"""audio_problems: silence gap, clipped burst, level jump, clean signal."""
import sys
from pathlib import Path
import unittest

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from pydub import AudioSegment
from pydub.generators import Sine, Square

from core.audio import audio_problems

SR = 24000


def tone(ms, gain=-20):
    return Sine(300, sample_rate=SR).to_audio_segment(ms).apply_gain(gain)


def kinds(seg):
    return {p["kind"] for p in audio_problems(seg)}


class AudioProblemTests(unittest.TestCase):
    def test_clean(self):
        self.assertEqual(audio_problems(tone(4000, -18).set_frame_rate(SR)), [])

    def test_silence_gap(self):
        seg = tone(2000) + AudioSegment.silent(2000, frame_rate=SR) + tone(2000)
        p = [x for x in audio_problems(seg) if x["kind"] == "silence"]
        self.assertEqual(len(p), 1)
        self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)

    def test_edge_silence_ignored(self):
        seg = AudioSegment.silent(3000, frame_rate=SR) + tone(2000) + AudioSegment.silent(3000, frame_rate=SR)
        self.assertNotIn("silence", kinds(seg))

    def test_clipping(self):
        burst = Square(300, sample_rate=SR).to_audio_segment(400).apply_gain(+10)
        seg = tone(2000) + burst + tone(2000)
        p = [x for x in audio_problems(seg) if x["kind"] == "clipping"]
        self.assertTrue(p)
        self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)

    def test_level_jump(self):
        seg = tone(2000, -40) + tone(2000, -10)
        p = [x for x in audio_problems(seg) if x["kind"] == "level_jump"]
        self.assertEqual(len(p), 1)
        self.assertAlmostEqual(p[0]["start_s"], 2.0, delta=0.1)


class VoiceHealthTests(unittest.TestCase):
    def test_analyze_and_stored(self):
        import tempfile
        from core.voice import _voice_health, _validate_voice_meta
        with tempfile.TemporaryDirectory() as d:
            wav = Path(d) / "EN_F_test.wav"
            (tone(2000) + AudioSegment.silent(2000, frame_rate=SR) + tone(2000)).export(str(wav), format="wav")
            h = _voice_health(wav, meta={}, transcript="hi", duration=6.0, analyze=True)
            self.assertEqual([p["kind"] for p in h["problems"]], ["silence"])
            self.assertIn("Long silence in reference audio", h["warnings"])
            stored = _voice_health(wav, meta={"audio_problems": h["problems"]}, transcript="hi", duration=6.0)
            self.assertEqual(stored["problems"], h["problems"])
            self.assertEqual(_voice_health(wav, meta={}, transcript="hi", duration=6.0)["problems"], [])
            with self.assertRaises(ValueError):
                _validate_voice_meta({"audio_problems": "x"})


if __name__ == "__main__":
    unittest.main()