Get Started

1. Install Ax:
   • Linux
   • Mac

   pip3 install ax-platform
   
2. Run an optimization:
   
   

   
   >>> from ax import *
   
   >>> client = Client()
   >>> client.configure_experiment(
       experiment_config=ExperimentConfig(
           name="booth_function",
           parameters=[
               RangeParameterConfig(
                   name="x1",
                   bounds=(-10.0, 10.0),
                   parameter_type=ParameterType.FLOAT,
               ),
               RangeParameterConfig(
                   name="x2",
                   bounds=(-10.0, 10.0),
                   parameter_type=ParameterType.FLOAT,
               ),
           ],
       )
   )
   >>> client.configure_optimization(objective="-1 * booth")
   
   >>> for _ in range(20):
   >>>     for trial_index, parameters in client.get_next_trials(max_trials=1).items():
   >>>         client.complete_trial(
   >>>             trial_index=trial_index,
   >>>             raw_data={
   >>>                 "booth": (parameters["x1"] + 2 * parameters["x2"] - 7) ** 2
   >>>                 + (2 * parameters["x1"] + parameters["x2"] - 5) ** 2
   >>>             },
   >>>         )
   
   >>> client.get_best_parameterization()
   {'x1': 1.02, 'x2': 2.97}  # true min is (1, 3)