# Convert Japanese text to phonemes which is
# compatible with Julius https://github.com/julius-speech/segmentation-kit
import re
import unicodedata

from transformers import AutoTokenizer

from text import punctuation, symbols

try:
    import MeCab
except ImportError as e:
    raise ImportError("Japanese requires mecab-python3 and unidic-lite.") from e
from num2words import num2words

_CONVRULES = [
    # Conversion of 2 letters
    "アァ/ a a",
    "イィ/ i i",
    "イェ/ i e",
    "イャ/ y a",
    "ウゥ/ u:",
    "エェ/ e e",
    "オォ/ o:",
    "カァ/ k a:",
    "キィ/ k i:",
    "クゥ/ k u:",
    "クャ/ ky a",
    "クュ/ ky u",
    "クョ/ ky o",
    "ケェ/ k e:",
    "コォ/ k o:",
    "ガァ/ g a:",
    "ギィ/ g i:",
    "グゥ/ g u:",
    "グャ/ gy a",
    "グュ/ gy u",
    "グョ/ gy o",
    "ゲェ/ g e:",
    "ゴォ/ g o:",
    "サァ/ s a:",
    "シィ/ sh i:",
    "スゥ/ s u:",
    "スャ/ sh a",
    "スュ/ sh u",
    "スョ/ sh o",
    "セェ/ s e:",
    "ソォ/ s o:",
    "ザァ/ z a:",
    "ジィ/ j i:",
    "ズゥ/ z u:",
    "ズャ/ zy a",
    "ズュ/ zy u",
    "ズョ/ zy o",
    "ゼェ/ z e:",
    "ゾォ/ z o:",
    "タァ/ t a:",
    "チィ/ ch i:",
    "ツァ/ ts a",
    "ツィ/ ts i",
    "ツゥ/ ts u:",
    "ツャ/ ch a",
    "ツュ/ ch u",
    "ツョ/ ch o",
    "ツェ/ ts e",
    "ツォ/ ts o",
    "テェ/ t e:",
    "トォ/ t o:",
    "ダァ/ d a:",
    "ヂィ/ j i:",
    "ヅゥ/ d u:",
    "ヅャ/ zy a",
    "ヅュ/ zy u",
    "ヅョ/ zy o",
    "デェ/ d e:",
    "ドォ/ d o:",
    "ナァ/ n a:",
    "ニィ/ n i:",
    "ヌゥ/ n u:",
    "ヌャ/ ny a",
    "ヌュ/ ny u",
    "ヌョ/ ny o",
    "ネェ/ n e:",
    "ノォ/ n o:",
    "ハァ/ h a:",
    "ヒィ/ h i:",
    "フゥ/ f u:",
    "フャ/ hy a",
    "フュ/ hy u",
    "フョ/ hy o",
    "ヘェ/ h e:",
    "ホォ/ h o:",
    "バァ/ b a:",
    "ビィ/ b i:",
    "ブゥ/ b u:",
    "フャ/ hy a",
    "ブュ/ by u",
    "フョ/ hy o",
    "ベェ/ b e:",
    "ボォ/ b o:",
    "パァ/ p a:",
    "ピィ/ p i:",
    "プゥ/ p u:",
    "プャ/ py a",
    "プュ/ py u",
    "プョ/ py o",
    "ペェ/ p e:",
    "ポォ/ p o:",
    "マァ/ m a:",
    "ミィ/ m i:",
    "ムゥ/ m u:",
    "ムャ/ my a",
    "ムュ/ my u",
    "ムョ/ my o",
    "メェ/ m e:",
    "モォ/ m o:",
    "ヤァ/ y a:",
    "ユゥ/ y u:",
    "ユャ/ y a:",
    "ユュ/ y u:",
    "ユョ/ y o:",
    "ヨォ/ y o:",
    "ラァ/ r a:",
    "リィ/ r i:",
    "ルゥ/ r u:",
    "ルャ/ ry a",
    "ルュ/ ry u",
    "ルョ/ ry o",
    "レェ/ r e:",
    "ロォ/ r o:",
    "ワァ/ w a:",
    "ヲォ/ o:",
    "ディ/ d i",
    "デェ/ d e:",
    "デャ/ dy a",
    "デュ/ dy u",
    "デョ/ dy o",
    "ティ/ t i",
    "テェ/ t e:",
    "テャ/ ty a",
    "テュ/ ty u",
    "テョ/ ty o",
    "スィ/ s i",
    "ズァ/ z u a",
    "ズィ/ z i",
    "ズゥ/ z u",
    "ズャ/ zy a",
    "ズュ/ zy u",
    "ズョ/ zy o",
    "ズェ/ z e",
    "ズォ/ z o",
    "キャ/ ky a",
    "キュ/ ky u",
    "キョ/ ky o",
    "シャ/ sh a",
    "シュ/ sh u",
    "シェ/ sh e",
    "ショ/ sh o",
    "チャ/ ch a",
    "チュ/ ch u",
    "チェ/ ch e",
    "チョ/ ch o",
    "トゥ/ t u",
    "トャ/ ty a",
    "トュ/ ty u",
    "トョ/ ty o",
    "ドァ/ d o a",
    "ドゥ/ d u",
    "ドャ/ dy a",
    "ドュ/ dy u",
    "ドョ/ dy o",
    "ドォ/ d o:",
    "ニャ/ ny a",
    "ニュ/ ny u",
    "ニョ/ ny o",
    "ヒャ/ hy a",
    "ヒュ/ hy u",
    "ヒョ/ hy o",
    "ミャ/ my a",
    "ミュ/ my u",
    "ミョ/ my o",
    "リャ/ ry a",
    "リュ/ ry u",
    "リョ/ ry o",
    "ギャ/ gy a",
    "ギュ/ gy u",
    "ギョ/ gy o",
    "ヂェ/ j e",
    "ヂャ/ j a",
    "ヂュ/ j u",
    "ヂョ/ j o",
    "ジェ/ j e",
    "ジャ/ j a",
    "ジュ/ j u",
    "ジョ/ j o",
    "ビャ/ by a",
    "ビュ/ by u",
    "ビョ/ by o",
    "ピャ/ py a",
    "ピュ/ py u",
    "ピョ/ py o",
    "ウァ/ u a",
    "ウィ/ w i",
    "ウェ/ w e",
    "ウォ/ w o",
    "ファ/ f a",
    "フィ/ f i",
    "フゥ/ f u",
    "フャ/ hy a",
    "フュ/ hy u",
    "フョ/ hy o",
    "フェ/ f e",
    "フォ/ f o",
    "ヴァ/ b a",
    "ヴィ/ b i",
    "ヴェ/ b e",
    "ヴォ/ b o",
    "ヴュ/ by u",
    "アー/ a:",
    "イー/ i:",
    "ウー/ u:",
    "エー/ e:",
    "オー/ o:",
    "カー/ k a:",
    "キー/ k i:",
    "クー/ k u:",
    "ケー/ k e:",
    "コー/ k o:",
    "サー/ s a:",
    "シー/ sh i:",
    "スー/ s u:",
    "セー/ s e:",
    "ソー/ s o:",
    "ター/ t a:",
    "チー/ ch i:",
    "ツー/ ts u:",
    "テー/ t e:",
    "トー/ t o:",
    "ナー/ n a:",
    "ニー/ n i:",
    "ヌー/ n u:",
    "ネー/ n e:",
    "ノー/ n o:",
    "ハー/ h a:",
    "ヒー/ h i:",
    "フー/ f u:",
    "ヘー/ h e:",
    "ホー/ h o:",
    "マー/ m a:",
    "ミー/ m i:",
    "ムー/ m u:",
    "メー/ m e:",
    "モー/ m o:",
    "ラー/ r a:",
    "リー/ r i:",
    "ルー/ r u:",
    "レー/ r e:",
    "ロー/ r o:",
    "ガー/ g a:",
    "ギー/ g i:",
    "グー/ g u:",
    "ゲー/ g e:",
    "ゴー/ g o:",
    "ザー/ z a:",
    "ジー/ j i:",
    "ズー/ z u:",
    "ゼー/ z e:",
    "ゾー/ z o:",
    "ダー/ d a:",
    "ヂー/ j i:",
    "ヅー/ z u:",
    "デー/ d e:",
    "ドー/ d o:",
    "バー/ b a:",
    "ビー/ b i:",
    "ブー/ b u:",
    "ベー/ b e:",
    "ボー/ b o:",
    "パー/ p a:",
    "ピー/ p i:",
    "プー/ p u:",
    "ペー/ p e:",
    "ポー/ p o:",
    "ヤー/ y a:",
    "ユー/ y u:",
    "ヨー/ y o:",
    "ワー/ w a:",
    "ヰー/ i:",
    "ヱー/ e:",
    "ヲー/ o:",
    "ヴー/ b u:",
    # Conversion of 1 letter
    "ア/ a",
    "イ/ i",
    "ウ/ u",
    "エ/ e",
    "オ/ o",
    "カ/ k a",
    "キ/ k i",
    "ク/ k u",
    "ケ/ k e",
    "コ/ k o",
    "サ/ s a",
    "シ/ sh i",
    "ス/ s u",
    "セ/ s e",
    "ソ/ s o",
    "タ/ t a",
    "チ/ ch i",
    "ツ/ ts u",
    "テ/ t e",
    "ト/ t o",
    "ナ/ n a",
    "ニ/ n i",
    "ヌ/ n u",
    "ネ/ n e",
    "ノ/ n o",
    "ハ/ h a",
    "ヒ/ h i",
    "フ/ f u",
    "ヘ/ h e",
    "ホ/ h o",
    "マ/ m a",
    "ミ/ m i",
    "ム/ m u",
    "メ/ m e",
    "モ/ m o",
    "ラ/ r a",
    "リ/ r i",
    "ル/ r u",
    "レ/ r e",
    "ロ/ r o",
    "ガ/ g a",
    "ギ/ g i",
    "グ/ g u",
    "ゲ/ g e",
    "ゴ/ g o",
    "ザ/ z a",
    "ジ/ j i",
    "ズ/ z u",
    "ゼ/ z e",
    "ゾ/ z o",
    "ダ/ d a",
    "ヂ/ j i",
    "ヅ/ z u",
    "デ/ d e",
    "ド/ d o",
    "バ/ b a",
    "ビ/ b i",
    "ブ/ b u",
    "ベ/ b e",
    "ボ/ b o",
    "パ/ p a",
    "ピ/ p i",
    "プ/ p u",
    "ペ/ p e",
    "ポ/ p o",
    "ヤ/ y a",
    "ユ/ y u",
    "ヨ/ y o",
    "ワ/ w a",
    "ヰ/ i",
    "ヱ/ e",
    "ヲ/ o",
    "ン/ N",
    "ッ/ q",
    "ヴ/ b u",
    "ー/:", #这个不起作用
    # Try converting broken text
    "ァ/ a",
    "ィ/ i",
    "ゥ/ u",
    "ェ/ e",
    "ォ/ o",
    "ヮ/ w a",
    "ォ/ o",
    # Symbols
    "、/ ,",
    "。/ .",
    "！/ !",
    "？/ ?",
    "・/ ,",
]

_COLON_RX = re.compile(":+")
_REJECT_RX = re.compile("[^ a-zA-Z:,.?]")


def _makerulemap():
    l = [tuple(x.split("/")) for x in _CONVRULES]
    return tuple({k: v for k, v in l if len(k) == i} for i in (1, 2))


_RULEMAP1, _RULEMAP2 = _makerulemap()


def kata2phoneme(text: str) -> str:
    """Convert katakana text to phonemes."""
    text = text.strip()
    res = []
    while text:
        if len(text) >= 2:
            x = _RULEMAP2.get(text[:2])
            if x is not None:
                text = text[2:]
                res += x.split(" ")[1:]
                continue
        x = _RULEMAP1.get(text[0])
        if x is not None:
            text = text[1:]
            res += x.split(" ")[1:]
            continue
        res.append(text[0])
        text = text[1:]
    # res = _COLON_RX.sub(":", res)
    return res


_KATAKANA = "".join(chr(ch) for ch in range(ord("ァ"), ord("ン") + 1))
_HIRAGANA = "".join(chr(ch) for ch in range(ord("ぁ"), ord("ん") + 1))
_HIRA2KATATRANS = str.maketrans(_HIRAGANA, _KATAKANA)


def hira2kata(text: str) -> str:
    text = text.translate(_HIRA2KATATRANS)
    return text.replace("う゛", "ヴ")


_SYMBOL_TOKENS = set(list("・、。？！"))
_NO_YOMI_TOKENS = set(list("「」『』―（）［］[]"))
_TAGGER = MeCab.Tagger()


def text2kata(text: str) -> str:
    parsed = _TAGGER.parse(text)
    res = []
    for line in parsed.split("\n"):
        if line == "EOS":
            break
        parts = line.split("\t")

        word, yomi = parts[0], parts[1]
        if yomi:
            res.append(yomi)
        else:
            if word in _SYMBOL_TOKENS:
                res.append(word)
            elif word in ("っ", "ッ"):
                res.append("ッ")
            elif word in _NO_YOMI_TOKENS:
                pass
            else:
                res.append(word)
    return hira2kata("".join(res))


def text2sep_kata(text: str) -> (list, list):
    parsed = _TAGGER.parse(text)
    res = []
    sep = []
    for line in parsed.split("\n"):
        if line == "EOS":
            break
        parts = line.split("\t")

        word, yomi = parts[0], parts[1]
        if yomi:
            res.append(yomi)
        else:
            if word in _SYMBOL_TOKENS:
                res.append(word)
            elif word in ("っ", "ッ"):
                res.append("ッ")
            elif word in _NO_YOMI_TOKENS:
                pass
            else:
                res.append(word)
        sep.append(word)
    return sep, [hira2kata(i) for i in res]


_ALPHASYMBOL_YOMI = {
    "#": "シャープ",
    "%": "パーセント",
    "&": "アンド",
    "+": "プラス",
    "-": "マイナス",
    ":": "コロン",
    ";": "セミコロン",
    "<": "小なり",
    "=": "イコール",
    ">": "大なり",
    "@": "アット",
    "a": "エー",
    "b": "ビー",
    "c": "シー",
    "d": "ディー",
    "e": "イー",
    "f": "エフ",
    "g": "ジー",
    "h": "エイチ",
    "i": "アイ",
    "j": "ジェー",
    "k": "ケー",
    "l": "エル",
    "m": "エム",
    "n": "エヌ",
    "o": "オー",
    "p": "ピー",
    "q": "キュー",
    "r": "アール",
    "s": "エス",
    "t": "ティー",
    "u": "ユー",
    "v": "ブイ",
    "w": "ダブリュー",
    "x": "エックス",
    "y": "ワイ",
    "z": "ゼット",
    "α": "アルファ",
    "β": "ベータ",
    "γ": "ガンマ",
    "δ": "デルタ",
    "ε": "イプシロン",
    "ζ": "ゼータ",
    "η": "イータ",
    "θ": "シータ",
    "ι": "イオタ",
    "κ": "カッパ",
    "λ": "ラムダ",
    "μ": "ミュー",
    "ν": "ニュー",
    "ξ": "クサイ",
    "ο": "オミクロン",
    "π": "パイ",
    "ρ": "ロー",
    "σ": "シグマ",
    "τ": "タウ",
    "υ": "ウプシロン",
    "φ": "ファイ",
    "χ": "カイ",
    "ψ": "プサイ",
    "ω": "オメガ",
}


_NUMBER_WITH_SEPARATOR_RX = re.compile("[0-9]{1,3}(,[0-9]{3})+")
_CURRENCY_MAP = {"$": "ドル", "¥": "円", "£": "ポンド", "€": "ユーロ"}
_CURRENCY_RX = re.compile(r"([$¥£€])([0-9.]*[0-9])")
_NUMBER_RX = re.compile(r"[0-9]+(\.[0-9]+)?")


def japanese_convert_numbers_to_words(text: str) -> str:
    res = _NUMBER_WITH_SEPARATOR_RX.sub(lambda m: m[0].replace(",", ""), text)
    res = _CURRENCY_RX.sub(lambda m: m[2] + _CURRENCY_MAP.get(m[1], m[1]), res)
    res = _NUMBER_RX.sub(lambda m: num2words(m[0], lang="ja"), res)
    return res


def japanese_convert_alpha_symbols_to_words(text: str) -> str:
    return "".join([_ALPHASYMBOL_YOMI.get(ch, ch) for ch in text.lower()])


def japanese_text_to_phonemes(text: str) -> str:
    """Convert Japanese text to phonemes."""
    res = unicodedata.normalize("NFKC", text)
    res = japanese_convert_numbers_to_words(res)
    # res = japanese_convert_alpha_symbols_to_words(res)
    res = text2kata(res)
    res = kata2phoneme(res)
    return res


def is_japanese_character(char):
    # 定义日语文字系统的 Unicode 范围
    japanese_ranges = [
        (0x3040, 0x309F),  # 平假名
        (0x30A0, 0x30FF),  # 片假名
        (0x4E00, 0x9FFF),  # 汉字 (CJK Unified Ideographs)
        (0x3400, 0x4DBF),  # 汉字扩展 A
        (0x20000, 0x2A6DF),  # 汉字扩展 B
        # 可以根据需要添加其他汉字扩展范围
    ]

    # 将字符的 Unicode 编码转换为整数
    char_code = ord(char)

    # 检查字符是否在任何一个日语范围内
    for start, end in japanese_ranges:
        if start <= char_code <= end:
            return True

    return False


rep_map = {
    "：": ",",
    "；": ",",
    "，": ",",
    "。": ".",
    "！": "!",
    "？": "?",
    "\n": ".",
    "·": ",",
    "、": ",",
    "…": "...",
}


def replace_punctuation(text):
    pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys()))

    replaced_text = pattern.sub(lambda x: rep_map[x.group()], text)

    replaced_text = re.sub(
        r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF"
        + "".join(punctuation)
        + r"]+",
        "",
        replaced_text,
    )

    return replaced_text


def text_normalize(text):
    res = unicodedata.normalize("NFKC", text)
    res = japanese_convert_numbers_to_words(res)
    # res = "".join([i for i in res if is_japanese_character(i)])
    res = replace_punctuation(res)
    return res


def distribute_phone(n_phone, n_word):
    phones_per_word = [0] * n_word
    for task in range(n_phone):
        min_tasks = min(phones_per_word)
        min_index = phones_per_word.index(min_tasks)
        phones_per_word[min_index] += 1
    return phones_per_word


tokenizer = AutoTokenizer.from_pretrained("./bert/bert-base-japanese-v3")


def g2p(norm_text):
    sep_text, sep_kata = text2sep_kata(norm_text)
    sep_tokenized = [tokenizer.tokenize(i) for i in sep_text]
    sep_phonemes = [kata2phoneme(i) for i in sep_kata]
    # 异常处理，MeCab不认识的词的话会一路传到这里来，然后炸掉。目前来看只有那些超级稀有的生僻词会出现这种情况
    for i in sep_phonemes:
        for j in i:
            assert j in symbols, (sep_text, sep_kata, sep_phonemes)

    word2ph = []
    for token, phoneme in zip(sep_tokenized, sep_phonemes):
        phone_len = len(phoneme)
        word_len = len(token)

        aaa = distribute_phone(phone_len, word_len)
        word2ph += aaa
    phones = ["_"] + [j for i in sep_phonemes for j in i] + ["_"]
    tones = [0 for i in phones]
    word2ph = [1] + word2ph + [1]
    return phones, tones, word2ph

if __name__ == "__main__":
    tokenizer = AutoTokenizer.from_pretrained("./bert/bert-base-japanese-v3")
    text = "だったら私、スズカさんと同じチームに入りたいです！ スズカさんの走りを毎日近くで、なんなら真横から見ていたいので！"
    #print(_TAGGER.parse(text))
   # nodes = [{"surface": "こんにちは", "pos": "感動詞:*:*:*", "pron": "コンニチワ", "c_type": "*", "c_form": "*", "accent_type": 0, "accent_con_type": "-1", "chain_flag": -1}]
    nodes = [{"surface":"こんにちは","pron": "コンニチワ","pos": "感動詞:*:*:*",}]
    from text.japanese_bert import get_bert_feature
    import pyopenjtalk
    from marine.predict import Predictor
    from marine.utils.openjtalk_util import convert_njd_feature_to_marine_feature
    text = text_normalize(text)
    NJD_NODES = pyopenjtalk.run_frontend(text)
    predictor = Predictor()
 #   important_info = [{"string":i["string"],"pron":i["pron"],"acc":i["acc"]}for i in pyopenjtalk.estimate_accent(NJD_NODES)]
    print(text)
    
    marine_feature = convert_njd_feature_to_marine_feature(NJD_NODES)
    results = predictor.predict([marine_feature])
    for mora,acc in zip(results["mora"][0],results["accent_status"][0]):
        print(f"{mora}:{acc}")
    # for i in pyopenjtalk.estimate_accent(NJD_NODES):
    #     print(f"{i['string']}:{i['pron']}:{i['acc']}")
#     info = pyopenjtalk.extract_fullcontext(text,run_marine=True)
#     info_nomarine = pyopenjtalk.extract_fullcontext(text,run_marine=False)
#    # nodes = pyopenjtalk
#    # print(info)
#     for i,j in zip(info,info_nomarine):
#         print(i)
#         print(j)
#         print("\n")
    # predictor = Predictor()
    #print(pyopenjtalk.estimate_accent(text))
    # output = predictor.predict([nodes],accent_represent_mode="high_low")
    #print(output)
    # phones, tones, word2ph = g2p(text)
    # bert = get_bert_feature(text, word2ph)

    # print(phones, tones, word2ph, bert.shape)