ultraopt.facade package

Submodules

ultraopt.facade.fmin module

ultraopt.facade.fmin.fmin(eval_func: Callable, config_space: Union[ConfigSpace.configuration_space.ConfigurationSpace, dict], optimizer: Union[ultraopt.optimizer.base_opt.BaseOptimizer, str, Type] = 'ETPE', initial_points: Union[None, List[ConfigSpace.configuration_space.Configuration], List[dict]] = None, random_state=42, n_iterations=100, n_jobs=1, parallel_strategy='AsyncComm', auto_identify_serial_strategy=True, multi_fidelity_iter_generator: Optional[ultraopt.multi_fidelity.iter_gen.base_gen.BaseIterGenerator] = None, previous_result: Optional[Union[ultraopt.facade.result.FMinResult, ultraopt.optimizer.base_opt.BaseOptimizer, str]] = None, warm_start_strategy='continue', show_progressbar=True, checkpoint_file=None, checkpoint_freq=10, verbose=0, run_id=None, ns_host='127.0.0.1', ns_port=0)

ultraopt.facade.result module

class ultraopt.facade.result.FMinResult(optimizer: ultraopt.optimizer.base_opt.BaseOptimizer)

基类：object

get_str()

plot_concurrent_over_time(ax=None, num_points=512, alpha=0.5)

plot_convergence(budget=None, xlabel='Number of iterations $n$', ylabel='$\\min f(x)$ after $n$ iterations', ax=None, name=None, alpha=0.2, yscale=None, color=None, true_minimum=None, **kwargs)

Plot one or several convergence traces.

参数

• args[i] (OptimizeResult, list of OptimizeResult, or tuple) –

  The result(s) for which to plot the convergence trace.

  • if OptimizeResult, then draw the corresponding single trace;

  • if list of OptimizeResult, then draw the corresponding convergence traces in transparency, along with the average convergence trace;

  • if tuple, then args[i][0] should be a string label and args[i][1] an OptimizeResult or a list of OptimizeResult.

• ax (Axes, optional) – The matplotlib axes on which to draw the plot, or None to create a new one.

• true_minimum (float, optional) – The true minimum value of the function, if known.

• yscale (None or string, optional) – The scale for the y-axis.

返回

ax – The matplotlib axes.

返回类型

Axes

plot_convergence_over_iter(budget=None, xlabel='Number of iterations $n$', ylabel='$\\min f(x)$ after $n$ iterations', ax=None, name=None, alpha=0.2, yscale=None, color=None, true_minimum=None, **kwargs)

Plot one or several convergence traces.

参数

• args[i] (OptimizeResult, list of OptimizeResult, or tuple) –

  The result(s) for which to plot the convergence trace.

  • if OptimizeResult, then draw the corresponding single trace;

  • if list of OptimizeResult, then draw the corresponding convergence traces in transparency, along with the average convergence trace;

  • if tuple, then args[i][0] should be a string label and args[i][1] an OptimizeResult or a list of OptimizeResult.

• ax (Axes, optional) – The matplotlib axes on which to draw the plot, or None to create a new one.

• true_minimum (float, optional) – The true minimum value of the function, if known.

• yscale (None or string, optional) – The scale for the y-axis.

返回

ax – The matplotlib axes.

返回类型

Axes

plot_convergence_over_time(xlabel='time [s]', ylabel='$\\min f(x)$ over time', ax=None, names=None, alpha=0.2, yscale=None, colors=None, true_minimum=None, **kwargs)

plot_correlation_across_budgets(ax=None)

plot_finished_over_time(ax=None, alpha=0.5)

plot_hi(budget=None, target_name='loss', loss2target_func=None, return_data_only=False)

ultraopt.facade.utils module

ultraopt.facade.utils.get_wanted(opt_: ultraopt.optimizer.base_opt.BaseOptimizer)

ultraopt.facade.utils.warm_start_optimizer(optimizer: ultraopt.optimizer.base_opt.BaseOptimizer, previous_result, warm_start_strategy='resume')

Module contents