import numpy as np
from conftest import sine, speechish

from producer import meters


def test_rms_and_peak_of_sine(sr):
    x = sine(1000, 3.0, sr, peak_dbfs=-17.0)
    assert abs(meters.rms_db(x) + 20.0) < 0.1
    assert abs(meters.sample_peak_db(x) + 17.0) < 0.05


def test_true_peak_bounds(sr):
    x = sine(1000, 3.0, sr, peak_dbfs=-17.0)
    tp = meters.true_peak_db(x, sr)
    sp = meters.sample_peak_db(x)
    assert sp - 0.01 <= tp <= sp + 0.6


def test_true_peak_blockwise_matches_whole_file(sr):
    from scipy import signal

    rng = np.random.default_rng(3)
    n = sr * 75
    x = (
        0.5 * np.sin(2 * np.pi * 997.0 * np.arange(n) / sr) + 0.02 * rng.standard_normal(n)
    ).astype(np.float32)
    half = 10 * 4
    h = signal.firwin(2 * half + 1, 0.25, window=("kaiser", 8.0)).astype(np.float32)
    ref = meters.sample_peak_db(signal.resample_poly(x, 4, 1, window=h))
    assert abs(meters.true_peak_db(x, sr) - ref) < 0.01


def test_lufs_of_sine(sr):
    x = sine(1000, 3.0, sr, peak_dbfs=-17.0)
    assert abs(meters.lufs(x, sr) + 20.05) < 0.2


def test_lufs_silence():
    assert meters.lufs(np.zeros(48000, dtype=np.float32), 48000) == meters.SILENCE_DB


def test_noise_floor_below_speech(sr):
    x = speechish(8.0, sr, level_dbfs=-20.0)
    floor = meters.noise_floor_db(x, sr)
    assert floor < meters.rms_db(x) - 4.0


def test_speech_level_db_ignores_leading_silence(sr):
    x = speechish(6.0, sr, level_dbfs=-20.0)
    y = np.concatenate([np.zeros(sr * 4, dtype=np.float32), x])
    assert abs(meters.speech_level_db(x, sr) - meters.speech_level_db(y, sr)) < 1.0
    assert meters.speech_level_db(x, sr) > meters.rms_db(x)


def test_all_meters_keys(sr):
    d = meters.all_meters(speechish(3.0, sr), sr)
    assert set(d) == {
        "rms_db",
        "sample_peak_db",
        "true_peak_db",
        "lufs",
        "noise_floor_db",
        "duration_s",
    }