result of ClassicSeasonalDecomposition is all Nan

[sangyx]

Hi, I used ClassicSeasonalDecomposition for my own dataset, while the result was all Nan. Could you help me to figure it out? My code is:

import pandas as pd
from adtk.detector import *
from adtk.transformer import *
from adtk.data import validate_series
from adtk.visualization import plot

def sd(file):
    key, _, _, idx = file.split("_")
    idx = int(idx[:-4])
    df = pd.read_csv(file, names=["val"])
    df["id"] = df.index
    df.index = pd.DatetimeIndex(
        pd.date_range(start="20000101", periods=len(df), freq="30T")
    )
    s_train = validate_series(df.iloc[:idx]["val"])
    s_test = validate_series(df.iloc[idx:]["val"])

    tsf = ClassicSeasonalDecomposition(trend=True)

    st_train = tsf.fit_transform(s_train).rename("Train: transformed")
    plot(pd.concat([s_train, st_train], axis=1), ts_markersize=1)
    st_test = tsf.transform(s_test).rename("Test: transformed")
    plot(pd.concat([s_test, st_test], axis=1), ts_markersize=1)

    print(st_train)
    print(st_test)

if __name__ == "__main__":
    sd("001_UCR_Anomaly_35000.txt")

The dataset I used is: 001_UCR_Anomaly_35000.txt