benchopt.BaseObjective

class benchopt.BaseObjective(**parameters)

Base class to define an objective function

Objectives that derive from this class should implement three methods:

• set_data(**data): stores the info from a given dataset to be able to compute the objective value on these data.

• get_objective(): exports the data from the dataset and the parameters from the objective function as a dictionary that will be passed as parameters of the solver’s set_objective method in order to specify the objective function of the benchmark.

• compute(beta): computes the value of the objective function for an given estimate beta. Beta is given as np.array of size corresponding to the dimension value returned by Dataset.get_data. The output should be a float or a dictionary of floats. If a dictionary is returned, it should at least contain a key value associated to a scalar value which will be used to detect convergence. With a dictionary, multiple metric values can be stored at once instead of runnning each separately.

abstract compute(beta)

Compute the value of the objective given the current estimate beta.

Parameters

betandarray or tuple of ndarray

The current estimate of the parameters being optimized.

Returns

objective_valuefloat or dict {‘name’: float}

The value(s) of the objective function. If a dictionary is returned, it should at least contain a key value associated to a scalar value which will be used to detect convergence. With a dictionary, multiple metric values can be stored at once instead of runnning each separately.

abstract get_objective()

Return the objective parameters for the solver.

Returns

objective_dict: dict

Parameters of the objective that will be given to the solver when calling Solver.set_objective(**objective_dict).

abstract get_one_solution()

Return one solution for which the objective can be evaluated.

This method is mainly for testing purposes, to check that the method Objective.compute can be called and that it returns a compatible type for benchopt. The returned object will be passed to Objective.compute.

abstract set_data(**data)

Store the info on a dataset to be able to compute the objective.

Parameters

**data: dict

Extra parameters of the objective. This dictionary is retrieved by calling data = Dataset.get_data().

skip(**data)

Used to decide if the Objective is compatible with the data.

Parameters

**data: dict

Extra parameters of the objective. This dictionary is retrieved by calling data = Dataset.get_data().

Returns

skipbool

Whether this objective should be skipped or not for this data (accessible in the objective attributes).

reasonstr | None

The reason why it should be skipped for display purposes. If skip is False, the reason should be None.