twinlab.MaximizeParams

class twinlab.MaximizeParams(opt_weights=None)

Parameter configuration for finding the location of the maximum output of your emulator.

Variables:

opt_weights (Union[List[float], None], optional) – A list of weighting values that are used to create a scalar objective function in the case of a multi-output model. The maximize functionality can only work on a single scalar function, so in the case of a multi-output model, the outputs must be combined into a single scalar value. The weights create a linear combinations of the outputs, where the weights are the coefficients of the linear combination. In the case of a single-output model, the weights are not used and have no impact. If the output dimensions are not equally important, the weights can be used to reflect this. If the output values have different units, the weights must be chosen to reflect this. For example, if two outputs have units of distance and time the weights implicitly have units such that these can be combined (i.e., per metre and per second). A list of values is used here, where the first value corresponds to the first output, the second value to the second output, and so on. For example, [1, 2, 3] would create a linear combination of the outputs where the first output is multiplied by 1, the second output by 2, and the third output by 3. In this case, the third output is considered to be three times as important as the first output. If the values [0, 1] are used, the first output is ignored and the second output is used as the scalar objective function. If the values [-1, 0] are used, the first output is used as the scalar objective function, and is minimized. The default value, None, applies equal weight to each output dimension. This is recommended for functional emulators.

__init__(opt_weights=None)

Methods

__init__([opt_weights])
unpack_parameters()