Merge pull request #21 from BBVA/develop

Release 1.4

config/app.cfg

@@ -0,0 +1,8 @@
+VARIABLE_NAME = "variable value"
+PORT = 80
+DEBUG = True
+DEVELOPMENT = True
+SECRET_KEY = 'do-i-really-need-this'
+SQLALCHEMY_DATABASE_URI= "sqlite:///Timecop_modelsv1.db"
+DB_NAME= "sqlite:///Timecop_modelsv1.db"
+ENV="development"

engines/BBDD.py

@@ -38,7 +38,7 @@ class Model(Base):
         __tablename__ = 'models'
         TS_name = Column(String(250), nullable=False,primary_key=True)
         TS_winner_name = Column(String(250), nullable=False)
-        TS_model = Column(LargeBinary)
+        TS_model = Column(LargeBinary())
         TS_model_params = Column(String(250))
         TS_metric = Column(Numeric)
         TS_update = Column('TS_update', DATETIME, index=False, nullable=False,primary_key=True,default=datetime.datetime.utcnow)
@@ -50,15 +50,15 @@ class TS(Base):
         TS_update = Column('TS_update', DATETIME, index=False, nullable=False,primary_key=True,default=datetime.datetime.utcnow)
 
 
-    DB_NAME = 'sqlite:///Timecop_models.db'
+    DB_NAME = 'sqlite:///Timecop_modelsv1.db'
     engine = create_engine(DB_NAME)
     #self.__db.echo = True
     Base.metadata.create_all(engine)
 
 
 def get_ts(name):
 
-    DB_NAME = 'sqlite:///Timecop_models.db'
+    DB_NAME = 'sqlite:///Timecop_modelsv1.db'
     engine = create_engine(DB_NAME)
     DBSession = sessionmaker(bind=engine)
     session = DBSession()
@@ -69,7 +69,7 @@ def get_ts(name):
 
 def set_ts(name, data):
 
-    DB_NAME = 'sqlite:///Timecop_models.db'
+    DB_NAME = 'sqlite:///Timecop_modelsv1.db'
     engine = create_engine(DB_NAME)
 
     DBSession = sessionmaker(bind=engine)
@@ -83,19 +83,20 @@ def set_ts(name, data):
 
 def new_model(name, winner, model,params,metric):
 
-    DB_NAME = 'sqlite:///Timecop_models.db'
+    DB_NAME = 'sqlite:///Timecop_modelsv1.db'
     engine = create_engine(DB_NAME)
 
     DBSession = sessionmaker(bind=engine)
     session = DBSession()
+    print ("Model saved")
+    print(model)
 
-
-    new_model = Model(TS_name=name, TS_winner_name = winner, TS_model=model,TS_model_params= params,TS_metric=metric)
+    new_model = Model(TS_name=name, TS_winner_name = winner, TS_model=bytearray(model),TS_model_params= params,TS_metric=metric)
     session.add(new_model)
     session.commit()
 
 def get_best_model(name):
-    DB_NAME = 'sqlite:///Timecop_models.db'
+    DB_NAME = 'sqlite:///Timecop_modelsv1.db'
     engine = create_engine(DB_NAME)
 
     DBSession = sessionmaker(bind=engine)
@@ -107,5 +108,8 @@ def get_best_model(name):
     #     print (mt.TS_name)
     #     print (mt.TS_winner_name)
     #     print (mt.TS_update)
-    salida = session.query(Model).filter(Model.TS_name == name).order_by(desc('TS_update')).first()
+    #filter(Note.message.like("%somestr%")
+    winner_model_type = session.query(Model).filter(Model.TS_name.like('winner%')).order_by(desc('TS_update')).first()
+
+    salida = session.query(Model).filter(Model.TS_name == name).filter(Model.TS_winner_name == winner_model_type.TS_winner_name).order_by(desc('TS_update')).first()
     return ( salida.TS_winner_name,salida.TS_model,salida.TS_model_params)

engines/functions_timeseries.py

@@ -19,10 +19,10 @@ def model_univariate(lista_datos,num_fut,desv_mse,train,name):
 
 
     if not train:
-        filename = './models_temp/'+name
-        with open(filename,'r') as f:
-            winner = f.read()
-            f.close()
+        # filename = './models_temp/'+name
+        # with open(filename,'r') as f:
+        #     winner = f.read()
+        #     f.close()
 
         (model_name,model,params)=get_best_model('winner_'+name)
         # print ("recupero el motor " )
@@ -97,10 +97,10 @@ def model_univariate(lista_datos,num_fut,desv_mse,train,name):
                 winner=key
             print(winner)
 
-        filename = './models_temp/'+name
-        with open(filename,'w') as f:
-            f.write(winner)
-            f.close()
+        # filename = './models_temp/'+name
+        # with open(filename,'w') as f:
+        #     f.write(winner)
+        #     f.close()
         new_model('winner_'+name, winner, pack('N', 365),'',0)
 
 

engines/lstm.py

@@ -214,16 +214,23 @@ def anomaly_uni_LSTM(lista_datos,num_forecast=10,desv_mse=2,train='True',name='t
         models_dict[best_model].save('./models_temp/lstm.model'+name)
         print ("insertando modelo LSTM")
         with open('./models_temp/lstm.model'+name,'rb') as f:
-            mymodel = bytearray(f.read())
-            new_model(name, 'LSTM', mymodel,'',dict_mse_models[best_model])
+            mymodel = f.read()
 
+            new_model(name, 'LSTM', bytearray(mymodel),'',dict_mse_models[best_model])
+            f.close()
         actual_model= models_dict[best_model]
 
     else:
 
+        print ("Adquiring best LSTM model")
         (model_name,mymodel,params)=get_best_model(name)
+        print("el modelo es")
+        print(model_name)
+        print (mymodel)
         with open('./models_temp/lstm.model'+name, "wb") as newFile:
             newFile.write(mymodel)
+            newFile.close()
+
 
         actual_model= load_model('./models_temp/lstm.model'+name)
 

models_temp/learned_model_holt_winterstest

@@ -1 +1 @@
-3
+10,add

models_temp/learned_model_holt_winterstest1

@@ -1 +1 @@
-15
+12,add

models_temp/learned_model_holt_winterstest12

@@ -0,0 +1 @@
+12,add

models_temp/learned_model_holt_winterstest13

@@ -0,0 +1 @@
+12,add

models_temp/learned_model_holt_winterstest22

@@ -0,0 +1 @@
+12,add

models_temp/learned_model_holt_winterstest40

@@ -0,0 +1 @@
+12,add

models_temp/learned_model_holt_winterstest44

@@ -0,0 +1 @@
+12,add

models_temp/learned_model_vartest

@@ -1 +1 @@
-324
+0

models_temp/learned_model_vartest1

@@ -1 +1 @@
-108
+23

models_temp/learned_model_vartest12

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest13

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest14

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest15

@@ -0,0 +1 @@
+36

models_temp/learned_model_vartest16

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest17

@@ -0,0 +1 @@
+36

models_temp/learned_model_vartest18

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest19

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest20

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest22

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest33

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest40

@@ -0,0 +1 @@
+23

models_temp/learned_model_vartest44

@@ -0,0 +1 @@
+23

models_temp/test

@@ -1 +1 @@
-VAR
+Holtwinters

server.py

@@ -4,17 +4,24 @@
 
 import engines.functions_timeseries as ft
 import engines.BBDD as db
-
+import os
 
 
 app = Flask(__name__)
 CORS(app)
 
 
-#db.init_database()
+app.config.from_pyfile(os.path.join(".", "config/app.cfg"), silent=False)
+
+db.init_database()
+
+DB_NAME= app.config.get("DB_NAME")
+PORT = app.config.get("PORT")
 
 @app.route('/univariate', methods=['POST'])
 def univariate_engine():
+    db.init_database()
+
     if not request.json:
         abort(400)
 
@@ -37,8 +44,8 @@ def univariate_engine():
     if(name != 'NA'):
         filename= './lst/'+name+'.lst'
         try:
-            with open(filename, 'r') as filehandle:
-                previousList = json.load(filehandle)
+            # with open(filename, 'r') as filehandle:
+            #     previousList = json.load(filehandle)
             previousList=db.get_ts(name).split(',')
             previousList = list(map(int, previousList))
         except Exception:
@@ -48,8 +55,8 @@ def univariate_engine():
         if  not restart :
             print ("Lista append")
             lista = previousList + lista
-        with open(filename, 'w') as filehandle:
-            json.dump(lista,filehandle)
+        # with open(filename, 'w') as filehandle:
+        #     json.dump(lista,filehandle)
         str_lista= ",".join(str(v) for v in lista)
         db.set_ts(name,str_lista)
 
@@ -124,4 +131,4 @@ def index():
     return "Timecop ready to play"
 
 if __name__ == '__main__':
-    app.run(debug=True,host = '0.0.0.0',port=80)
+    app.run(host = '0.0.0.0',port=PORT)

static/index.html

@@ -0,0 +1 @@
+<!DOCTYPE html><html><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1"><title>timecop</title><link href="https://fonts.googleapis.com/css?family=Roboto:300,400,500,700|Material+Icons" rel=stylesheet><link href=./static/css/app.14daf9aed06f69ef52ff8971689f65e3.css rel=stylesheet></head><body><div id=app></div><script type=text/javascript src=./static/js/manifest.3ad1d5771e9b13dbdad2.js></script><script type=text/javascript src=./static/js/vendor.c2a07eda06ceb06f9226.js></script><script type=text/javascript src=./static/js/app.1ad26df5b1044be50976.js></script></body></html>