Source code for surrogate.mutation.mutGaussian

# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
# Author: Quan Pan <>
# License: Apache License, Version 2.0
# Create: 2016-12-02

import random
from collections import Sequence
from itertools import repeat

[docs]def mutGaussian(variable, mu=1, sigma=0.5, prob=0.5): """This function applies a gaussian mutation of mean *mu* and standard deviation *sigma* on the input individual. This mutation expects a :term:`sequence` individual composed of real valued attributes. The *prob* argument is the probability of each attribute to be mutated. :param variable: Decision Variable to be mutated. :param mu: Mean or :term:`python:sequence` of means for the gaussian addition mutation. :param sigma: Standard deviation or :term:`python:sequence` of standard deviations for the gaussian addition mutation. :param prob: Independent probability for each attribute to be mutated. :returns: A tuple of one variable. This function uses the :func:`~random.random` and :func:`~random.gauss` functions from the python base :mod:`random` module. """ size = len(variable) # size = variable.size if not isinstance(mu, Sequence): mu = repeat(mu, size) elif len(mu) < size: raise IndexError("mu must be at least the size of variable: %d < %d" % (len(mu), size)) if not isinstance(sigma, Sequence): sigma = repeat(sigma, size) elif len(sigma) < size: raise IndexError("sigma must be at least the size of variable: %d < %d" % (len(sigma), size)) for i, m, s in zip(xrange(size), mu, sigma): if random.random() < prob: variable[i] += random.gauss(m, s) return variable