ee1e8abd87
* feat(tools): add seed/solution restore script * chore(curriculum): remove empty sections' markers * chore(curriculum): add seed + solution to Chinese * chore: remove old formatter * fix: update getChallenges parse translated challenges separately, without reference to the source * chore(curriculum): add dashedName to English * chore(curriculum): add dashedName to Chinese * refactor: remove unused challenge property 'name' * fix: relax dashedName requirement * fix: stray tag Remove stray `pre` tag from challenge file. Signed-off-by: nhcarrigan <nhcarrigan@gmail.com> Co-authored-by: nhcarrigan <nhcarrigan@gmail.com>
99 lines
1.7 KiB
Markdown
99 lines
1.7 KiB
Markdown
---
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id: 599d15309e88c813a40baf58
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title: 熵
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challengeType: 5
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videoUrl: ''
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dashedName: entropy
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---
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# --description--
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任务：
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计算给定输入字符串的香农熵H.
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给定谨慎的随机变量$ X $，它是$ N $“符号”（总字符）的字符串，由$ n $个不同的字符组成（对于二进制，n = 2），位/符号中X的香农熵是：
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$ H*2（X）= - \\ sum* {i = 1} ^ n \\ frac {count_i} {N} \\ log_2 \\ left（\\ frac {count_i} {N} \\ right）$
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其中$ count_i $是字符$ n_i $的计数。
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# --hints--
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`entropy`是一种功能。
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```js
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assert(typeof entropy === 'function');
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```
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`entropy("0")`应该返回`0`
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```js
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assert.equal(entropy('0'), 0);
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```
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`entropy("01")`应该返回`1`
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```js
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assert.equal(entropy('01'), 1);
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```
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`entropy("0123")`应该返回`2`
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```js
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assert.equal(entropy('0123'), 2);
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```
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`entropy("01234567")`应该返回`3`
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```js
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assert.equal(entropy('01234567'), 3);
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```
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`entropy("0123456789abcdef")`应返回`4`
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```js
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assert.equal(entropy('0123456789abcdef'), 4);
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```
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`entropy("1223334444")`应返回`1.8464393446710154`
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```js
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assert.equal(entropy('1223334444'), 1.8464393446710154);
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```
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# --seed--
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## --seed-contents--
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```js
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function entropy(s) {
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}
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```
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# --solutions--
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```js
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function entropy(s) {
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// Create a dictionary of character frequencies and iterate over it.
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function process(s, evaluator) {
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let h = Object.create(null),
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k;
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s.split('').forEach(c => {
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h[c] && h[c]++ || (h[c] = 1); });
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if (evaluator) for (k in h) evaluator(k, h[k]);
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return h;
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}
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// Measure the entropy of a string in bits per symbol.
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let sum = 0,
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len = s.length;
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process(s, (k, f) => {
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const p = f / len;
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sum -= p * Math.log(p) / Math.log(2);
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});
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return sum;
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}
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```
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