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.gitattributes

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 # Video files - compressed
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 *.webm filter=lfs diff=lfs merge=lfs -text
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+imputation/electricity/electricity.csv filter=lfs diff=lfs merge=lfs -text
+long_term_forecast/traffic/traffic.csv filter=lfs diff=lfs merge=lfs -text
+short_term_forecast/m4/Daily-train.csv filter=lfs diff=lfs merge=lfs -text
+short_term_forecast/m4/Monthly-train.csv filter=lfs diff=lfs merge=lfs -text
+short_term_forecast/m4/Quarterly-train.csv filter=lfs diff=lfs merge=lfs -text
+short_term_forecast/m4/Yearly-train.csv filter=lfs diff=lfs merge=lfs -text
+short_term_forecast/m4/submission-Naive2.csv filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: mit
+task_categories:
+  - time-series-forecasting
+  - time-series-classification
+tags:
+  - time-series
+  - benchmark
+  - forecasting
+  - anomaly-detection
+size_categories:
+  - 1M<n<10M
+---
+
+# PaperBenchPro Time Series Datasets
+
+时序分析基准数据集合集，按任务类型组织。
+
+## 📂 目录结构
+
+```
+dataset_by_task/
+├── anomaly_detection/      # 异常检测
+│   ├── MSL/
+│   ├── PSM/
+│   ├── SMAP/
+│   ├── SMD/
+│   └── SWaT/
+├── classification/         # 时序分类
+│   ├── EthanolConcentration/
+│   ├── FaceDetection/
+│   ├── Handwriting/
+│   ├── Heartbeat/
+│   ├── JapaneseVowels/
+│   ├── PEMS-SF/
+│   ├── SelfRegulationSCP1/
+│   ├── SelfRegulationSCP2/
+│   ├── SpokenArabicDigits/
+│   └── UWaveGestureLibrary/
+├── imputation/             # 数据填补
+│   ├── electricity/
+│   ├── ETT-small/
+│   └── weather/
+├── long_term_forecast/     # 长期预测
+│   ├── electricity/
+│   ├── ETT-small/
+│   ├── exchange_rate/
+│   ├── illness/
+│   ├── traffic/
+│   └── weather/
+└── short_term_forecast/    # 短期预测
+    └── m4/
+```
+
+## 📊 任务说明
+
+| 任务类型 | 描述 | 数据集数量 |
+|---------|------|-----------|
+| anomaly_detection | 时序异常检测 | 5 |
+| classification | 时序分类 | 10 |
+| imputation | 缺失值填补 | 6 |
+| long_term_forecast | 长期预测 (96/192/336/720步) | 9 |
+| short_term_forecast | 短期预测 (M4竞赛) | 1 |
+
+## 🚀 使用方式
+
+```python
+from huggingface_hub import snapshot_download
+
+# 下载全部数据
+snapshot_download(repo_id="hahuh/PaperBenchPro", repo_type="dataset")
+
+# 只下载特定任务
+snapshot_download(
+    repo_id="hahuh/PaperBenchPro",
+    repo_type="dataset",
+    allow_patterns="anomaly_detection/*"
+)
+```
+
+## 📝 引用
+
+如果使用本数据集，请引用相关论文。
+

anomaly_detection/MSL/MSL_test.npy

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anomaly_detection/SWaT/data.py

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+import xlrd
+import csv
+
+'''def xlsx_to_csv():
+    workbook = xlrd.open_workbook('SWaT_Dataset_Normal_v1.xlsx')
+    table = workbook.sheet_by_index(0)
+    with open('swat_train.csv', 'w', encoding='utf-8') as f:
+        write = csv.writer(f)
+        for row_num in range(table.nrows):
+            row_value = table.row_values(row_num)
+            write.writerow(row_value)
+
+if __name__ == '__main__':
+    xlsx_to_csv()'''
+'''import pandas as pd
+import csv
+f = open('swat_train2.csv','w',encoding='utf-8')
+csv_writer = csv.writer(f)
+csv_writer.writerow(['FIT101' ,'LIT101' ,' MV101', 'P101' ,'P102', ' AIT201', 'AIT202',
+ 'AIT203' ,'FIT201' ,' MV201' ,' P201', ' P202', 'P203' ,' P204', 'P205', 'P206',
+ 'DPIT301' ,'FIT301', 'LIT301' ,'MV301' ,'MV302', ' MV303', 'MV304' ,'P301'
+, 'P302', 'AIT401', 'AIT402', 'FIT401', 'LIT401', 'P401', 'P402', 'P403', 'P404',
+ 'UV401' ,'AIT501', 'AIT502', 'AIT503', 'AIT504', 'FIT501', 'FIT502' ,'FIT503',
+ 'FIT504', 'P501', 'P502', 'PIT501', 'PIT502', 'PIT503', 'FIT601', 'P601', 'P602',
+ 'P603', 'Normal/Attack'])
+
+df = pd.read_csv('swat_train.csv')
+df = df.values
+for u in range(1,len(df)):
+    tem = df[u][1:]
+    tem2 = []
+    for i in range(len(tem)-1):
+        tem2.append(float(tem[i]))
+    if(tem[-1]=='Normal'):
+        tem2.append(0)
+    else:
+        tem2.append(1)
+    csv_writer.writerow(tem2)'''
+import pandas as pd
+df = pd.read_csv('swat_train2.csv')
+df = df.values
+print(df.shape)
+ano = 0
+for u in range(len(df)):
+    if(df[u][-1]==1):
+        ano = ano+1
+print(ano)
+print(ano/len(df))
+
+

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