STMatrix.py 文件源码

def create_dataset(self, len_closeness=3, len_trend=3, TrendInterval=7, len_period=3, PeriodInterval=1):
        """current version
        """
        # offset_week = pd.DateOffset(days=7)
        offset_frame = pd.DateOffset(minutes=24 * 60 // self.T)
        XC = []
        XP = []
        XT = []
        Y = []
        timestamps_Y = []
        depends = [range(1, len_closeness+1),
                   [PeriodInterval * self.T * j for j in range(1, len_period+1)],
                   [TrendInterval * self.T * j for j in range(1, len_trend+1)]]

        i = max(self.T * TrendInterval * len_trend, self.T * PeriodInterval * len_period, len_closeness)
        while i < len(self.pd_timestamps):
            Flag = True
            for depend in depends:
                if Flag is False:
                    break
                Flag = self.check_it([self.pd_timestamps[i] - j * offset_frame for j in depend])

            if Flag is False:
                i += 1
                continue
            x_c = [self.get_matrix(self.pd_timestamps[i] - j * offset_frame) for j in depends[0]]
            x_p = [self.get_matrix(self.pd_timestamps[i] - j * offset_frame) for j in depends[1]]
            x_t = [self.get_matrix(self.pd_timestamps[i] - j * offset_frame) for j in depends[2]]
            y = self.get_matrix(self.pd_timestamps[i])
            if len_closeness > 0:
                XC.append(np.vstack(x_c))
            if len_period > 0:
                XP.append(np.vstack(x_p))
            if len_trend > 0:
                XT.append(np.vstack(x_t))
            Y.append(y)
            timestamps_Y.append(self.timestamps[i])
            i += 1
        XC = np.asarray(XC)
        XP = np.asarray(XP)
        XT = np.asarray(XT)
        Y = np.asarray(Y)
        print("XC shape: ", XC.shape, "XP shape: ", XP.shape, "XT shape: ", XT.shape, "Y shape:", Y.shape)
        return XC, XP, XT, Y, timestamps_Y