feature_engineering.py 文件源码

def transform_inverse(self, df):
        price = pd.read_csv(self.path_to_price, parse_dates=True, index_col='Unnamed: 0')
        #
        index = []
        values = []
        days = extract_days(df)
        time_intervs_in_day = [d.time() for i, d in enumerate(price.index)]
        for day in days:
            i = 0
            for time_intv in time_intervs_in_day:
                if time_intv <= df.index[i].time():
                    values.append(df.values[i][0])
                    index.append(datetime.combine(day, time_intv))
                else:
                    i+=1
                    values.append(df.values[i][0])
                    index.append(datetime.combine(day, time_intv))
        df_out = pd.DataFrame(values, columns=[df.columns[0]], index=index)
        return df_out