# ADAPTED from https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/paddlespeech/t2s/frontend/tone_sandhi.py
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import List
from typing import Tuple

import jieba
from pypinyin import lazy_pinyin
from pypinyin import Style

BU = '不'
YI = '一'
X_ENG = frozenset(['x', 'eng'])
class ToneSandhi():
    def __repr__(self):
        return "MandarinToneSandhi"

    def __init__(self):
        self.must_neural_tone_words = {
            '麻烦', '麻利', '鸳鸯', '高粱', '骨头', '骆驼', '马虎', '首饰', '馒头', '馄饨', '风筝',
            '难为', '队伍', '阔气', '闺女', '门道', '锄头', '铺盖', '铃铛', '铁匠', '钥匙', '里脊',
            '里头', '部分', '那么', '道士', '造化', '迷糊', '连累', '这么', '这个', '运气', '过去',
            '软和', '转悠', '踏实', '跳蚤', '跟头', '趔趄', '财主', '豆腐', '讲究', '记性', '记号',
            '认识', '规矩', '见识', '裁缝', '补丁', '衣裳', '衣服', '衙门', '街坊', '行李', '行当',
            '蛤蟆', '蘑菇', '薄荷', '葫芦', '葡萄', '萝卜', '荸荠', '苗条', '苗头', '苍蝇', '芝麻',
            '舒服', '舒坦', '舌头', '自在', '膏药', '脾气', '脑袋', '脊梁', '能耐', '胳膊', '胭脂',
            '胡萝', '胡琴', '胡同', '聪明', '耽误', '耽搁', '耷拉', '耳朵', '老爷', '老实', '老婆',
            '戏弄', '将军', '翻腾', '罗嗦', '罐头', '编辑', '结实', '红火', '累赘', '糨糊', '糊涂',
            '精神', '粮食', '簸箕', '篱笆', '算计', '算盘', '答应', '笤帚', '笑语', '笑话', '窟窿',
            '窝囊', '窗户', '稳当', '稀罕', '称呼', '秧歌', '秀气', '秀才', '福气', '祖宗', '砚台',
            '码头', '石榴', '石头', '石匠', '知识', '眼睛', '眯缝', '眨巴', '眉毛', '相声', '盘算',
            '白净', '痢疾', '痛快', '疟疾', '疙瘩', '疏忽', '畜生', '生意', '甘蔗', '琵琶', '琢磨',
            '琉璃', '玻璃', '玫瑰', '玄乎', '狐狸', '状元', '特务', '牲口', '牙碜', '牌楼', '爽快',
            '爱人', '热闹', '烧饼', '烟筒', '烂糊', '点心', '炊帚', '灯笼', '火候', '漂亮', '滑溜',
            '溜达', '温和', '清楚', '消息', '浪头', '活泼', '比方', '正经', '欺负', '模糊', '槟榔',
            '棺材', '棒槌', '棉花', '核桃', '栅栏', '柴火', '架势', '枕头', '枇杷', '机灵', '本事',
            '木头', '木匠', '朋友', '月饼', '月亮', '暖和', '明白', '时候', '新鲜', '故事', '收拾',
            '收成', '提防', '挖苦', '挑剔', '指甲', '指头', '拾掇', '拳头', '拨弄', '招牌', '招呼',
            '抬举', '护士', '折腾', '扫帚', '打量', '打算', '打扮', '打听', '打发', '扎实', '扁担',
            '戒指', '懒得', '意识', '意思', '悟性', '怪物', '思量', '怎么', '念头', '念叨', '别人',
            '快活', '忙活', '志气', '心思', '得罪', '张罗', '弟兄', '开通', '应酬', '庄稼', '干事',
            '帮手', '帐篷', '希罕', '师父', '师傅', '巴结', '巴掌', '差事', '工夫', '岁数', '屁股',
            '尾巴', '少爷', '小气', '小伙', '将就', '对头', '对付', '寡妇', '家伙', '客气', '实在',
            '官司', '学问', '字号', '嫁妆', '媳妇', '媒人', '婆家', '娘家', '委屈', '姑娘', '姐夫',
            '妯娌', '妥当', '妖精', '奴才', '女婿', '头发', '太阳', '大爷', '大方', '大意', '大夫',
            '多少', '多么', '外甥', '壮实', '地道', '地方', '在乎', '困难', '嘴巴', '嘱咐', '嘟囔',
            '嘀咕', '喜欢', '喇嘛', '喇叭', '商量', '唾沫', '哑巴', '哈欠', '哆嗦', '咳嗽', '和尚',
            '告诉', '告示', '含糊', '吓唬', '后头', '名字', '名堂', '合同', '吆喝', '叫唤', '口袋',
            '厚道', '厉害', '千斤', '包袱', '包涵', '匀称', '勤快', '动静', '动弹', '功夫', '力气',
            '前头', '刺猬', '刺激', '别扭', '利落', '利索', '利害', '分析', '出息', '凑合', '凉快',
            '冷战', '冤枉', '冒失', '养活', '关系', '先生', '兄弟', '便宜', '使唤', '佩服', '作坊',
            '体面', '位置', '似的', '伙计', '休息', '什么', '人家', '亲戚', '亲家', '交情', '云彩',
            '事情', '买卖', '主意', '丫头', '丧气', '两口', '东西', '东家', '世故', '不由', '下水',
            '下巴', '上头', '上司', '丈夫', '丈人', '一辈', '那个', '菩萨', '父亲', '母亲', '咕噜',
            '邋遢', '费用', '冤家', '甜头', '介绍', '荒唐', '大人', '泥鳅', '幸福', '熟悉', '计划',
            '扑腾', '蜡烛', '姥爷', '照顾', '喉咙', '吉他', '弄堂', '蚂蚱', '凤凰', '拖沓', '寒碜',
            '糟蹋', '倒腾', '报复', '逻辑', '盘缠', '喽啰', '牢骚', '咖喱', '扫把', '惦记'
        }
        self.must_not_neural_tone_words = {
            '男子', '女子', '分子', '原子', '量子', '莲子', '石子', '瓜子', '电子', '人人', '虎虎',
            '幺幺', '干嘛', '学子', '哈哈', '数数', '袅袅', '局地', '以下', '娃哈哈', '花花草草', '留得',
            '耕地', '想想', '熙熙', '攘攘', '卵子', '死死', '冉冉', '恳恳', '佼佼', '吵吵', '打打',
            '考考', '整整', '莘莘', '落地', '算子', '家家户户', '青青'
        }
        self.punc = "、：，；。？！“”‘’':,;.?!"

    def _split_word(self, word: str) -> List[str]:
        word_list = jieba.cut_for_search(word)
        word_list = sorted(word_list, key=lambda i: len(i), reverse=False)
        first_subword = word_list[0]
        first_begin_idx = word.find(first_subword)
        if first_begin_idx == 0:
            second_subword = word[len(first_subword):]
            new_word_list = [first_subword, second_subword]
        else:
            second_subword = word[:-len(first_subword)]
            new_word_list = [second_subword, first_subword]
        return new_word_list

    # the meaning of jieba pos tag: https://blog.csdn.net/weixin_44174352/article/details/113731041
    # e.g.
    # word: "家里"
    # pos: "s"
    # finals: ['ia1', 'i3']
    def _neural_sandhi(self, word: str, pos: str,
                       finals: List[str]) -> List[str]:
        if word in self.must_not_neural_tone_words:
            return finals
        # reduplication words for n. and v. e.g. 奶奶, 试试, 旺旺
        for j, item in enumerate(word):
            if j - 1 >= 0 and item == word[j - 1] and pos[0] in {"n", "v", "a"}:
                finals[j] = finals[j][:-1] + "5"
        ge_idx = word.find("个")
        if len(word) >= 1 and word[-1] in "吧呢啊呐噻嘛吖嗨呐哦哒滴哩哟喽啰耶喔诶":
            finals[-1] = finals[-1][:-1] + "5"
        elif len(word) >= 1 and word[-1] in "的地得":
            finals[-1] = finals[-1][:-1] + "5"
        # e.g. 走了, 看着, 去过
        elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}:
            finals[-1] = finals[-1][:-1] + "5"
        elif len(word) > 1 and word[-1] in "们子" and pos in {"r", "n"}:
            finals[-1] = finals[-1][:-1] + "5"
        # e.g. 桌上, 地下
        elif len(word) > 1 and word[-1] in "上下" and pos in {"s", "l", "f"}:
            finals[-1] = finals[-1][:-1] + "5"
        # e.g. 上来, 下去
        elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开":
            finals[-1] = finals[-1][:-1] + "5"
        # 个做量词
        elif (ge_idx >= 1 and
              (word[ge_idx - 1].isnumeric() or
               word[ge_idx - 1] in "几有两半多各整每做是")) or word == '个':
            finals[ge_idx] = finals[ge_idx][:-1] + "5"
        else:
            if word in self.must_neural_tone_words or word[
                    -2:] in self.must_neural_tone_words:
                finals[-1] = finals[-1][:-1] + "5"

        word_list = self._split_word(word)
        finals_list = [finals[:len(word_list[0])], finals[len(word_list[0]):]]
        for i, word in enumerate(word_list):
            # conventional neural in Chinese
            if word in self.must_neural_tone_words or word[
                    -2:] in self.must_neural_tone_words:
                finals_list[i][-1] = finals_list[i][-1][:-1] + "5"
        finals = sum(finals_list, [])
        return finals

    def _bu_sandhi(self, word: str, finals: List[str]) -> List[str]:
        # e.g. 看不懂
        if len(word) == 3 and word[1] == BU:
            finals[1] = finals[1][:-1] + "5"
        else:
            for i, char in enumerate(word):
                # "不" before tone4 should be bu2, e.g. 不怕
                if char == BU and i + 1 < len(word) and finals[i +
                                                                1][-1] == "4":
                    finals[i] = finals[i][:-1] + "2"
        return finals

    def _yi_sandhi(self, word: str, finals: List[str]) -> List[str]:
        # "一" in number sequences, e.g. 一零零, 二一零
        if word.find(YI) != -1 and all(
            [item.isnumeric() for item in word if item != YI]):
            return finals
        # "一" between reduplication words shold be yi5, e.g. 看一看
        elif len(word) == 3 and word[1] == YI and word[0] == word[-1]:
            finals[1] = finals[1][:-1] + "5"
        # when "一" is ordinal word, it should be yi1
        elif word.startswith("第一"):
            finals[1] = finals[1][:-1] + "1"
        else:
            for i, char in enumerate(word):
                if char == YI and i + 1 < len(word):
                    # "一" before tone4 should be yi2, e.g. 一段
                    if finals[i + 1][-1] in {'4', '5'}:
                        finals[i] = finals[i][:-1] + "2"
                    # "一" before non-tone4 should be yi4, e.g. 一天
                    else:
                        # "一" 后面如果是标点，还读一声
                        if word[i + 1] not in self.punc:
                            finals[i] = finals[i][:-1] + "4"
        return finals

    def _all_tone_three(self, finals: List[str]) -> bool:
        return all(x[-1] == "3" for x in finals)

    def _three_sandhi(self, word: str, finals: List[str]) -> List[str]:

        if len(word) == 2 and self._all_tone_three(finals):
            finals[0] = finals[0][:-1] + "2"
        elif len(word) == 3:
            word_list = self._split_word(word)
            if self._all_tone_three(finals):
                #  disyllabic + monosyllabic, e.g. 蒙古/包
                if len(word_list[0]) == 2:
                    finals[0] = finals[0][:-1] + "2"
                    finals[1] = finals[1][:-1] + "2"
                #  monosyllabic + disyllabic, e.g. 纸/老虎
                elif len(word_list[0]) == 1:
                    finals[1] = finals[1][:-1] + "2"
            else:
                finals_list = [
                    finals[:len(word_list[0])], finals[len(word_list[0]):]
                ]
                if len(finals_list) == 2:
                    for i, sub in enumerate(finals_list):
                        # e.g. 所有/人
                        if self._all_tone_three(sub) and len(sub) == 2:
                            finals_list[i][0] = finals_list[i][0][:-1] + "2"
                        # e.g. 好/喜欢
                        elif i == 1 and not self._all_tone_three(sub) and finals_list[i][0][-1] == "3" and \
                                finals_list[0][-1][-1] == "3":

                            finals_list[0][-1] = finals_list[0][-1][:-1] + "2"
                        finals = sum(finals_list, [])
        # split idiom into two words who's length is 2
        elif len(word) == 4:
            finals_list = [finals[:2], finals[2:]]
            finals = []
            for sub in finals_list:
                if self._all_tone_three(sub):
                    sub[0] = sub[0][:-1] + "2"
                finals += sub

        return finals

    # merge "不" and the word behind it
    # if don't merge, "不" sometimes appears alone according to jieba, which may occur sandhi error
    def _merge_bu(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        for i, (word, pos) in enumerate(seg):
            if pos not in X_ENG:
                last_word = None
                if i > 0:
                    last_word, _ = seg[i - 1]
                if last_word == BU:
                    word = last_word + word
            next_pos = None
            if i + 1 < len(seg):
                _, next_pos = seg[i + 1]
            if word != BU or next_pos is None or next_pos in X_ENG:
                new_seg.append((word, pos))
        return new_seg

    # function 1: merge "一" and reduplication words in it's left and right, e.g. "听","一","听" ->"听一听"
    # function 2: merge single  "一" and the word behind it
    # if don't merge, "一" sometimes appears alone according to jieba, which may occur sandhi error
    # e.g.
    # input seg: [('听', 'v'), ('一', 'm'), ('听', 'v')]
    # output seg: [['听一听', 'v']]
    def _merge_yi(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        skip_next = False
        # function 1
        for i, (word, pos) in enumerate(seg):
            if skip_next:
                skip_next = False
                continue
            if i - 1 >= 0 and word == YI and i + 1 < len(seg) and seg[i - 1][
                    0] == seg[i + 1][0] and seg[i - 1][1] == "v" and seg[
                    i + 1][1] not in X_ENG:
                new_seg[-1] = (new_seg[-1][0] + YI + seg[i + 1][0],
                               new_seg[-1][1])
                skip_next = True
            else:
                new_seg.append((word, pos))
        seg = new_seg
        new_seg = []
        # function 2
        for i, (word, pos) in enumerate(seg):
            if new_seg and new_seg[-1][0] == YI and pos not in X_ENG:
                new_seg[-1] = (new_seg[-1][0] + word, new_seg[-1][1])
            else:
                new_seg.append((word, pos))
        return new_seg

    # the first and the second words are all_tone_three
    def _merge_continuous_three_tones(
            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        sub_finals_list = []
        for (word, pos) in seg:
            if pos in X_ENG:
                sub_finals_list.append(['0'])
                continue
            orig_finals = lazy_pinyin(
                word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
            # after pypinyin==0.44.0, '嗯' need to be n2, cause the initial and final consonants cannot be empty at the same time
            en_index = [index for index, c in enumerate(word) if c == "嗯"]
            for i in en_index:
                orig_finals[i] = "n2"
            sub_finals_list.append(orig_finals)

        assert len(sub_finals_list) == len(seg)
        merge_last = [False] * len(seg)
        for i, (word, pos) in enumerate(seg):
            if pos not in X_ENG and i - 1 >= 0 and self._all_tone_three(
                    sub_finals_list[i - 1]) and self._all_tone_three(
                        sub_finals_list[i]) and not merge_last[i - 1]:
                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
                if not self._is_reduplication(seg[i - 1][0]) and len(
                        seg[i - 1][0]) + len(seg[i][0]) <= 3:
                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
                    merge_last[i] = True
                else:
                    new_seg.append([word, pos])
            else:
                new_seg.append([word, pos])

        return new_seg

    def _is_reduplication(self, word: str) -> bool:
        return len(word) == 2 and word[0] == word[1]

    # the last char of first word and the first char of second word is tone_three
    def _merge_continuous_three_tones_2(
            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        sub_finals_list = []
        for (word, pos) in seg:
            if pos in X_ENG:
                sub_finals_list.append(['0'])
                continue
            orig_finals = lazy_pinyin(
                word, neutral_tone_with_five=True, style=Style.FINALS_TONE3)
            # after pypinyin==0.44.0, '嗯' need to be n2, cause the initial and final consonants cannot be empty at the same time
            en_index = [index for index, c in enumerate(word) if c == "嗯"]
            for i in en_index:
                orig_finals[i] = "n2"
            sub_finals_list.append(orig_finals)
        assert len(sub_finals_list) == len(seg)
        merge_last = [False] * len(seg)
        for i, (word, pos) in enumerate(seg):
            if pos not in X_ENG and i - 1 >= 0 and \
                    sub_finals_list[i - 1][-1][-1] == "3" and \
                    sub_finals_list[i][0][-1] == "3" and not \
                    merge_last[i - 1]:
                # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi
                if not self._is_reduplication(seg[i - 1][0]) and len(
                        seg[i - 1][0]) + len(seg[i][0]) <= 3:
                    new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
                    merge_last[i] = True
                else:
                    new_seg.append([word, pos])
            else:
                new_seg.append([word, pos])
        return new_seg

    def _merge_er(self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        for i, (word, pos) in enumerate(seg):
            if i - 1 >= 0 and word == "儿" and new_seg[-1][1] not in X_ENG:
                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
            else:
                new_seg.append([word, pos])
        return new_seg

    def _merge_reduplication(
            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        new_seg = []
        for i, (word, pos) in enumerate(seg):
            if new_seg and word == new_seg[-1][0] and pos not in X_ENG:
                new_seg[-1][0] = new_seg[-1][0] + seg[i][0]
            else:
                new_seg.append([word, pos])
        return new_seg

    def pre_merge_for_modify(
            self, seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
        """
            seg: [(word, pos), ...]
        """
        seg = self._merge_bu(seg)
        seg = self._merge_yi(seg)
        seg = self._merge_reduplication(seg)
        seg = self._merge_continuous_three_tones(seg)
        seg = self._merge_continuous_three_tones_2(seg)
        seg = self._merge_er(seg)
        return seg

    def modified_tone(self, word: str, pos: str,
                      finals: List[str]) -> List[str]:
        """
            word: 分词
            pos: 词性
            finals: 带调韵母, [final1, ..., finaln]
        """
        finals = self._bu_sandhi(word, finals)
        finals = self._yi_sandhi(word, finals)
        finals = self._neural_sandhi(word, pos, finals)
        finals = self._three_sandhi(word, finals)
        return finals
