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msgstr ""
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"Project-Id-Version : Python 3.11\n "
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"Report-Msgid-Bugs-To : \n "
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- "POT-Creation-Date : 2023-03-17 00:32 +0000\n "
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+ "POT-Creation-Date : 2023-05-15 00:31 +0000\n "
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"PO-Revision-Date : 2023-01-23 22:47+0800\n "
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"
Last-Translator :
Allen Wu <[email protected] >\n "
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"Language-Team : Chinese - TAIWAN (https://github.com/python/python-docs-zh- "
@@ -531,29 +531,29 @@ msgstr ""
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#: ../../library/random.rst:313
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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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+ "Gamma distribution. (*Not* the gamma function!) The shape and scale "
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+ "parameters, *alpha* and *beta*, must have positive values. (Calling "
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+ "conventions vary and some sources define 'beta' as the inverse of the scale)."
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msgstr ""
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- "Gamma(伽瑪)分佈。(*不是* Gamma 函式!)參數的條件為 ``alpha > 0`` 和 "
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- "``beta > 0``。"
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- #: ../../library/random.rst:316
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+ #: ../../library/random.rst:318
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msgid "The probability distribution function is::"
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msgstr ""
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"Probability distribution function(機率密度函式)是:\n"
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"\n"
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"::"
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- #: ../../library/random.rst:325
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+ #: ../../library/random.rst:327
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+ #, fuzzy
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msgid ""
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- "Normal distribution, also called the Gaussian distribution. *mu* is the "
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+ "Normal distribution, also called the Gaussian distribution. *mu* is the "
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"mean, and *sigma* is the standard deviation. This is slightly faster than "
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"the :func:`normalvariate` function defined below."
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msgstr ""
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"常態分佈,也稱為高斯分佈。*mu* 是平均數,*sigma* 是標準差。這比下面定義的 :"
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"func:`normalvariate` 函式快一點。"
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- #: ../../library/random.rst:329
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+ #: ../../library/random.rst:332
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msgid ""
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"Multithreading note: When two threads call this function simultaneously, it "
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"is possible that they will receive the same return value. This can be "
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"可以透過三種方式避免。1)讓每個執行緒使用隨機數產生器的不同實例。2)在所有呼"
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"叫周圍加鎖。3)使用較慢但執行緒安全的 :func:`normalvariate` 函式代替。"
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- #: ../../library/random.rst:336 ../../library/random.rst:352
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+ #: ../../library/random.rst:339 ../../library/random.rst:355
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msgid "*mu* and *sigma* now have default arguments."
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msgstr ""
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- #: ../../library/random.rst:342
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+ #: ../../library/random.rst:345
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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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"對數常態分佈。如果你取此分佈的自然對數,你將獲得一個具有平均數 *mu* 和標準差 "
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"*sigma* 的常態分佈。*mu* 可以為任何值,並且 *sigma* 必須大於零。"
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- #: ../../library/random.rst:350
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+ #: ../../library/random.rst:353
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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 "常態分佈。*mu* 是平均數,*sigma* 是標準差。"
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- #: ../../library/random.rst:358
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+ #: ../../library/random.rst:361
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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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"大於或等於零。如果 *kappa* 等於零,則此分佈在 0 到 2\\ *\\ *pi* 的範圍內將減小"
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"為均勻的隨機角度。"
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- #: ../../library/random.rst:366
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+ #: ../../library/random.rst:369
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msgid "Pareto distribution. *alpha* is the shape parameter."
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msgstr "Pareto distribution(柏拉圖分佈)。*alpha* 是形狀參數。"
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- #: ../../library/random.rst:371
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+ #: ../../library/random.rst:374
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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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"Weibull distribution(韋伯分佈)。*alpha* 是比例參數,*beta* 是形狀參數。"
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- #: ../../library/random.rst:376
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+ #: ../../library/random.rst:379
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msgid "Alternative Generator"
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msgstr "替代產生器"
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- #: ../../library/random.rst:380
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+ #: ../../library/random.rst:383
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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 "實現 :mod:`random` 模組使用的預設偽隨機數產生器的 class。"
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- #: ../../library/random.rst:383
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+ #: ../../library/random.rst:386
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msgid ""
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"In the future, the *seed* must be one of the following types: :class:"
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"`NoneType`, :class:`int`, :class:`float`, :class:`str`, :class:`bytes`, or :"
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"將來,*seed* 必須是以下類型之一:\\ :class:`NoneType`、\\ :class:`int`、\\ :"
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"class:`float`、\\ :class:`str`、\\ :class:`bytes`、\\ :class:`bytearray`。"
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- #: ../../library/random.rst:390
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+ #: ../../library/random.rst:393
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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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"有效果且被忽略。如果呼叫 :meth:`getstate` 和 :meth:`setstate` 方法會引發 :"
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"exc:`NotImplementedError`。"
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- #: ../../library/random.rst:399
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+ #: ../../library/random.rst:402
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msgid "Notes on Reproducibility"
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msgstr "關於 Reproducibility(復現性)的注意事項"
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- #: ../../library/random.rst:401
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+ #: ../../library/random.rst:404
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msgid ""
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"Sometimes it is useful to be able to reproduce the sequences given by a "
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"pseudo-random number generator. By re-using a seed value, the same sequence "
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"有時,能夠重現偽隨機數產生器給出的序列很有用。只要多執行緒未運行,透過重複使"
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"用種子值,同一序列就應該可以被復現。"
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- #: ../../library/random.rst:405
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+ #: ../../library/random.rst:408
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msgid ""
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"Most of the random module's algorithms and seeding functions are subject to "
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"change across Python versions, but two aspects are guaranteed not to change:"
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msgstr ""
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"大多數隨機 module 的演算法和 seed 設定函式在 Python 版本中可能會發生變化,但"
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"可以保證兩個方面不會改變:"
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- #: ../../library/random.rst:408
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+ #: ../../library/random.rst:411
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msgid ""
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"If a new seeding method is added, then a backward compatible seeder will be "
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"offered."
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msgstr "如果增加了新的 seed 設定函式,則將提供向後相容的播種器 (seeder)。"
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- #: ../../library/random.rst:411
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+ #: ../../library/random.rst:414
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msgid ""
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"The generator's :meth:`~Random.random` method will continue to produce the "
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"same sequence when the compatible seeder is given the same seed."
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msgstr ""
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"當相容的播種器被賦予相同的種子時,產生器的 :meth:`~Random.random` 方法將持續"
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"產生相同的序列。"
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- #: ../../library/random.rst:417
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+ #: ../../library/random.rst:420
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msgid "Examples"
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msgstr "範例"
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- #: ../../library/random.rst:419
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+ #: ../../library/random.rst:422
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msgid "Basic examples::"
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msgstr ""
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"基礎範例:\n"
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"\n"
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"::"
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- #: ../../library/random.rst:447
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+ #: ../../library/random.rst:450
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msgid "Simulations::"
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msgstr ""
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"模擬:\n"
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"\n"
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"::"
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- #: ../../library/random.rst:475
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+ #: ../../library/random.rst:478
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msgid ""
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"Example of `statistical bootstrapping <https://en.wikipedia.org/wiki/"
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"Bootstrapping_(statistics)>`_ using resampling with replacement to estimate "
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"\n"
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"::"
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- #: ../../library/random.rst:488
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+ #: ../../library/random.rst:491
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msgid ""
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"Example of a `resampling permutation test <https://en.wikipedia.org/wiki/"
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"Resampling_(statistics)#Permutation_tests>`_ to determine the statistical "
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"\n"
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"::"
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- #: ../../library/random.rst:515
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+ #: ../../library/random.rst:518
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msgid ""
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"Simulation of arrival times and service deliveries for a multiserver queue::"
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msgstr ""
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"模擬多伺服器佇列 (queue) 的到達時間與服務交付:\n"
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"\n"
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"::"
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- #: ../../library/random.rst:544
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+ #: ../../library/random.rst:547
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msgid ""
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"`Statistics for Hackers <https://www.youtube.com/watch?v=Iq9DzN6mvYA>`_ a "
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"video tutorial by `Jake Vanderplas <https://us.pycon.org/2016/speaker/"
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"`Jake Vanderplas <https://us.pycon.org/2016/speaker/profile/295/>`_ 製作的教"
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"學影片,僅使用幾個基本概念(包括模擬、取樣、洗牌、交叉驗證)進行統計分析。"
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- #: ../../library/random.rst:550
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+ #: ../../library/random.rst:553
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msgid ""
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"`Economics Simulation <https://nbviewer.jupyter.org/url/norvig.com/ipython/"
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"Economics.ipynb>`_ a simulation of a marketplace by `Peter Norvig <https://"
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"場進行的模擬,顯示了該模組提供的許多工具和分佈(高斯、均勻、樣本、 beta 變"
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"數、選擇,三角形、隨機數)的有效使用。"
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- #: ../../library/random.rst:557
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+ #: ../../library/random.rst:560
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msgid ""
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"`A Concrete Introduction to Probability (using Python) <https://nbviewer."
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"jupyter.org/url/norvig.com/ipython/Probability.ipynb>`_ a tutorial by `Peter "
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"html>`_ 的教學課程,涵蓋了機率理論的基礎知識與如何模擬以及使用 Python 執行數"
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"據分析。"
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- #: ../../library/random.rst:565
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+ #: ../../library/random.rst:568
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msgid "Recipes"
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msgstr "使用方案"
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- #: ../../library/random.rst:567
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+ #: ../../library/random.rst:570
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msgid ""
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"These recipes show how to efficiently make random selections from the "
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"combinatoric iterators in the :mod:`itertools` module:"
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msgstr ""
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- #: ../../library/random.rst:599
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+ #: ../../library/random.rst:602
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msgid ""
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"The default :func:`.random` returns multiples of 2⁻⁵³ in the range *0.0 ≤ x "
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"< 1.0*. All such numbers are evenly spaced and are exactly representable as "
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"均勻分佈的,並且可以完全表示為 Python float。但是,該間隔中的許多其他可表示"
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"的 float 不是可能的選擇。 例如 ``0.05954861408025609`` 不是 2⁻⁵³ 的整數倍。"
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- #: ../../library/random.rst:605
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+ #: ../../library/random.rst:608
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msgid ""
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"The following recipe takes a different approach. All floats in the interval "
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"are possible selections. The mantissa comes from a uniform distribution of "
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"數 < 2⁵³* 範圍內的整數均勻分佈。指數來自幾何分佈,其中小於 *-53* 的指數的出現"
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"頻率是下一個較大指數的一半。"
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- #: ../../library/random.rst:627
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+ #: ../../library/random.rst:630
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msgid ""
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"All :ref:`real valued distributions <real-valued-distributions>` in the "
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"class will use the new method::"
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"\n"
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"::"
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- #: ../../library/random.rst:636
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+ #: ../../library/random.rst:639
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msgid ""
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"The recipe is conceptually equivalent to an algorithm that chooses from all "
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"the multiples of 2⁻¹⁰⁷⁴ in the range *0.0 ≤ x < 1.0*. All such numbers are "
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"示的 Python float。(2⁻¹⁰⁷⁴ 是最小為正的非正規化 float,等於 ``math."
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"ulp(0.0)``)"
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- #: ../../library/random.rst:645
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+ #: ../../library/random.rst:648
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msgid ""
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"`Generating Pseudo-random Floating-Point Values <https://allendowney.com/"
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"research/rand/downey07randfloat.pdf>`_ a paper by Allen B. Downey describing "
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"pdf>`_ Allen B. Downey 的一篇論文描述了產生比通常由 :func:`.random` 產生的 "
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"float 更 fine-grained(細粒的)的方法。"
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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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+ #~ "Gamma(伽瑪)分佈。(*不是* Gamma 函式!)參數的條件為 ``alpha > 0`` 和 "
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+ #~ "``beta > 0``。"
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+
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#~ msgid ""
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#~ "The optional argument *random* is a 0-argument function returning a "
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#~ "random float in [0.0, 1.0); by default, this is the function :func:`."
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