How to use the gluonts.dataset.artificial._base.ConstantDataset function in gluonts

ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_short/",
        ConstantDataset(is_noise=True, is_short=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales_noise/",
        ConstantDataset(is_noise=True, is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_zeros_and_nans/", ConstantDataset(is_nan=True)
    )
    generate_sf2s_and_csv(  # Requires is_random_constant to be set to True
        file_path,
        "constant_piecewise/",
        ConstantDataset(is_piecewise=True, is_random_constant=True),
    )
    generate_sf2s_and_csv(
        file_path, "complex_seasonal_noise_scale/", ComplexSeasonalTimeSeries()
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal_noise/",
        ComplexSeasonalTimeSeries(is_scale=False),

file_path, "constant_missing/", ConstantDataset(), is_missing=True
    )
    generate_sf2s_and_csv(
        file_path, "constant_random/", ConstantDataset(is_random_constant=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_one_ts/",
        ConstantDataset(
            num_timeseries=num_timeseries, is_random_constant=True
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales/",
        ConstantDataset(is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_noise/", ConstantDataset(is_noise=True)
    )
    generate_sf2s_and_csv(
        file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_linear_trend_noise/",
        ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),

file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_linear_trend_noise/",
        ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_short/",
        ConstantDataset(is_noise=True, is_short=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales_noise/",
        ConstantDataset(is_noise=True, is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_zeros_and_nans/", ConstantDataset(is_nan=True)
    )
    generate_sf2s_and_csv(  # Requires is_random_constant to be set to True
        file_path,
        "constant_piecewise/",
        ConstantDataset(is_piecewise=True, is_random_constant=True),
    )
    generate_sf2s_and_csv(
        file_path, "complex_seasonal_noise_scale/", ComplexSeasonalTimeSeries()

file_path, "constant_random/", ConstantDataset(is_random_constant=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_one_ts/",
        ConstantDataset(
            num_timeseries=num_timeseries, is_random_constant=True
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales/",
        ConstantDataset(is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_noise/", ConstantDataset(is_noise=True)
    )
    generate_sf2s_and_csv(
        file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_linear_trend_noise/",
        ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),
    )
    generate_sf2s_and_csv(
        file_path,

if __name__ == "__main__":
    num_timeseries = 1
    file_path = "../../../datasets/synthetic/"
    generate_sf2s_and_csv(file_path, "constant/", ConstantDataset())
    generate_sf2s_and_csv(
        file_path, "constant_missing/", ConstantDataset(), is_missing=True
    )
    generate_sf2s_and_csv(
        file_path, "constant_random/", ConstantDataset(is_random_constant=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_one_ts/",
        ConstantDataset(
            num_timeseries=num_timeseries, is_random_constant=True
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales/",
        ConstantDataset(is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_noise/", ConstantDataset(is_noise=True)
    )
    generate_sf2s_and_csv(
        file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,

)
    generate_sf2s_and_csv(
        file_path, "constant_noise/", ConstantDataset(is_noise=True)
    )
    generate_sf2s_and_csv(
        file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_linear_trend_noise/",
        ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_short/",
        ConstantDataset(is_noise=True, is_short=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales_noise/",
        ConstantDataset(is_noise=True, is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_zeros_and_nans/", ConstantDataset(is_nan=True)
    )
    generate_sf2s_and_csv(  # Requires is_random_constant to be set to True
        file_path,

"constant_missing_middle/",
        ConstantDataset(num_steps=500, num_missing_middle=100),
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal_random_start_dates_weekly/",
        ComplexSeasonalTimeSeries(
            freq_str="W",
            percentage_unique_timestamps=1,
            is_out_of_bounds_date=True,
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_promotions/",
        ConstantDataset(
            is_promotions=True,
            freq="M",
            start="2015-11-30",
            num_timeseries=100,
            num_steps=50,
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_holidays/",
        ConstantDataset(
            start="2017-07-01",
            freq="D",
            holidays=list(holidays.UnitedStates(years=[2017, 2018]).keys()),
            num_steps=365,
        ),

file_path,
        "constant_noise_short/",
        ConstantDataset(is_noise=True, is_short=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales_noise/",
        ConstantDataset(is_noise=True, is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_zeros_and_nans/", ConstantDataset(is_nan=True)
    )
    generate_sf2s_and_csv(  # Requires is_random_constant to be set to True
        file_path,
        "constant_piecewise/",
        ConstantDataset(is_piecewise=True, is_random_constant=True),
    )
    generate_sf2s_and_csv(
        file_path, "complex_seasonal_noise_scale/", ComplexSeasonalTimeSeries()
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal_noise/",
        ComplexSeasonalTimeSeries(is_scale=False),
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal/",
        ComplexSeasonalTimeSeries(is_scale=False, is_noise=False),
    )
    generate_sf2s_and_csv(
        file_path,

ComplexSeasonalTimeSeries(is_scale=False),
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal/",
        ComplexSeasonalTimeSeries(is_scale=False, is_noise=False),
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal_missing/",
        ComplexSeasonalTimeSeries(proportion_missing_values=0.8),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_missing_middle/",
        ConstantDataset(num_steps=500, num_missing_middle=100),
    )
    generate_sf2s_and_csv(
        file_path,
        "complex_seasonal_random_start_dates_weekly/",
        ComplexSeasonalTimeSeries(
            freq_str="W",
            percentage_unique_timestamps=1,
            is_out_of_bounds_date=True,
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_promotions/",
        ConstantDataset(
            is_promotions=True,
            freq="M",

file_path,
        "constant_one_ts/",
        ConstantDataset(
            num_timeseries=num_timeseries, is_random_constant=True
        ),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_diff_scales/",
        ConstantDataset(is_different_scales=True),
    )
    generate_sf2s_and_csv(
        file_path, "constant_noise/", ConstantDataset(is_noise=True)
    )
    generate_sf2s_and_csv(
        file_path, "constant_linear_trend/", ConstantDataset(is_trend=True)
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_linear_trend_noise/",
        ConstantDataset(is_noise=True, is_trend=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_long/",
        ConstantDataset(is_noise=True, is_long=True),
    )
    generate_sf2s_and_csv(
        file_path,
        "constant_noise_short/",
        ConstantDataset(is_noise=True, is_short=True),
    )