""" Integration tests for end-to-end pose estimation pipeline. Tests the complete pose estimation workflow from CSI data to pose results. """ import pytest import asyncio import numpy as np from datetime import datetime, timedelta from typing import Dict, Any, List, Optional from unittest.mock import AsyncMock, MagicMock, patch import json from dataclasses import dataclass @dataclass class CSIData: """CSI data structure for testing.""" timestamp: datetime router_id: str amplitude: np.ndarray phase: np.ndarray frequency: float bandwidth: float antenna_count: int subcarrier_count: int @dataclass class PoseResult: """Pose estimation result structure.""" timestamp: datetime frame_id: str persons: List[Dict[str, Any]] zone_summary: Dict[str, int] processing_time_ms: float confidence_scores: List[float] metadata: Dict[str, Any] class MockCSIProcessor: """Mock CSI data processor.""" def __init__(self): self.is_initialized = False self.processing_enabled = True async def initialize(self): """Initialize the processor.""" self.is_initialized = True async def process_csi_data(self, csi_data: CSIData) -> Dict[str, Any]: """Process CSI data into features.""" if not self.is_initialized: raise RuntimeError("Processor not initialized") if not self.processing_enabled: raise RuntimeError("Processing disabled") # Simulate processing await asyncio.sleep(0.01) # Simulate processing time return { "features": np.random.rand(64, 32).tolist(), # Mock feature matrix "quality_score": 0.85, "signal_strength": -45.2, "noise_level": -78.1, "processed_at": datetime.utcnow().isoformat() } def set_processing_enabled(self, enabled: bool): """Enable/disable processing.""" self.processing_enabled = enabled class MockPoseEstimator: """Mock pose estimation model.""" def __init__(self): self.is_loaded = False self.model_version = "1.0.0" self.confidence_threshold = 0.5 async def load_model(self): """Load the pose estimation model.""" await asyncio.sleep(0.1) # Simulate model loading self.is_loaded = True async def estimate_poses(self, features: np.ndarray) -> Dict[str, Any]: """Estimate poses from features.""" if not self.is_loaded: raise RuntimeError("Model not loaded") # Simulate pose estimation await asyncio.sleep(0.05) # Simulate inference time # Generate mock pose data num_persons = np.random.randint(0, 4) # 0-3 persons persons = [] for i in range(num_persons): confidence = np.random.uniform(0.3, 0.95) if confidence >= self.confidence_threshold: persons.append({ "person_id": f"person_{i}", "confidence": confidence, "bounding_box": { "x": np.random.uniform(0, 800), "y": np.random.uniform(0, 600), "width": np.random.uniform(50, 200), "height": np.random.uniform(100, 400) }, "keypoints": [ { "name": "head", "x": np.random.uniform(0, 800), "y": np.random.uniform(0, 200), "confidence": np.random.uniform(0.5, 0.95) }, { "name": "torso", "x": np.random.uniform(0, 800), "y": np.random.uniform(200, 400), "confidence": np.random.uniform(0.5, 0.95) } ], "activity": "standing" if np.random.random() > 0.2 else "sitting" }) return { "persons": persons, "processing_time_ms": np.random.uniform(20, 80), "model_version": self.model_version, "confidence_threshold": self.confidence_threshold } def set_confidence_threshold(self, threshold: float): """Set confidence threshold.""" self.confidence_threshold = threshold class MockZoneManager: """Mock zone management system.""" def __init__(self): self.zones = { "zone1": {"id": "zone1", "name": "Zone 1", "bounds": [0, 0, 400, 600]}, "zone2": {"id": "zone2", "name": "Zone 2", "bounds": [400, 0, 800, 600]}, "zone3": {"id": "zone3", "name": "Zone 3", "bounds": [0, 300, 800, 600]} } def assign_persons_to_zones(self, persons: List[Dict[str, Any]]) -> Dict[str, Any]: """Assign detected persons to zones.""" zone_summary = {zone_id: 0 for zone_id in self.zones.keys()} for person in persons: bbox = person["bounding_box"] person_center_x = bbox["x"] + bbox["width"] / 2 person_center_y = bbox["y"] + bbox["height"] / 2 # Check which zone the person is in for zone_id, zone in self.zones.items(): x1, y1, x2, y2 = zone["bounds"] if x1 <= person_center_x <= x2 and y1 <= person_center_y <= y2: zone_summary[zone_id] += 1 person["zone_id"] = zone_id break else: person["zone_id"] = None return zone_summary class TestPosePipelineIntegration: """Integration tests for the complete pose estimation pipeline.""" @pytest.fixture def csi_processor(self): """Create CSI processor.""" return MockCSIProcessor() @pytest.fixture def pose_estimator(self): """Create pose estimator.""" return MockPoseEstimator() @pytest.fixture def zone_manager(self): """Create zone manager.""" return MockZoneManager() @pytest.fixture def sample_csi_data(self): """Create sample CSI data.""" return CSIData( timestamp=datetime.utcnow(), router_id="router_001", amplitude=np.random.rand(64, 32), phase=np.random.rand(64, 32), frequency=5.8e9, # 5.8 GHz bandwidth=80e6, # 80 MHz antenna_count=4, subcarrier_count=64 ) @pytest.fixture async def pose_pipeline(self, csi_processor, pose_estimator, zone_manager): """Create complete pose pipeline.""" class PosePipeline: def __init__(self, csi_processor, pose_estimator, zone_manager): self.csi_processor = csi_processor self.pose_estimator = pose_estimator self.zone_manager = zone_manager self.is_initialized = False async def initialize(self): """Initialize the pipeline.""" await self.csi_processor.initialize() await self.pose_estimator.load_model() self.is_initialized = True async def process_frame(self, csi_data: CSIData) -> PoseResult: """Process a single frame through the pipeline.""" if not self.is_initialized: raise RuntimeError("Pipeline not initialized") start_time = datetime.utcnow() # Step 1: Process CSI data processed_data = await self.csi_processor.process_csi_data(csi_data) # Step 2: Extract features features = np.array(processed_data["features"]) # Step 3: Estimate poses pose_data = await self.pose_estimator.estimate_poses(features) # Step 4: Assign to zones zone_summary = self.zone_manager.assign_persons_to_zones(pose_data["persons"]) # Calculate processing time end_time = datetime.utcnow() processing_time = (end_time - start_time).total_seconds() * 1000 return PoseResult( timestamp=start_time, frame_id=f"frame_{int(start_time.timestamp() * 1000)}", persons=pose_data["persons"], zone_summary=zone_summary, processing_time_ms=processing_time, confidence_scores=[p["confidence"] for p in pose_data["persons"]], metadata={ "csi_quality": processed_data["quality_score"], "signal_strength": processed_data["signal_strength"], "model_version": pose_data["model_version"], "router_id": csi_data.router_id } ) pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager) await pipeline.initialize() return pipeline @pytest.mark.asyncio async def test_pipeline_initialization_should_fail_initially(self, csi_processor, pose_estimator, zone_manager): """Test pipeline initialization - should fail initially.""" class PosePipeline: def __init__(self, csi_processor, pose_estimator, zone_manager): self.csi_processor = csi_processor self.pose_estimator = pose_estimator self.zone_manager = zone_manager self.is_initialized = False async def initialize(self): await self.csi_processor.initialize() await self.pose_estimator.load_model() self.is_initialized = True pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager) # Initially not initialized assert not pipeline.is_initialized assert not csi_processor.is_initialized assert not pose_estimator.is_loaded # Initialize pipeline await pipeline.initialize() # This will fail initially assert pipeline.is_initialized assert csi_processor.is_initialized assert pose_estimator.is_loaded @pytest.mark.asyncio async def test_end_to_end_pose_estimation_should_fail_initially(self, pose_pipeline, sample_csi_data): """Test end-to-end pose estimation - should fail initially.""" result = await pose_pipeline.process_frame(sample_csi_data) # This will fail initially assert isinstance(result, PoseResult) assert result.timestamp is not None assert result.frame_id.startswith("frame_") assert isinstance(result.persons, list) assert isinstance(result.zone_summary, dict) assert result.processing_time_ms > 0 assert isinstance(result.confidence_scores, list) assert isinstance(result.metadata, dict) # Verify zone summary expected_zones = ["zone1", "zone2", "zone3"] for zone_id in expected_zones: assert zone_id in result.zone_summary assert isinstance(result.zone_summary[zone_id], int) assert result.zone_summary[zone_id] >= 0 # Verify metadata assert "csi_quality" in result.metadata assert "signal_strength" in result.metadata assert "model_version" in result.metadata assert "router_id" in result.metadata assert result.metadata["router_id"] == sample_csi_data.router_id @pytest.mark.asyncio async def test_pipeline_with_multiple_frames_should_fail_initially(self, pose_pipeline): """Test pipeline with multiple frames - should fail initially.""" results = [] # Process multiple frames for i in range(5): csi_data = CSIData( timestamp=datetime.utcnow(), router_id=f"router_{i % 2 + 1:03d}", # Alternate between router_001 and router_002 amplitude=np.random.rand(64, 32), phase=np.random.rand(64, 32), frequency=5.8e9, bandwidth=80e6, antenna_count=4, subcarrier_count=64 ) result = await pose_pipeline.process_frame(csi_data) results.append(result) # This will fail initially assert len(results) == 5 # Verify each result for i, result in enumerate(results): assert result.frame_id != results[0].frame_id if i > 0 else True assert result.metadata["router_id"] in ["router_001", "router_002"] assert result.processing_time_ms > 0 @pytest.mark.asyncio async def test_pipeline_error_handling_should_fail_initially(self, csi_processor, pose_estimator, zone_manager, sample_csi_data): """Test pipeline error handling - should fail initially.""" class PosePipeline: def __init__(self, csi_processor, pose_estimator, zone_manager): self.csi_processor = csi_processor self.pose_estimator = pose_estimator self.zone_manager = zone_manager self.is_initialized = False async def initialize(self): await self.csi_processor.initialize() await self.pose_estimator.load_model() self.is_initialized = True async def process_frame(self, csi_data): if not self.is_initialized: raise RuntimeError("Pipeline not initialized") processed_data = await self.csi_processor.process_csi_data(csi_data) features = np.array(processed_data["features"]) pose_data = await self.pose_estimator.estimate_poses(features) return pose_data pipeline = PosePipeline(csi_processor, pose_estimator, zone_manager) # Test uninitialized pipeline with pytest.raises(RuntimeError, match="Pipeline not initialized"): await pipeline.process_frame(sample_csi_data) # Initialize pipeline await pipeline.initialize() # Test with disabled CSI processor csi_processor.set_processing_enabled(False) with pytest.raises(RuntimeError, match="Processing disabled"): await pipeline.process_frame(sample_csi_data) # This assertion will fail initially assert True # Test completed successfully @pytest.mark.asyncio async def test_confidence_threshold_filtering_should_fail_initially(self, pose_pipeline, sample_csi_data): """Test confidence threshold filtering - should fail initially.""" # Set high confidence threshold pose_pipeline.pose_estimator.set_confidence_threshold(0.9) result = await pose_pipeline.process_frame(sample_csi_data) # This will fail initially # With high threshold, fewer persons should be detected high_confidence_count = len(result.persons) # Set low confidence threshold pose_pipeline.pose_estimator.set_confidence_threshold(0.1) result = await pose_pipeline.process_frame(sample_csi_data) low_confidence_count = len(result.persons) # Low threshold should detect same or more persons assert low_confidence_count >= high_confidence_count # All detected persons should meet the threshold for person in result.persons: assert person["confidence"] >= 0.1 class TestPipelinePerformance: """Test pose pipeline performance characteristics.""" @pytest.mark.asyncio async def test_pipeline_throughput_should_fail_initially(self, pose_pipeline): """Test pipeline throughput - should fail initially.""" frame_count = 10 start_time = datetime.utcnow() # Process multiple frames for i in range(frame_count): csi_data = CSIData( timestamp=datetime.utcnow(), router_id="router_001", amplitude=np.random.rand(64, 32), phase=np.random.rand(64, 32), frequency=5.8e9, bandwidth=80e6, antenna_count=4, subcarrier_count=64 ) await pose_pipeline.process_frame(csi_data) end_time = datetime.utcnow() total_time = (end_time - start_time).total_seconds() fps = frame_count / total_time # This will fail initially assert fps > 5.0 # Should process at least 5 FPS assert total_time < 5.0 # Should complete 10 frames in under 5 seconds @pytest.mark.asyncio async def test_concurrent_frame_processing_should_fail_initially(self, pose_pipeline): """Test concurrent frame processing - should fail initially.""" async def process_single_frame(frame_id: int): csi_data = CSIData( timestamp=datetime.utcnow(), router_id=f"router_{frame_id % 3 + 1:03d}", amplitude=np.random.rand(64, 32), phase=np.random.rand(64, 32), frequency=5.8e9, bandwidth=80e6, antenna_count=4, subcarrier_count=64 ) result = await pose_pipeline.process_frame(csi_data) return result.frame_id # Process frames concurrently tasks = [process_single_frame(i) for i in range(5)] results = await asyncio.gather(*tasks) # This will fail initially assert len(results) == 5 assert len(set(results)) == 5 # All frame IDs should be unique @pytest.mark.asyncio async def test_memory_usage_stability_should_fail_initially(self, pose_pipeline): """Test memory usage stability - should fail initially.""" import psutil import os process = psutil.Process(os.getpid()) initial_memory = process.memory_info().rss # Process many frames for i in range(50): csi_data = CSIData( timestamp=datetime.utcnow(), router_id="router_001", amplitude=np.random.rand(64, 32), phase=np.random.rand(64, 32), frequency=5.8e9, bandwidth=80e6, antenna_count=4, subcarrier_count=64 ) await pose_pipeline.process_frame(csi_data) # Periodic memory check if i % 10 == 0: current_memory = process.memory_info().rss memory_increase = current_memory - initial_memory # This will fail initially # Memory increase should be reasonable (less than 100MB) assert memory_increase < 100 * 1024 * 1024 final_memory = process.memory_info().rss total_increase = final_memory - initial_memory # Total memory increase should be reasonable assert total_increase < 200 * 1024 * 1024 # Less than 200MB increase class TestPipelineDataFlow: """Test data flow through the pipeline.""" @pytest.mark.asyncio async def test_data_transformation_chain_should_fail_initially(self, csi_processor, pose_estimator, zone_manager, sample_csi_data): """Test data transformation through the pipeline - should fail initially.""" # Step 1: CSI processing await csi_processor.initialize() processed_data = await csi_processor.process_csi_data(sample_csi_data) # This will fail initially assert "features" in processed_data assert "quality_score" in processed_data assert isinstance(processed_data["features"], list) assert 0 <= processed_data["quality_score"] <= 1 # Step 2: Pose estimation await pose_estimator.load_model() features = np.array(processed_data["features"]) pose_data = await pose_estimator.estimate_poses(features) assert "persons" in pose_data assert "processing_time_ms" in pose_data assert isinstance(pose_data["persons"], list) # Step 3: Zone assignment zone_summary = zone_manager.assign_persons_to_zones(pose_data["persons"]) assert isinstance(zone_summary, dict) assert all(isinstance(count, int) for count in zone_summary.values()) # Verify person zone assignments for person in pose_data["persons"]: if "zone_id" in person and person["zone_id"]: assert person["zone_id"] in zone_summary @pytest.mark.asyncio async def test_pipeline_state_consistency_should_fail_initially(self, pose_pipeline, sample_csi_data): """Test pipeline state consistency - should fail initially.""" # Process the same frame multiple times results = [] for _ in range(3): result = await pose_pipeline.process_frame(sample_csi_data) results.append(result) # This will fail initially # Results should be consistent (same input should produce similar output) assert len(results) == 3 # All results should have the same router_id router_ids = [r.metadata["router_id"] for r in results] assert all(rid == router_ids[0] for rid in router_ids) # Processing times should be reasonable and similar processing_times = [r.processing_time_ms for r in results] assert all(10 <= pt <= 200 for pt in processing_times) # Between 10ms and 200ms