Update app.py

app.py

@@ -181,7 +181,10 @@ def predict_inverse(hardness_original_target, ys_original_target, metals_to_use,
                 print(optimized_x[c])
                 optimized_x[c]=round(optimized_x[c]*(scaling_factors[c][1]-scaling_factors[c][0])+scaling_factors[c][0], 2)
     result = optimized_x
+    print(result)
     result = result[result>0.0].dropna(axis=1)
+    print("-------------")
+    print(result)
 
     # Normalize metals outputs
     sum_metals = np.sum(result[c] for c in list(result.columns) if c.startswith("PROPERTY: Metal"))