code: def align(
      self, df: DataFrame, id_col: str, time_col: str, target_col: str
  ) -> "TimeSeriesDataset":
      # Protect consistency
      df = ufp.copy_if_pandas(df, deep=False)
  
      # Add Nones to missing columns (without available_mask)
      temporal_cols = self.temporal_cols.copy()
      for col in temporal_cols:
          if col not in df.columns:
              df = ufp.assign_columns(df, col, np.nan)
          if col == "available_mask":
              df = ufp.assign_columns(df, col, 1.0)
  
      # Sort columns to match self.temporal_cols (without available_mask)
      df = df[[id_col, time_col] + temporal_cols.tolist()]
  
      # Process future_df
      dataset, *_ = TimeSeriesDataset.from_df(
          df=df,
          sort_df=self.sorted,
          id_col=id_col,
          time_col=time_col,
          target_col=target_col,
      )
      return dataset
  
imports: import warnings
  from collections.abc import Mapping
  import numpy
  import pandas
  import pytorch_lightning
  import torch
  import utilsforecast.processing
  from torch.utils.data import Dataset, DataLoader
  from utilsforecast.compat import DataFrame, pl_Series
label_desc: Use image node_id 6 for calling the TimeSeriesDataset obj's underlying member method code with example usage: obj.align(df, id_col, time_col, target_col) and returns: dataset