Example #1
0
    def execute_scheme(self):

        model = TimeSeriesPredictionNeuralNet(self.settings)
        model.setup()
        model.compile_model()

        connection = SQLAConnection()
        query_generator = QueryGenerator(
            self.settings.sensors,
            self.settings.start_date,
            self.settings.end_date
            )
        data = Data(query_generator,connection)
        if self.args.load_dataframe:
            data.load_dfs(date='2020-11-01')
            #data.load_extend_dfs(date='2020-11-02')
            #data.load_extend_dfs(date='2020-11-03')
            #data.load_extend_dfs(date='2020-11-04')
            #data.load_extend_dfs(date='2020-11-08')
            #data.load_extend_dfs(date='2020-11-12')
            #data.load_extend_dfs(date='2020-11-16')
            #data.load_extend_dfs(date='2020-11-20')
            #data.load_extend_dfs(date='2020-11-24')
            #data.load_extend_dfs(date='2020-11-28')
            #data.load_extend_dfs(date='2020-12-02')  
            #data.load_extend_dfs(date='2020-12-18')
            #data.load_extend_dfs(date='2020-12-30')       
            #data.load_extend_dfs(date='2020-12-08')      
        else:
            data.make_df_postgres()
            data.find_discontinuities()
            data.split_at_discontinuities()
            data.preprocess(self.settings.normalization)
            data.add_trig()
        data.train_test_split(self.data_split)      
        model.make_timeseries_dataset(data)
        model.print_shape()
        model.plot_example()
        #model.save_dataset()           
        if self.args.load: 
            model.load_nn()
           
        model.train()
        model.plot_history()
        model.evaluate()
        model.save_nn(overwrite=True)
        model.test()
        model.plot_outliers()
        model.plot_example()
Example #2
0
                self.settings.sensors,
                self.settings.start_date,
                self.settings.end_date
                )
            data = Data(query_generator,connection)
            if self.args.load_dataframe:
                data.load_dfs(date='2020-11-01')  
            else:
                data.make_df_postgres()
                data.find_discontinuities()
                data.split_at_discontinuities()
                data.preprocess(self.settings.normalization)
                #data.fast_fourier_transform()
                #data.wawelet()
                #data.STL()
                data.add_trig()
                #data.add_temp()
            data.train_test_split(self.data_split)      
            model.make_timeseries_dataset(data)
            #model.save_dataset()           
        if self.args.load: 
            model.load_nn()
=======
        # Läs in neuralnät
        #model.load_nn()
        
        connection = SQLAConnection()
        query_generator = QueryGenerator(
            self.settings.sensors,
            self.settings.start_date,
            self.settings.end_date