text: """Example using Sigopt's multi-objective functionality."""
  import sys
  import time
  
  import numpy as np
  from ray import tune
  from ray.tune.suggest.sigopt import SigOptSearch
  
  np.random.seed(0)
  vector1 = np.random.normal(0, 0.1, 100)
  vector2 = np.random.normal(0, 0.1, 100)
  
  
  def evaluate(w1, w2):
      total = w1 * vector1 + w2 * vector2
      return total.mean(), total.std()
  
  
  def easy_objective(config):
      # Hyperparameters
      w1 = config["w1"]
      w2 = config["total_weight"] - w1
  
      average, std = evaluate(w1, w2)
      tune.report(average=average, std=std, sharpe=average / std)
      time.sleep(0.1)
  
  
  if __name__ == "__main__":
      import argparse
      import os
  
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--smoke-test", action="store_true", help="Finish quickly for testing"
      )
      args, _ = parser.parse_known_args()
  
      if "SIGOPT_KEY" not in os.environ:
          if args.smoke_test:
              print("SigOpt API Key not found. Skipping smoke test.")
              sys.exit(0)
          else:
              raise ValueError(
                  "SigOpt API Key not found. Please set the SIGOPT_KEY "
                  "environment variable."
              )
  
      space = [
          {
              "name": "w1",
              "type": "double",
              "bounds": {"min": 0, "max": 1},
          },
      ]
  
      algo = SigOptSearch(
          space,
          name="SigOpt Example Multi Objective Experiment",
          observation_budget=4 if args.smoke_test else 100,
          max_concurrent=1,
          metric=["average", "std", "sharpe"],
          mode=["max", "min", "obs"],
      )
  
      analysis = tune.run(
          easy_objective,
          name="my_exp",
          search_alg=algo,
          num_samples=4 if args.smoke_test else 100,
          config={"total_weight": 1},
      )
      print(
          "Best hyperparameters found were: ", analysis.get_best_config("average", "min")
      )
  