original_docstring: 
      Write the SMILES and properties in the summary dictionary
      to a csv file.
      Args:
        summary_dic (dict): dictionary of the form {smiles: sub_dic},
          where `sub_dic` is a dictionary with all the species properties
          apart from its conformers.
        props (list[str]): list of property names that you want to predict
        csv_file (str): path to csv file that you want to write to
      Returns:
        None
      
docstring: Write the SMILES and properties in the summary dictionary
  to a csv file.
docstring_tokens: Write the SMILES and properties in the summary dictionary to a csv file .
code: def to_csv(summary_dic,
             props,
             csv_file):
      """
      Write the SMILES and properties in the summary dictionary
      to a csv file.
      Args:
        summary_dic (dict): dictionary of the form {smiles: sub_dic},
          where `sub_dic` is a dictionary with all the species properties
          apart from its conformers.
        props (list[str]): list of property names that you want to predict
        csv_file (str): path to csv file that you want to write to
      Returns:
        None
      """
  
      columns = ['smiles'] + props
      dict_data = []
      for smiles, sub_dic in summary_dic.items():
          dic = {}
          for prop in props:
              if prop.startswith("log_"):
                  base_prop = prop.split("log_")[-1]
                  if base_prop in sub_dic:
                      dic[prop] = np.log(sub_dic[base_prop])
  
          dic = {prop: sub_dic[prop] for prop in props}
          dic["smiles"] = smiles
          dict_data.append(dic)
  
      with open(csv_file, 'w') as csvfile:
          writer = csv.DictWriter(csvfile, fieldnames=columns)
          writer.writeheader()
          for data in dict_data:
              writer.writerow(data)
code_tokens: def to_csv ( summary_dic , props , csv_file ) : columns = [ 'smiles' ] + props dict_data = [ ] for smiles , sub_dic in summary_dic . items ( ) : dic = { } for prop in props : if prop . startswith ( "log_" ) : base_prop = prop . split ( "log_" ) [ - 1 ] if base_prop in sub_dic : dic [ prop ] = np . log ( sub_dic [ base_prop ] ) dic = { prop : sub_dic [ prop ] for prop in props } dic [ "smiles" ] = smiles dict_data . append ( dic ) with open ( csv_file , 'w' ) as csvfile : writer = csv . DictWriter ( csvfile , fieldnames = columns ) writer . writeheader ( ) for data in dict_data : writer . writerow ( data )
short_docstring: Write the SMILES and properties in the summary dictionary
  to a csv file.
short_docstring_tokens: Write the SMILES and properties in the summary dictionary to a csv file .
comment: """
      Write the SMILES and properties in the summary dictionary
      to a csv file.
      Args:
        summary_dic (dict): dictionary of the form {smiles: sub_dic},
          where `sub_dic` is a dictionary with all the species properties
          apart from its conformers.
        props (list[str]): list of property names that you want to predict
        csv_file (str): path to csv file that you want to write to
      Returns:
        None
      """