100 lines
3.8 KiB
Python
100 lines
3.8 KiB
Python
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import argparse
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from pathlib import Path
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from lxml import etree
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from tqdm import tqdm
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from collections import Counter
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def main():
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# 设定目标文件夹路径，你可以修改这里的路径，或者运行脚本时手动输入
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# 默认为当前目录 '.'
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# target_dir = "/mnt/disk_wd/marques_dataset/shhs/polysomnography/annotations-events-nsrr/shhs1"
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target_dir = "/mnt/disk_wd/marques_dataset/shhs/polysomnography/annotations-events-nsrr/shhs2"
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folder_path = Path(target_dir)
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if not folder_path.exists():
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print(f"错误: 路径 '{folder_path}' 不存在。")
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return
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# 1. 获取所有 XML 文件 (扁平结构，不递归子目录)
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xml_files = list(folder_path.glob("*.xml"))
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total_files = len(xml_files)
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if total_files == 0:
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print(f"在 '{folder_path}' 中没有找到 XML 文件。")
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return
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print(f"找到 {total_files} 个 XML 文件，准备开始处理...")
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# 用于统计 (EventType, EventConcept) 组合的计数器
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stats_counter = Counter()
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# 2. 遍历文件，使用 tqdm 显示进度条
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for xml_file in tqdm(xml_files, desc="Processing XMLs", unit="file"):
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try:
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# 使用 lxml 解析
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tree = etree.parse(str(xml_file))
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root = tree.getroot()
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# 3. 定位到 ScoredEvent 节点
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# SHHS XML 结构通常是: PSGAnnotation -> ScoredEvents -> ScoredEvent
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# 我们直接查找所有的 ScoredEvent 节点
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events = root.findall(".//ScoredEvent")
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for event in events:
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# 提取 EventType
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type_node = event.find("EventType")
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# 处理节点不存在或文本为空的情况
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e_type = type_node.text.strip() if (type_node is not None and type_node.text) else "N/A"
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# 提取 EventConcept
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concept_node = event.find("EventConcept")
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e_concept = concept_node.text.strip() if (concept_node is not None and concept_node.text) else "N/A"
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# 4. 组合并计数
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# 组合键为元组 (EventType, EventConcept)
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key = (e_type, e_concept)
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stats_counter[key] += 1
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except etree.XMLSyntaxError:
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print(f"\n[警告] 文件格式错误，跳过: {xml_file.name}")
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except Exception as e:
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print(f"\n[错误] 处理文件 {xml_file.name} 时出错: {e}")
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# 5. 打印结果到终端
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if stats_counter:
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# --- 动态计算列宽 ---
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# 获取所有 EventType 的最大长度，默认长度 9
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max_type_width = max((len(k[0]) for k in stats_counter.keys()), default=9)
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max_type_width = max(max_type_width, 9)
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# 获取所有 EventConcept 的最大长度，默认长度 12
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max_conc_width = max((len(k[1]) for k in stats_counter.keys()), default=12)
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max_conc_width = max(max_conc_width, 12)
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# 计算表格总宽度
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total_line_width = max_type_width + max_conc_width + 10 + 6
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print("\n" + "=" * total_line_width)
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print(f"{'EventType':<{max_type_width}} | {'EventConcept':<{max_conc_width}} | {'Count':>10}")
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print("-" * total_line_width)
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# --- 修改处：按名称排序 ---
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# sorted() 默认会对元组 (EventType, EventConcept) 进行字典序排序
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# 即先按 EventType A-Z 排序，再按 EventConcept A-Z 排序
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for (e_type, e_concept), count in sorted(stats_counter.items()):
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print(f"{e_type:<{max_type_width}} | {e_concept:<{max_conc_width}} | {count:>10}")
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print("=" * total_line_width)
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else:
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print("\n未提取到任何事件数据。")
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print("=" * 90)
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print(f"统计完成。共扫描 {total_files} 个文件。")
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if __name__ == "__main__":
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main() |