Steepest Descent¶
does this and that…
- 
class 
olympus.planners.SteepestDescent(goal='minimize', learning_rate=0.001, dx=1e-05, random_seed=None, init_guess=None, init_guess_method='random', init_guess_seed=None)[source] - Parameters
 goal –
learning_rate –
dx –
random_seed –
init_guess (array, optional) – initial guess for the optimization
init_guess_method (str) – method to construct initial guesses if init_guess is not provided. Choose from: random
init_guess_seed (str) – random seed for init_guess_method
Methods
tell([observations])Provide the planner with all previous observations.
ask([return_as])suggest new set of parameters
recommend([observations, return_as])Consecutively executes tell and ask: tell the planner about all previous observations, and ask about the next query point.
optimize(emulator[, num_iter, verbose])Optimizes a surface for a fixed number of iterations.
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ask(return_as=None) suggest new set of parameters
- Parameters
 return_as (string) – choose data type for returned parameters allowed options (dict, array)
- Returns
 newly generated parameters
- Return type
 ParameterVector
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optimize(emulator, num_iter=1, verbose=False) Optimizes a surface for a fixed number of iterations.
- Parameters
 emulator (object) – Emulator or a Surface instance to optimize over.
num_iter (int) – Maximum number of iterations allowed.
verbose (bool) – Whether to print information to screen.
- Returns
 - Campaign object with information about the optimization, including all parameters
 tested and measurements obtained.
- Return type
 campaign (Campaign)
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recommend(observations=None, return_as=None) Consecutively executes tell and ask: tell the planner about all previous observations, and ask about the next query point.
- Parameters
 observations (list of ???) –
return_as (string) – choose data type for returned parameters allowed options (dict, array)
- Returns
 newly generated parameters
- Return type
 list
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set_param_space(param_space) Defines the parameter space over which the planner will search.
- Parameters
 param_space (ParameterSpace) – a ParameterSpace object defining the space over which to search.
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tell(observations=<olympus.campaigns.observations.Observations object>) Provide the planner with all previous observations.
- Parameters
 observations (Observations) – an Observation object containing all previous observations. This defines the history of the campaign seen by the planner. The default is None, i.e. there are no previous observations.