init

README.md

@@ -1,6 +1,16 @@
 # StockPredictor
 
 
+## Reference
+* Vision Transormers 참고
+  * https://github.com/NielsRogge/Transformers-Tutorials/blob/master/VisionTransformer/Fine_tuning_the_Vision_Transformer_on_CIFAR_10_with_the_%F0%9F%A4%97_Trainer.ipynb
+  * How to convert datasets from a python dictionary
+    * https://huggingface.co/docs/datasets/v1.1.1/loading_datasets.html
+  * numpy -> tensor -> PILImage 변환 방법
+    * https://qlsenddl-lab.tistory.com/37
+* Image Classification Models
+  * https://github.com/weiaicunzai/awesome-image-classification
+
 ## Troubleshoot
 1. OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.
     ```

Simulation.py

@@ -166,10 +166,10 @@ if __name__ == "__main__":
     stock_codes = {
         # 252670
         # 122630
-        "252670": ['20220804'],
+        "252670": ['20220805'],
     }
 
-    method = "answer" # "ml", "answer"
+    method = "" # "ml", "answer"
     for stock_code in stock_codes:
         simulation = Simulation(RESOURCE_PATH)
 

stock/util/Stock2Vector.py

@@ -159,7 +159,7 @@ class Stock2Vector(HTS):
         conn = sqlite3.connect(os.path.join(self.RESOURCE_PATH, "hts.db"))
         cursor = conn.cursor()
 
-        cursor.execute('SELECT ymd, hms, open, high, low, close, volume, label FROM ' + tableName + ' WHERE CODE=? and (ymd >= ? and  ymd <= ?) order by ymd desc, hms ', (stock_code, "20220701", "20220731"))
+        cursor.execute('SELECT ymd, hms, open, high, low, close, volume, label FROM ' + tableName + ' WHERE CODE=? and (ymd >= ? and  ymd <= ?) order by ymd desc, hms ', (stock_code, "20220726", "20220731"))
         #cursor.execute('SELECT ymd, hms, open, high, low, close, volume, label FROM ' + tableName + ' WHERE CODE=? order by ymd desc, hms ', (stock_code,))
         db_result = cursor.fetchall()
         temp_result = []
@@ -269,13 +269,13 @@ class Stock2Vector(HTS):
             X.append(temp_X)
             if TOTAL_Y[0][i] == 0:
                 #Y.append([1, 0, 0])
-                Y.append([0])
+                Y.append(0)
             elif TOTAL_Y[0][i] == 0.5:
                 #Y.append([0, 1, 0])
-                Y.append([1])
+                Y.append(1)
             else:
                 #Y.append([0, 0, 1])
-                Y.append([2])
+                Y.append(2)
 
         X = np.asarray(X)
         Y = np.asarray(Y)