Expand Up @@ -3,25 +3,26 @@ # # Translators: # Allen Wu <allen91.wu@gmail.com>, 2021 # Dr.XYZ <dr.xyz.tw@gmail.com>, 2025 msgid "" msgstr "" "Project-Id-Version: Python 3.13\n" "Report-Msgid-Bugs-To: \n" "POT-Creation-Date: 2024-09-27 00:14+0000\n" "PO-Revision-Date:2023-01-23 22:47 +0800\n" "Last-Translator:Allen Wu <allen91.wu @gmail.com>\n" "PO-Revision-Date:2025-03-07 19:17 +0800\n" "Last-Translator:Dr.XYZ <dr.xyz.tw @gmail.com>\n" "Language-Team: Chinese - TAIWAN (https://github.com/python/python-docs-zh-" "tw)\n" "Language: zh_TW\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=UTF-8\n" "Content-Transfer-Encoding: 8bit\n" "Plural-Forms: nplurals=1; plural=0;\n" "X-Generator: Poedit 3.2.2 \n" "X-Generator: Poedit 3.5 \n" #: ../../library/random.rst:2 msgid ":mod:`!random` --- Generate pseudo-random numbers" msgstr ":mod:`!random` ---生成偽隨機數 " msgstr ":mod:`!random` ---產生偽隨機數 " #: ../../library/random.rst:7 msgid "**Source code:** :source:`Lib/random.py`" Expand All @@ -41,7 +42,7 @@ msgid "" "replacement." msgstr "" "對於整數，可以從範圍中進行均勻選擇。對於序列，有一個隨機元素的均勻選擇，一個" "用來原地 (in-place) 產生隨機排列清單的函式，以及一個用來隨機取樣不替換的函 " "用來原地 (in-place) 產生隨機排列清單的函式，以及一個用來隨機取樣不重置的函 " "式。" #: ../../library/random.rst:19 Expand All @@ -51,7 +52,7 @@ msgid "" "generating distributions of angles, the von Mises distribution is available." msgstr "" "在實數線上，有一些函式用於處理均勻分佈、常態分佈（高斯分佈）、對數常態分佈、" "負指數分佈、gamma 分佈和 Beta 分佈。對於生成角度分佈 ，可以使用馮·米塞斯分佈 " "負指數分佈、gamma 分佈和 Beta 分佈。對於產生角度分佈 ，可以使用馮·米塞斯分佈 " "(von Mises distribution)。" #: ../../library/random.rst:23 Expand All @@ -66,7 +67,7 @@ msgid "" "purposes, and is completely unsuitable for cryptographic purposes." msgstr "" "幾乎所有 module 函式都相依於基本函式 :func:`.random`，此函式在半開放範圍 " "``0.0 <= X < 1.0``內均勻地生成一個隨機 float（浮點數）。Python 使用 " "``0.0 <= X < 1.0``內均勻地產生一個隨機 float（浮點數）。Python 使用 " "Mersenne Twister（梅森旋轉演算法）作為核心的產生器，它產生 53 位元精度 " "float，其週期為 2\\*\\*19937-1，透過 C 語言進行底層的實作既快速又支援執行緒安" "全 (threadsafe)。Mersenne Twister 是現存最廣泛被驗證的隨機數產生器之一，但是" Expand Down Expand Up @@ -137,6 +138,9 @@ msgid "" "contention and poor performance. Consider using separate instances of :class:" "`Random` per thread instead." msgstr "" "全域隨機數產生器和 :class:`Random` 的實例是執行緒安全的。然而，在自由執行緒構" "建中，對全域產生器或同一 :class:`Random` 實例的並行呼叫可能會遇到爭用和性能不" "佳。請考慮改為每個執行緒使用單獨的 :class:`Random` 實例。" #: ../../library/random.rst:70 msgid "Bookkeeping functions" Expand Down Expand Up @@ -177,7 +181,7 @@ msgid "" "generates a narrower range of seeds." msgstr "" "若使用版本 1（為復現於舊版本 Python 中產生隨機序列而提供），:class:`str` 和 :" "class:`bytes`的演算法會生成範圍更窄的種子 (seed)。" "class:`bytes`的演算法會產生範圍更窄的種子 (seed)。" #: ../../library/random.rst:90 msgid "" Expand Down Expand Up @@ -816,6 +820,31 @@ msgid "" ">>> sample([10, 20, 30, 40, 50], k=4) # Four samples without replacement\n" "[40, 10, 50, 30]" msgstr "" ">>> random() # 隨機浮點數：0.0 <= x < 1.0\n" "0.37444887175646646\n" "\n" ">>> uniform(2.5, 10.0) # 隨機浮點數：2.5 <= x <= 10.0\n" "3.1800146073117523\n" "\n" ">>> expovariate(1 / 5) # 到達間隔平均為 5 秒\n" "5.148957571865031\n" "\n" ">>> randrange(10) # 0 到 9（含）的整數\n" "7\\n\n" "\n" ">>> randrange(0, 101, 2) # 0 到 100（含）的偶數整數\n" "26\\n\n" "\n" ">>> choice(['win', 'lose', 'draw']) # 從序列中隨機選取單一元素\n" "'draw'\n" "\n" ">>> deck = 'ace two three four'.split()\n" ">>> shuffle(deck) # 打亂串列\n" ">>> deck\n" "['four', 'two', 'ace', 'three']\n" "\n" ">>> sample([10, 20, 30, 40, 50], k=4) # 四個無重置的樣本\n" "[40, 10, 50, 30]" #: ../../library/random.rst:510 msgid "Simulations::" Expand Down Expand Up @@ -846,6 +875,27 @@ msgid "" ">>> sum(trial() for i in range(10_000)) / 10_000\n" "0.7958" msgstr "" ">>> # 六次輪盤旋轉（有重置的加權抽樣）\n" ">>> choices(['red', 'black', 'green'], [18, 18, 2], k=6)\n" "['red', 'green', 'black', 'black', 'red', 'black']\n" "\n" ">>> # 從一副 52 張撲克牌中無重置發 20 張牌\n" ">>> # 並確定具有十點值的牌的比例：十、傑克、王后或國王\n" ">>> deal = sample(['tens', 'low cards'], counts=[16, 36], k=20)\n" ">>> deal.count('tens') / 20\n" "0.15\n" "\n" ">>> # 估計從 7 次旋轉中得到 5 次或更多正面的概率\n" ">>> # 使用一枚 60% 概率為正面的偏幣\n" ">>> sum(binomialvariate(n=7, p=0.6) >= 5 for i in range(10_000)) / 10_000\n" "0.4169\n" "\n" ">>> # 計算 5 個樣本的中位數位於中間兩個四分位數的概率\n" ">>> def trial():\n" "... return 2_500 <= sorted(choices(range(10_000), k=5))[2] < 7_500\n" "...\n" ">>> sum(trial() for i in range(10_000)) / 10_000\n" "0.7958" #: ../../library/random.rst:535 msgid "" Expand Down Expand Up @@ -916,6 +966,26 @@ msgid "" "print(f'hypothesis that there is no difference between the drug and the " "placebo.')" msgstr "" "# 範例來自 Dennis Shasha 和 Manda Wilson 的 \"Statistics is Easy\"\n" "from statistics import fmean as mean\n" "from random import shuffle\n" "\n" "drug = [54, 73, 53, 70, 73, 68, 52, 65, 65]\n" "placebo = [54, 51, 58, 44, 55, 52, 42, 47, 58, 46]\n" "observed_diff = mean(drug) - mean(placebo)\n" "\n" "n = 10_000\n" "count = 0\n" "combined = drug + placebo\n" "for i in range(n):\n" " shuffle(combined)\n" " new_diff = mean(combined[:len(drug)]) - mean(combined[len(drug):])\n" " count += (new_diff >= observed_diff)\n" "\n" "print(f'{n} 次標籤重新洗牌僅產生 {count} 個差異實例')\n" "print(f'至少與觀察到的差異 {observed_diff:.1f} 一樣極端。')\n" "print(f'單邊 p 值 {count / n:.4f} 使我們拒絕無效假設')\n" "print(f'即藥物與安慰劑之間沒有差異。')" #: ../../library/random.rst:575 msgid "" Expand Down Expand Up @@ -950,6 +1020,31 @@ msgid "" "print(f'Mean wait: {mean(waits):.1f} Max wait: {max(waits):.1f}')\n" "print('Quartiles:', [round(q, 1) for q in quantiles(waits)])" msgstr "" "from heapq import heapify, heapreplace\n" "from random import expovariate, gauss\n" "from statistics import mean, quantiles\n" "\n" "average_arrival_interval = 5.6\n" "average_service_time = 15.0\n" "stdev_service_time = 3.5\n" "num_servers = 3\n" "\n" "waits = []\n" "arrival_time = 0.0\n" "servers = [0.0] * num_servers # 每個伺服器可用的時間\n" "heapify(servers)\n" "for i in range(1_000_000):\n" " arrival_time += expovariate(1.0 / average_arrival_interval)\n" " next_server_available = servers[0]\n" " wait = max(0.0, next_server_available - arrival_time)\n" " waits.append(wait)\n" " service_duration = max(0.0, gauss(average_service_time, " "stdev_service_time))\n" " service_completed = arrival_time + wait + service_duration\n" " heapreplace(servers, service_completed)\n" "\n" "print(f'平均等待時間：{mean(waits):.1f} 最大等待時間：{max(waits):.1f}')\n" "print('四分位數：', [round(q, 1) for q in quantiles(waits)])" #: ../../library/random.rst:604 msgid "" Expand Down Expand Up @@ -1028,6 +1123,31 @@ msgid "" " indices = sorted(random.choices(range(n), k=r))\n" " return tuple(pool[i] for i in indices)" msgstr "" "def random_product(*args, repeat=1):\n" " \"從 itertools.product(*args, **kwds) 中隨機選擇\"\n" " pools = [tuple(pool) for pool in args] * repeat\n" " return tuple(map(random.choice, pools))\n" "\n" "def random_permutation(iterable, r=None):\n" " \"從 itertools.permutations(iterable, r) 中隨機選擇\"\n" " pool = tuple(iterable)\n" " r = len(pool) if r is None else r\n" " return tuple(random.sample(pool, r))\n" "\n" "def random_combination(iterable, r):\n" " \"從 itertools.combinations(iterable, r) 中隨機選擇\"\n" " pool = tuple(iterable)\n" " n = len(pool)\n" " indices = sorted(random.sample(range(n), r))\n" " return tuple(pool[i] for i in indices)\n" "\n" "def random_combination_with_replacement(iterable, r):\n" " \"有重置地選擇 r 個元素。結果按可疊代物件排序。\"\n" " # 結果將在 set(itertools.combinations_with_replacement(iterable, r)) 中\n" " pool = tuple(iterable)\n" " n = len(pool)\n" " indices = sorted(random.choices(range(n), k=r))\n" " return tuple(pool[i] for i in indices)" #: ../../library/random.rst:659 msgid "" Expand Down Expand Up @@ -1131,64 +1251,64 @@ msgstr "" #: ../../library/random.rst:713 msgid "Command-line usage" msgstr "" msgstr "命令列用法 " #: ../../library/random.rst:717 msgid "The :mod:`!random` module can be executed from the command line." msgstr "" msgstr ":mod:`!random` 模組可以從命令列執行。 " #: ../../library/random.rst:719 msgid "" "python -m random [-h] [-c CHOICE [CHOICE ...] | -i N | -f N] [input ...]" msgstr "" "python -m random [-h] [-c CHOICE [CHOICE ...] | -i N | -f N] [input ...]" #: ../../library/random.rst:723 #, fuzzy msgid "The following options are accepted:" msgstr "以下函式產生離散分佈。 " msgstr "接受以下選項： " #: ../../library/random.rst:729 msgid "Show the help message and exit." msgstr "" msgstr "顯示幫助訊息並退出。 " #: ../../library/random.rst:734 msgid "Print a random choice, using :meth:`choice`." msgstr "" msgstr "列印一個隨機選擇，使用 :meth:`choice`。 " #: ../../library/random.rst:739 msgid "" "Print a random integer between 1 and N inclusive, using :meth:`randint`." msgstr "" msgstr "列印 1 到 N（含）之間的隨機整數，使用 :meth:`randint`。 " #: ../../library/random.rst:744 msgid "" "Print a random floating-point number between 0 and N inclusive, using :meth:" "`uniform`." msgstr "" msgstr "列印 0 到 N（含）之間的隨機浮點數，使用 :meth:`uniform`。 " #: ../../library/random.rst:747 msgid "If no options are given, the output depends on the input:" msgstr "" msgstr "如果未給定選項，則輸出取決於輸入： " #: ../../library/random.rst:749 msgid "String or multiple: same as :option:`--choice`." msgstr "" msgstr "字串或多個：與 :option:`--choice` 相同。 " #: ../../library/random.rst:750 msgid "Integer: same as :option:`--integer`." msgstr "" msgstr "整數：與 :option:`--integer` 相同。 " #: ../../library/random.rst:751 msgid "Float: same as :option:`--float`." msgstr "" msgstr "浮點數：與 :option:`--float` 相同。 " #: ../../library/random.rst:756 msgid "Command-line example" msgstr "" msgstr "命令列範例 " #: ../../library/random.rst:758 msgid "Here are some examples of the :mod:`!random` command-line interface:" msgstr "" msgstr "以下是 :mod:`!random` 命令列介面的一些範例： " #: ../../library/random.rst:760 msgid "" Expand Down Expand Up @@ -1222,3 +1342,32 @@ msgid "" "$ python -m random --float 6\n" "3.1942323316565915" msgstr "" "$ # 隨機選擇一個\n" "$ python -m random egg bacon sausage spam \"Lobster Thermidor aux " "crevettes with a Mornay sauce\"\n" "Lobster Thermidor aux crevettes with a Mornay sauce\n" "\n" "$ # 隨機整數\n" "$ python -m random 6\n" "6\n" "\n" "$ # 隨機浮點數\n" "$ python -m random 1.8\n" "1.7080016272295635\n" "\n" "$ # 使用明確的引數\n" "$ python -m random --choice egg bacon sausage spam \"Lobster Thermidor " "aux crevettes with a Mornay sauce\"\n" "egg\n" "\n" "$ python -m random --integer 6\n" "3\n" "\n" "$ python -m random --float 1.8\n" "1.5666339105010318\n" "\n" "$ python -m random --integer 6\n" "5\n" "\n" "$ python -m random --float 6\n" "3.1942323316565915"