original_docstring: 
          Add a dataframe of frequency and intensities to the session U-line dictionary. This function provides more
          manual control over what can be processed in the assignment pipeline, as not everything can be picked
          up by the peak finding algorithm.
  
          Parameters
          ----------
          dataframe : pandas dataframe
              Dataframe containing a frequency and intensity column to add to the uline list.
          freq_col : None or str
              Specify column to use for frequencies. If None, uses the session value freq_col.
          int_col : None or str
              Specify column to use for intensities. If None, uses the session value int_col.
          
docstring: Add a dataframe of frequency and intensities to the session U-line dictionary. This function provides more
  manual control over what can be processed in the assignment pipeline, as not everything can be picked
  up by the peak finding algorithm.
  
  Parameters
  
  dataframe : pandas dataframe
  Dataframe containing a frequency and intensity column to add to the uline list.
  freq_col : None or str
  Specify column to use for frequencies. If None, uses the session value freq_col.
  int_col : None or str
  Specify column to use for intensities. If None, uses the session value int_col.
docstring_tokens: Add a dataframe of frequency and intensities to the session U - line dictionary . This function provides more manual control over what can be processed in the assignment pipeline as not everything can be picked up by the peak finding algorithm . Parameters dataframe : pandas dataframe Dataframe containing a frequency and intensity column to add to the uline list . freq_col : None or str Specify column to use for frequencies . If None uses the session value freq_col . int_col : None or str Specify column to use for intensities . If None uses the session value int_col .
code: def df2ulines(self, dataframe: pd.DataFrame, freq_col=None, int_col=None):
          """
          Add a dataframe of frequency and intensities to the session U-line dictionary. This function provides more
          manual control over what can be processed in the assignment pipeline, as not everything can be picked
          up by the peak finding algorithm.
  
          Parameters
          ----------
          dataframe : pandas dataframe
              Dataframe containing a frequency and intensity column to add to the uline list.
          freq_col : None or str
              Specify column to use for frequencies. If None, uses the session value freq_col.
          int_col : None or str
              Specify column to use for intensities. If None, uses the session value int_col.
          """
          if freq_col is None:
              freq_col = self.freq_col
          if int_col is None:
              int_col = self.int_col
          self.logger.info("Modifying the experiment LineList.")
          # Set up session information to be passed in the U-line
          skip = [
              "temperature",
              "doppler",
              "freq_abs",
              "freq_prox",
              "noise_rms",
              "baseline",
              "header",
              "noise_region",
              "composition",
              "name",
              "max_uncertainty",
          ]
          selected_session = {
              key: self.session.__dict__[key]
              for key in self.session.__dict__
              if key not in skip
          }
          # If the Peaks key has not been set up yet, we set it up now
          if "Peaks" not in self.line_lists:
              self.line_lists["Peaks"] = LineList.from_dataframe(
                  dataframe,
                  name="Peaks",
                  freq_col=freq_col,
                  int_col=int_col,
                  **selected_session,
              )
          # Otherwise, we'll just update the existing LineList
          else:
              vfunc = np.vectorize(Transition)
              transitions = vfunc(
                  frequency=dataframe[freq_col],
                  intensity=dataframe[int_col],
                  **selected_session,
              )
              self.line_lists["Peaks"].update_linelist(transitions)
          new_remaining = len(self.line_lists["Peaks"])
          self.logger.info(f"There are now {new_remaining} line entries in this session.")
          peaks_df = self.line_lists["Peaks"].to_dataframe()[["frequency", "intensity"]]
          peaks_df.columns = ["Frequency", "Intensity"]
          self.peaks = peaks_df
code_tokens: def df2ulines ( self , dataframe : pd . DataFrame , freq_col = None , int_col = None ) : if freq_col is None : freq_col = self . freq_col if int_col is None : int_col = self . int_col self . logger . info ( "Modifying the experiment LineList." ) skip = [ "temperature" , "doppler" , "freq_abs" , "freq_prox" , "noise_rms" , "baseline" , "header" , "noise_region" , "composition" , "name" , "max_uncertainty" , ] selected_session = { key : self . session . __dict__ [ key ] for key in self . session . __dict__ if key not in skip } if "Peaks" not in self . line_lists : self . line_lists [ "Peaks" ] = LineList . from_dataframe ( dataframe , name = "Peaks" , freq_col = freq_col , int_col = int_col , ** selected_session , ) else : vfunc = np . vectorize ( Transition ) transitions = vfunc ( frequency = dataframe [ freq_col ] , intensity = dataframe [ int_col ] , ** selected_session , ) self . line_lists [ "Peaks" ] . update_linelist ( transitions ) new_remaining = len ( self . line_lists [ "Peaks" ] ) self . logger . info ( f"There are now {new_remaining} line entries in this session." ) peaks_df = self . line_lists [ "Peaks" ] . to_dataframe ( ) [ [ "frequency" , "intensity" ] ] peaks_df . columns = [ "Frequency" , "Intensity" ] self . peaks = peaks_df
short_docstring: Add a dataframe of frequency and intensities to the session U-line dictionary.
short_docstring_tokens: Add a dataframe of frequency and intensities to the session U - line dictionary .
comment: """
          Add a dataframe of frequency and intensities to the session U-line dictionary. This function provides more
          manual control over what can be processed in the assignment pipeline, as not everything can be picked
          up by the peak finding algorithm.
  
          Parameters
          ----------
          dataframe : pandas dataframe
              Dataframe containing a frequency and intensity column to add to the uline list.
          freq_col : None or str
              Specify column to use for frequencies. If None, uses the session value freq_col.
          int_col : None or str
              Specify column to use for intensities. If None, uses the session value int_col.
          """$SEP$# Set up session information to be passed in the U-line$SEP$# If the Peaks key has not been set up yet, we set it up now$SEP$# Otherwise, we'll just update the existing LineList