Store all population and obj values

Preference information doesn't need to be limited by the nadir point. It should only be dominated by the ideal point.

Show in the documentation, if we have the other MOO problem, how to write the code to solve it with rvea

For translation in RVEA.

I have tried to get the final non-dominated points in DTLZ3 test problem by using the following commends:

xoptTemp = pop.non_dominated()
print(xoptTemp)

But I got the following results:

Plot saved as: DTLZ3_3.html
View the plot by opening the file in browser.
To view the plot in Jupyter Notebook, use the IFrame command.
Iteration: 0%| | 0/9 [00:00<?, ?it/s]/home/babooshka/Desktop/ANOVAMOP/pyRVEA/pyrvea/OtherTools/ReferenceVectors.py:224: RuntimeWarning:

invalid value encountered in arccos

Iteration: 100%|███████████████████████████████████████████████████████████████████████████████| 9/9 [01:10<00:00, 7.79s/it]
([array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,
39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,
65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103,
104])], [array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64), array([], dtype=int64)], array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]), array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]))

Required for the binder page

used for evonn, biogp

No clue what happened

While the support for parallel plot is basically non-existent, the "grammar of graphics" seems appealing. On the JS side, vega seems appealing too.

PyGMO cannot be installed using pip on mac. Consider removing that package dependency and replacing it with functions taken from deap.

See sklearn QuantileTransformer