Optimization Objective

class edbo.objective.objective(results_path=None, results=Empty DataFrame Columns: [] Index: [], domain_path=None, domain=Empty DataFrame Columns: [] Index: [], exindex_path=None, exindex=Empty DataFrame Columns: [] Index: [], target=-1, gpu=False, computational_objective=None)

Objective funciton data container and operations.

Note

Objective internally standardizes response values to zero mean and unit variance.

__init__(results_path=None, results=Empty DataFrame Columns: [] Index: [], domain_path=None, domain=Empty DataFrame Columns: [] Index: [], exindex_path=None, exindex=Empty DataFrame Columns: [] Index: [], target=-1, gpu=False, computational_objective=None)
Parameters

  • results_path (str, optional) – Path to experimental results.

  • results (pandas.DataFrame, optional) – Experimental results with X values matching the domain.

  • domain_path (str, optional) –

    Path to experimental domain.

    Note

    A domain_path or domain are required.

  • domain (pandas.DataFrame, optional) – Experimental domain specified as a matrix of possible configurations.

  • exindex_path (str, optional) – Path to experiment results index if available.

  • exindex (pandas.DataFrame, optional) – Experiment results index matching domain format. Used as lookup table for simulations.

  • target (str) – Column label of optimization objective. If set to -1, the last column of the DataFrame will be set as the target.

  • gpu (bool) – Carry out GPyTorch computations on a GPU if available.

  • computational_objective (function, optional) – Function to be optimized for computational objectives.

get_results(domain_points, append=False)

Returns target values corresponding to domain_points.

Parameters

  • domain_points (pandas.DataFrame) – Points from experiment index to retrieve responses for. If the objective is a computational function, run function and return responses.

  • append (bool) – If true append points to results and update X and y.

Returns

Proposed experiments.

Return type

pandas.DataFrame

clear_results()

Clear results and reset X and y.

Returns

Return type

None

results_input()

Return unstandardized results.

Returns

Unstandardized results.

Return type

pandas.DataFrame