"""HII gauge-rain aggregate: pure-function tests (no DB)."""

import numpy as np
import pandas as pd

from src.ml import hii_rain


def _hourly(start, n):
    return pd.date_range(start, periods=n, freq="h")


def test_compare_identical_series_has_zero_bias():
    idx = _hourly("2026-08-12", 200)
    rng = np.random.default_rng(1)
    rain = pd.Series(rng.exponential(0.5, len(idx)), index=idx)
    out = hii_rain.compare_with_openmeteo(rain, rain.copy(), window_h=24)
    assert out["overlap_hours"] == 200
    assert out["bias_mm"] == 0.0
    assert out["mae_mm"] == 0.0
    assert out["corr"] > 0.999


def test_compare_reports_constant_bias():
    idx = _hourly("2026-08-12", 100)
    gauge = pd.Series(1.0, index=idx)
    model = pd.Series(1.5, index=idx)  # model wetter by 0.5 mm/h
    out = hii_rain.compare_with_openmeteo(gauge, model, window_h=24)
    assert abs(out["bias_mm"] - 12.0) < 1e-9  # 0.5 mm/h x 24 h


def test_compare_uses_overlap_only():
    gauge = pd.Series(1.0, index=_hourly("2026-08-12", 100))
    model = pd.Series(1.0, index=_hourly("2026-08-14", 100))  # 52 h overlap
    out = hii_rain.compare_with_openmeteo(gauge, model, window_h=24)
    assert out["overlap_hours"] == 52


def test_compare_no_overlap():
    gauge = pd.Series(1.0, index=_hourly("2026-01-01", 10))
    model = pd.Series(1.0, index=_hourly("2026-06-01", 10))
    assert hii_rain.compare_with_openmeteo(gauge, model) == {"overlap_hours": 0}


def test_load_gauge_mean_without_db_returns_none(monkeypatch):
    monkeypatch.setattr(hii_rain, "resolve_db_url", lambda *a, **k: None)
    assert hii_rain.load_gauge_mean() is None