import os
import platform
from pathlib import Path

from torchaudio.datasets import tedlium
from torchaudio_unittest.common_utils import (
    get_whitenoise,
    save_wav,
    skipIfNoSox,
    TempDirMixin,
    TorchaudioTestCase,
)

# Used to generate a unique utterance for each dummy audio file
_UTTERANCES = [
    "AaronHuey_2010X 1 AaronHuey_2010X 0.0 2.0 <o,f0,female> script1\n",
    "AaronHuey_2010X 1 AaronHuey_2010X 2.0 4.0 <o,f0,female> script2\n",
    "AaronHuey_2010X 1 AaronHuey_2010X 4.0 6.0 <o,f0,female> script3\n",
    "AaronHuey_2010X 1 AaronHuey_2010X 6.0 8.0 <o,f0,female> script4\n",
    "AaronHuey_2010X 1 AaronHuey_2010X 8.0 10.0 <o,f0,female> script5\n",
]

_PHONEME = [
    "a AH",
    "a(2) EY",
    "aachen AA K AH N",
    "aad AE D",
    "aaden EY D AH N",
    "aadmi AE D M IY",
    "aae EY EY",
]


def get_mock_dataset(dataset_dir):
    """
    dataset_dir: directory of the mocked dataset
    """
    mocked_samples = {}
    os.makedirs(dataset_dir, exist_ok=True)
    sample_rate = 16000  # 16kHz
    seed = 0

    for release in ["release1", "release2", "release3"]:
        data = get_whitenoise(sample_rate=sample_rate, duration=10.00, n_channels=1, dtype="float32", seed=seed)
        if release in ["release1", "release2"]:
            release_dir = os.path.join(
                dataset_dir,
                tedlium._RELEASE_CONFIGS[release]["folder_in_archive"],
                tedlium._RELEASE_CONFIGS[release]["subset"],
            )
        else:
            release_dir = os.path.join(
                dataset_dir,
                tedlium._RELEASE_CONFIGS[release]["folder_in_archive"],
                tedlium._RELEASE_CONFIGS[release]["data_path"],
            )
        os.makedirs(release_dir, exist_ok=True)
        os.makedirs(os.path.join(release_dir, "stm"), exist_ok=True)  # Subfolder for transcripts
        os.makedirs(os.path.join(release_dir, "sph"), exist_ok=True)  # Subfolder for audio files
        filename = f"{release}.sph"
        path = os.path.join(os.path.join(release_dir, "sph"), filename)
        save_wav(path, data, sample_rate)

        trans_filename = f"{release}.stm"
        trans_path = os.path.join(os.path.join(release_dir, "stm"), trans_filename)
        with open(trans_path, "w") as f:
            f.write("".join(_UTTERANCES))

        dict_filename = f"{release}.dic"
        dict_path = os.path.join(release_dir, dict_filename)
        with open(dict_path, "w") as f:
            f.write("\n".join(_PHONEME))

        # Create a samples list to compare with
        mocked_samples[release] = []
        for utterance in _UTTERANCES:
            talk_id, _, speaker_id, start_time, end_time, identifier, transcript = utterance.split(" ", 6)
            start_time = int(float(start_time)) * sample_rate
            end_time = int(float(end_time)) * sample_rate
            sample = (
                data[:, start_time:end_time],
                sample_rate,
                transcript,
                talk_id,
                speaker_id,
                identifier,
            )
            mocked_samples[release].append(sample)
        seed += 1
    return mocked_samples


class Tedlium(TempDirMixin):
    root_dir = None
    samples = {}

    @classmethod
    def setUpClass(cls):
        cls.root_dir = cls.get_base_temp_dir()
        cls.root_dir = dataset_dir = os.path.join(cls.root_dir, "tedlium")
        cls.samples = get_mock_dataset(dataset_dir)

    def _test_tedlium(self, dataset, release):
        num_samples = 0
        for i, (data, sample_rate, transcript, talk_id, speaker_id, identifier) in enumerate(dataset):
            self.assertEqual(data, self.samples[release][i][0], atol=5e-5, rtol=1e-8)
            assert sample_rate == self.samples[release][i][1]
            assert transcript == self.samples[release][i][2]
            assert talk_id == self.samples[release][i][3]
            assert speaker_id == self.samples[release][i][4]
            assert identifier == self.samples[release][i][5]
            num_samples += 1

        assert num_samples == len(self.samples[release])

        dataset._dict_path = os.path.join(dataset._path, f"{release}.dic")
        phoneme_dict = dataset.phoneme_dict
        phoenemes = [f"{key} {' '.join(value)}" for key, value in phoneme_dict.items()]
        assert phoenemes == _PHONEME

    def test_tedlium_release1_str(self):
        release = "release1"
        dataset = tedlium.TEDLIUM(self.root_dir, release=release)
        self._test_tedlium(dataset, release)

    def test_tedlium_release1_path(self):
        release = "release1"
        dataset = tedlium.TEDLIUM(Path(self.root_dir), release=release)
        self._test_tedlium(dataset, release)

    def test_tedlium_release2(self):
        release = "release2"
        dataset = tedlium.TEDLIUM(self.root_dir, release=release)
        self._test_tedlium(dataset, release)

    def test_tedlium_release3(self):
        release = "release3"
        dataset = tedlium.TEDLIUM(self.root_dir, release=release)
        self._test_tedlium(dataset, release)


class TestTedliumSoundfile(Tedlium, TorchaudioTestCase):
    backend = "soundfile"


if platform.system() != "Windows":

    @skipIfNoSox
    class TestTedliumSoxIO(Tedlium, TorchaudioTestCase):
        backend = "sox_io"
