code: def process_comparison_options(filter_df, option):
      color = "type"
      if option == "CPU vs Plaintext":
          filter_df = filter_df[filter_df["device"] == "cpu"]
          filter_df["type"] = np.where(
              filter_df["is plain text"], "Plain Text", "CrypTen"
          )
      elif option == "GPU vs Plaintext":
          filter_df = filter_df[filter_df["device"] == "gpu"]
          if not filter_df.empty:
              filter_df["type"] = np.where(
                  filter_df["is plain text"], "Plain Text", "CrypTen"
              )
      elif option == "CPU vs GPU":
          filter_df = filter_df[filter_df["is plain text"] is False]
          color = "device"
  
      return filter_df, color
  
imports: import pathlib
  import dash
  import dash_core_components
  import dash_html_components
  import numpy
  import pandas
  import plotly.express
  import plotly.graph_objects
  from dash.dependencies import Input, Output
  from load_data import get_aggregated_data, get_available_dates
  from plotly.subplots import make_subplots
label_desc: Use image node_id 5 for calling a global function with example usage: process_comparison_options(filter_df, option) and returns: filter_df,  color