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replace random.random with np.random.choice in selRoulette #689

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replace random.random with np.random.choice in selRoulette #689

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ae40803
replace random.random with np.random.choice in selRoulette
Mach-2 Mar 10, 2023
5dc8947
use random.choices in selRoulette
Mach-2 Mar 10, 2023
5136793
avoid dividing by zero when all individuals have zero fitness
Mach-2 Mar 10, 2023
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22 changes: 9 additions & 13 deletions deap/tools/selection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -78,26 +78,22 @@ def selRoulette(individuals, k, fit_attr="fitness"):
:param fit_attr: The attribute of individuals to use as selection criterion
:returns: A list of selected individuals.

This function uses the :func:`~random.random` function from the python base
This function uses the :func:`~random.choices` 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(fit_attr), reverse=True)
sum_fits = sum(getattr(ind, fit_attr).values[0] for ind in individuals)
chosen = []
for i in range(k):
u = random.random() * sum_fits
sum_ = 0
for ind in s_inds:
sum_ += getattr(ind, fit_attr).values[0]
if sum_ > u:
chosen.append(ind)
break

fits = [getattr(ind,fit_attr).values[0] for ind in individuals]
sum_fits = sum(fits)
if sum_fits == 0:
# If all individuals have zero fitness, evenly distribute probability of selection
fitness_proportions = [1/k for i in fits]
else: fitness_proportions = [i/sum_fits for i in fits]

chosen = random.choices(individuals, weights=fitness_proportions, k=k)
return chosen


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