# Copyright (C) 2001-2018, Python Software Foundation # For licence information, see README file. # msgid "" msgstr "" "Project-Id-Version: Python 3.6\n" "Report-Msgid-Bugs-To: \n" "POT-Creation-Date: 2017-05-27 19:40+0200\n" "PO-Revision-Date: 2018-12-06 22:18+0100\n" "Last-Translator: Julien Palard \n" "Language-Team: FRENCH \n" "Language: fr\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=UTF-8\n" "Content-Transfer-Encoding: 8bit\n" "X-Generator: Poedit 2.2\n" #: ../Doc/library/random.rst:2 msgid ":mod:`random` --- Generate pseudo-random numbers" msgstr ":mod:`random` --- Génère des nombres pseudo-aléatoires" #: ../Doc/library/random.rst:7 msgid "**Source code:** :source:`Lib/random.py`" msgstr "**Code source :** :source:`Lib/random.py`" #: ../Doc/library/random.rst:11 msgid "" "This module implements pseudo-random number generators for various " "distributions." msgstr "" "Ce module implémente des générateurs de nombres pseudo-aléatoires pour " "différentes distributions." #: ../Doc/library/random.rst:14 msgid "" "For integers, there is uniform selection from a range. For sequences, there " "is uniform selection of a random element, a function to generate a random " "permutation of a list in-place, and a function for random sampling without " "replacement." msgstr "" "Pour les entiers, il existe une sélection uniforme à partir d'une plage. " "Pour les séquences, il existe une sélection uniforme d'un élément aléatoire, " "une fonction pour générer une permutation aléatoire d'une liste sur place et " "une fonction pour un échantillonnage aléatoire sans remplacement." #: ../Doc/library/random.rst:19 msgid "" "On the real line, there are functions to compute uniform, normal (Gaussian), " "lognormal, negative exponential, gamma, and beta distributions. For " "generating distributions of angles, the von Mises distribution is available." msgstr "" "Pour l'ensemble des réels, il y a des fonctions pour calculer des " "distributions uniformes, normales (gaussiennes), log-normales, " "exponentielles négatives, gamma et bêta. Pour générer des distributions " "d'angles, la distribution de *von Mises* est disponible." #: ../Doc/library/random.rst:23 msgid "" "Almost all module functions depend on the basic function :func:`.random`, " "which generates a random float uniformly in the semi-open range [0.0, 1.0). " "Python uses the Mersenne Twister as the core generator. It produces 53-bit " "precision floats and has a period of 2\\*\\*19937-1. The underlying " "implementation in C is both fast and threadsafe. The Mersenne Twister is " "one of the most extensively tested random number generators in existence. " "However, being completely deterministic, it is not suitable for all " "purposes, and is completely unsuitable for cryptographic purposes." msgstr "" "Presque toutes les fonctions du module dépendent de la fonction de base :" "func:`.random`, qui génère un nombre à virgule flottante aléatoire de façon " "uniforme dans la plage semi-ouverte [0.0, 1.0). Python utilise l'algorithme " "*Mersenne Twister* comme générateur de noyau. Il produit des flottants de " "précision de 53 bits et a une période de 2\\*\\*\\*19937-1. " "L'implémentation sous-jacente en C est à la fois rapide et *threadsafe*. Le " "*Mersenne Twister* est l'un des générateurs de nombres aléatoires les plus " "largement testés qui existent. Cependant, étant complètement déterministe, " "il n'est pas adapté à tous les usages et est totalement inadapté à des fins " "cryptographiques." #: ../Doc/library/random.rst:32 msgid "" "The functions supplied by this module are actually bound methods of a hidden " "instance of the :class:`random.Random` class. You can instantiate your own " "instances of :class:`Random` to get generators that don't share state." msgstr "" "Les fonctions fournies par ce module dépendent en réalité de méthodes d’une " "instance cachée de la classe :class:`randon.random`. Vous pouvez créer vos " "propres instances de :class:`Random` pour obtenir des générateurs sans états " "partagés." #: ../Doc/library/random.rst:36 msgid "" "Class :class:`Random` can also be subclassed if you want to use a different " "basic generator of your own devising: in that case, override the :meth:" "`~Random.random`, :meth:`~Random.seed`, :meth:`~Random.getstate`, and :meth:" "`~Random.setstate` methods. Optionally, a new generator can supply a :meth:" "`~Random.getrandbits` method --- this allows :meth:`randrange` to produce " "selections over an arbitrarily large range." msgstr "" "La classe :class:`Random` peut également être sous-classée si vous voulez " "utiliser un générateur de base différent, de votre propre conception. Dans " "ce cas, remplacez les méthodes :meth:`~Random.random`, :meth:`~Random." "seed`, :meth:`~Random.gettate`, et :meth:`~Random.setstate`. En option, un " "nouveau générateur peut fournir une méthode :meth:`~Random.getrandbits` --- " "ce qui permet à :meth:`randrange` de produire des sélections sur une plage " "de taille arbitraire." #: ../Doc/library/random.rst:42 msgid "" "The :mod:`random` module also provides the :class:`SystemRandom` class which " "uses the system function :func:`os.urandom` to generate random numbers from " "sources provided by the operating system." msgstr "" #: ../Doc/library/random.rst:48 msgid "" "The pseudo-random generators of this module should not be used for security " "purposes. For security or cryptographic uses, see the :mod:`secrets` module." msgstr "" #: ../Doc/library/random.rst:54 msgid "" "M. Matsumoto and T. Nishimura, \"Mersenne Twister: A 623-dimensionally " "equidistributed uniform pseudorandom number generator\", ACM Transactions on " "Modeling and Computer Simulation Vol. 8, No. 1, January pp.3--30 1998." msgstr "" #: ../Doc/library/random.rst:59 msgid "" "`Complementary-Multiply-with-Carry recipe `_ for a compatible alternative random number generator with " "a long period and comparatively simple update operations." msgstr "" #: ../Doc/library/random.rst:66 msgid "Bookkeeping functions" msgstr "" #: ../Doc/library/random.rst:70 msgid "Initialize the random number generator." msgstr "" #: ../Doc/library/random.rst:72 msgid "" "If *a* is omitted or ``None``, the current system time is used. If " "randomness sources are provided by the operating system, they are used " "instead of the system time (see the :func:`os.urandom` function for details " "on availability)." msgstr "" #: ../Doc/library/random.rst:77 msgid "If *a* is an int, it is used directly." msgstr "" #: ../Doc/library/random.rst:79 msgid "" "With version 2 (the default), a :class:`str`, :class:`bytes`, or :class:" "`bytearray` object gets converted to an :class:`int` and all of its bits are " "used." msgstr "" #: ../Doc/library/random.rst:82 msgid "" "With version 1 (provided for reproducing random sequences from older " "versions of Python), the algorithm for :class:`str` and :class:`bytes` " "generates a narrower range of seeds." msgstr "" #: ../Doc/library/random.rst:86 msgid "" "Moved to the version 2 scheme which uses all of the bits in a string seed." msgstr "" #: ../Doc/library/random.rst:91 msgid "" "Return an object capturing the current internal state of the generator. " "This object can be passed to :func:`setstate` to restore the state." msgstr "" #: ../Doc/library/random.rst:97 msgid "" "*state* should have been obtained from a previous call to :func:`getstate`, " "and :func:`setstate` restores the internal state of the generator to what it " "was at the time :func:`getstate` was called." msgstr "" #: ../Doc/library/random.rst:104 msgid "" "Returns a Python integer with *k* random bits. This method is supplied with " "the MersenneTwister generator and some other generators may also provide it " "as an optional part of the API. When available, :meth:`getrandbits` enables :" "meth:`randrange` to handle arbitrarily large ranges." msgstr "" #: ../Doc/library/random.rst:111 msgid "Functions for integers" msgstr "" #: ../Doc/library/random.rst:116 msgid "" "Return a randomly selected element from ``range(start, stop, step)``. This " "is equivalent to ``choice(range(start, stop, step))``, but doesn't actually " "build a range object." msgstr "" #: ../Doc/library/random.rst:120 msgid "" "The positional argument pattern matches that of :func:`range`. Keyword " "arguments should not be used because the function may use them in unexpected " "ways." msgstr "" #: ../Doc/library/random.rst:123 msgid "" ":meth:`randrange` is more sophisticated about producing equally distributed " "values. Formerly it used a style like ``int(random()*n)`` which could " "produce slightly uneven distributions." msgstr "" #: ../Doc/library/random.rst:130 msgid "" "Return a random integer *N* such that ``a <= N <= b``. Alias for " "``randrange(a, b+1)``." msgstr "" #: ../Doc/library/random.rst:135 msgid "Functions for sequences" msgstr "" #: ../Doc/library/random.rst:139 msgid "" "Return a random element from the non-empty sequence *seq*. If *seq* is " "empty, raises :exc:`IndexError`." msgstr "" #: ../Doc/library/random.rst:144 msgid "" "Return a *k* sized list of elements chosen from the *population* with " "replacement. If the *population* is empty, raises :exc:`IndexError`." msgstr "" #: ../Doc/library/random.rst:147 msgid "" "If a *weights* sequence is specified, selections are made according to the " "relative weights. Alternatively, if a *cum_weights* sequence is given, the " "selections are made according to the cumulative weights (perhaps computed " "using :func:`itertools.accumulate`). For example, the relative weights " "``[10, 5, 30, 5]`` are equivalent to the cumulative weights ``[10, 15, 45, " "50]``. Internally, the relative weights are converted to cumulative weights " "before making selections, so supplying the cumulative weights saves work." msgstr "" #: ../Doc/library/random.rst:156 msgid "" "If neither *weights* nor *cum_weights* are specified, selections are made " "with equal probability. If a weights sequence is supplied, it must be the " "same length as the *population* sequence. It is a :exc:`TypeError` to " "specify both *weights* and *cum_weights*." msgstr "" #: ../Doc/library/random.rst:161 msgid "" "The *weights* or *cum_weights* can use any numeric type that interoperates " "with the :class:`float` values returned by :func:`random` (that includes " "integers, floats, and fractions but excludes decimals)." msgstr "" #: ../Doc/library/random.rst:170 msgid "Shuffle the sequence *x* in place." msgstr "" #: ../Doc/library/random.rst:172 msgid "" "The optional argument *random* is a 0-argument function returning a random " "float in [0.0, 1.0); by default, this is the function :func:`.random`." msgstr "" #: ../Doc/library/random.rst:175 msgid "" "To shuffle an immutable sequence and return a new shuffled list, use " "``sample(x, k=len(x))`` instead." msgstr "" #: ../Doc/library/random.rst:178 msgid "" "Note that even for small ``len(x)``, the total number of permutations of *x* " "can quickly grow larger than the period of most random number generators. " "This implies that most permutations of a long sequence can never be " "generated. For example, a sequence of length 2080 is the largest that can " "fit within the period of the Mersenne Twister random number generator." msgstr "" #: ../Doc/library/random.rst:187 msgid "" "Return a *k* length list of unique elements chosen from the population " "sequence or set. Used for random sampling without replacement." msgstr "" #: ../Doc/library/random.rst:190 msgid "" "Returns a new list containing elements from the population while leaving the " "original population unchanged. The resulting list is in selection order so " "that all sub-slices will also be valid random samples. This allows raffle " "winners (the sample) to be partitioned into grand prize and second place " "winners (the subslices)." msgstr "" #: ../Doc/library/random.rst:196 msgid "" "Members of the population need not be :term:`hashable` or unique. If the " "population contains repeats, then each occurrence is a possible selection in " "the sample." msgstr "" #: ../Doc/library/random.rst:199 msgid "" "To choose a sample from a range of integers, use a :func:`range` object as " "an argument. This is especially fast and space efficient for sampling from " "a large population: ``sample(range(10000000), k=60)``." msgstr "" #: ../Doc/library/random.rst:203 msgid "" "If the sample size is larger than the population size, a :exc:`ValueError` " "is raised." msgstr "" #: ../Doc/library/random.rst:207 msgid "Real-valued distributions" msgstr "" #: ../Doc/library/random.rst:209 msgid "" "The following functions generate specific real-valued distributions. " "Function parameters are named after the corresponding variables in the " "distribution's equation, as used in common mathematical practice; most of " "these equations can be found in any statistics text." msgstr "" #: ../Doc/library/random.rst:217 msgid "Return the next random floating point number in the range [0.0, 1.0)." msgstr "" #: ../Doc/library/random.rst:222 msgid "" "Return a random floating point number *N* such that ``a <= N <= b`` for ``a " "<= b`` and ``b <= N <= a`` for ``b < a``." msgstr "" #: ../Doc/library/random.rst:225 msgid "" "The end-point value ``b`` may or may not be included in the range depending " "on floating-point rounding in the equation ``a + (b-a) * random()``." msgstr "" #: ../Doc/library/random.rst:231 msgid "" "Return a random floating point number *N* such that ``low <= N <= high`` and " "with the specified *mode* between those bounds. The *low* and *high* bounds " "default to zero and one. The *mode* argument defaults to the midpoint " "between the bounds, giving a symmetric distribution." msgstr "" #: ../Doc/library/random.rst:239 msgid "" "Beta distribution. Conditions on the parameters are ``alpha > 0`` and " "``beta > 0``. Returned values range between 0 and 1." msgstr "" #: ../Doc/library/random.rst:245 msgid "" "Exponential distribution. *lambd* is 1.0 divided by the desired mean. It " "should be nonzero. (The parameter would be called \"lambda\", but that is a " "reserved word in Python.) Returned values range from 0 to positive infinity " "if *lambd* is positive, and from negative infinity to 0 if *lambd* is " "negative." msgstr "" #: ../Doc/library/random.rst:254 msgid "" "Gamma distribution. (*Not* the gamma function!) Conditions on the " "parameters are ``alpha > 0`` and ``beta > 0``." msgstr "" #: ../Doc/library/random.rst:257 msgid "The probability distribution function is::" msgstr "" #: ../Doc/library/random.rst:266 msgid "" "Gaussian distribution. *mu* is the mean, and *sigma* is the standard " "deviation. This is slightly faster than the :func:`normalvariate` function " "defined below." msgstr "" #: ../Doc/library/random.rst:273 msgid "" "Log normal distribution. If you take the natural logarithm of this " "distribution, you'll get a normal distribution with mean *mu* and standard " "deviation *sigma*. *mu* can have any value, and *sigma* must be greater " "than zero." msgstr "" #: ../Doc/library/random.rst:281 msgid "" "Normal distribution. *mu* is the mean, and *sigma* is the standard " "deviation." msgstr "" #: ../Doc/library/random.rst:286 msgid "" "*mu* is the mean angle, expressed in radians between 0 and 2\\*\\ *pi*, and " "*kappa* is the concentration parameter, which must be greater than or equal " "to zero. If *kappa* is equal to zero, this distribution reduces to a " "uniform random angle over the range 0 to 2\\*\\ *pi*." msgstr "" #: ../Doc/library/random.rst:294 msgid "Pareto distribution. *alpha* is the shape parameter." msgstr "" #: ../Doc/library/random.rst:299 msgid "" "Weibull distribution. *alpha* is the scale parameter and *beta* is the " "shape parameter." msgstr "" #: ../Doc/library/random.rst:304 msgid "Alternative Generator" msgstr "" #: ../Doc/library/random.rst:308 msgid "" "Class that uses the :func:`os.urandom` function for generating random " "numbers from sources provided by the operating system. Not available on all " "systems. Does not rely on software state, and sequences are not " "reproducible. Accordingly, the :meth:`seed` method has no effect and is " "ignored. The :meth:`getstate` and :meth:`setstate` methods raise :exc:" "`NotImplementedError` if called." msgstr "" #: ../Doc/library/random.rst:317 msgid "Notes on Reproducibility" msgstr "" #: ../Doc/library/random.rst:319 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:323 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:326 msgid "" "If a new seeding method is added, then a backward compatible seeder will be " "offered." msgstr "" #: ../Doc/library/random.rst:329 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:335 msgid "Examples and Recipes" msgstr "" #: ../Doc/library/random.rst:337 msgid "Basic examples::" msgstr "Utilisation basique : ::" #: ../Doc/library/random.rst:365 msgid "Simulations::" msgstr "" #: ../Doc/library/random.rst:390 msgid "" "Example of `statistical bootstrapping `_ using resampling with replacement to estimate " "a confidence interval for the mean of a sample of size five::" msgstr "" #: ../Doc/library/random.rst:404 msgid "" "Example of a `resampling permutation test `_ to determine the statistical " "significance or `p-value `_ of an " "observed difference between the effects of a drug versus a placebo::" msgstr "" #: ../Doc/library/random.rst:431 msgid "" "Simulation of arrival times and service deliveries in a single server queue::" msgstr "" #: ../Doc/library/random.rst:462 msgid "" "`Statistics for Hackers `_ a " "video tutorial by `Jake Vanderplas `_ on statistical analysis using just a few fundamental " "concepts including simulation, sampling, shuffling, and cross-validation." msgstr "" #: ../Doc/library/random.rst:468 msgid "" "`Economics Simulation `_ a simulation of a marketplace by `Peter Norvig `_ 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:475 msgid "" "`A Concrete Introduction to Probability (using Python) `_ a tutorial by `Peter " "Norvig `_ covering the basics of probability " "theory, how to write simulations, and how to perform data analysis using " "Python." msgstr ""