Refactorign method position.

Author: fnunnari

PostProcessing/PostProcessVideos.py

@@ -8,30 +8,9 @@
 
 from pathlib import Path
 
+from dataframes import compute_time_range, trim_into_interval
 
-THRESHOLD_NS = 10 * 1000
-
-
-def compute_time_range(dfs):
-    # Find the lowest and highest numbers in all the data frames
-    min_common = max(df.iloc[:,0].min() for df in dfs)
-    max_common = min(df.iloc[:,0].max() for df in dfs)
-
-    # Print the results
-    print(f"The lowest common number is {min_common}")
-    print(f"The highest common number is {max_common}")
-    
-    return (min_common, max_common)
-
-
-def trim_into_interval(csv_path, dfs, min_common, max_common):
-    # Trim each data frame to the min_common and max_common interval and save to a new file
-    for i, df in enumerate(dfs):
-        df_trimmed = df[(df.iloc[:,0] >= min_common) & (df.iloc[:,0] <= max_common)]
-        df_trimmed.to_csv(f"{csv_path}trimmed_df_{i+1}.csv", header=False, index=False)
-
-    # Print the results
-    print(f"{len(dfs)} data frames trimmed and saved to {csv_path}")
+THRESHOLD_NS = 10 * 1000 * 1000
 
 
 def extract(input_dir, output_dir):

PostProcessing/dataframes.py

@@ -4,3 +4,24 @@
 def repair_dropped_frames(df: pd.DataFrame) -> pd.DataFrame:
     pass
 
+
+def compute_time_range(dfs):
+    # Find the lowest and highest numbers in all the data frames
+    min_common = max(df.iloc[:,0].min() for df in dfs)
+    max_common = min(df.iloc[:,0].max() for df in dfs)
+
+    # Print the results
+    print(f"The lowest common number is {min_common}")
+    print(f"The highest common number is {max_common}")
+
+    return (min_common, max_common)
+
+
+def trim_into_interval(csv_path, dfs, min_common, max_common):
+    # Trim each data frame to the min_common and max_common interval and save to a new file
+    for i, df in enumerate(dfs):
+        df_trimmed = df[(df.iloc[:,0] >= min_common) & (df.iloc[:,0] <= max_common)]
+        df_trimmed.to_csv(f"{csv_path}trimmed_df_{i+1}.csv", header=False, index=False)
+
+    # Print the results
+    print(f"{len(dfs)} data frames trimmed and saved to {csv_path}")