This commit is contained in:
krahets
2026-03-29 05:07:03 +08:00
parent 9e8c0cb36c
commit 9466700256
841 changed files with 38622 additions and 119252 deletions
@@ -18,7 +18,7 @@
<link rel="prev" href="../chapter_introduction/summary/">
<link rel="next" href="performance_evaluation/">
<link rel="next" href="./performance_evaluation/">
@@ -35,18 +35,23 @@
<link rel="icon" href="../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
<title>第 2 章   複雜度分析 - Hello 演算法</title>
<title>第 2 章 複雜度分析 - Hello 演算法</title>
<link rel="stylesheet" href="../assets/stylesheets/main.484c7ddc.min.css">
<link rel="stylesheet" href="../assets/stylesheets/palette.ab4e12ef.min.css">
<link rel="stylesheet" href="../assets/stylesheets/modern/main.6f2fbb28.min.css">
<link rel="stylesheet" href="../assets/stylesheets/modern/palette.dfe2e883.min.css">
@@ -60,29 +65,20 @@
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,500,500i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
<style>:root{--md-text-font:"Noto Sans SC";--md-code-font:"JetBrains Mono"}</style>
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html.glightbox-open { overflow: initial; height: 100%; }
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@@ -97,7 +93,7 @@
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<input class="md-toggle" data-md-toggle="search" type="checkbox" id="__search" autocomplete="off">
<label class="md-overlay" for="__drawer"></label>
<label class="md-overlay" for="__drawer" aria-label="導航"></label>
<div data-md-component="skip">
@@ -137,14 +133,14 @@
<header class="md-header md-header--shadow" data-md-component="header">
<nav class="md-header__inner md-grid" aria-label="頁首">
<a href=".." title="Hello 演算法" class="md-header__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<a href="./.." title="Hello 演算法" class="md-header__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../assets/images/logo.svg" alt="logo">
<img src="../assets/images/logo.svg" alt="Hello 演算法">
</a>
<label class="md-header__button md-icon" for="__drawer">
<label class="md-header__button md-icon" for="__drawer" aria-label="導航">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M3 6h18v2H3zm0 5h18v2H3zm0 5h18v2H3z"/></svg>
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<div class="md-header__title" data-md-component="header-title">
<div class="md-header__ellipsis">
@@ -169,7 +165,7 @@
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<input class="md-option" data-md-color-media="none" data-md-color-scheme="default" data-md-color-primary="white" data-md-color-accent="teal" aria-label="深色模式" type="radio" name="__palette" id="__palette_0">
<label class="md-header__button md-icon" title="深色模式" for="__palette_1" hidden>
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@@ -179,7 +175,7 @@
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<label class="md-header__button md-icon" title="淺色模式" for="__palette_0" hidden>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M7.5 2c-1.79 1.15-3 3.18-3 5.5s1.21 4.35 3.03 5.5C4.46 13 2 10.54 2 7.5A5.5 5.5 0 0 1 7.5 2m11.57 1.5 1.43 1.43L4.93 20.5 3.5 19.07zm-6.18 2.43L11.41 5 9.97 6l.42-1.7L9 3.24l1.75-.12.58-1.65L12 3.1l1.73.03-1.35 1.13zm-3.3 3.61-1.16-.73-1.12.78.34-1.32-1.09-.83 1.36-.09.45-1.29.51 1.27 1.36.03-1.05.87zM19 13.5a5.5 5.5 0 0 1-5.5 5.5c-1.22 0-2.35-.4-3.26-1.07l7.69-7.69c.67.91 1.07 2.04 1.07 3.26m-4.4 6.58 2.77-1.15-.24 3.35zm4.33-2.7 1.15-2.77 2.2 2.54zm1.15-4.96-1.14-2.78 3.34.24zM9.63 18.93l2.77 1.15-2.53 2.19z"/></svg>
@@ -197,7 +193,7 @@
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<button class="md-header__button md-icon" aria-label="選擇語言">
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<svg xmlns="http://www.w3.org/2000/svg" fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" class="lucide lucide-languages" viewBox="0 0 24 24"><path d="m5 8 6 6M4 14l6-6 2-3M2 5h12M7 2h1M22 22l-5-10-5 10M14 18h6"/></svg>
</button>
<div class="md-select__inner">
<ul class="md-select__list">
@@ -240,64 +236,30 @@
<label class="md-header__button md-icon" for="__search">
<label class="md-header__button md-icon" for="__search" aria-label="搜尋">
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</label>
<div class="md-search" data-md-component="search" role="dialog">
<label class="md-search__overlay" for="__search"></label>
<div class="md-search__inner" role="search">
<form class="md-search__form" name="search">
<input type="text" class="md-search__input" name="query" aria-label="搜尋" placeholder="搜尋" autocapitalize="off" autocorrect="off" autocomplete="off" spellcheck="false" data-md-component="search-query" required>
<label class="md-search__icon md-icon" for="__search">
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</label>
<nav class="md-search__options" aria-label="搜尋">
<a href="javascript:void(0)" class="md-search__icon md-icon" title="分享" aria-label="分享" data-clipboard data-clipboard-text="" data-md-component="search-share" tabindex="-1">
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<div class="md-search-result" data-md-component="search-result">
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正在初始化搜尋引擎
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<ol class="md-search-result__list" role="presentation"></ol>
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<div class="md-search" data-md-component="search" role="dialog" aria-label="搜尋">
<button type="button" class="md-search__button">
搜尋
</button>
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<div class="md-header__source">
<div class="md-header__source">
<a href="https://github.com/krahets/hello-algo" title="前往倉庫" class="md-source" data-md-component="source">
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<div class="md-source__repository">
krahets/hello-algo
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</a>
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@@ -323,9 +285,9 @@
<nav class="md-nav md-nav--primary" aria-label="導航" data-md-level="0">
<label class="md-nav__title" for="__drawer">
<a href=".." title="Hello 演算法" class="md-nav__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<a href="./.." title="Hello 演算法" class="md-nav__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../assets/images/logo.svg" alt="logo">
<img src="../assets/images/logo.svg" alt="Hello 演算法">
</a>
Hello 演算法
@@ -335,7 +297,7 @@
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@@ -35,18 +35,23 @@
<link rel="icon" href="../../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
<title>2.2   迭代與遞迴 - Hello 演算法</title>
<title>2.2 迭代與遞迴 - Hello 演算法</title>
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<link rel="stylesheet" href="../../assets/stylesheets/modern/palette.dfe2e883.min.css">
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
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<input class="md-toggle" data-md-toggle="search" type="checkbox" id="__search" autocomplete="off">
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<nav class="md-header__inner md-grid" aria-label="頁首">
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<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
</a>
<label class="md-header__button md-icon" for="__drawer">
<label class="md-header__button md-icon" for="__drawer" aria-label="導航">
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<div class="md-source__icon md-icon">
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path fill="currentColor" d="M173.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6m-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3m44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9M252.8 8C114.1 8 8 113.3 8 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C436.2 457.8 504 362.9 504 252 504 113.3 391.5 8 252.8 8M105.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1m-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7m32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1m-11.4-14.7c-1.6 1-1.6 3.6 0 5.9s4.3 3.3 5.6 2.3c1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2"/></svg>
</div>
<div class="md-source__repository">
krahets/hello-algo
</div>
</a>
</div>
</div>
</nav>
</header>
@@ -325,7 +287,7 @@
<label class="md-nav__title" for="__drawer">
<a href="../.." title="Hello 演算法" class="md-nav__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
</a>
Hello 演算法
@@ -335,7 +297,7 @@
<a href="https://github.com/krahets/hello-algo" title="前往倉庫" class="md-source" data-md-component="source">
<div class="md-source__icon md-icon">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path d="M173.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6m-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3m44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9M252.8 8C114.1 8 8 113.3 8 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C436.2 457.8 504 362.9 504 252 504 113.3 391.5 8 252.8 8M105.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1m-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7m32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1m-11.4-14.7c-1.6 1-1.6 3.6 0 5.9s4.3 3.3 5.6 2.3c1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2"/></svg>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path fill="currentColor" d="M173.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6m-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3m44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9M252.8 8C114.1 8 8 113.3 8 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C436.2 457.8 504 362.9 504 252 504 113.3 391.5 8 252.8 8M105.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1m-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7m32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1m-11.4-14.7c-1.6 1-1.6 3.6 0 5.9s4.3 3.3 5.6 2.3c1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2"/></svg>
</div>
<div class="md-source__repository">
krahets/hello-algo
@@ -871,7 +833,7 @@
<span class="md-nav__icon md-icon"></span>
</label>
<a href="./" class="md-nav__link md-nav__link--active">
<a href="././" class="md-nav__link md-nav__link--active">
@@ -890,6 +852,7 @@
<nav class="md-nav md-nav--secondary" aria-label="目錄">
@@ -912,7 +875,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.2.1   迭代">
<nav class="md-nav" aria-label="2.2.1 迭代">
<ul class="md-nav__list">
<li class="md-nav__item">
@@ -962,7 +925,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.2.2   遞迴">
<nav class="md-nav" aria-label="2.2.2 遞迴">
<ul class="md-nav__list">
<li class="md-nav__item">
@@ -4415,6 +4378,7 @@
<div class="md-sidebar__inner">
<nav class="md-nav md-nav--secondary" aria-label="目錄">
@@ -4437,7 +4401,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.2.1   迭代">
<nav class="md-nav" aria-label="2.2.1 迭代">
<ul class="md-nav__list">
<li class="md-nav__item">
@@ -4487,7 +4451,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.2.2   遞迴">
<nav class="md-nav" aria-label="2.2.2 遞迴">
<ul class="md-nav__list">
<li class="md-nav__item">
@@ -4567,7 +4531,7 @@
class="md-content__button md-icon"
>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path d="M441 58.9 453.1 71c9.4 9.4 9.4 24.6 0 33.9L424 134.1 377.9 88 407 58.9c9.4-9.4 24.6-9.4 33.9 0zM209.8 256.2 344 121.9l46.1 46.1-134.3 134.2c-2.9 2.9-6.5 5-10.4 6.1L186.9 325l16.7-58.5c1.1-3.9 3.2-7.5 6.1-10.4zM373.1 25 175.8 222.2c-8.7 8.7-15 19.4-18.3 31.1l-28.6 100c-2.4 8.4-.1 17.4 6.1 23.6s15.2 8.5 23.6 6.1l100-28.6c11.8-3.4 22.5-9.7 31.1-18.3L487 138.9c28.1-28.1 28.1-73.7 0-101.8L474.9 25c-28.1-28.1-73.7-28.1-101.8 0M88 64c-48.6 0-88 39.4-88 88v272c0 48.6 39.4 88 88 88h272c48.6 0 88-39.4 88-88V312c0-13.3-10.7-24-24-24s-24 10.7-24 24v112c0 22.1-17.9 40-40 40H88c-22.1 0-40-17.9-40-40V152c0-22.1 17.9-40 40-40h112c13.3 0 24-10.7 24-24s-10.7-24-24-24z"/></svg>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path fill="currentColor" d="M441 58.9 453.1 71c9.4 9.4 9.4 24.6 0 33.9L424 134.1 377.9 88 407 58.9c9.4-9.4 24.6-9.4 33.9 0zM209.8 256.2 344 121.9l46.1 46.1-134.3 134.2c-2.9 2.9-6.5 5-10.4 6.1L186.9 325l16.7-58.5c1.1-3.9 3.2-7.5 6.1-10.4zM373.1 25 175.8 222.2c-8.7 8.7-15 19.4-18.3 31.1l-28.6 100c-2.4 8.4-.1 17.4 6.1 23.6s15.2 8.5 23.6 6.1l100-28.6c11.8-3.4 22.5-9.7 31.1-18.3L487 138.9c28.1-28.1 28.1-73.7 0-101.8L474.9 25c-28.1-28.1-73.7-28.1-101.8 0M88 64c-48.6 0-88 39.4-88 88v272c0 48.6 39.4 88 88 88h272c48.6 0 88-39.4 88-88V312c0-13.3-10.7-24-24-24s-24 10.7-24 24v112c0 22.1-17.9 40-40 40H88c-22.1 0-40-17.9-40-40V152c0-22.1 17.9-40 40-40h112c13.3 0 24-10.7 24-24s-10.7-24-24-24z"/></svg>
</a>
@@ -4749,7 +4713,7 @@
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20for_loop%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22for%20%E8%BF%B4%E5%9C%88%22%22%22%0A%20%20%20%20res%20%3D%200%0A%20%20%20%20%23%20%E8%BF%B4%E5%9C%88%E6%B1%82%E5%92%8C%201%2C%202%2C%20...%2C%20n-1%2C%20n%0A%20%20%20%20for%20i%20in%20range%281%2C%20n%20%2B%201%29%3A%0A%20%20%20%20%20%20%20%20res%20%2B%3D%20i%0A%20%20%20%20return%20res%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20res%20%3D%20for_loop%28n%29%0A%20%20%20%20print%28f%22%5Cnfor%20%E8%BF%B4%E5%9C%88%E7%9A%84%E6%B1%82%E5%92%8C%E7%B5%90%E6%9E%9C%20res%20%3D%20%7Bres%7D%22%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p>圖 2-1 是該求和函式的流程框圖。</p>
<p><a class="glightbox" href="../iteration_and_recursion.assets/iteration.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="求和函式的流程框圖" class="animation-figure" src="../iteration_and_recursion.assets/iteration.png" /></a></p>
<p><img alt="求和函式的流程框圖" class="animation-figure" src="../iteration_and_recursion.assets/iteration.png" /></p>
<p align="center"> 圖 2-1 &nbsp; 求和函式的流程框圖 </p>
<p>此求和函式的操作數量與輸入資料大小 <span class="arithmatex">\(n\)</span> 成正比,或者說成“線性關係”。實際上,<strong>時間複雜度描述的就是這個“線性關係”</strong>。相關內容將會在下一節中詳細介紹。</p>
@@ -5382,7 +5346,7 @@
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20nested_for_loop%28n%3A%20int%29%20-%3E%20str%3A%0A%20%20%20%20%22%22%22%E9%9B%99%E5%B1%A4%20for%20%E8%BF%B4%E5%9C%88%22%22%22%0A%20%20%20%20res%20%3D%20%22%22%0A%20%20%20%20%23%20%E8%BF%B4%E5%9C%88%20i%20%3D%201%2C%202%2C%20...%2C%20n-1%2C%20n%0A%20%20%20%20for%20i%20in%20range%281%2C%20n%20%2B%201%29%3A%0A%20%20%20%20%20%20%20%20%23%20%E8%BF%B4%E5%9C%88%20j%20%3D%201%2C%202%2C%20...%2C%20n-1%2C%20n%0A%20%20%20%20%20%20%20%20for%20j%20in%20range%281%2C%20n%20%2B%201%29%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20res%20%2B%3D%20f%22%28%7Bi%7D%2C%20%7Bj%7D%29%2C%20%22%0A%20%20%20%20return%20res%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20res%20%3D%20nested_for_loop%28n%29%0A%20%20%20%20print%28f%22%5Cn%E9%9B%99%E5%B1%A4%20for%20%E8%BF%B4%E5%9C%88%E7%9A%84%E8%B5%B0%E8%A8%AA%E7%B5%90%E6%9E%9C%20%7Bres%7D%22%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p>圖 2-2 是該巢狀迴圈的流程框圖。</p>
<p><a class="glightbox" href="../iteration_and_recursion.assets/nested_iteration.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="巢狀迴圈的流程框圖" class="animation-figure" src="../iteration_and_recursion.assets/nested_iteration.png" /></a></p>
<p><img alt="巢狀迴圈的流程框圖" class="animation-figure" src="../iteration_and_recursion.assets/nested_iteration.png" /></p>
<p align="center"> 圖 2-2 &nbsp; 巢狀迴圈的流程框圖 </p>
<p>在這種情況下,函式的操作數量與 <span class="arithmatex">\(n^2\)</span> 成正比,或者說演算法執行時間和輸入資料大小 <span class="arithmatex">\(n\)</span> 成“平方關係”。</p>
@@ -5577,7 +5541,7 @@
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20recur%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E9%81%9E%E8%BF%B4%22%22%22%0A%20%20%20%20%23%20%E7%B5%82%E6%AD%A2%E6%A2%9D%E4%BB%B6%0A%20%20%20%20if%20n%20%3D%3D%201%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20%23%20%E9%81%9E%EF%BC%9A%E9%81%9E%E8%BF%B4%E5%91%BC%E5%8F%AB%0A%20%20%20%20res%20%3D%20recur%28n%20-%201%29%0A%20%20%20%20%23%20%E8%BF%B4%EF%BC%9A%E8%BF%94%E5%9B%9E%E7%B5%90%E6%9E%9C%0A%20%20%20%20return%20n%20%2B%20res%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20res%20%3D%20recur%28n%29%0A%20%20%20%20print%28f%22%5Cn%E9%81%9E%E8%BF%B4%E5%87%BD%E5%BC%8F%E7%9A%84%E6%B1%82%E5%92%8C%E7%B5%90%E6%9E%9C%20res%20%3D%20%7Bres%7D%22%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p>圖 2-3 展示了該函式的遞迴過程。</p>
<p><a class="glightbox" href="../iteration_and_recursion.assets/recursion_sum.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="求和函式的遞迴過程" class="animation-figure" src="../iteration_and_recursion.assets/recursion_sum.png" /></a></p>
<p><img alt="求和函式的遞迴過程" class="animation-figure" src="../iteration_and_recursion.assets/recursion_sum.png" /></p>
<p align="center"> 圖 2-3 &nbsp; 求和函式的遞迴過程 </p>
<p>雖然從計算角度看,迭代與遞迴可以得到相同的結果,<strong>但它們代表了兩種完全不同的思考和解決問題的範式</strong></p>
@@ -5597,7 +5561,7 @@
<li>遞迴呼叫函式會產生額外的開銷。<strong>因此遞迴通常比迴圈的時間效率更低</strong></li>
</ul>
<p>如圖 2-4 所示,在觸發終止條件前,同時存在 <span class="arithmatex">\(n\)</span> 個未返回的遞迴函式,<strong>遞迴深度為 <span class="arithmatex">\(n\)</span></strong></p>
<p><a class="glightbox" href="../iteration_and_recursion.assets/recursion_sum_depth.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="遞迴呼叫深度" class="animation-figure" src="../iteration_and_recursion.assets/recursion_sum_depth.png" /></a></p>
<p><img alt="遞迴呼叫深度" class="animation-figure" src="../iteration_and_recursion.assets/recursion_sum_depth.png" /></p>
<p align="center"> 圖 2-4 &nbsp; 遞迴呼叫深度 </p>
<p>在實際中,程式語言允許的遞迴深度通常是有限的,過深的遞迴可能導致堆疊溢位錯誤。</p>
@@ -5764,7 +5728,7 @@
<li><strong>普通遞迴</strong>:求和操作是在“迴”的過程中執行的,每層返回後都要再執行一次求和操作。</li>
<li><strong>尾遞迴</strong>:求和操作是在“遞”的過程中執行的,“迴”的過程只需層層返回。</li>
</ul>
<p><a class="glightbox" href="../iteration_and_recursion.assets/tail_recursion_sum.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="尾遞迴過程" class="animation-figure" src="../iteration_and_recursion.assets/tail_recursion_sum.png" /></a></p>
<p><img alt="尾遞迴過程" class="animation-figure" src="../iteration_and_recursion.assets/tail_recursion_sum.png" /></p>
<p align="center"> 圖 2-5 &nbsp; 尾遞迴過程 </p>
<div class="admonition tip">
@@ -5960,7 +5924,7 @@
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</details>
<p>觀察以上程式碼,我們在函式內遞迴呼叫了兩個函式,<strong>這意味著從一個呼叫產生了兩個呼叫分支</strong>。如圖 2-6 所示,這樣不斷遞迴呼叫下去,最終將產生一棵層數為 <span class="arithmatex">\(n\)</span><u>遞迴樹(recursion tree</u></p>
<p><a class="glightbox" href="../iteration_and_recursion.assets/recursion_tree.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="費波那契數列的遞迴樹" class="animation-figure" src="../iteration_and_recursion.assets/recursion_tree.png" /></a></p>
<p><img alt="費波那契數列的遞迴樹" class="animation-figure" src="../iteration_and_recursion.assets/recursion_tree.png" /></p>
<p align="center"> 圖 2-6 &nbsp; 費波那契數列的遞迴樹 </p>
<p>從本質上看,遞迴體現了“將問題分解為更小子問題”的思維範式,這種分治策略至關重要。</p>
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@@ -35,18 +35,23 @@
<link rel="icon" href="../../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
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<title>2.1 演算法效率評估 - Hello 演算法</title>
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<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
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html.glightbox-open { overflow: initial; height: 100%; }
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<input class="md-toggle" data-md-toggle="search" type="checkbox" id="__search" autocomplete="off">
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<label class="md-overlay" for="__drawer" aria-label="導航"></label>
<div data-md-component="skip">
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<nav class="md-header__inner md-grid" aria-label="頁首">
<a href="../.." title="Hello 演算法" class="md-header__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
</a>
<label class="md-header__button md-icon" for="__drawer">
<label class="md-header__button md-icon" for="__drawer" aria-label="導航">
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<div class="md-header__title" data-md-component="header-title">
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<ul class="md-select__list">
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<label class="md-header__button md-icon" for="__search" aria-label="搜尋">
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<div class="md-search__scrollwrap" tabindex="0" data-md-scrollfix>
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正在初始化搜尋引擎
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<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
</a>
Hello 演算法
@@ -335,7 +297,7 @@
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@@ -35,18 +35,23 @@
<link rel="icon" href="../../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
<title>2.4   空間複雜度 - Hello 演算法</title>
<title>2.4 空間複雜度 - Hello 演算法</title>
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<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
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<nav class="md-header__inner md-grid" aria-label="頁首">
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<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
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krahets/hello-algo
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@@ -325,7 +287,7 @@
<label class="md-nav__title" for="__drawer">
<a href="../.." title="Hello 演算法" class="md-nav__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
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Hello 演算法
@@ -335,7 +297,7 @@
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krahets/hello-algo
@@ -927,7 +889,7 @@
<span class="md-nav__icon md-icon"></span>
</label>
<a href="./" class="md-nav__link md-nav__link--active">
<a href="././" class="md-nav__link md-nav__link--active">
@@ -946,6 +908,7 @@
<nav class="md-nav md-nav--secondary" aria-label="目錄">
@@ -990,7 +953,7 @@
</span>
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<nav class="md-nav" aria-label="2.4.3   常見型別">
<nav class="md-nav" aria-label="2.4.3 常見型別">
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@@ -4409,6 +4372,7 @@
<div class="md-sidebar__inner">
<nav class="md-nav md-nav--secondary" aria-label="目錄">
@@ -4453,7 +4417,7 @@
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@@ -4555,7 +4519,7 @@
class="md-content__button md-icon"
>
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><!--! Font Awesome Free 7.1.0 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2025 Fonticons, Inc.--><path d="M441 58.9 453.1 71c9.4 9.4 9.4 24.6 0 33.9L424 134.1 377.9 88 407 58.9c9.4-9.4 24.6-9.4 33.9 0zM209.8 256.2 344 121.9l46.1 46.1-134.3 134.2c-2.9 2.9-6.5 5-10.4 6.1L186.9 325l16.7-58.5c1.1-3.9 3.2-7.5 6.1-10.4zM373.1 25 175.8 222.2c-8.7 8.7-15 19.4-18.3 31.1l-28.6 100c-2.4 8.4-.1 17.4 6.1 23.6s15.2 8.5 23.6 6.1l100-28.6c11.8-3.4 22.5-9.7 31.1-18.3L487 138.9c28.1-28.1 28.1-73.7 0-101.8L474.9 25c-28.1-28.1-73.7-28.1-101.8 0M88 64c-48.6 0-88 39.4-88 88v272c0 48.6 39.4 88 88 88h272c48.6 0 88-39.4 88-88V312c0-13.3-10.7-24-24-24s-24 10.7-24 24v112c0 22.1-17.9 40-40 40H88c-22.1 0-40-17.9-40-40V152c0-22.1 17.9-40 40-40h112c13.3 0 24-10.7 24-24s-10.7-24-24-24z"/></svg>
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</a>
@@ -4581,7 +4545,7 @@
<li><strong>指令空間</strong>:用於儲存編譯後的程式指令,在實際統計中通常忽略不計。</li>
</ul>
<p>在分析一段程式的空間複雜度時,<strong>我們通常統計暫存資料、堆疊幀空間和輸出資料三部分</strong>,如圖 2-15 所示。</p>
<p><a class="glightbox" href="../space_complexity.assets/space_types.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="演算法使用的相關空間" class="animation-figure" src="../space_complexity.assets/space_types.png" /></a></p>
<p><img alt="演算法使用的相關空間" class="animation-figure" src="../space_complexity.assets/space_types.png" /></p>
<p align="center"> 圖 2-15 &nbsp; 演算法使用的相關空間 </p>
<p>相關程式碼如下:</p>
@@ -5299,7 +5263,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n^2) &lt; O(2^n) \newline
\text{常數階} &lt; \text{對數階} &lt; \text{線性階} &lt; \text{平方階} &lt; \text{指數階}
\end{aligned}
\]</div>
<p><a class="glightbox" href="../space_complexity.assets/space_complexity_common_types.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="常見的空間複雜度型別" class="animation-figure" src="../space_complexity.assets/space_complexity_common_types.png" /></a></p>
<p><img alt="常見的空間複雜度型別" class="animation-figure" src="../space_complexity.assets/space_complexity_common_types.png" /></p>
<p align="center"> 圖 2-16 &nbsp; 常見的空間複雜度型別 </p>
<h3 id="1-o1">1. &nbsp; 常數階 <span class="arithmatex">\(O(1)\)</span><a class="headerlink" href="#1-o1" title="Permanent link">&para;</a></h3>
@@ -6029,7 +5993,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n^2) &lt; O(2^n) \newline
<p><div style="height: 441px; width: 100%;"><iframe class="pythontutor-iframe" src="https://pythontutor.com/iframe-embed.html#code=def%20linear_recur%28n%3A%20int%29%3A%0A%20%20%20%20%22%22%22%E7%B7%9A%E6%80%A7%E9%9A%8E%EF%BC%88%E9%81%9E%E8%BF%B4%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20print%28%22%E9%81%9E%E8%BF%B4%20n%20%3D%22%2C%20n%29%0A%20%20%20%20if%20n%20%3D%3D%201%3A%0A%20%20%20%20%20%20%20%20return%0A%20%20%20%20linear_recur%28n%20-%201%29%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20%23%20%E7%B7%9A%E6%80%A7%E9%9A%8E%0A%20%20%20%20linear_recur%28n%29&codeDivHeight=472&codeDivWidth=350&cumulative=false&curInstr=25&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false"> </iframe></div>
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</details>
<p><a class="glightbox" href="../space_complexity.assets/space_complexity_recursive_linear.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="遞迴函式產生的線性階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_recursive_linear.png" /></a></p>
<p><img alt="遞迴函式產生的線性階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_recursive_linear.png" /></p>
<p align="center"> 圖 2-17 &nbsp; 遞迴函式產生的線性階空間複雜度 </p>
<h3 id="3-on2">3. &nbsp; 平方階 <span class="arithmatex">\(O(n^2)\)</span><a class="headerlink" href="#3-on2" title="Permanent link">&para;</a></h3>
@@ -6395,7 +6359,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n^2) &lt; O(2^n) \newline
<p><div style="height: 459px; width: 100%;"><iframe class="pythontutor-iframe" src="https://pythontutor.com/iframe-embed.html#code=def%20quadratic_recur%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E5%B9%B3%E6%96%B9%E9%9A%8E%EF%BC%88%E9%81%9E%E8%BF%B4%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20if%20n%20%3C%3D%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20%23%20%E9%99%A3%E5%88%97%20nums%20%E9%95%B7%E5%BA%A6%E7%82%BA%20n%2C%20n-1%2C%20...%2C%202%2C%201%0A%20%20%20%20nums%20%3D%20%5B0%5D%20%2A%20n%0A%20%20%20%20return%20quadratic_recur%28n%20-%201%29%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20%23%20%E5%B9%B3%E6%96%B9%E9%9A%8E%0A%20%20%20%20quadratic_recur%28n%29&codeDivHeight=472&codeDivWidth=350&cumulative=false&curInstr=28&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false"> </iframe></div>
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20quadratic_recur%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E5%B9%B3%E6%96%B9%E9%9A%8E%EF%BC%88%E9%81%9E%E8%BF%B4%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20if%20n%20%3C%3D%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20%23%20%E9%99%A3%E5%88%97%20nums%20%E9%95%B7%E5%BA%A6%E7%82%BA%20n%2C%20n-1%2C%20...%2C%202%2C%201%0A%20%20%20%20nums%20%3D%20%5B0%5D%20%2A%20n%0A%20%20%20%20return%20quadratic_recur%28n%20-%201%29%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%205%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20%23%20%E5%B9%B3%E6%96%B9%E9%9A%8E%0A%20%20%20%20quadratic_recur%28n%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=28&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p><a class="glightbox" href="../space_complexity.assets/space_complexity_recursive_quadratic.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="遞迴函式產生的平方階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_recursive_quadratic.png" /></a></p>
<p><img alt="遞迴函式產生的平方階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_recursive_quadratic.png" /></p>
<p align="center"> 圖 2-18 &nbsp; 遞迴函式產生的平方階空間複雜度 </p>
<h3 id="4-o2n">4. &nbsp; 指數階 <span class="arithmatex">\(O(2^n)\)</span><a class="headerlink" href="#4-o2n" title="Permanent link">&para;</a></h3>
@@ -6564,7 +6528,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n^2) &lt; O(2^n) \newline
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</details>
<p><a class="glightbox" href="../space_complexity.assets/space_complexity_exponential.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="滿二元樹產生的指數階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_exponential.png" /></a></p>
<p><img alt="滿二元樹產生的指數階空間複雜度" class="animation-figure" src="../space_complexity.assets/space_complexity_exponential.png" /></p>
<p align="center"> 圖 2-19 &nbsp; 滿二元樹產生的指數階空間複雜度 </p>
<h3 id="5-olog-n">5. &nbsp; 對數階 <span class="arithmatex">\(O(\log n)\)</span><a class="headerlink" href="#5-olog-n" title="Permanent link">&para;</a></h3>
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@@ -35,18 +35,23 @@
<link rel="icon" href="../../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
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<link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Noto+Sans+SC:300,300i,400,400i,700,700i%7CJetBrains+Mono:400,400i,700,700i&display=fallback">
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<input class="md-toggle" data-md-toggle="search" type="checkbox" id="__search" autocomplete="off">
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<div data-md-component="skip">
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<nav class="md-header__inner md-grid" aria-label="頁首">
<a href="../.." title="Hello 演算法" class="md-header__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
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<label class="md-header__button md-icon" for="__drawer" aria-label="導航">
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<ul class="md-select__list">
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<label class="md-header__button md-icon" for="__search" aria-label="搜尋">
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<link rel="icon" href="../../assets/images/favicon.png">
<meta name="generator" content="mkdocs-1.6.1, mkdocs-material-9.7.1">
<meta name="generator" content="zensical-0.0.29">
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<nav class="md-header__inner md-grid" aria-label="頁首">
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<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
</a>
<label class="md-header__button md-icon" for="__drawer">
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@@ -325,7 +287,7 @@
<label class="md-nav__title" for="__drawer">
<a href="../.." title="Hello 演算法" class="md-nav__button md-logo" aria-label="Hello 演算法" data-md-component="logo">
<img src="../../assets/images/logo.svg" alt="logo">
<img src="../../assets/images/logo.svg" alt="Hello 演算法">
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Hello 演算法
@@ -335,7 +297,7 @@
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krahets/hello-algo
@@ -899,7 +861,7 @@
<span class="md-nav__icon md-icon"></span>
</label>
<a href="./" class="md-nav__link md-nav__link--active">
<a href="././" class="md-nav__link md-nav__link--active">
@@ -918,6 +880,7 @@
<nav class="md-nav md-nav--secondary" aria-label="目錄">
@@ -962,7 +925,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.3.3   推算方法">
<nav class="md-nav" aria-label="2.3.3 推算方法">
<ul class="md-nav__list">
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@@ -1001,7 +964,7 @@
</span>
</a>
<nav class="md-nav" aria-label="2.3.4   常見型別">
<nav class="md-nav" aria-label="2.3.4 常見型別">
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@@ -4470,6 +4433,7 @@
<div class="md-sidebar__inner">
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@@ -4514,7 +4478,7 @@
</span>
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<nav class="md-nav" aria-label="2.3.3 推算方法">
<ul class="md-nav__list">
<li class="md-nav__item">
@@ -4553,7 +4517,7 @@
</span>
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<nav class="md-nav" aria-label="2.3.4 常見型別">
<ul class="md-nav__list">
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@@ -4677,7 +4641,7 @@
class="md-content__button md-icon"
>
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</a>
@@ -5125,7 +5089,7 @@
<li>演算法 <code>B</code> 中的列印操作需要迴圈 <span class="arithmatex">\(n\)</span> 次,演算法執行時間隨著 <span class="arithmatex">\(n\)</span> 增大呈線性增長。此演算法的時間複雜度被稱為“線性階”。</li>
<li>演算法 <code>C</code> 中的列印操作需要迴圈 <span class="arithmatex">\(1000000\)</span> 次,雖然執行時間很長,但它與輸入資料大小 <span class="arithmatex">\(n\)</span> 無關。因此 <code>C</code> 的時間複雜度和 <code>A</code> 相同,仍為“常數階”。</li>
</ul>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_simple_example.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="演算法 A、B 和 C 的時間增長趨勢" class="animation-figure" src="../time_complexity.assets/time_complexity_simple_example.png" /></a></p>
<p><img alt="演算法 A、B 和 C 的時間增長趨勢" class="animation-figure" src="../time_complexity.assets/time_complexity_simple_example.png" /></p>
<p align="center"> 圖 2-7 &nbsp; 演算法 A、B 和 C 的時間增長趨勢 </p>
<p>相較於直接統計演算法的執行時間,時間複雜度分析有哪些特點呢?</p>
@@ -5307,7 +5271,7 @@ T(n) = 3 + 2n
<p>若存在正實數 <span class="arithmatex">\(c\)</span> 和實數 <span class="arithmatex">\(n_0\)</span> ,使得對於所有的 <span class="arithmatex">\(n &gt; n_0\)</span> ,均有 <span class="arithmatex">\(T(n) \leq c \cdot f(n)\)</span> ,則可認為 <span class="arithmatex">\(f(n)\)</span> 給出了 <span class="arithmatex">\(T(n)\)</span> 的一個漸近上界,記為 <span class="arithmatex">\(T(n) = O(f(n))\)</span></p>
</div>
<p>如圖 2-8 所示,計算漸近上界就是尋找一個函式 <span class="arithmatex">\(f(n)\)</span> ,使得當 <span class="arithmatex">\(n\)</span> 趨向於無窮大時,<span class="arithmatex">\(T(n)\)</span><span class="arithmatex">\(f(n)\)</span> 處於相同的增長級別,僅相差一個常數係數 <span class="arithmatex">\(c\)</span></p>
<p><a class="glightbox" href="../time_complexity.assets/asymptotic_upper_bound.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="函式的漸近上界" class="animation-figure" src="../time_complexity.assets/asymptotic_upper_bound.png" /></a></p>
<p><img alt="函式的漸近上界" class="animation-figure" src="../time_complexity.assets/asymptotic_upper_bound.png" /></p>
<p align="center"> 圖 2-8 &nbsp; 函式的漸近上界 </p>
<h2 id="233">2.3.3 &nbsp; 推算方法<a class="headerlink" href="#233" title="Permanent link">&para;</a></h2>
@@ -5593,7 +5557,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n \log n) &lt; O(n^2) &lt; O(2^n) &lt; O(n!
\text{常數階} &lt; \text{對數階} &lt; \text{線性階} &lt; \text{線性對數階} &lt; \text{平方階} &lt; \text{指數階} &lt; \text{階乘階}
\end{aligned}
\]</div>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_common_types.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="常見的時間複雜度型別" class="animation-figure" src="../time_complexity.assets/time_complexity_common_types.png" /></a></p>
<p><img alt="常見的時間複雜度型別" class="animation-figure" src="../time_complexity.assets/time_complexity_common_types.png" /></p>
<p align="center"> 圖 2-9 &nbsp; 常見的時間複雜度型別 </p>
<h3 id="1-o1">1. &nbsp; 常數階 <span class="arithmatex">\(O(1)\)</span><a class="headerlink" href="#1-o1" title="Permanent link">&para;</a></h3>
@@ -6258,7 +6222,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n \log n) &lt; O(n^2) &lt; O(2^n) &lt; O(n!
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20quadratic%28n%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E5%B9%B3%E6%96%B9%E9%9A%8E%22%22%22%0A%20%20%20%20count%20%3D%200%0A%20%20%20%20%23%20%E8%BF%B4%E5%9C%88%E6%AC%A1%E6%95%B8%E8%88%87%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%E6%88%90%E5%B9%B3%E6%96%B9%E9%97%9C%E4%BF%82%0A%20%20%20%20for%20i%20in%20range%28n%29%3A%0A%20%20%20%20%20%20%20%20for%20j%20in%20range%28n%29%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20quadratic%28n%29%0A%20%20%20%20print%28%22%E5%B9%B3%E6%96%B9%E9%9A%8E%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p>圖 2-10 對比了常數階、線性階和平方階三種時間複雜度。</p>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_constant_linear_quadratic.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="常數階、線性階和平方階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_constant_linear_quadratic.png" /></a></p>
<p><img alt="常數階、線性階和平方階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_constant_linear_quadratic.png" /></p>
<p align="center"> 圖 2-10 &nbsp; 常數階、線性階和平方階的時間複雜度 </p>
<p>以泡沫排序為例,外層迴圈執行 <span class="arithmatex">\(n - 1\)</span> 次,內層迴圈執行 <span class="arithmatex">\(n-1\)</span><span class="arithmatex">\(n-2\)</span><span class="arithmatex">\(\dots\)</span><span class="arithmatex">\(2\)</span><span class="arithmatex">\(1\)</span> 次,平均為 <span class="arithmatex">\(n / 2\)</span> 次,因此時間複雜度為 <span class="arithmatex">\(O((n - 1) n / 2) = O(n^2)\)</span> </p>
@@ -6765,7 +6729,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n \log n) &lt; O(n^2) &lt; O(2^n) &lt; O(n!
<p><div style="height: 531px; width: 100%;"><iframe class="pythontutor-iframe" src="https://pythontutor.com/iframe-embed.html#code=def%20exponential%28n%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E6%8C%87%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20count%20%3D%200%0A%20%20%20%20base%20%3D%201%0A%20%20%20%20%23%20%E7%B4%B0%E8%83%9E%E6%AF%8F%E8%BC%AA%E4%B8%80%E5%88%86%E7%82%BA%E4%BA%8C%EF%BC%8C%E5%BD%A2%E6%88%90%E6%95%B8%E5%88%97%201%2C%202%2C%204%2C%208%2C%20...%2C%202%5E%28n-1%29%0A%20%20%20%20for%20_%20in%20range%28n%29%3A%0A%20%20%20%20%20%20%20%20for%20_%20in%20range%28base%29%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20%20%20%20%20base%20%2A%3D%202%0A%20%20%20%20%23%20count%20%3D%201%20%2B%202%20%2B%204%20%2B%208%20%2B%20..%20%2B%202%5E%28n-1%29%20%3D%202%5En%20-%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20exponential%28n%29%0A%20%20%20%20print%28%22%E6%8C%87%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=472&codeDivWidth=350&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false"> </iframe></div>
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20exponential%28n%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E6%8C%87%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20count%20%3D%200%0A%20%20%20%20base%20%3D%201%0A%20%20%20%20%23%20%E7%B4%B0%E8%83%9E%E6%AF%8F%E8%BC%AA%E4%B8%80%E5%88%86%E7%82%BA%E4%BA%8C%EF%BC%8C%E5%BD%A2%E6%88%90%E6%95%B8%E5%88%97%201%2C%202%2C%204%2C%208%2C%20...%2C%202%5E%28n-1%29%0A%20%20%20%20for%20_%20in%20range%28n%29%3A%0A%20%20%20%20%20%20%20%20for%20_%20in%20range%28base%29%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20%20%20%20%20base%20%2A%3D%202%0A%20%20%20%20%23%20count%20%3D%201%20%2B%202%20%2B%204%20%2B%208%20%2B%20..%20%2B%202%5E%28n-1%29%20%3D%202%5En%20-%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20exponential%28n%29%0A%20%20%20%20print%28%22%E6%8C%87%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_exponential.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="指數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_exponential.png" /></a></p>
<p><img alt="指數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_exponential.png" /></p>
<p align="center"> 圖 2-11 &nbsp; 指數階的時間複雜度 </p>
<p>在實際演算法中,指數階常出現於遞迴函式中。例如在以下程式碼中,其遞迴地一分為二,經過 <span class="arithmatex">\(n\)</span> 次分裂後停止:</p>
@@ -7064,7 +7028,7 @@ O(1) &lt; O(\log n) &lt; O(n) &lt; O(n \log n) &lt; O(n^2) &lt; O(2^n) &lt; O(n!
<p><div style="height: 459px; width: 100%;"><iframe class="pythontutor-iframe" src="https://pythontutor.com/iframe-embed.html#code=def%20logarithmic%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E5%B0%8D%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20count%20%3D%200%0A%20%20%20%20while%20n%20%3E%201%3A%0A%20%20%20%20%20%20%20%20n%20%3D%20n%20/%202%0A%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20logarithmic%28n%29%0A%20%20%20%20print%28%22%E5%B0%8D%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=472&codeDivWidth=350&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false"> </iframe></div>
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20logarithmic%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E5%B0%8D%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%22%22%22%0A%20%20%20%20count%20%3D%200%0A%20%20%20%20while%20n%20%3E%201%3A%0A%20%20%20%20%20%20%20%20n%20%3D%20n%20/%202%0A%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20logarithmic%28n%29%0A%20%20%20%20print%28%22%E5%B0%8D%E6%95%B8%E9%9A%8E%EF%BC%88%E8%BF%B4%E5%9C%88%E5%AF%A6%E7%8F%BE%EF%BC%89%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=3&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_logarithmic.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="對數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_logarithmic.png" /></a></p>
<p><img alt="對數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_logarithmic.png" /></p>
<p align="center"> 圖 2-12 &nbsp; 對數階的時間複雜度 </p>
<p>與指數階類似,對數階也常出現於遞迴函式中。以下程式碼形成了一棵高度為 <span class="arithmatex">\(\log_2 n\)</span> 的遞迴樹:</p>
@@ -7379,7 +7343,7 @@ O(\log_m n) = O(\log_k n / \log_k m) = O(\log_k n)
<div style="margin-top: 5px;"><a href="https://pythontutor.com/iframe-embed.html#code=def%20linear_log_recur%28n%3A%20int%29%20-%3E%20int%3A%0A%20%20%20%20%22%22%22%E7%B7%9A%E6%80%A7%E5%B0%8D%E6%95%B8%E9%9A%8E%22%22%22%0A%20%20%20%20if%20n%20%3C%3D%201%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20count%20%3D%20linear_log_recur%28n%20//%202%29%20%2B%20linear_log_recur%28n%20//%202%29%0A%20%20%20%20for%20_%20in%20range%28n%29%3A%0A%20%20%20%20%20%20%20%20count%20%2B%3D%201%0A%20%20%20%20return%20count%0A%0A%22%22%22Driver%20Code%22%22%22%0Aif%20__name__%20%3D%3D%20%22__main__%22%3A%0A%20%20%20%20n%20%3D%208%0A%20%20%20%20print%28%22%E8%BC%B8%E5%85%A5%E8%B3%87%E6%96%99%E5%A4%A7%E5%B0%8F%20n%20%3D%22%2C%20n%29%0A%0A%20%20%20%20count%20%3D%20linear_log_recur%28n%29%0A%20%20%20%20print%28%22%E7%B7%9A%E6%80%A7%E5%B0%8D%E6%95%B8%E9%9A%8E%EF%BC%88%E9%81%9E%E8%BF%B4%E5%AF%A6%E7%8F%BE%EF%BC%89%E7%9A%84%E6%93%8D%E4%BD%9C%E6%95%B8%E9%87%8F%20%3D%22%2C%20count%29&codeDivHeight=800&codeDivWidth=600&cumulative=false&curInstr=4&heapPrimitives=nevernest&origin=opt-frontend.js&py=311&rawInputLstJSON=%5B%5D&textReferences=false" target="_blank" rel="noopener noreferrer">全螢幕觀看 &gt;</a></div></p>
</details>
<p>圖 2-13 展示了線性對數階的生成方式。二元樹的每一層的操作總數都為 <span class="arithmatex">\(n\)</span> ,樹共有 <span class="arithmatex">\(\log_2 n + 1\)</span> 層,因此時間複雜度為 <span class="arithmatex">\(O(n \log n)\)</span></p>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_logarithmic_linear.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="線性對數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_logarithmic_linear.png" /></a></p>
<p><img alt="線性對數階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_logarithmic_linear.png" /></p>
<p align="center"> 圖 2-13 &nbsp; 線性對數階的時間複雜度 </p>
<p>主流排序演算法的時間複雜度通常為 <span class="arithmatex">\(O(n \log n)\)</span> ,例如快速排序、合併排序、堆積排序等。</p>
@@ -7575,7 +7539,7 @@ n! = n \times (n - 1) \times (n - 2) \times \dots \times 2 \times 1
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</details>
<p><a class="glightbox" href="../time_complexity.assets/time_complexity_factorial.png" data-type="image" data-width="100%" data-height="auto" data-desc-position="bottom"><img alt="階乘階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_factorial.png" /></a></p>
<p><img alt="階乘階的時間複雜度" class="animation-figure" src="../time_complexity.assets/time_complexity_factorial.png" /></p>
<p align="center"> 圖 2-14 &nbsp; 階乘階的時間複雜度 </p>
<p>請注意,因為當 <span class="arithmatex">\(n \geq 4\)</span> 時恆有 <span class="arithmatex">\(n! &gt; 2^n\)</span> ,所以階乘階比指數階增長得更快,在 <span class="arithmatex">\(n\)</span> 較大時也是不可接受的。</p>
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