import pytest
import pandas as pd
from datetime import datetime, timedelta
from src.core.workout_data import WorkoutData, WorkoutMetadata, PowerData, HeartRateData, SpeedData, ElevationData
from src.core.chart_generator import ChartGenerator

@pytest.fixture
def sample_workout_data():
    # Create dummy time-series data
    timestamps = pd.to_datetime([datetime(2025, 1, 1, 10, 0, 0) + timedelta(seconds=i) for i in range(600)])
    power = pd.Series([150 + 50 * (i % 10) for i in range(600)], index=timestamps)
    heart_rate = pd.Series([120 + 10 * (i % 5) for i in range(600)], index=timestamps)
    speed = pd.Series([5 + 2 * (i % 7) for i in range(600)], index=timestamps)
    altitude = pd.Series([100 + 10 * (i % 12) for i in range(600)], index=timestamps)

    time_series_data = pd.DataFrame({
        "power": power,
        "heart_rate": heart_rate,
        "speed": speed,
        "altitude": altitude
    })

    metadata = WorkoutMetadata(
        start_time=datetime(2025, 1, 1, 10, 0, 0),
        duration=timedelta(minutes=10),
        device="Garmin",
        file_type="FIT"
    )

    power_data = PowerData(
        raw_power_stream=power.tolist(),
        average_power=power.mean(),
        normalized_power=power.mean() * 1.05, # Dummy value
        intensity_factor=0.8,
        training_stress_score=50,
        zone_distribution={'Z1': 100, 'Z2': 200, 'Z3': 300}
    )

    heart_rate_data = HeartRateData(
        raw_hr_stream=heart_rate.tolist(),
        average_hr=heart_rate.mean(),
        max_hr=heart_rate.max(),
        zone_distribution={'Z1': 150, 'Z2': 250, 'Z3': 200}
    )

    speed_data = SpeedData(
        raw_speed_stream=speed.tolist(),
        average_speed=speed.mean(),
        max_speed=speed.max(),
        zone_distribution={'S1': 100, 'S2': 200, 'S3': 300}
    )

    elevation_data = ElevationData(
        raw_elevation_stream=altitude.tolist(),
        total_ascent=100,
        total_descent=50,
        max_elevation=200,
        min_elevation=50
    )

    return WorkoutData(
        metadata=metadata,
        time_series_data=time_series_data,
        power_data=power_data,
        heart_rate_data=heart_rate_data,
        speed_data=speed_data,
        elevation_data=elevation_data
    )

def test_generate_power_curve_chart(sample_workout_data, tmp_path):
    chart_generator = ChartGenerator(sample_workout_data)
    output_file = tmp_path / "power_curve.png"
    chart_generator.generate_power_curve_chart(output_file)
    assert output_file.exists()
    assert output_file.stat().st_size > 0

def test_generate_elevation_profile_chart(sample_workout_data, tmp_path):
    chart_generator = ChartGenerator(sample_workout_data)
    output_file = tmp_path / "elevation_profile.png"
    chart_generator.generate_elevation_profile_chart(output_file)
    assert output_file.exists()
    assert output_file.stat().st_size > 0

def test_generate_power_zone_distribution_chart(sample_workout_data, tmp_path):
    chart_generator = ChartGenerator(sample_workout_data)
    output_file = tmp_path / "power_zone_distribution.png"
    chart_generator.generate_zone_distribution_chart("power", output_file)
    assert output_file.exists()
    assert output_file.stat().st_size > 0

def test_generate_hr_zone_distribution_chart(sample_workout_data, tmp_path):
    chart_generator = ChartGenerator(sample_workout_data)
    output_file = tmp_path / "hr_zone_distribution.png"
    chart_generator.generate_zone_distribution_chart("heart_rate", output_file)
    assert output_file.exists()
    assert output_file.stat().st_size > 0

def test_generate_speed_zone_distribution_chart(sample_workout_data, tmp_path):
    chart_generator = ChartGenerator(sample_workout_data)
    output_file = tmp_path / "speed_zone_distribution.png"
    chart_generator.generate_zone_distribution_chart("speed", output_file)
    assert output_file.exists()
    assert output_file.stat().st_size > 0