total_whv_rect#
- moocore.total_whv_rect(x, /, rectangles, *, ref, maximise=False, ideal=None, scalefactor=0.1)[source]#
Compute total weighted hypervolume given a set of rectangles.
Calculates the hypervolume weighted by a set of rectangles (with zero weight outside the rectangles). The function
total_whv_rect()
calculates the total weighted hypervolume ashypervolume()
+ scalefactor * abs(prod(ref - ideal)) *
whv_rect()
. The details of the computation are given by Diaz and López-Ibáñez[1].Warning
The current implementation only supports 2 objectives.
- Parameters:
x – Numpy array of numerical values, where each row gives the coordinates of a point. If the array is created from the
read_datasets()
function, remove the last column.rectangles – Weighted rectangles that will bias the computation of the hypervolume. Maybe generated by
eafdiff()
withrectangles=True
or bychoose_eafdiff()
.ref – Reference point as a 1D vector. Must be same length as a single row in
x
.maximise (
bool
oror list
ofbool
) – Whether the objectives must be maximised instead of minimised. Either a single boolean value that applies to all objectives or a list of booleans, with one value per objective. Also accepts a 1D numpy array with values 0 or 1 for each objective.ideal (default:
None
) – Ideal point as a vector of numerical values. IfNone
, it is calculated as minimum (or maximum if maximising that objective) of each objective in the input data.scalefactor (
float
, default:0.1
) – Real value within \((0,1]\) that scales the overall weight of the differences. This is parameter psi (\(\psi\)) in Diaz and López-Ibáñez[1].
- Returns:
float
– A single numerical value, the weighted hypervolume
See also
References
Examples
>>> rectangles = np.array( ... [ ... [1.0, 3.0, 2.0, np.inf, 1], ... [2.0, 3.5, 2.5, np.inf, 2], ... [2.0, 3.0, 3.0, 3.5, 3], ... ] ... ) >>> whv_rect([[2, 2]], rectangles, ref=6) 4.0 >>> whv_rect([[2, 1]], rectangles, ref=6) 4.0 >>> whv_rect([[1, 2]], rectangles, ref=6) 7.0 >>> total_whv_rect([[2, 2]], rectangles, ref=6, ideal=1) 26.0 >>> total_whv_rect([[2, 1]], rectangles, ref=6, ideal=1) 30.0 >>> total_whv_rect([[1, 2]], rectangles, ref=6, ideal=1) 37.5