import pytest
import math
from src.calculation_target_reliability.service import calculate_asset_eaf_contributions

def test_calculate_asset_eaf_contributions_basic():
    # Mock plant result
    plant_result = {
        "total_uptime": 7000,
        "total_downtime": 1000,
        "eaf": 85.0
    }
    # total_hours = 8000
    
    # Mock equipment results
    eq_results = [
        {
            "aeros_node": {"node_name": "Asset1"},
            "num_events": 5,
            "contribution_factor": 0.5,
            "contribution": 0.1, # Birnbaum
            "availability": 0.9,
            "total_downtime": 100
        },
        {
            "aeros_node": {"node_name": "Asset2"},
            "num_events": 2,
            "contribution_factor": 0.3,
            "contribution": 0.05,
            "availability": 0.95,
            "total_downtime": 50
        }
    ]
    
    standard_scope = ["Asset1", "Asset2"]
    eaf_gap = 2.0 # 2% gap
    scheduled_outage = 500
    
    results = calculate_asset_eaf_contributions(
        plant_result, eq_results, standard_scope, eaf_gap, scheduled_outage
    )
    
    assert len(results) == 2
    # Check sorting (highest birnbaum first)
    assert results[0].node["node_name"] == "Asset1"
    assert results[0].birbaum > results[1].birbaum
    
    # Check that required_improvement is positive
    assert results[0].required_improvement > 0
    assert results[0].improvement_impact > 0

def test_calculate_asset_eaf_contributions_skipping():
    plant_result = {"total_uptime": 1000, "total_downtime": 0, "eaf": 100}
    eq_results = [{
        "aeros_node": {"node_name": "Asset1"},
        "num_events": 0, 
        "contribution_factor": 0.5,
        "contribution": 0.1,
        "availability": 1.0,
        "total_downtime": 0
    }]
    results = calculate_asset_eaf_contributions(
        plant_result, eq_results, ["Asset1"], 1.0, 0
    )
    assert len(results) == 0