Merge pull request #46 from midaa1/metrics-modification

Fixing the precision and accuracy calculations for X and Y axes

Author: jvJUCA

app/services/metrics.py

@@ -11,8 +11,9 @@ def func_precision_x(group):
     Returns:
         float: The precision value.
     """
-    return np.sqrt(np.sum(np.square([group["Predicted X"], group["True X"]])))
-
+    return np.sqrt(
+        np.mean(np.square(group["Predicted X"] - np.mean(group["Predicted X"])))
+    )
 
 def func_presicion_y(group):
     """
@@ -24,7 +25,9 @@ def func_presicion_y(group):
     Returns:
         float: The precision value.
     """
-    return np.sqrt(np.sum(np.square([group["Predicted Y"], group["True Y"]])))
+    return np.sqrt(
+        np.mean(np.square(group["Predicted Y"] - np.mean(group["Predicted Y"])))
+    )
 
 
 def func_accuracy_x(group):
@@ -37,7 +40,9 @@ def func_accuracy_x(group):
     Returns:
         float: The accuracy value.
     """
-    return np.sqrt(np.sum(np.square([group["True X"] - group["Predicted X"]])))
+    
+    return np.sqrt(np.mean(np.square(group["True X"] - group["Predicted X"])))
+
 
 
 def func_accuracy_y(group):
@@ -50,4 +55,5 @@ def func_accuracy_y(group):
     Returns:
         float: The accuracy value.
     """
-    return np.sqrt(np.sum(np.square([group["True Y"] - group["Predicted Y"]])))
+    return np.sqrt(np.mean(np.square(group["True Y"] - group["Predicted Y"])))
+