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@@ -57,3 +57,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+SWaT_Dataset_Attack_v0.xlsx filter=lfs diff=lfs merge=lfs -text
+SWaT_Dataset_Normal_v1.xlsx filter=lfs diff=lfs merge=lfs -text
+swat2.csv filter=lfs diff=lfs merge=lfs -text
+swat_raw.csv filter=lfs diff=lfs merge=lfs -text
+swat_train.csv filter=lfs diff=lfs merge=lfs -text
+swat_train2.csv filter=lfs diff=lfs merge=lfs -text

SWaT_Dataset_Attack_v0.xlsx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6cc72c24425453879bac1565cae4c6f35ad585a578510ab2a27b325d1bac2e8d
+size 116016616

SWaT_Dataset_Normal_v1.xlsx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb7bb0a9c10f86ad29d8f2ae4fd09284e7db70c76350f5b2afcca58d9ace6c49
+size 130566907

data.py

@@ -0,0 +1,50 @@
+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))
+
+

swat2.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23c5bacf78de7527aac031ad43acc7ac99ec49b17b645aaa2a74a4a7d60a0a80
+size 164416771

swat_raw.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e44e3088f2e012edb2b79315691e1f7da0f855feb994fa28fd3e02ea65575294
+size 133006459

swat_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:18791beeb471336ae26e2a2c58d73ef18f9cffa998304259d9b381de7e57cd05
+size 176313757

swat_train2.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfdba4611fd7b093246309eae7b249da05decff8cde640c8283bfef8e6eaf5fb
+size 182817723