docstr: Make sure BO still works with only one initial data point.
docstr_tok: ["Make","sure","BO","still","works","with","only","one","initial","data","point","."]
code: def test_one_initial_data_point(self):
      """Make sure BO still works with only one initial data point."""
      bounds = [
          {"name": "var_1", "type": "continuous", "domain": (-1, 1)}
      ]
      # Remove hyperparameter optimization, not needed here
      model = GPyOpt.models.GPModel(max_iters=0)
      opt = BayesianOptimization(
          lambda x: x, bounds, model=model, initial_design_numdata=1
      )
  
      # Make sure run_optimization works
      opt.run_optimization(max_iter=1)
      assert len(opt.Y) > 1
  
file_path: GPyOpt/GPyOpt/testing/methods_tests/test_bayesian_optimization.py
imports: import unittest
  import numpy
  import GPyOpt
  from GPyOpt.methods import BayesianOptimization
label_desc: Use image node_id 3 for calling the TestBayesianOptimization obj's underlying member method code with example usage: obj.test_one_initial_data_point() without return types