offline_data_model_pipline/data_generate/query_completion/count_cluster.py

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2025-05-13 13:00:51 +08:00
import json
from collections import defaultdict
import pandas as pd
def classify_data_by_cluster_center(input_file, output_jsonl, output_excel):
"""
根据 cluster_center 对数据进行分类
每个 cluster_center 对应一个列表存储去掉了 embedding 的数据
输出 JSONL 文件按类型的数据量从多到少排序并记录每种类型的数量
同时将类型及其数量导出到 Excel 表格中
每个 cluster 对应的 data_list 会根据 'score' 字段降序排序
"""
# 初始化分类字典
classified_data = defaultdict(list)
# 读取输入文件
with open(input_file, 'r', encoding='utf-8') as f:
for line in f:
record = json.loads(line.strip())
# 提取 cluster_center 部分
cluster_center = record.get("cluster_center")
# 如果 cluster_center 存在,则根据其值分类
if cluster_center is not None:
record_without_embedding = {k: v for k, v in record.items() if k != "embedding"}
classified_data[cluster_center].append(record_without_embedding)
else:
# 如果没有 cluster_center则归类到 "null"
record_without_embedding = {k: v for k, v in record.items() if k != "embedding"}
classified_data["null"].append(record_without_embedding)
# 对每个 cluster_center 下的 data_list 按照 score 排序默认为0
for center in classified_data:
classified_data[center].sort(key=lambda x: x.get('score', 0), reverse=True)
# 按类型的数据量从多到少排序
sorted_classified_data = sorted(classified_data.items(), key=lambda x: len(x[1]), reverse=True)
# 写入 JSONL 文件
total_types = len(sorted_classified_data)
with open(output_jsonl, 'w', encoding='utf-8') as out_f:
for cluster_center, data_list in sorted_classified_data:
entry = {
str(cluster_center): data_list,
#"count": len(data_list)
}
out_f.write(json.dumps(entry, ensure_ascii=False) + '\n')
# 准备 Excel 数据
excel_data = []
for cluster_center, data_list in sorted_classified_data:
excel_data.append({"Cluster Center": cluster_center, "Count": len(data_list)})
# 导出到 Excel 文件
df = pd.DataFrame(excel_data)
df.to_excel(output_excel, index=False)
print(f"Total types: {total_types}")
return total_types
# 示例用法
if __name__ == "__main__":
input_file = './dhbq/dhbq_merged_with_score_0513.jsonl'
output_jsonl = './dhbq/dhbq_count_cluster_0513.jsonl'
output_excel = './dhbq/dhbq_count_cluster_0513.xlsx'
total_types = classify_data_by_cluster_center(input_file, output_jsonl, output_excel)
print(f"Total types found: {total_types}")