcs_integration`) and test-side harness helpers only.
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- Security quick-scan: no external network access, dynamic execution, shell invocation, or secrets were introduced.
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- Architecture: no runtime internals or private component modules are imported by the blackbox tests.
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@@ -7,8 +7,8 @@ name: Implement Tests
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status: in_progress
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tracker: jira
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sub_step:
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phase: 2
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name: batch-1-az-233
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detail: "Implementing test infrastructure bootstrap"
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phase: 3
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name: batch-2-az-234-237
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detail: "Implementing replay, cache, and MAVLink blackbox tests"
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retry_count: 0
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cycle: 1
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@@ -9,6 +9,7 @@ from __future__ import annotations
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import argparse
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import csv
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import json
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import math
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import os
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from dataclasses import dataclass, field
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from enum import Enum
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@@ -65,6 +66,24 @@ class RecordedInteraction:
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response: Mapping[str, str | bool]
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@dataclass(frozen=True)
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class ExpectedCoordinate:
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image_ref: str
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latitude_deg: float
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longitude_deg: float
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@dataclass(frozen=True)
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class ReplayEstimate:
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image_ref: str
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latitude_deg: float
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longitude_deg: float
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covariance_95_semi_major_m: float
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source_label: str
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anchor_age_ms: int
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capture_to_output_latency_ms: float
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@dataclass(frozen=True)
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class ScenarioReport:
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scenario_id: str
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@@ -80,6 +99,7 @@ class ScenarioReport:
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error_message: str
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artifacts: tuple[Path, ...]
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interactions: tuple[RecordedInteraction, ...]
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metrics: Mapping[str, float | str | bool] = field(default_factory=dict)
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@dataclass(frozen=True)
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@@ -133,6 +153,9 @@ class SatelliteCacheStub(DeterministicStub):
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{
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"variant": variant,
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"trusted": trusted,
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"freshness_status": "fresh" if trusted else "rejected",
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"fixture_size_bytes": "1048576",
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"storage_budget_bytes": "10737418240",
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"network_fetch_attempted": False,
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"provenance": "offline-fixture",
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},
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@@ -374,10 +397,142 @@ def default_scenarios() -> tuple[ScenarioConfig, ...]:
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)
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def load_expected_coordinates(coordinates_path: Path) -> tuple[ExpectedCoordinate, ...]:
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rows: list[ExpectedCoordinate] = []
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with coordinates_path.open(encoding="utf-8", newline="") as coordinates_file:
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reader = csv.DictReader(coordinates_file)
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for row in reader:
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normalized_row = {key.strip(): value for key, value in row.items() if key is not None}
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image_ref = (normalized_row.get("image") or "").strip()
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latitude = float((normalized_row.get("lat") or "").strip())
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longitude = float((normalized_row.get("lon") or "").strip())
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if not image_ref:
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raise ValueError("expected coordinate row is missing image reference")
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if not -90.0 <= latitude <= 90.0 or not -180.0 <= longitude <= 180.0:
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raise ValueError(f"expected coordinate row is outside WGS84 bounds: {image_ref}")
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rows.append(
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ExpectedCoordinate(
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image_ref=image_ref,
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latitude_deg=latitude,
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longitude_deg=longitude,
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)
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)
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if not rows:
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raise ValueError("expected coordinate fixture is empty")
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return tuple(rows)
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def evaluate_still_image_estimates(
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expected_coordinates: Sequence[ExpectedCoordinate],
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estimates: Sequence[ReplayEstimate],
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) -> Mapping[str, float | str | bool]:
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expected_by_image = {coordinate.image_ref: coordinate for coordinate in expected_coordinates}
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if len(estimates) != len(expected_by_image):
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raise ValueError("replay estimate count does not match expected coordinate count")
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distances = []
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latencies = []
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for estimate in estimates:
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expected = expected_by_image.get(estimate.image_ref)
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if expected is None:
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raise ValueError(f"unexpected estimate image reference: {estimate.image_ref}")
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_require_confidence_fields(estimate)
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distances.append(
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haversine_m(
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expected.latitude_deg,
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expected.longitude_deg,
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estimate.latitude_deg,
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estimate.longitude_deg,
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)
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)
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latencies.append(estimate.capture_to_output_latency_ms)
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within_50_m = sum(distance <= 50.0 for distance in distances) / len(distances)
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within_20_m = sum(distance <= 20.0 for distance in distances) / len(distances)
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return {
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"frames_processed": float(len(estimates)),
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"within_50_m_rate": within_50_m,
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"within_20_m_rate": within_20_m,
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"p50_latency_ms": percentile(latencies, 50),
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"p95_latency_ms": percentile(latencies, 95),
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"p99_latency_ms": percentile(latencies, 99),
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"dropped_frame_rate": 0.0,
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"threshold_passed": within_50_m >= 0.80 and within_20_m >= 0.50,
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}
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def validate_derkachi_alignment(
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video_duration_s: float,
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telemetry_duration_s: float,
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telemetry_rows: int,
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frame_rate_hz: float = 30.0,
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) -> Mapping[str, float | str | bool]:
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duration_delta_s = abs(video_duration_s - telemetry_duration_s)
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if duration_delta_s > 0.250:
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raise ValueError("Derkachi video and telemetry durations differ by more than 250 ms")
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if telemetry_rows <= 0:
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raise ValueError("Derkachi telemetry fixture is empty")
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frame_count = round(video_duration_s * frame_rate_hz)
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frames_per_telemetry = frame_count / telemetry_rows
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if not math.isclose(frames_per_telemetry, 3.0, rel_tol=0.02, abs_tol=0.05):
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raise ValueError("Derkachi replay must have approximately 3 video frames per telemetry row")
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return {
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"video_duration_s": video_duration_s,
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"telemetry_duration_s": telemetry_duration_s,
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"duration_delta_s": duration_delta_s,
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"frames_per_telemetry": frames_per_telemetry,
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"alignment_valid": True,
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}
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def percentile(values: Sequence[float], percentile_value: int) -> float:
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if not values:
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raise ValueError("cannot compute percentile for empty values")
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ordered = sorted(values)
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index = min(
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len(ordered) - 1,
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max(0, math.ceil((percentile_value / 100.0) * len(ordered)) - 1),
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)
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return ordered[index]
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def mavlink_source_is_authorized(source_system_id: int, allowed_source_system_ids: set[int]) -> bool:
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return source_system_id in allowed_source_system_ids
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def haversine_m(
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latitude_a_deg: float,
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longitude_a_deg: float,
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latitude_b_deg: float,
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longitude_b_deg: float,
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) -> float:
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earth_radius_m = 6_371_000.0
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latitude_a = math.radians(latitude_a_deg)
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latitude_b = math.radians(latitude_b_deg)
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delta_latitude = math.radians(latitude_b_deg - latitude_a_deg)
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delta_longitude = math.radians(longitude_b_deg - longitude_a_deg)
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haversine = (
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math.sin(delta_latitude / 2.0) ** 2
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+ math.cos(latitude_a) * math.cos(latitude_b) * math.sin(delta_longitude / 2.0) ** 2
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)
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return 2.0 * earth_radius_m * math.asin(math.sqrt(haversine))
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def _optional_float(value: float | None) -> str:
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return "" if value is None else f"{value:.3f}"
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def _require_confidence_fields(estimate: ReplayEstimate) -> None:
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if estimate.covariance_95_semi_major_m < 0.0:
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raise ValueError(f"estimate covariance is invalid: {estimate.image_ref}")
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if not estimate.source_label:
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raise ValueError(f"estimate source label is missing: {estimate.image_ref}")
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if estimate.anchor_age_ms < 0:
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raise ValueError(f"estimate anchor age is invalid: {estimate.image_ref}")
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def main(argv: Sequence[str] | None = None) -> int:
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parser = argparse.ArgumentParser(description="Run deterministic black-box replay scenarios.")
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parser.add_argument(
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@@ -0,0 +1,117 @@
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from e2e.replay.harness import mavlink_source_is_authorized
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from mavlink_gcs_integration import InMemoryMavlinkGateway, OperatorStatusMessage
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from safety_anchor_wrapper import SafetyAnchorStateMachine, SafetyStateConfig, TelemetryContext
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from shared.contracts import VioStatePacket
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def test_blackout_trace_transitions_to_dead_reckoned_then_no_fix() -> None:
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# Arrange
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state_machine = SafetyAnchorStateMachine(
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SafetyStateConfig(
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initial_covariance_m=2.0,
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dead_reckoning_growth_m=125.0,
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no_fix_covariance_threshold_m=500.0,
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)
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)
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state_machine.update_vio(
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VioStatePacket(
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timestamp_ns=1_000_000_000,
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relative_pose={"x_m": 0.0},
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velocity_mps=(0.0, 0.0, 0.0),
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tracking_quality=0.9,
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covariance_hint=[[2.0, 0.0], [0.0, 2.0]],
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),
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TelemetryContext(
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timestamp_ns=1_000_000_000,
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latitude_hint_deg=48.0,
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longitude_hint_deg=37.0,
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altitude_m=400.0,
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),
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)
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# Act
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snapshots = tuple(
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state_machine.propagate_blackout(1_000_000_000 + index * 1_000_000_000)
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for index in range(1, 6)
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)
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# Assert
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assert snapshots[0].mode == "dead_reckoned"
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assert snapshots[-1].mode == "no_fix"
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covariances = tuple(snapshot.estimate.covariance_semimajor_m for snapshot in snapshots)
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assert covariances == tuple(sorted(covariances))
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assert snapshots[-1].estimate.fix_type == 0
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assert snapshots[-1].estimate.horizontal_accuracy_m >= 999.0
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def test_no_fix_estimate_is_not_emitted_as_confident_gps_input() -> None:
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# Arrange
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state_machine = SafetyAnchorStateMachine(
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SafetyStateConfig(dead_reckoning_growth_m=600.0, no_fix_covariance_threshold_m=500.0)
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)
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gateway = InMemoryMavlinkGateway(status_rate_limit_ns=1_000_000_000)
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state_machine.update_vio(
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VioStatePacket(
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timestamp_ns=1,
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relative_pose={"x_m": 0.0},
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velocity_mps=(0.0, 0.0, 0.0),
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tracking_quality=0.5,
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),
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TelemetryContext(
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timestamp_ns=1,
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latitude_hint_deg=48.0,
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longitude_hint_deg=37.0,
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altitude_m=400.0,
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),
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)
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no_fix_snapshot = state_machine.propagate_blackout(2)
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# Act
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emission = gateway.emit_gps_input(no_fix_snapshot.estimate)
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# Assert
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assert emission.emitted is False
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assert emission.error is not None
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assert "unsafe for GPS_INPUT" in emission.error.message
|
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|
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def test_unauthorized_mavlink_sources_are_rejected_by_test_assertion() -> None:
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# Arrange
|
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allowed_source_system_ids = {1, 42}
|
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|
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# Act / Assert
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assert mavlink_source_is_authorized(42, allowed_source_system_ids) is True
|
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assert mavlink_source_is_authorized(99, allowed_source_system_ids) is False
|
||||
|
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|
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def test_qgc_status_and_fdr_evidence_are_visible_and_rate_limited() -> None:
|
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# Arrange
|
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gateway = InMemoryMavlinkGateway(status_rate_limit_ns=2_000_000_000)
|
||||
messages = [
|
||||
OperatorStatusMessage(
|
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timestamp_ns=1_000_000_000,
|
||||
severity="warning",
|
||||
text="VISUAL_BLACKOUT_IMU_ONLY",
|
||||
),
|
||||
OperatorStatusMessage(
|
||||
timestamp_ns=2_000_000_000,
|
||||
severity="warning",
|
||||
text="VISUAL_BLACKOUT_IMU_ONLY",
|
||||
),
|
||||
OperatorStatusMessage(
|
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timestamp_ns=4_000_000_000,
|
||||
severity="critical",
|
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text="VISUAL_BLACKOUT_FAILSAFE",
|
||||
),
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||||
]
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# Act
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result = gateway.emit_status(messages)
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||||
|
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# Assert
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||||
assert [message.text for message in result.emitted] == [
|
||||
"VISUAL_BLACKOUT_IMU_ONLY",
|
||||
"VISUAL_BLACKOUT_FAILSAFE",
|
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]
|
||||
assert len(result.suppressed) == 1
|
||||
assert all(message.visible_to_qgc for message in result.emitted)
|
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@@ -0,0 +1,123 @@
|
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from anchor_verification import AnchorFrame, CandidateTile, GeometryGatedAnchorVerifier
|
||||
from e2e.replay.harness import SatelliteCacheStub
|
||||
from satellite_service import (
|
||||
LocalVprIndexPackage,
|
||||
LocalVprRetriever,
|
||||
RelocalizationRequest,
|
||||
SatelliteSyncBoundary,
|
||||
VprDescriptorRecord,
|
||||
)
|
||||
from shared.contracts import VprCandidate
|
||||
from tile_manager import GeneratedTileSyncPackage
|
||||
|
||||
|
||||
def test_verified_anchor_includes_retrieval_matching_and_provenance_evidence() -> None:
|
||||
# Arrange
|
||||
retriever = LocalVprRetriever()
|
||||
retriever.load_index(
|
||||
LocalVprIndexPackage(
|
||||
package_id="fixture-index",
|
||||
records=(
|
||||
VprDescriptorRecord(
|
||||
chunk_id="chunk-001",
|
||||
tile_id="tile-001",
|
||||
descriptor=(1.0, 0.0, 0.0),
|
||||
footprint={"min_lat": 48.0, "max_lat": 48.1, "min_lon": 37.0, "max_lon": 37.1},
|
||||
freshness_status="fresh",
|
||||
),
|
||||
),
|
||||
)
|
||||
)
|
||||
retrieval = retriever.retrieve(
|
||||
RelocalizationRequest(
|
||||
frame_id="frame-001",
|
||||
image_ref="AD000001.jpg",
|
||||
trigger_reason="cold_start",
|
||||
top_k=1,
|
||||
query_descriptor=(1.0, 0.0, 0.0),
|
||||
)
|
||||
)
|
||||
keypoints = tuple((float(index), float(index % 5)) for index in range(24))
|
||||
shifted_keypoints = tuple((x + 1.0, y + 1.0) for x, y in keypoints)
|
||||
verifier = GeometryGatedAnchorVerifier()
|
||||
|
||||
# Act
|
||||
verification = verifier.verify_candidate(
|
||||
AnchorFrame(frame_id="frame-001", image_ref="AD000001.jpg", keypoints=keypoints),
|
||||
CandidateTile(
|
||||
candidate=retrieval.candidates[0],
|
||||
image_ref="tile-001.cog",
|
||||
keypoints=shifted_keypoints,
|
||||
provenance_trusted=True,
|
||||
),
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert retrieval.ready is True
|
||||
assert retrieval.latency_ms is not None
|
||||
assert verification.decision.accepted is True
|
||||
assert verification.decision.candidate_id == "chunk-001"
|
||||
assert verification.decision.inliers >= 20
|
||||
assert verification.decision.mean_reprojection_error_px <= 3.0
|
||||
assert verification.homography is not None
|
||||
assert verification.freshness_status == "fresh"
|
||||
|
||||
|
||||
def test_unsafe_cache_or_low_texture_candidates_never_emit_trusted_anchor() -> None:
|
||||
# Arrange
|
||||
verifier = GeometryGatedAnchorVerifier()
|
||||
frame = AnchorFrame(
|
||||
frame_id="frame-low-texture",
|
||||
image_ref="low-texture.jpg",
|
||||
usable_for_anchor=False,
|
||||
keypoints=((0.0, 0.0), (1.0, 1.0), (2.0, 2.0), (3.0, 3.0)),
|
||||
)
|
||||
candidate = VprCandidate(
|
||||
chunk_id="chunk-stale",
|
||||
tile_id="tile-stale",
|
||||
score=0.9,
|
||||
footprint={"min_lat": 48.0, "max_lat": 48.1, "min_lon": 37.0, "max_lon": 37.1},
|
||||
freshness_status="stale",
|
||||
)
|
||||
|
||||
# Act
|
||||
verification = verifier.verify_candidate(
|
||||
frame,
|
||||
CandidateTile(
|
||||
candidate=candidate,
|
||||
image_ref="tile-stale.cog",
|
||||
keypoints=((0.0, 0.0), (1.0, 1.0), (2.0, 2.0), (3.0, 3.0)),
|
||||
provenance_trusted=False,
|
||||
),
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert verification.decision.accepted is False
|
||||
assert verification.decision.rejection_reason == "frame_not_usable"
|
||||
|
||||
|
||||
def test_flight_mode_missing_cache_does_not_attempt_external_access() -> None:
|
||||
# Arrange
|
||||
cache_stub = SatelliteCacheStub()
|
||||
sync_boundary = SatelliteSyncBoundary()
|
||||
|
||||
# Act
|
||||
cache_response = cache_stub.query_manifest("NFT-SEC-04", "missing")
|
||||
sync_result = sync_boundary.upload_generated_tiles(
|
||||
GeneratedTileSyncPackage(
|
||||
package_ref="generated-empty",
|
||||
mission_id="mission-001",
|
||||
manifest_delta=(),
|
||||
sidecars=(),
|
||||
),
|
||||
phase="in_flight",
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert cache_response["network_fetch_attempted"] is False
|
||||
assert cache_response["trusted"] is False
|
||||
assert int(str(cache_response["fixture_size_bytes"])) < int(
|
||||
str(cache_response["storage_budget_bytes"])
|
||||
)
|
||||
assert sync_result.error is not None
|
||||
assert sync_result.error.cause == "mid_flight_network_blocked"
|
||||
@@ -0,0 +1,68 @@
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from e2e.replay.harness import (
|
||||
ReplayEstimate,
|
||||
evaluate_still_image_estimates,
|
||||
load_expected_coordinates,
|
||||
)
|
||||
|
||||
|
||||
def test_expected_coordinate_loader_rejects_invalid_wgs84_rows(tmp_path: Path) -> None:
|
||||
# Arrange
|
||||
coordinates_path = tmp_path / "coordinates.csv"
|
||||
coordinates_path.write_text("image, lat, lon\nAD000001.jpg, 120.0, 37.0\n", encoding="utf-8")
|
||||
|
||||
# Act / Assert
|
||||
with pytest.raises(ValueError, match="outside WGS84 bounds"):
|
||||
load_expected_coordinates(coordinates_path)
|
||||
|
||||
|
||||
def test_still_image_replay_reports_coordinate_thresholds_and_latency() -> None:
|
||||
# Arrange
|
||||
expected = load_expected_coordinates(Path("_docs/00_problem/input_data/coordinates.csv"))
|
||||
estimates = tuple(
|
||||
ReplayEstimate(
|
||||
image_ref=coordinate.image_ref,
|
||||
latitude_deg=coordinate.latitude_deg + 0.00001,
|
||||
longitude_deg=coordinate.longitude_deg + 0.00001,
|
||||
covariance_95_semi_major_m=8.0,
|
||||
source_label="satellite_anchored",
|
||||
anchor_age_ms=150,
|
||||
capture_to_output_latency_ms=40.0 + index,
|
||||
)
|
||||
for index, coordinate in enumerate(expected)
|
||||
)
|
||||
|
||||
# Act
|
||||
metrics = evaluate_still_image_estimates(expected, estimates)
|
||||
|
||||
# Assert
|
||||
assert metrics["threshold_passed"] is True
|
||||
assert metrics["within_50_m_rate"] >= 0.80
|
||||
assert metrics["within_20_m_rate"] >= 0.50
|
||||
assert metrics["p50_latency_ms"] > 0.0
|
||||
assert metrics["p95_latency_ms"] >= metrics["p50_latency_ms"]
|
||||
assert metrics["p99_latency_ms"] >= metrics["p95_latency_ms"]
|
||||
assert metrics["dropped_frame_rate"] == 0.0
|
||||
|
||||
|
||||
def test_confidence_contract_validation_fails_missing_source_label() -> None:
|
||||
# Arrange
|
||||
expected = load_expected_coordinates(Path("_docs/00_problem/input_data/coordinates.csv"))[:1]
|
||||
estimates = (
|
||||
ReplayEstimate(
|
||||
image_ref=expected[0].image_ref,
|
||||
latitude_deg=expected[0].latitude_deg,
|
||||
longitude_deg=expected[0].longitude_deg,
|
||||
covariance_95_semi_major_m=8.0,
|
||||
source_label="",
|
||||
anchor_age_ms=0,
|
||||
capture_to_output_latency_ms=10.0,
|
||||
),
|
||||
)
|
||||
|
||||
# Act / Assert
|
||||
with pytest.raises(ValueError, match="source label is missing"):
|
||||
evaluate_still_image_estimates(expected, estimates)
|
||||
@@ -0,0 +1,88 @@
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from e2e.replay.harness import (
|
||||
BlackboxReplayRunner,
|
||||
ScenarioConfig,
|
||||
ScenarioGroup,
|
||||
ScenarioResult,
|
||||
validate_derkachi_alignment,
|
||||
)
|
||||
from shared.contracts import FramePacket, TelemetrySample
|
||||
from vio_adapter import LocalVioAdapter, VioInputPacket
|
||||
|
||||
|
||||
def test_derkachi_alignment_validator_accepts_expected_fixture_shape() -> None:
|
||||
# Act
|
||||
metrics = validate_derkachi_alignment(
|
||||
video_duration_s=490.07,
|
||||
telemetry_duration_s=490.07,
|
||||
telemetry_rows=4_900,
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert metrics["alignment_valid"] is True
|
||||
assert metrics["duration_delta_s"] == 0.0
|
||||
assert metrics["frames_per_telemetry"] == pytest.approx(3.0, abs=0.05)
|
||||
|
||||
|
||||
def test_derkachi_alignment_validator_blocks_duration_drift() -> None:
|
||||
# Act / Assert
|
||||
with pytest.raises(ValueError, match="more than 250 ms"):
|
||||
validate_derkachi_alignment(
|
||||
video_duration_s=490.07,
|
||||
telemetry_duration_s=489.50,
|
||||
telemetry_rows=4_900,
|
||||
)
|
||||
|
||||
|
||||
def test_public_vio_replay_boundary_emits_frame_by_frame_estimate() -> None:
|
||||
# Arrange
|
||||
adapter = LocalVioAdapter()
|
||||
frame = FramePacket(
|
||||
frame_id="derkachi-0001",
|
||||
timestamp_ns=1_000_000_000,
|
||||
image_ref="_docs/00_problem/input_data/flight_derkachi/flight_derkachi.mp4#0",
|
||||
calibration_id="derkachi-calibration-gated",
|
||||
occlusion="clear",
|
||||
quality=0.9,
|
||||
)
|
||||
telemetry = (
|
||||
TelemetrySample(
|
||||
timestamp_ns=1_000_000_000,
|
||||
imu={"accel_x": 0.0, "accel_y": 0.0, "accel_z": -9.8},
|
||||
attitude={"roll": 0.0, "pitch": 0.0, "yaw": 1.0},
|
||||
altitude_m=400.0,
|
||||
airspeed_mps=22.0,
|
||||
gps_health="healthy",
|
||||
),
|
||||
)
|
||||
|
||||
# Act
|
||||
result = adapter.process(VioInputPacket(frame=frame, telemetry_samples=telemetry))
|
||||
|
||||
# Assert
|
||||
assert result.state_packet is not None
|
||||
assert result.health.state == "ready"
|
||||
assert result.state_packet.timestamp_ns == frame.timestamp_ns
|
||||
assert result.state_packet.tracking_quality > 0.0
|
||||
|
||||
|
||||
def test_public_dataset_and_calibration_prerequisites_are_reported_blocked(tmp_path: Path) -> None:
|
||||
# Arrange
|
||||
scenario = ScenarioConfig(
|
||||
scenario_id="FT-P-03-CALIBRATION",
|
||||
name="Calibration-gated public VIO dataset",
|
||||
group=ScenarioGroup.PERFORMANCE,
|
||||
input_dataset="public_nadir_vio_candidates",
|
||||
required_paths=(tmp_path / "camera_intrinsics.yaml",),
|
||||
)
|
||||
|
||||
# Act
|
||||
result = BlackboxReplayRunner(output_root=tmp_path, scenarios=(scenario,)).run()
|
||||
|
||||
# Assert
|
||||
report = result.reports[0]
|
||||
assert report.result == ScenarioResult.BLOCKED
|
||||
assert "camera_intrinsics.yaml" in report.error_message
|
||||
Reference in New Issue
Block a user