code: def _ros_plot_pos(row, censorship, cohn):
      """
      ROS-specific plotting positions.
  
      Computes the plotting position for an observation based on its rank,
      censorship status, and detection limit index.
  
      Parameters
      ----------
      row : {Series, dict}
          Full observation (row) from a censored dataset. Requires a
          'rank', 'detection_limit', and `censorship` column.
  
      censorship : str
          Name of the column in the dataframe that indicates that a
          observation is left-censored. (i.e., True -> censored,
          False -> uncensored)
  
      cohn : DataFrame
          DataFrame of Cohn numbers.
  
      Returns
      -------
      plotting_position : float
  
      See Also
      --------
      cohn_numbers
      """
  
      DL_index = row["det_limit_index"]
      rank = row["rank"]
      censored = row[censorship]
  
      dl_1 = cohn.iloc[DL_index]
      dl_2 = cohn.iloc[DL_index + 1]
      if censored:
          return (
              (1 - dl_1["prob_exceedance"])
              * rank
              / (dl_1["ncen_equal"] + 1)
          )
      else:
          return (1 - dl_1["prob_exceedance"]) + (
              dl_1["prob_exceedance"] - dl_2["prob_exceedance"]
          ) * rank / (dl_1["nuncen_above"] + 1)
  
file_path: statsmodels/statsmodels/imputation/ros.py
imports: import warnings
  import numpy
  import pandas
  from scipy import stats
label_desc: Use image node_id 5 for calling a global function with example usage: _ros_plot_pos(row, censorship, cohn) and returns: unknown, unknown