forked from AFPy/python-docs-fr
548 lines
20 KiB
Plaintext
548 lines
20 KiB
Plaintext
# Copyright (C) 2001-2018, Python Software Foundation
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# For licence information, see README file.
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#
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msgid ""
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msgstr ""
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"Project-Id-Version: Python 3.6\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2019-09-04 11:33+0200\n"
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"PO-Revision-Date: 2018-12-06 22:18+0100\n"
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"Last-Translator: Julien Palard <julien@palard.fr>\n"
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"Language-Team: FRENCH <traductions@lists.afpy.org>\n"
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"Language: fr\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=UTF-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"X-Generator: Poedit 2.2\n"
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#: ../Doc/library/random.rst:2
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msgid ":mod:`random` --- Generate pseudo-random numbers"
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msgstr ":mod:`random` --- Génère des nombres pseudo-aléatoires"
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#: ../Doc/library/random.rst:7
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msgid "**Source code:** :source:`Lib/random.py`"
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msgstr "**Code source :** :source:`Lib/random.py`"
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#: ../Doc/library/random.rst:11
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msgid ""
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"This module implements pseudo-random number generators for various "
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"distributions."
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msgstr ""
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"Ce module implémente des générateurs de nombres pseudo-aléatoires pour "
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"différentes distributions."
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#: ../Doc/library/random.rst:14
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msgid ""
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"For integers, there is uniform selection from a range. For sequences, there "
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"is uniform selection of a random element, a function to generate a random "
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"permutation of a list in-place, and a function for random sampling without "
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"replacement."
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msgstr ""
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"Pour les entiers, il existe une sélection uniforme à partir d'une plage. "
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"Pour les séquences, il existe une sélection uniforme d'un élément aléatoire, "
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"une fonction pour générer une permutation aléatoire d'une liste sur place et "
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"une fonction pour un échantillonnage aléatoire sans remplacement."
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#: ../Doc/library/random.rst:19
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msgid ""
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"On the real line, there are functions to compute uniform, normal (Gaussian), "
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"lognormal, negative exponential, gamma, and beta distributions. For "
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"generating distributions of angles, the von Mises distribution is available."
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msgstr ""
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"Pour l'ensemble des réels, il y a des fonctions pour calculer des "
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"distributions uniformes, normales (gaussiennes), log-normales, "
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"exponentielles négatives, gamma et bêta. Pour générer des distributions "
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"d'angles, la distribution de *von Mises* est disponible."
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#: ../Doc/library/random.rst:23
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msgid ""
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"Almost all module functions depend on the basic function :func:`.random`, "
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"which generates a random float uniformly in the semi-open range [0.0, 1.0). "
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"Python uses the Mersenne Twister as the core generator. It produces 53-bit "
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"precision floats and has a period of 2\\*\\*19937-1. The underlying "
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"implementation in C is both fast and threadsafe. The Mersenne Twister is "
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"one of the most extensively tested random number generators in existence. "
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"However, being completely deterministic, it is not suitable for all "
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"purposes, and is completely unsuitable for cryptographic purposes."
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msgstr ""
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"Presque toutes les fonctions du module dépendent de la fonction de base :"
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"func:`.random`, qui génère un nombre à virgule flottante aléatoire de façon "
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"uniforme dans la plage semi-ouverte [0.0, 1.0). Python utilise l'algorithme "
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"*Mersenne Twister* comme générateur de base. Il produit des flottants de "
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"précision de 53 bits et a une période de 2\\*\\*\\*19937-1. L'implémentation "
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"sous-jacente en C est à la fois rapide et compatible avec les programmes "
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"ayant de multiples fils d'exécution. Le *Mersenne Twister* est l'un des "
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"générateurs de nombres aléatoires les plus largement testés qui existent. "
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"Cependant, étant complètement déterministe, il n'est pas adapté à tous les "
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"usages et est totalement inadapté à des fins cryptographiques."
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#: ../Doc/library/random.rst:32
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msgid ""
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"The functions supplied by this module are actually bound methods of a hidden "
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"instance of the :class:`random.Random` class. You can instantiate your own "
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"instances of :class:`Random` to get generators that don't share state."
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msgstr ""
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"Les fonctions fournies par ce module dépendent en réalité de méthodes d’une "
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"instance cachée de la classe :class:`random.Random`. Vous pouvez créer vos "
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"propres instances de :class:`Random` pour obtenir des générateurs sans états "
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"partagés."
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#: ../Doc/library/random.rst:36
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msgid ""
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"Class :class:`Random` can also be subclassed if you want to use a different "
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"basic generator of your own devising: in that case, override the :meth:"
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"`~Random.random`, :meth:`~Random.seed`, :meth:`~Random.getstate`, and :meth:"
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"`~Random.setstate` methods. Optionally, a new generator can supply a :meth:"
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"`~Random.getrandbits` method --- this allows :meth:`randrange` to produce "
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"selections over an arbitrarily large range."
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msgstr ""
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"La classe :class:`Random` peut également être sous-classée si vous voulez "
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"utiliser un générateur de base différent, de votre propre conception. Dans "
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"ce cas, remplacez les méthodes :meth:`~Random.random`, :meth:`~Random."
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"seed`, :meth:`~Random.gettsate` et :meth:`~Random.setstate`. En option, un "
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"nouveau générateur peut fournir une méthode :meth:`~Random.getrandbits` --- "
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"ce qui permet à :meth:`randrange` de produire des sélections sur une plage "
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"de taille arbitraire."
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#: ../Doc/library/random.rst:42
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msgid ""
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"The :mod:`random` module also provides the :class:`SystemRandom` class which "
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"uses the system function :func:`os.urandom` to generate random numbers from "
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"sources provided by the operating system."
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msgstr ""
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#: ../Doc/library/random.rst:48
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msgid ""
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"The pseudo-random generators of this module should not be used for security "
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"purposes. For security or cryptographic uses, see the :mod:`secrets` module."
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msgstr ""
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#: ../Doc/library/random.rst:54
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msgid ""
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"M. Matsumoto and T. Nishimura, \"Mersenne Twister: A 623-dimensionally "
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"equidistributed uniform pseudorandom number generator\", ACM Transactions on "
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"Modeling and Computer Simulation Vol. 8, No. 1, January pp.3--30 1998."
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msgstr ""
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#: ../Doc/library/random.rst:59
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msgid ""
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"`Complementary-Multiply-with-Carry recipe <https://code.activestate.com/"
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"recipes/576707/>`_ for a compatible alternative random number generator with "
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"a long period and comparatively simple update operations."
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msgstr ""
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#: ../Doc/library/random.rst:66
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msgid "Bookkeeping functions"
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msgstr ""
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#: ../Doc/library/random.rst:70
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msgid "Initialize the random number generator."
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msgstr ""
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#: ../Doc/library/random.rst:72
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msgid ""
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"If *a* is omitted or ``None``, the current system time is used. If "
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"randomness sources are provided by the operating system, they are used "
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"instead of the system time (see the :func:`os.urandom` function for details "
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"on availability)."
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msgstr ""
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#: ../Doc/library/random.rst:77
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msgid "If *a* is an int, it is used directly."
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msgstr ""
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#: ../Doc/library/random.rst:79
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msgid ""
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"With version 2 (the default), a :class:`str`, :class:`bytes`, or :class:"
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"`bytearray` object gets converted to an :class:`int` and all of its bits are "
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"used."
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msgstr ""
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#: ../Doc/library/random.rst:82
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msgid ""
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"With version 1 (provided for reproducing random sequences from older "
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"versions of Python), the algorithm for :class:`str` and :class:`bytes` "
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"generates a narrower range of seeds."
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msgstr ""
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#: ../Doc/library/random.rst:86
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msgid ""
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"Moved to the version 2 scheme which uses all of the bits in a string seed."
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msgstr ""
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#: ../Doc/library/random.rst:91
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msgid ""
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"Return an object capturing the current internal state of the generator. "
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"This object can be passed to :func:`setstate` to restore the state."
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msgstr ""
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#: ../Doc/library/random.rst:97
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msgid ""
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"*state* should have been obtained from a previous call to :func:`getstate`, "
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"and :func:`setstate` restores the internal state of the generator to what it "
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"was at the time :func:`getstate` was called."
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msgstr ""
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#: ../Doc/library/random.rst:104
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msgid ""
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"Returns a Python integer with *k* random bits. This method is supplied with "
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"the MersenneTwister generator and some other generators may also provide it "
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"as an optional part of the API. When available, :meth:`getrandbits` enables :"
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"meth:`randrange` to handle arbitrarily large ranges."
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msgstr ""
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#: ../Doc/library/random.rst:111
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msgid "Functions for integers"
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msgstr ""
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#: ../Doc/library/random.rst:116
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msgid ""
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"Return a randomly selected element from ``range(start, stop, step)``. This "
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"is equivalent to ``choice(range(start, stop, step))``, but doesn't actually "
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"build a range object."
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msgstr ""
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#: ../Doc/library/random.rst:120
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msgid ""
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"The positional argument pattern matches that of :func:`range`. Keyword "
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"arguments should not be used because the function may use them in unexpected "
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"ways."
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msgstr ""
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#: ../Doc/library/random.rst:123
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msgid ""
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":meth:`randrange` is more sophisticated about producing equally distributed "
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"values. Formerly it used a style like ``int(random()*n)`` which could "
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"produce slightly uneven distributions."
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msgstr ""
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#: ../Doc/library/random.rst:130
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msgid ""
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"Return a random integer *N* such that ``a <= N <= b``. Alias for "
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"``randrange(a, b+1)``."
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msgstr ""
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#: ../Doc/library/random.rst:135
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msgid "Functions for sequences"
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msgstr ""
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#: ../Doc/library/random.rst:139
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msgid ""
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"Return a random element from the non-empty sequence *seq*. If *seq* is "
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"empty, raises :exc:`IndexError`."
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msgstr ""
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#: ../Doc/library/random.rst:144
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msgid ""
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"Return a *k* sized list of elements chosen from the *population* with "
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"replacement. If the *population* is empty, raises :exc:`IndexError`."
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msgstr ""
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#: ../Doc/library/random.rst:147
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msgid ""
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"If a *weights* sequence is specified, selections are made according to the "
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"relative weights. Alternatively, if a *cum_weights* sequence is given, the "
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"selections are made according to the cumulative weights (perhaps computed "
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"using :func:`itertools.accumulate`). For example, the relative weights "
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"``[10, 5, 30, 5]`` are equivalent to the cumulative weights ``[10, 15, 45, "
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"50]``. Internally, the relative weights are converted to cumulative weights "
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"before making selections, so supplying the cumulative weights saves work."
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msgstr ""
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#: ../Doc/library/random.rst:156
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msgid ""
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"If neither *weights* nor *cum_weights* are specified, selections are made "
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"with equal probability. If a weights sequence is supplied, it must be the "
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"same length as the *population* sequence. It is a :exc:`TypeError` to "
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"specify both *weights* and *cum_weights*."
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msgstr ""
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#: ../Doc/library/random.rst:161
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msgid ""
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"The *weights* or *cum_weights* can use any numeric type that interoperates "
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"with the :class:`float` values returned by :func:`random` (that includes "
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"integers, floats, and fractions but excludes decimals). Weights are assumed "
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"to be non-negative."
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msgstr ""
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#: ../Doc/library/random.rst:166
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msgid ""
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"For a given seed, the :func:`choices` function with equal weighting "
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"typically produces a different sequence than repeated calls to :func:"
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"`choice`. The algorithm used by :func:`choices` uses floating point "
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"arithmetic for internal consistency and speed. The algorithm used by :func:"
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"`choice` defaults to integer arithmetic with repeated selections to avoid "
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"small biases from round-off error."
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msgstr ""
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#: ../Doc/library/random.rst:178
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msgid "Shuffle the sequence *x* in place."
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msgstr ""
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#: ../Doc/library/random.rst:180
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msgid ""
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"The optional argument *random* is a 0-argument function returning a random "
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"float in [0.0, 1.0); by default, this is the function :func:`.random`."
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msgstr ""
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#: ../Doc/library/random.rst:183
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msgid ""
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"To shuffle an immutable sequence and return a new shuffled list, use "
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"``sample(x, k=len(x))`` instead."
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msgstr ""
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#: ../Doc/library/random.rst:186
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msgid ""
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"Note that even for small ``len(x)``, the total number of permutations of *x* "
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"can quickly grow larger than the period of most random number generators. "
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"This implies that most permutations of a long sequence can never be "
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"generated. For example, a sequence of length 2080 is the largest that can "
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"fit within the period of the Mersenne Twister random number generator."
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msgstr ""
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#: ../Doc/library/random.rst:195
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msgid ""
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"Return a *k* length list of unique elements chosen from the population "
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"sequence or set. Used for random sampling without replacement."
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msgstr ""
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#: ../Doc/library/random.rst:198
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msgid ""
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"Returns a new list containing elements from the population while leaving the "
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"original population unchanged. The resulting list is in selection order so "
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"that all sub-slices will also be valid random samples. This allows raffle "
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"winners (the sample) to be partitioned into grand prize and second place "
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"winners (the subslices)."
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msgstr ""
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#: ../Doc/library/random.rst:204
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msgid ""
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"Members of the population need not be :term:`hashable` or unique. If the "
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"population contains repeats, then each occurrence is a possible selection in "
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"the sample."
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msgstr ""
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#: ../Doc/library/random.rst:207
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msgid ""
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"To choose a sample from a range of integers, use a :func:`range` object as "
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"an argument. This is especially fast and space efficient for sampling from "
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"a large population: ``sample(range(10000000), k=60)``."
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msgstr ""
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#: ../Doc/library/random.rst:211
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msgid ""
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"If the sample size is larger than the population size, a :exc:`ValueError` "
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"is raised."
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msgstr ""
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#: ../Doc/library/random.rst:215
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msgid "Real-valued distributions"
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msgstr ""
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#: ../Doc/library/random.rst:217
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msgid ""
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"The following functions generate specific real-valued distributions. "
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"Function parameters are named after the corresponding variables in the "
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"distribution's equation, as used in common mathematical practice; most of "
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"these equations can be found in any statistics text."
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msgstr ""
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#: ../Doc/library/random.rst:225
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msgid "Return the next random floating point number in the range [0.0, 1.0)."
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msgstr ""
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#: ../Doc/library/random.rst:230
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msgid ""
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"Return a random floating point number *N* such that ``a <= N <= b`` for ``a "
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"<= b`` and ``b <= N <= a`` for ``b < a``."
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msgstr ""
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#: ../Doc/library/random.rst:233
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msgid ""
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"The end-point value ``b`` may or may not be included in the range depending "
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"on floating-point rounding in the equation ``a + (b-a) * random()``."
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msgstr ""
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#: ../Doc/library/random.rst:239
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msgid ""
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"Return a random floating point number *N* such that ``low <= N <= high`` and "
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"with the specified *mode* between those bounds. The *low* and *high* bounds "
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"default to zero and one. The *mode* argument defaults to the midpoint "
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"between the bounds, giving a symmetric distribution."
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msgstr ""
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#: ../Doc/library/random.rst:247
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msgid ""
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"Beta distribution. Conditions on the parameters are ``alpha > 0`` and "
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"``beta > 0``. Returned values range between 0 and 1."
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msgstr ""
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#: ../Doc/library/random.rst:253
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msgid ""
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"Exponential distribution. *lambd* is 1.0 divided by the desired mean. It "
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"should be nonzero. (The parameter would be called \"lambda\", but that is a "
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"reserved word in Python.) Returned values range from 0 to positive infinity "
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"if *lambd* is positive, and from negative infinity to 0 if *lambd* is "
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"negative."
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msgstr ""
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#: ../Doc/library/random.rst:262
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msgid ""
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"Gamma distribution. (*Not* the gamma function!) Conditions on the "
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"parameters are ``alpha > 0`` and ``beta > 0``."
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msgstr ""
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#: ../Doc/library/random.rst:265
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msgid "The probability distribution function is::"
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msgstr ""
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#: ../Doc/library/random.rst:274
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msgid ""
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"Gaussian distribution. *mu* is the mean, and *sigma* is the standard "
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"deviation. This is slightly faster than the :func:`normalvariate` function "
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"defined below."
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msgstr ""
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#: ../Doc/library/random.rst:281
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msgid ""
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"Log normal distribution. If you take the natural logarithm of this "
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"distribution, you'll get a normal distribution with mean *mu* and standard "
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"deviation *sigma*. *mu* can have any value, and *sigma* must be greater "
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"than zero."
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msgstr ""
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#: ../Doc/library/random.rst:289
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msgid ""
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"Normal distribution. *mu* is the mean, and *sigma* is the standard "
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"deviation."
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msgstr ""
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#: ../Doc/library/random.rst:294
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msgid ""
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"*mu* is the mean angle, expressed in radians between 0 and 2\\*\\ *pi*, and "
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"*kappa* is the concentration parameter, which must be greater than or equal "
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"to zero. If *kappa* is equal to zero, this distribution reduces to a "
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"uniform random angle over the range 0 to 2\\*\\ *pi*."
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msgstr ""
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#: ../Doc/library/random.rst:302
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msgid "Pareto distribution. *alpha* is the shape parameter."
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msgstr ""
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#: ../Doc/library/random.rst:307
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msgid ""
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"Weibull distribution. *alpha* is the scale parameter and *beta* is the "
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"shape parameter."
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msgstr ""
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#: ../Doc/library/random.rst:312
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msgid "Alternative Generator"
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msgstr ""
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#: ../Doc/library/random.rst:316
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#, fuzzy
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msgid ""
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"Class that implements the default pseudo-random number generator used by "
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"the :mod:`random` module."
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msgstr ""
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"Ce module implémente des générateurs de nombres pseudo-aléatoires pour "
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"différentes distributions."
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#: ../Doc/library/random.rst:321
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msgid ""
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"Class that uses the :func:`os.urandom` function for generating random "
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"numbers from sources provided by the operating system. Not available on all "
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"systems. Does not rely on software state, and sequences are not "
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"reproducible. Accordingly, the :meth:`seed` method has no effect and is "
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"ignored. The :meth:`getstate` and :meth:`setstate` methods raise :exc:"
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"`NotImplementedError` if called."
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msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:330
|
||
msgid "Notes on Reproducibility"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:332
|
||
msgid ""
|
||
"Sometimes it is useful to be able to reproduce the sequences given by a "
|
||
"pseudo random number generator. By re-using a seed value, the same sequence "
|
||
"should be reproducible from run to run as long as multiple threads are not "
|
||
"running."
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:336
|
||
msgid ""
|
||
"Most of the random module's algorithms and seeding functions are subject to "
|
||
"change across Python versions, but two aspects are guaranteed not to change:"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:339
|
||
msgid ""
|
||
"If a new seeding method is added, then a backward compatible seeder will be "
|
||
"offered."
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:342
|
||
msgid ""
|
||
"The generator's :meth:`~Random.random` method will continue to produce the "
|
||
"same sequence when the compatible seeder is given the same seed."
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:348
|
||
msgid "Examples and Recipes"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:350
|
||
msgid "Basic examples::"
|
||
msgstr "Utilisation basique ::"
|
||
|
||
#: ../Doc/library/random.rst:378
|
||
msgid "Simulations::"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:407
|
||
msgid ""
|
||
"Example of `statistical bootstrapping <https://en.wikipedia.org/wiki/"
|
||
"Bootstrapping_(statistics)>`_ using resampling with replacement to estimate "
|
||
"a confidence interval for the mean of a sample of size five::"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:421
|
||
msgid ""
|
||
"Example of a `resampling permutation test <https://en.wikipedia.org/wiki/"
|
||
"Resampling_(statistics)#Permutation_tests>`_ to determine the statistical "
|
||
"significance or `p-value <https://en.wikipedia.org/wiki/P-value>`_ of an "
|
||
"observed difference between the effects of a drug versus a placebo::"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:448
|
||
msgid ""
|
||
"Simulation of arrival times and service deliveries in a single server queue::"
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:479
|
||
msgid ""
|
||
"`Statistics for Hackers <https://www.youtube.com/watch?v=Iq9DzN6mvYA>`_ a "
|
||
"video tutorial by `Jake Vanderplas <https://us.pycon.org/2016/speaker/"
|
||
"profile/295/>`_ on statistical analysis using just a few fundamental "
|
||
"concepts including simulation, sampling, shuffling, and cross-validation."
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:485
|
||
msgid ""
|
||
"`Economics Simulation <http://nbviewer.jupyter.org/url/norvig.com/ipython/"
|
||
"Economics.ipynb>`_ a simulation of a marketplace by `Peter Norvig <http://"
|
||
"norvig.com/bio.html>`_ that shows effective use of many of the tools and "
|
||
"distributions provided by this module (gauss, uniform, sample, betavariate, "
|
||
"choice, triangular, and randrange)."
|
||
msgstr ""
|
||
|
||
#: ../Doc/library/random.rst:492
|
||
msgid ""
|
||
"`A Concrete Introduction to Probability (using Python) <http://nbviewer."
|
||
"jupyter.org/url/norvig.com/ipython/Probability.ipynb>`_ a tutorial by `Peter "
|
||
"Norvig <http://norvig.com/bio.html>`_ covering the basics of probability "
|
||
"theory, how to write simulations, and how to perform data analysis using "
|
||
"Python."
|
||
msgstr ""
|