# Copyright (C) 2025 AIDC-AI
# Tests for ObjectiveMetricsCalculator

import pytest
from pathlib import Path

from pixelle_video.services.quality.objective_metrics import (
    ObjectiveMetricsCalculator,
    TechnicalMetrics,
)


class TestTechnicalMetrics:
    """Tests for TechnicalMetrics dataclass"""

    def test_default_values(self):
        metrics = TechnicalMetrics()
        assert metrics.sharpness_score == 0.0
        assert metrics.overall_technical == 0.0
        assert metrics.issues == []

    def test_to_dict(self):
        metrics = TechnicalMetrics(
            sharpness_score=0.8,
            brightness_score=0.5,
            issues=["test issue"]
        )
        d = metrics.to_dict()
        assert d["sharpness_score"] == 0.8
        assert "test issue" in d["issues"]


class TestObjectiveMetricsCalculator:
    """Tests for ObjectiveMetricsCalculator"""

    def test_init_default(self):
        calc = ObjectiveMetricsCalculator()
        assert calc.sharpness_threshold == 0.3

    def test_init_custom(self):
        calc = ObjectiveMetricsCalculator(sharpness_threshold=0.5)
        assert calc.sharpness_threshold == 0.5

    def test_analyze_nonexistent_image(self):
        calc = ObjectiveMetricsCalculator()
        metrics = calc.analyze_image("/nonexistent/path.png")
        assert len(metrics.issues) > 0
        assert "failed" in metrics.issues[0].lower()

    def test_analyze_real_image(self, tmp_path):
        """Test with a real image file"""
        from PIL import Image

        # Create test image
        img = Image.new("RGB", (256, 256), color=(128, 128, 128))
        img_path = tmp_path / "test.png"
        img.save(img_path)

        calc = ObjectiveMetricsCalculator()
        metrics = calc.analyze_image(str(img_path))

        assert 0.0 <= metrics.sharpness_score <= 1.0
        assert 0.0 <= metrics.brightness_score <= 1.0
        assert 0.0 <= metrics.overall_technical <= 1.0