Update draw_sub_dimension.py

draw_sub_dimension.py

@@ -16,23 +16,24 @@ def sub_consist_attr(model,high=15,low=1):
     interval = high - low
     score = []
     df = pd.read_csv(model)  
+    total_videos = df.shape[0] - 1
     
     color = []
     for i in color_indices:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 color.append((s-low)/interval)
                 
     shape = []
     for i in shape_indices:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 shape.append((s-low)/interval)
     texture = []
     for i in texture_indices:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 texture.append((s-low)/interval)
@@ -60,17 +61,18 @@ def sub_action(model,high=10,low=1):
     interval = high - low
     score = []
     df = pd.read_csv(model)  
+    total_videos = df.shape[0] - 1
     
     common = []
     for i in common_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 common.append((s-low)/interval)
                 
     uncommon = []
     for i in uncommon_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 uncommon.append((s-low)/interval)
@@ -94,17 +96,18 @@ def sub_interaction(model,high=10,low=1):
     interval = high - low
     score = []
     df = pd.read_csv(model)  
+    total_videos = df.shape[0] - 1
     
     physical = []
     for i in physical_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 physical.append((s-low)/interval)
                 
     social = []
     for i in social_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 social.append((s-low)/interval)
@@ -136,45 +139,46 @@ def sub_spatial(model):
 
     record = {}
     df = pd.read_csv(model)  # Replace with your CSV file path
-
+    total_videos = df.shape[0] - 1
+    
     scores = df.iloc[:, -1].tolist()
     scores = scores[:200]
     
     left = []
     for i in left_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 left.append(s)
     right = []
     for i in right_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 right.append(s)
                 
     above = []
     for i in above_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 above.append(s)
     below = []
     for i in below_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 below.append(s)
     
     front = []
     for i in front_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 front.append(s)
     behind = []
     for i in behind_ind:
-        for j in range(200):
+        for j in range(total_videos):
             if df.iloc[j, 0][:4] == f"{i:04d}":
                 s = float(df.iloc[j, -1])
                 behind.append(s)            
@@ -306,9 +310,6 @@ def sub_motion(model):
     left_thresh = 5 #5%
     up_thresh = 5 #5%
 
-   
-   
-
     distance = []
     direction = []