# Source code for surrogate.selection.selRoulette

# Copyright 2016 Quan Pan
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# Author: Quan Pan <quanpan302@hotmail.com>
# License: Apache License, Version 2.0
# Create: 2016-12-02
import random
from operator import attrgetter
[docs]def selRoulette(individuals, k=1):
"""Select *k* individuals from the input *individuals* using *k*
spins of a roulette. The selection is made by looking only at the first
objective of each individual. The list returned contains references to
the input *individuals*.
:param individuals: A list of individuals to select from.
:param k: The number of individuals to select.
:returns: A list of selected individuals.
This function uses the :func:`~random.random` function from the python base
:mod:`random` module.
.. warning::
The roulette selection by definition cannot be used for minimization
or when the fitness can be smaller or equal to 0.
"""
s_inds = sorted(individuals, key=attrgetter("fitness"), reverse=True)
# TODO 20161204 individual property fitness.values[]
# sum_fits = sum(ind.fitness.values[0] for ind in individuals)
sum_fits = sum(ind.fitness for ind in individuals)
chosen = []
for i in xrange(k):
u = random.random() * sum_fits
sum_ = 0
for ind in s_inds:
# sum_ += ind.fitness.values[0]
sum_ += ind.fitness
if sum_ > u:
chosen.append(ind)
break
return chosen