import pandas as pd
import pytest

from data_processing import classify_treatments, glucose_status, summarize_time_in_range


@pytest.fixture
def sample_glucose():
    return pd.DataFrame(
        {
            "timestamp": pd.to_datetime(
                ["2026-07-25 08:00", "2026-07-25 09:00", "2026-07-25 10:00", "2026-07-25 11:00"]
            ),
            "mmol": [3.5, 6.0, 11.0, 7.0],  # laag, in bereik, hoog, in bereik
        }
    )


@pytest.fixture
def sample_treatments():
    return pd.DataFrame(
        {
            "timestamp": pd.to_datetime(
                [
                    "2026-07-25 08:00",
                    "2026-07-25 12:00",
                    "2026-07-24 09:00",
                    "2026-07-20 09:00",
                ]
            ),
            "eventType": ["Meal Bolus", "Correction Bolus", "Site Change", "Sensor Change"],
            "insulin": [4.0, 1.5, None, None],
            "carbs": [45.0, None, None, None],
        }
    )


def test_glucose_status_classifies_correctly():
    assert glucose_status(3.5) == "low"
    assert glucose_status(6.0) == "in_range"
    assert glucose_status(11.0) == "high"


def test_summarize_time_in_range(sample_glucose):
    result = summarize_time_in_range(sample_glucose)
    assert result == {"low": 25.0, "in_range": 50.0, "high": 25.0}


def test_summarize_time_in_range_handles_empty_input():
    empty = pd.DataFrame(columns=["timestamp", "mmol"])
    result = summarize_time_in_range(empty)
    assert result == {"low": 0.0, "in_range": 0.0, "high": 0.0}


def test_classify_treatments_splits_into_expected_subsets(sample_treatments):
    events = classify_treatments(sample_treatments)

    assert len(events["insulin"]) == 2
    assert set(events["insulin"]["insulin"]) == {4.0, 1.5}

    assert len(events["carbs"]) == 1
    assert events["carbs"].iloc[0]["carbs"] == 45.0

    assert len(events["site_changes"]) == 1
    assert events["site_changes"].iloc[0]["eventType"] == "Site Change"

    assert len(events["sensor_changes"]) == 1
    assert events["sensor_changes"].iloc[0]["eventType"] == "Sensor Change"


def test_classify_treatments_handles_empty_input():
    empty = pd.DataFrame(columns=["timestamp", "eventType", "insulin", "carbs"])
    events = classify_treatments(empty)
    assert all(df.empty for df in events.values())