"""
Batch processing functions for CSV file assessments
"""
from spatial_queries import get_terrain_metrics, distance_to_water
from vulnerability import calculate_vulnerability_index, calculate_multi_hazard_vulnerability
from height_predictor.inference import get_predictor
from height_predictor.get_height_gba import GlobalBuildingAtlasHeight

# Initialize GBA getter (singleton pattern)
gba_getter = GlobalBuildingAtlasHeight()


def process_single_row(row, use_predicted_height=False, use_gba_height=False):
    """Process a single row from CSV - used for parallel processing."""
    try:
        lat = row['latitude']
        lon = row['longitude']
        height = row.get('height', 0.0)
        basement = row.get('basement', 0.0)
        
        if use_gba_height:
            try:
                result = gba_getter.get_height_m(lat, lon, buffer_m=5.0)
                if result.get('status') == 'success' and result.get('predicted_height') is not None:
                    h = result['predicted_height']
                    if h >= 0:  # Only use valid positive heights
                        height = h
            except Exception as e:
                print(f"GBA height failed for {lat},{lon}: {e}")
        elif use_predicted_height:
            try:
                predictor = get_predictor()
                pred = predictor.predict_from_coordinates(lat, lon)
                if pred['status'] == 'success' and pred['predicted_height'] is not None:
                    height = pred['predicted_height']
            except Exception as e:
                print(f"Height prediction failed for {lat},{lon}: {e}")

        terrain = get_terrain_metrics(lat, lon)
        water_dist = distance_to_water(lat, lon)

        result = calculate_vulnerability_index(
            lat=lat,
            lon=lon,
            height=height,
            basement=basement,
            terrain_metrics=terrain,
            water_distance=water_dist
        )

        # CSV output - essential columns
        return {
            'latitude': lat,
            'longitude': lon,
            'height': height,
            'basement': basement,
            'vulnerability_index': result['vulnerability_index'],
            'ci_lower_95': result['confidence_interval']['lower_bound_95'],
            'ci_upper_95': result['confidence_interval']['upper_bound_95'],
            'vulnerability_level': result['risk_level'],
            'confidence': result['uncertainty_analysis']['confidence'],
            'confidence_interpretation': result['uncertainty_analysis']['interpretation'],
            'elevation_m': result['elevation_m'],
            'tpi_m': result['relative_elevation_m'],
            'slope_degrees': result['slope_degrees'],
            'distance_to_water_m': result['distance_to_water_m'],
            'quality_flags': ','.join(result['uncertainty_analysis']['data_quality_flags']) if result['uncertainty_analysis']['data_quality_flags'] else ''
        }

    except Exception as e:
        return {
            'latitude': row.get('latitude'),
            'longitude': row.get('longitude'),
            'height': row.get('height', 0.0),
            'basement': row.get('basement', 0.0),
            'error': str(e),
            'vulnerability_index': None,
            'ci_lower_95': None,
            'ci_upper_95': None,
            'risk_level': None,
            'confidence': None,
            'confidence_interpretation': None,
            'elevation_m': None,
            'tpi_m': None,
            'slope_degrees': None,
            'distance_to_water_m': None,
            'quality_flags': ''
        }


def process_single_row_multihazard(row, use_predicted_height=False, use_gba_height=False):
    """Process a single row with multi-hazard assessment."""
    try:
        lat = row['latitude']
        lon = row['longitude']
        height = row.get('height', 0.0)
        basement = row.get('basement', 0.0)

        if use_gba_height:
            try:
                result = gba_getter.get_height_m(lat, lon, buffer_m=5.0)
                if result.get('status') == 'success' and result.get('predicted_height') is not None:
                    h = result['predicted_height']
                    if h >= 0:  # Only use valid positive heights
                        height = h
            except Exception as e:
                print(f"GBA height failed for {lat},{lon}: {e}")
        elif use_predicted_height:
            try:
                predictor = get_predictor()
                pred = predictor.predict_from_coordinates(lat, lon)
                if pred['status'] == 'success' and pred['predicted_height'] is not None:
                    height = pred['predicted_height']
            except Exception as e:
                print(f"Height prediction failed for {lat},{lon}: {e}")

        terrain = get_terrain_metrics(lat, lon)
        water_dist = distance_to_water(lat, lon)

        result = calculate_multi_hazard_vulnerability(
            lat=lat,
            lon=lon,
            height=height,
            basement=basement,
            terrain_metrics=terrain,
            water_distance=water_dist
        )

        return {
            'latitude': lat,
            'longitude': lon,
            'height': height,
            'basement': basement,
            'vulnerability_index': result['vulnerability_index'],
            'ci_lower_95': result['confidence_interval']['lower_bound_95'],
            'ci_upper_95': result['confidence_interval']['upper_bound_95'],
            'vulnerability_level': result['risk_level'],
            'confidence': result['uncertainty_analysis']['confidence'],
            'confidence_interpretation': result['uncertainty_analysis']['interpretation'],
            'elevation_m': result['elevation_m'],
            'tpi_m': result['relative_elevation_m'],
            'slope_degrees': result['slope_degrees'],
            'distance_to_water_m': result['distance_to_water_m'],
            'dominant_hazard': result['dominant_hazard'],
            'fluvial_risk': result['hazard_breakdown']['fluvial_riverine'],
            'coastal_risk': result['hazard_breakdown']['coastal_surge'],
            'pluvial_risk': result['hazard_breakdown']['pluvial_drainage'],
            'combined_risk': result['hazard_breakdown']['combined_index'],
            'quality_flags': ','.join(result['uncertainty_analysis']['data_quality_flags'])
                     if result['uncertainty_analysis']['data_quality_flags'] else ''
        }

    except Exception as e:
        return {
            'latitude': row.get('latitude'),
            'longitude': row.get('longitude'),
            'height': row.get('height', 0.0),
            'basement': row.get('basement', 0.0),
            'error': str(e),
            'vulnerability_index': None
        }