chore(i18n,learn): processed translations (#44851)

curriculum/challenges/japanese/10-coding-interview-prep/rosetta-code/entropy.md

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+---
+id: 599d15309e88c813a40baf58
+title: Entropy
+challengeType: 5
+forumTopicId: 302254
+dashedName: entropy
+---
+
+# --description--
+
+Calculate the Shannon entropy H of a given input string.
+
+Given the discreet random variable $X$ that is a string of $N$ "symbols" (total characters) consisting of $n$ different characters (n=2 for binary), the Shannon entropy of X in bits/symbol is:
+
+$H_2(X) = -\\sum\_{i=1}^n \\frac{count_i}{N} \\log_2 \\left(\\frac{count_i}{N}\\right)$
+
+where $count_i$ is the count of character $n_i$.
+
+# --hints--
+
+`entropy` should be a function.
+
+```js
+assert(typeof entropy === 'function');
+```
+
+`entropy("0")` should return `0`
+
+```js
+assert.equal(entropy('0'), 0);
+```
+
+`entropy("01")` should return `1`
+
+```js
+assert.equal(entropy('01'), 1);
+```
+
+`entropy("0123")` should return `2`
+
+```js
+assert.equal(entropy('0123'), 2);
+```
+
+`entropy("01234567")` should return `3`
+
+```js
+assert.equal(entropy('01234567'), 3);
+```
+
+`entropy("0123456789abcdef")` should return `4`
+
+```js
+assert.equal(entropy('0123456789abcdef'), 4);
+```
+
+`entropy("1223334444")` should return `1.8464393446710154`
+
+```js
+assert.equal(entropy('1223334444'), 1.8464393446710154);
+```
+
+# --seed--
+
+## --seed-contents--
+
+```js
+function entropy(s) {
+
+}
+```
+
+# --solutions--
+
+```js
+function entropy(s) {
+    // Create a dictionary of character frequencies and iterate over it.
+  function process(s, evaluator) {
+    let h = Object.create(null),
+      k;
+    s.split('').forEach(c => {
+      h[c] && h[c]++ || (h[c] = 1); });
+    if (evaluator) for (k in h) evaluator(k, h[k]);
+    return h;
+  }
+    // Measure the entropy of a string in bits per symbol.
+
+  let sum = 0,
+    len = s.length;
+  process(s, (k, f) => {
+    const p = f / len;
+    sum -= p * Math.log(p) / Math.log(2);
+  });
+  return sum;
+}
+```