/usr/lib/python3/dist-packages/deap/tools/init.py is in python3-deap 1.0.2.post2-2.
This file is owned by root:root, with mode 0o644.
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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 | def initRepeat(container, func, n):
"""Call the function *container* with a generator function corresponding
to the calling *n* times the function *func*.
:param container: The type to put in the data from func.
:param func: The function that will be called n times to fill the
container.
:param n: The number of times to repeat func.
:returns: An instance of the container filled with data from func.
This helper function can can be used in conjunction with a Toolbox
to register a generator of filled containers, as individuals or
population.
>>> initRepeat(list, random.random, 2) # doctest: +ELLIPSIS,
... # doctest: +NORMALIZE_WHITESPACE
[0.4761..., 0.6302...]
See the :ref:`list-of-floats` and :ref:`population` tutorials for more examples.
"""
return container(func() for _ in range(n))
def initIterate(container, generator):
"""Call the function *container* with an iterable as
its only argument. The iterable must be returned by
the method or the object *generator*.
:param container: The type to put in the data from func.
:param generator: A function returning an iterable (list, tuple, ...),
the content of this iterable will fill the container.
:returns: An instance of the container filled with data from the
generator.
This helper function can can be used in conjunction with a Toolbox
to register a generator of filled containers, as individuals or
population.
>>> from random import sample
>>> from functools import partial
>>> gen_idx = partial(sample, range(10), 10)
>>> initIterate(list, gen_idx)
[4, 5, 3, 6, 0, 9, 2, 7, 1, 8]
See the :ref:`permutation` and :ref:`arithmetic-expr` tutorials for
more examples.
"""
return container(generator())
def initCycle(container, seq_func, n=1):
"""Call the function *container* with a generator function corresponding
to the calling *n* times the functions present in *seq_func*.
:param container: The type to put in the data from func.
:param seq_func: A list of function objects to be called in order to
fill the container.
:param n: Number of times to iterate through the list of functions.
:returns: An instance of the container filled with data from the
returned by the functions.
This helper function can can be used in conjunction with a Toolbox
to register a generator of filled containers, as individuals or
population.
>>> func_seq = [lambda:1 , lambda:'a', lambda:3]
>>> initCycle(list, func_seq, n=2)
[1, 'a', 3, 1, 'a', 3]
See the :ref:`funky` tutorial for an example.
"""
return container(func() for _ in range(n) for func in seq_func)
__all__ = ['initRepeat', 'initIterate', 'initCycle']
if __name__ == "__main__":
import doctest
import random
random.seed(64)
doctest.run_docstring_examples(initRepeat, globals())
random.seed(64)
doctest.run_docstring_examples(initIterate, globals())
doctest.run_docstring_examples(initCycle, globals())
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