# Planned integration example
import speos
import os
from optixlog import Optixlog

# Initialize OptixLog
client = Optixlog(api_key=os.getenv("OPTIX_API_KEY"))
project = client.project(name="SPEOS_Simulations", create_if_not_exists=True)

# Create run with design parameters
run = project.run(
    name="headlamp_beam_pattern_v3",
    config={
        "tool": "Ansys SPEOS",
        "simulation_type": "Direct Simulation",
        "source": "LED_array",
        "num_rays": 10_000_000,
        "target_plane_distance": 25  # meters
    }
)

# Run SPEOS simulation
speos_session = speos.Session()
speos_session.load("headlamp_design.speos")
speos_session.run()

# Extract results
results = speos_session.get_results("illuminance_map")

# Log to OptixLog
run.log(step=0,
        max_illuminance=float(results["max_lux"]),
        min_illuminance=float(results["min_lux"]),
        uniformity_ratio=float(results["uniformity"]))

# Log visualization
run.log_matplotlib("beam_pattern", create_beam_plot(results))

# Track headlamp optimization
run = project.run(
    name="headlamp_optimization",
    config={
        "regulation": "ECE R112",
        "beam_type": "low_beam",
        "led_count": 48,
        "reflector_type": "freeform"
    }
)

# Log regulation compliance points
for point_name, measurement in regulation_points.items():
    run.log(step=0,
            point=point_name,
            required_lux=measurement["required"],
            measured_lux=measurement["actual"],
            compliant=measurement["actual"] >= measurement["required"])

run = project.run(
    name="interior_ambient_study",
    config={
        "vehicle": "SUV_2025",
        "time_of_day": "night",
        "ambient_mode": "relaxation"
    }
)

# Log human perception metrics
run.log(step=0,
        perceived_brightness=float(hv_results["brightness"]),
        color_uniformity=float(hv_results["delta_uv"]),
        glare_rating=float(hv_results["ugr"]))

run = project.run(
    name="lidar_validation",
    config={
        "sensor": "Velodyne_VLP16",
        "scenario": "urban_intersection",
        "weather": "rain_heavy"
    }
)

# Log detection performance
run.log(step=0,
        detection_range=float(results["max_range"]),
        point_density=float(results["points_per_deg"]),
        rain_attenuation_dB=float(results["attenuation"]))