Update restful/onnx_utilities.py

restful/onnx_utilities.py

@@ -13,8 +13,15 @@ class Utilities:
         self.posttrained_path = './indonesia_stocks/modeling_datas'
         self.scaler_path = './indonesia_stocks/min_max'
 
+    # def truncate_2_decimal(self, val: float):
+    #     return float(Decimal(str(val)).quantize(Decimal('0.01'), rounding=ROUND_DOWN))
     def truncate_2_decimal(self, val: float):
-        return float(Decimal(str(val)).quantize(Decimal('0.01'), rounding=ROUND_DOWN))
+        try:
+            return float(Decimal(str(float(val))).quantize(Decimal('0.01'), rounding=ROUND_DOWN))
+        except Exception as e:
+            print("Decimal error:", e)
+            return float(val)
+
 
     def denormalization(self, data, min_value, max_value):
         return (data * (max_value - min_value)) + min_value
@@ -58,7 +65,8 @@ class Utilities:
             value = np.array(predicted).flatten()[0]
             denorm_price = (value * (max_close - min_close)) + min_close
         
-            last_date += pd.Timedelta(days=1)
+            # last_date += pd.Timedelta(days=1)
+            last_date = pd.to_datetime(last_date) + pd.Timedelta(days=1)
             # predicted_prices[last_date.strftime('%Y-%m-%d')] = float(denorm_price)
             predicted_prices[last_date] = self.truncate_2_decimal(denorm_price)