ribs.archives.CQDScoreResult¶

class ribs.archives.CQDScoreResult(iterations: int | integer, mean: float | floating, scores: ndarray, target_points: ndarray, penalties: ndarray, obj_min: float | floating, obj_max: float | floating, dist_max: float | floating, dist_ord: Any)[source]¶

Stores the result of running cqd_score().

Methods

Attributes

iterations	Number of times the score was computed.
mean	The mean score.
scores	Array of scores obtained on each iteration.
target_points	(iterations, n, measure_dim) array of target points passed into the function.
penalties	1D array of penalties used in the computation.
obj_min	Minimum objective passed into the function.
obj_max	Maximum objective passed into the function.
dist_max	Max distance passed into the function.
dist_ord	Order of the norm for distance that was passed into the function.

dist_max : float | floating¶

Max distance passed into the function.

dist_ord : Any¶

Order of the norm for distance that was passed into the function. Refer to the ord argument in numpy.linalg.norm() for type info.

iterations : int | integer¶

Number of times the score was computed.

mean : float | floating¶

The mean score. This is the result most users will need.

obj_max : float | floating¶

Maximum objective passed into the function.

obj_min : float | floating¶

Minimum objective passed into the function.

penalties : ndarray¶

1D array of penalties used in the computation. If an array of penalties was passed in, this will be a copy of that array.

scores : ndarray¶

Array of scores obtained on each iteration.

target_points : ndarray¶

(iterations, n, measure_dim) array of target points passed into the function.