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dosangyoon
2022-08-16 21:23:40 +09:00
parent f9ffa363fa
commit 1eed2ea40e
6 changed files with 435 additions and 951 deletions
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14
stock/util/Stock2Vector.py
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@@ -140,7 +140,7 @@ class Stock2Vector(HTS):
result = self.getRealTime(stock_code, today, LAST_DATA)
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
df = self.buySellChecker.getVectorFeature(result)
df = self.buySellChecker.analyze(result)
minmax_df1 = (df - df.min()) / (df.max() - df.min())
minmax_df2 = minmax_df1.drop(["date"], axis="columns")
minmax_df = minmax_df2.join(df['date'])
@@ -198,7 +198,7 @@ class Stock2Vector(HTS):
def preprocessData(self, result):
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
df = self.buySellChecker.getVectorFeature(result)
df = self.buySellChecker.analyze(result)
minmax_df1 = (df - df.min()) / (df.max() - df.min())
minmax_df2 = minmax_df1.drop(["date"], axis="columns")
minmax_df = minmax_df2.join(df['date'])
@@ -236,7 +236,7 @@ class Stock2Vector(HTS):
result["label"].append(int(label))
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
df = self.buySellChecker.getVectorFeature(result)
df = self.buySellChecker.analyze(result)
minmax_df1 = (df - df.min()) / (df.max() - df.min())
minmax_df2 = minmax_df1.drop(["date"], axis="columns")
minmax_df = minmax_df2.join(df['date'])
@@ -289,7 +289,7 @@ class Stock2Vector(HTS):
return self.getVectorData_2(data, VECTOR_SIZE)
def getVectorData_1(self, data, VECTOR_SIZE):
df = self.buySellChecker.getVectorFeature(data)
df = self.buySellChecker.analyze(data)
# avg10, 볼린져밴드 상단과 하단의 차이, rsi, avg3만 이용한다.
# channel1: avg10, channel2: diff_upper_lower, channel3: abs_avg_2, channel4: abs_avg_3
@@ -330,14 +330,14 @@ class Stock2Vector(HTS):
return batch_X, batch_Y
def getVectorData_2(self, data, VECTOR_SIZE = 32):
df = self.buySellChecker.getVectorFeature(data)
df = self.buySellChecker.analyze(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()
avg12 = df['avg9'].tolist()
avg24 = df['avg9'].tolist()
diff_upper_lower = df['diff_upper_lower'].tolist()
rsi = df['rsi'].tolist()