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alpha-mind
Commit d966ef69 authored by Dr.李's avatar Dr.李
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FIX: fix duplicate codes and trade_dates

parent 228dc9f5
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Showing with 28 additions and 24 deletions
alphamind/data/engines/sqlengine/sqlengine_rl.py
View file @ d966ef69
......@@ -267,7 +267,7 @@ class SqlEngine:
IndexMarket.flag == 1
)
)
df2 = pd.read_sql(query, self.session.bind).dropna()
df2 = pd.read_sql(query, self.session.bind).dropna().drop_duplicates(["trade_date"])
df2 = self._create_stats(df2, horizon, offset, no_code=True).set_index("trade_date")
df['dx'] = df['dx'].values - df2.loc[df.index]['dx'].values
......@@ -305,7 +305,7 @@ class SqlEngine:
)
)
df = pd.read_sql(query, self.session.bind).dropna()
df = pd.read_sql(query, self.session.bind).dropna().drop_duplicates(["trade_date", "code"])
df = self._create_stats(df, horizon, offset)
if dates:
......@@ -369,6 +369,7 @@ class SqlEngine:
df = pd.read_sql(query, self.engine) \
.replace([-np.inf, np.inf], np.nan) \
.sort_values(['trade_date', 'code']) \
.drop_duplicates(["trade_date", "code"]) \
.set_index('trade_date')
res = transformer.transform('code', df).replace([-np.inf, np.inf], np.nan)
......@@ -433,15 +434,16 @@ class SqlEngine:
and_(
Market.code.in_(universe_df.code.unique().tolist()),
Market.trade_date.in_(dates) if dates is not None else Market.trade_date.between(
start_date, end_date)
start_date, end_date),
Market.flag == 1
)
).distinct()
df = pd.read_sql(query, self.engine).replace([-np.inf, np.inf], np.nan)
df = pd.read_sql(query, self.engine).replace([-np.inf, np.inf], np.nan).drop_duplicates(["trade_date", "code"])
if external_data is not None:
df = pd.merge(df, external_data, on=['trade_date', 'code']).dropna()
df.sort_values(['trade_date', 'code'], inplace=True)
df = df.sort_values(["trade_date", "code"]).drop_duplicates(subset=["trade_date", "code"])
df.set_index('trade_date', inplace=True)
res = transformer.transform('code', df).replace([-np.inf, np.inf], np.nan)
......@@ -566,7 +568,7 @@ class SqlEngine:
RiskExposure.flag == 1
))
risk_exp = pd.read_sql(query, self.engine).dropna()
risk_exp = pd.read_sql(query, self.engine).dropna().drop_duplicates(subset=["code"])
if not model_type:
return risk_cov, risk_exp
......@@ -630,7 +632,8 @@ class SqlEngine:
special_risk_table.SRISK.label('srisk')] + risk_exposure_cols).select_from(big_table) \
.distinct()
risk_exp = pd.read_sql(query, self.engine).sort_values(['trade_date', 'code']).dropna()
risk_exp = pd.read_sql(query, self.engine).sort_values(['trade_date', 'code']) \
.dropna().drop_duplicates(["trade_date", "code"])
risk_exp["trade_date"] = pd.to_datetime(risk_exp["trade_date"])
if not model_type:
......@@ -713,7 +716,7 @@ class SqlEngine:
)
).distinct()
df = pd.read_sql(query, self.engine)
df = pd.read_sql(query, self.engine).drop_duplicates(subset=["code"])
if codes:
df.set_index(['code'], inplace=True)
......@@ -752,7 +755,7 @@ class SqlEngine:
IndexComponent.indexCode == benchmark,
)
).distinct()
df = pd.read_sql(query, self.engine)
df = pd.read_sql(query, self.engine).drop_duplicates(["trade_date", "code"])
df["trade_date"] = pd.to_datetime(df["trade_date"])
return df
......@@ -841,7 +844,8 @@ class SqlEngine:
if __name__ == "__main__":
from PyFin.api import makeSchedule
db_url = "mysql+mysqldb://reader:Reader#2020@121.37.138.1:13317/vision?charset=utf8"
# db_url = "mysql+mysqldb://reader:Reader#2020@121.37.138.1:13317/vision?charset=utf8"
db_url = "mysql+mysqldb://dxrw:dxRW20_2@121.37.138.1:13317/dxtest?charset=utf8"
sql_engine = SqlEngine(db_url=db_url)
universe = Universe("hs300")
......@@ -854,14 +858,14 @@ if __name__ == "__main__":
print(ref_dates)
# df = sql_engine.fetch_factor("2020-02-21", factors=factors, codes=["2010031963"])
# print(df)
df = sql_engine.fetch_factor_range(universe=universe, dates=ref_dates, factors=factors)
print(df)
df = sql_engine.fetch_codes_range(start_date=start_date, end_date=end_date, universe=Universe("hs300"))
print(df)
# df = sql_engine.fetch_factor_range(universe=universe, dates=ref_dates, factors=factors)
# print(df)
# df = sql_engine.fetch_codes_range(start_date=start_date, end_date=end_date, universe=Universe("hs300"))
# print(df)
# df = sql_engine.fetch_dx_return("2020-10-09", codes=["2010031963"], benchmark=benchmark)
# print(df)
df = sql_engine.fetch_dx_return_range(universe, dates=ref_dates, horizon=9, offset=1, benchmark=benchmark)
print(df)
# df = sql_engine.fetch_dx_return_range(universe, dates=ref_dates, horizon=9, offset=1, benchmark=benchmark)
# print(df)
# df = sql_engine.fetch_dx_return_index("2020-10-09", index_code=benchmark)
# print(df)
# df = sql_engine.fetch_dx_return_index_range(start_date=start_date, end_date=end_date, index_code=benchmark, horizon=9, offset=1)
......@@ -882,8 +886,8 @@ if __name__ == "__main__":
# print(df)
# df = sql_engine.fetch_risk_model("2020-02-21", codes=["2010031963"])
# print(df)
df = sql_engine.fetch_risk_model("2020-02-21", codes=["2010031963"], model_type="factor")
print(df)
# df = sql_engine.fetch_risk_model("2020-02-21", codes=["2010031963"], model_type="factor")
# print(df)
df = sql_engine.fetch_risk_model_range(universe=universe,
start_date=start_date,
end_date=end_date)
......@@ -895,9 +899,9 @@ if __name__ == "__main__":
# print(df)
# df = sql_engine.fetch_data("2020-02-11", factors=factors, codes=["2010031963"], benchmark=300)
# print(df)
df = sql_engine.fetch_data_range(universe,
factors=factors,
dates=ref_dates,
benchmark=benchmark)["factor"]
print(df)
# df = sql_engine.fetch_data_range(universe,
# factors=factors,
# dates=ref_dates,
# benchmark=benchmark)["factor"]
# print(df)
entrypoint.sh
View file @ d966ef69
......@@ -3,5 +3,5 @@
export PYTHONPATH=$PYTHONPATH:/
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/alphamind/pfopt/lib
export DB_VENDOR="rl"
export DB_URI="mysql+mysqldb://reader:Reader#2020@121.37.138.1:13317/vision?charset=utf8"
export DB_URI="mysql+mysqldb://dxrw:dxRW20_2@121.37.138.1:13317/dxtest?charset=utf8"
jupyter lab --ip="0.0.0.0" --port=8080 --allow-root --NotebookApp.token='' --NotebookApp.password=''
\ No newline at end of file
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