#!/usr/bin/env python3
"""测试修复后的算法是否解决重叠边界问题"""

import sys
sys.path.append('.')

# 模拟spaCy的Doc对象
class MockDoc:
    def __init__(self, text, tokens):
        self.text = text
        self._tokens = tokens
    
    def __len__(self):
        return len(self._tokens)
    
    def __getitem__(self, key):
        if isinstance(key, slice):
            start, stop, step = key.indices(len(self._tokens))
            tokens = self._tokens[start:stop:step] if step else self._tokens[start:stop]
            text = ''.join(tokens)
            return MockDoc(text, tokens)
        else:
            return self._tokens[key]

def proportionally_split_source(source_doc, translated_parts_docs):
    """按翻译文本的token比例切分源文本，使用累积比例算法避免重叠"""
    if len(translated_parts_docs) <= 1:
        return [source_doc]
    
    # 计算每个翻译部分的token比例
    tr_token_counts = [len(doc) for doc in translated_parts_docs]
    total_tr_tokens = sum(tr_token_counts)
    
    if total_tr_tokens == 0:
        return [source_doc] + [source_doc[:0] for _ in range(len(translated_parts_docs) - 1)]
    
    # 使用累积比例算法确保无重叠
    src_parts = []
    total_src_tokens = len(source_doc)
    current_idx = 0
    cumulative_tr_tokens = 0
    
    print(f"源文本总token数: {total_src_tokens}")
    print(f"翻译部分token数: {tr_token_counts}, 总计: {total_tr_tokens}")
    
    for i, tr_token_count in enumerate(tr_token_counts):
        cumulative_tr_tokens += tr_token_count
        
        if i == len(tr_token_counts) - 1:
            # 最后一部分包含剩余所有tokens
            next_idx = total_src_tokens
        else:
            # 根据累积比例计算下一个分割点
            next_idx = round(total_src_tokens * cumulative_tr_tokens / total_tr_tokens)
        
        part_doc = source_doc[current_idx:next_idx]
        src_parts.append(part_doc)
        
        print(f"分片 {i}: [{current_idx}:{next_idx}] = '{part_doc.text}' ({len(part_doc)} tokens)")
        current_idx = next_idx
    
    return src_parts

def test_overlap_fix():
    """测试重叠边界修复"""
    
    # 创建测试数据：模拟会导致重叠的情况
    source_text = "新疆早餐配篝火歌舞"
    source_tokens = list(source_text)  # 每个字符是一个token
    source_doc = MockDoc(source_text, source_tokens)
    
    # 模拟翻译后的三个分片，token数量分别为3, 2, 3
    tr_part1 = MockDoc("Part1", ["tok1", "tok2", "tok3"])  # 3 tokens
    tr_part2 = MockDoc("Part2", ["tok4", "tok5"])          # 2 tokens  
    tr_part3 = MockDoc("Part3", ["tok6", "tok7", "tok8"])  # 3 tokens
    
    translated_parts_docs = [tr_part1, tr_part2, tr_part3]
    
    print("=== 测试累积比例算法 ===")
    src_parts = proportionally_split_source(source_doc, translated_parts_docs)
    
    # 检查是否有重叠
    print("\n=== 检查重叠情况 ===")
    total_chars = 0
    prev_end = 0
    
    for i, part in enumerate(src_parts):
        print(f"分片 {i}: '{part.text}' (长度: {len(part)})")
        total_chars += len(part)
        
        # 检查是否连续
        if i > 0:
            # 获取当前分片的起始位置（这里简化处理）
            current_start_char = part.text[0] if part.text else ""
            print(f"  检查连续性...")
    
    print(f"\n原始字符数: {len(source_text)}")
    print(f"分片总字符数: {total_chars}")
    print(f"是否相等: {len(source_text) == total_chars}")
    
    # 重组检查
    reconstructed = ''.join([part.text for part in src_parts])
    print(f"重组文本: '{reconstructed}'")
    print(f"是否与原文相同: {reconstructed == source_text}")

if __name__ == '__main__':
    test_overlap_fix()