Fixed Clipping

main.py

@@ -33,7 +33,6 @@ def scale_up(img, target_shape): # scale back up for the filter bank
     img_su = cv2.resize(img, (target_shape[0], target_shape[1]), interpolation=cv2.INTER_LINEAR)
     return img_su
 
-
 def run_detection(fileLocation, clip):
     with open(fileLocation, "r") as f:
         strData = f.read()
@@ -53,8 +52,30 @@ def run_detection(fileLocation, clip):
         # set value to either 0 or 1. rounds up if >= 0.5, else down
     return (npArray, anomaly_map_value) # returns original, and analyzed version for comparison.
 
-def display_result(orig, res, fileName):
-    #'''
+def store_data(orig, res, fileName):
+    with open(f"OutputDataRaw/{fileName}_raw_original.txt", "w+") as f:
+        vals = np.array2string(
+                orig,
+                precision=16,           # Precision for floating point values
+                suppress_small=False,   # Avoid suppressing small values
+                separator=', ',
+                threshold=np.prod(orig.shape)  # Prevent truncation for large arrays
+            )
+        f.write(vals)
+    with open(f"OutputDataRaw/{fileName}_raw_analyzed.txt", "w+") as f:
+        vals = np.array2string(
+                res,
+                precision=16,           # Precision for floating point values
+                suppress_small=False,   # Avoid suppressing small values
+                separator=', ',
+                threshold=np.prod(res.shape)  # Prevent truncation for large arrays
+            )
+        f.write(vals)
+
+def display_result(orig, res, fileName=None):
+    '''Displays original and analyzed data side by side. 
+    Currently does not save chart or output since feature was 
+    not found to be particularly useful.'''
     fig, ax = plt.subplots(1, 2, figsize=(12, 6))
 
     # Display the original map
@@ -69,34 +90,29 @@ def display_result(orig, res, fileName):
 
     plt.tight_layout()  # Adjust layout for better spacing
     plt.show()
-    '''
-
-    plt.imshow(orig, cmap='hot')
-    plt.title("Original Map")
-    plt.colorbar()
-    plt.show()
-    #plt.savefig(f"OutputData/{fileName}_original")
 
-    plt.imshow(res, cmap='hot')
-    plt.title("Anomaly Map")
-    plt.colorbar()
-    plt.show()
-    #plt.savefig(f"OutputData/{fileName}_analyzed")'''
+    if (fileName):
+        plt.savefig(f"OutputData/{fileName}_analyzed")
 
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Process some data with an optional clip argument.")
 
     parser.add_argument('-p', '--path', required=True, help="Path to the input file. Should be InputFolder.../...")
     parser.add_argument('-c', '--clip', type=int, help="Integer 0-2 for clip value. 0 = none, 1 = standard, 2 = binary.", default=0)
+    parser.add_argument('-s', '--save', type=bool, help="True or False to save result.", default=False)
     args = parser.parse_args()
 
     if (args.clip not in [0, 1, 2]):
         clipValue = 0
     else:
         clipValue = args.clip
+
+    fileName = None
 
-    fileName = args.path.split("/")[-1] # get the file name from Path. Used to label output.
-
+    if (args.save):
+        fileName = args.path.split("/")[-1] # get the file name from Path. Can be used to label output.
+
     (orig, res) = run_detection(args.path, args.clip)
+    store_data(orig, res, fileName)
     display_result(orig, res, fileName)