init

stock/util/Stock2Vector.py

@@ -285,9 +285,13 @@ class Stock2Vector(HTS):
         Y = np.asarray(Y, dtype='int64')
         return X, Y
 
-    def getVectorData(self, data, type="avg10", VECTOR_SIZE = 32):
+    def getVectorData(self, data, VECTOR_SIZE = 32):
+        return self.getVectorData_2(data, VECTOR_SIZE)
+
+    def getVectorData_1(self, data, VECTOR_SIZE):
         df = self.buySellChecker.getVectorFeature(data)
 
+        # avg10, 볼린져밴드 상단과 하단의 차이, rsi, avg3만 이용한다.
         # channel1: avg10, channel2: diff_upper_lower, channel3: abs_avg_2, channel4: abs_avg_3
         avg10 = df['avg10'].tolist()
         diff_upper_lower = df['diff_upper_lower'].tolist()
@@ -313,11 +317,55 @@ class Stock2Vector(HTS):
                         h = 0
                         batch_X.append(X)
             batch_Y.append(label[i])
-
+            """
+            if label[i] == 2:
+                batch_Y.append([0, 0, 1])
+            elif label[i] == 1:
+                batch_Y.append([0, 1, 0])
+            else:
+                batch_Y.append([1, 0, 0])
+            """
         batch_X = np.asarray(batch_X)
         batch_Y = np.asarray(batch_Y, dtype='int64')
         return batch_X, batch_Y
 
+    def getVectorData_2(self, data, VECTOR_SIZE = 32):
+        df = self.buySellChecker.getVectorFeature(data)
+
+        # avg10, 볼린져밴드 상단과 하단의 차이, rsi, avg3만 이용한다.
+        # channel1: avg10, channel2: diff_upper_lower, channel3: abs_avg_2, channel4: abs_avg_3
+        avg3 = df['avg3'].tolist()
+        avg6 = df['avg6'].tolist()
+        avg9 = df['avg9'].tolist()
+
+
+        diff_upper_lower = df['diff_upper_lower'].tolist()
+        rsi = df['rsi'].tolist()
+        abs_avg_3 = df['abs_avg_3'].tolist()
+
+        size = len(avg10)
+        batch_X, batch_Y = [], []
+        X = np.zeros((4, VECTOR_SIZE, VECTOR_SIZE))
+        label = df['label'].tolist()
+        for i in range(VECTOR_SIZE * VECTOR_SIZE - 1, size):
+            w, h = 0, 0
+            for j in range(i - VECTOR_SIZE * VECTOR_SIZE + 1, i + 1):
+                X[0, h, w] = avg10[j]
+                X[1, h, w] = diff_upper_lower[j]
+                X[2, h, w] = abs_avg_3[j]
+                X[3, h, w] = rsi[j]
+                w += 1
+                if w >= VECTOR_SIZE:
+                    w = 0
+                    h += 1
+                    if h >= VECTOR_SIZE:
+                        h = 0
+                        batch_X.append(X)
+            batch_Y.append(label[i])
+
+        batch_X = np.asarray(batch_X)
+        batch_Y = np.asarray(batch_Y, dtype='int64')
+        return batch_X, batch_Y
 
     def getDataset3D(self, data, VECTOR_SIZE = 299):
         df, minmax_df = self.preprocessData(data)