def helper_create_multivariate_linear_timeseries(
    n_components: int, components_names: Sequence[str] = None, **kwargs
) -> TimeSeries:
    """
    Helper function that creates a `linear_timeseries` with a specified number of
    components. To help distinguish each component from one another, `i` is added on
    to each value of the `i`th component. Any additional keyword arguments are passed
    to `linear_timeseries` (`start_value`, `end_value`, `start`, `end`, `length`, etc).
    """
    if components_names is None or len(components_names) < n_components:
        components_names = [f"lin_ts_{i}" for i in range(n_components)]
    timeseries = []
    for i in range(n_components):
        # Values of each component is 1 larger than the last:
        timeseries_i = linear_timeseries(column_name=components_names[i], **kwargs) + i
        timeseries.append(timeseries_i)
    return darts_concatenate(timeseries, axis=1)

    Helper function that creates a `linear_timeseries` with a specified number of
    components. To help distinguish each component from one another, `i` is added on
    to each value of the `i`th component. Any additional keyword arguments are passed
    to `linear_timeseries` (`start_value`, `end_value`, `start`, `end`, `length`, etc).
    
darts/tests/utils/tabularization/test_create_lagged_training_data.py