# Results

`class boulderopal.closed_loop.Results(parameters, costs, cost_uncertainties=None)`

Results from evaluating the closed-loop optimization cost function.

### Parameters

**parameters**(*np.ndarray*) – The parameters at which the cost function was evaluated as a 2D array of shape`(test_point_count, parameter_count)`

.**costs**(*np.ndarray*) – The evaluated costs from the cost function as a 1D array of shape`(test_point_count,)`

.**cost_uncertainties**(*np.ndarray**or**None**,**optional*) – The uncertainties associated with the costs. If provided, must have the same shape as costs. Defaults to None, in which case there is no uncertainty associated to the costs.

### SEE ALSO

`boulderopal.closed_loop.step`

: Perform a single step in a closed-loop optimization.