feat(number): add distributor functions

scripts/apidocs/utils/markdown.ts

@@ -26,13 +26,22 @@ const htmlSanitizeOptions: sanitizeHtml.IOptions = {
     'span',
     'strong',
     'ul',
+    'table',
+    'thead',
+    'tbody',
+    'tr',
+    'th',
+    'td',
   ],
   allowedAttributes: {
     a: ['href', 'target', 'rel'],
     button: ['class', 'title'],
     div: ['class'],
     pre: ['class', 'v-pre', 'tabindex'],
     span: ['class', 'style'],
+    table: ['tabindex'],
+    th: ['style'],
+    td: ['style'],
   },
   selfClosing: [],
 };

src/modules/number/index.ts

@@ -534,4 +534,165 @@ export class NumberModule extends SimpleModuleBase {
 
     return result;
   }
+
+  /**
+   * Generates a random number between `min` and `max` using an exponential distribution.
+   * The lower bound is inclusive, but the upper bound is exclusive.
+   *
+   * The following table shows the rough distribution of values generated using `Math.floor(exponentialDistribution({ min: 0, max: 10, base: x }))`:
+   *
+   * | Value | Base 0.1 | Base 0.5 | Base 1 | Base 2 | Base 10 |
+   * | :---: | -------: | -------: | -----: | -----: | ------: |
+   * |   0   |     4.1% |     7.4% |  10.0% |  13.8% |   27.8% |
+   * |   1   |     4.5% |     7.8% |  10.0% |  12.5% |   16.9% |
+   * |   2   |     5.0% |     8.2% |  10.0% |  11.5% |   12.1% |
+   * |   3   |     5.7% |     8.7% |  10.0% |  10.7% |    9.4% |
+   * |   4   |     6.6% |     9.3% |  10.0% |  10.0% |    7.8% |
+   * |   5   |     7.8% |     9.9% |  10.0% |   9.3% |    6.6% |
+   * |   6   |     9.4% |    10.7% |  10.0% |   8.8% |    5.7% |
+   * |   7   |    12.1% |    11.5% |  10.0% |   8.2% |    5.0% |
+   * |   8   |    16.9% |    12.6% |  10.0% |   7.8% |    4.5% |
+   * |   9   |    27.9% |    13.8% |  10.0% |   7.5% |    4.1% |
+   *
+   * The following table shows the rough distribution of values generated using `Math.floor(exponentialDistribution({ min: 0, max: 10, bias: x }))`:
+   *
+   * | Value | Bias -9 | Bias -1 | Bias 0 | Bias 1 | Bias 9 |
+   * | :---: | ------: | ------: | -----: | -----: | -----: |
+   * |   0   |   27.9% |   13.7% |  10.0% |   7.4% |   4.1% |
+   * |   1   |   16.9% |   12.5% |  10.0% |   7.8% |   4.5% |
+   * |   2   |   12.1% |   11.6% |  10.0% |   8.3% |   5.1% |
+   * |   3   |    9.5% |   10.7% |  10.0% |   8.8% |   5.7% |
+   * |   4   |    7.8% |   10.0% |  10.0% |   9.3% |   6.6% |
+   * |   5   |    6.6% |    9.3% |  10.0% |   9.9% |   7.7% |
+   * |   6   |    5.7% |    8.8% |  10.0% |  10.7% |   9.5% |
+   * |   7   |    5.0% |    8.2% |  10.0% |  11.5% |  12.1% |
+   * |   8   |    4.5% |    7.8% |  10.0% |  12.6% |  16.8% |
+   * |   9   |    4.1% |    7.4% |  10.0% |  13.7% |  27.9% |
+   *
+   * @param options The options for generating the number.
+   * @param options.min The minimum value to generate (inclusive). Defaults to `0`.
+   * @param options.max The maximum value to generate (exclusive). Defaults to `1`.
+   * @param options.base The base of the exponential distribution. Should be greater than `0`. Defaults to `2`.
+   *
+   * The higher/more above `1` the `base`, the more likely the number will be closer to the minimum value.
+   * The lower/closer to zero the base, the more likely the number will be closer to the maximum value.
+   * Values of `1` will generate a uniform distribution.
+   * The following table shows the rough distribution of values generated using `Math.floor(exponentialDistribution({ min: 0, max: 10, base: x }))`:
+   *
+   * | Value | Base 0.1 | Base 0.5 | Base 1 | Base 2 | Base 10 |
+   * | :---: | -------: | -------: | -----: | -----: | ------: |
+   * |   0   |     4.1% |     7.4% |  10.0% |  13.8% |   27.8% |
+   * |   1   |     4.5% |     7.8% |  10.0% |  12.5% |   16.9% |
+   * |   2   |     5.0% |     8.2% |  10.0% |  11.5% |   12.1% |
+   * |   3   |     5.7% |     8.7% |  10.0% |  10.7% |    9.4% |
+   * |   4   |     6.6% |     9.3% |  10.0% |  10.0% |    7.8% |
+   * |   5   |     7.8% |     9.9% |  10.0% |   9.3% |    6.6% |
+   * |   6   |     9.4% |    10.7% |  10.0% |   8.8% |    5.7% |
+   * |   7   |    12.1% |    11.5% |  10.0% |   8.2% |    5.0% |
+   * |   8   |    16.9% |    12.6% |  10.0% |   7.8% |    4.5% |
+   * |   9   |    27.9% |    13.8% |  10.0% |   7.5% |    4.1% |
+   *
+   * Can alternatively be configured using the `bias` option. `base` takes precedence over `bias`.
+   * @param options.bias An alternative way to specify the `base`. Also accepts values below zero.
+   *
+   * The higher/more positive the `bias`, the more likely the number will be closer to the maximum value.
+   * The lower/more negative the `bias`, the more likely the number will be closer to the minimum value.
+   * Values of 0 will generate a uniform distribution.
+   *
+   * The following table shows the rough distribution of values generated using `Math.floor(exponentialDistribution({ min: 0, max: 10, bias: x }))`:
+   *
+   * | Value | Bias -9 | Bias -1 | Bias 0 | Bias 1 | Bias 9 |
+   * | :---: | ------: | ------: | -----: | -----: | -----: |
+   * |   0   |   27.9% |   13.7% |  10.0% |   7.4% |   4.1% |
+   * |   1   |   16.9% |   12.5% |  10.0% |   7.8% |   4.5% |
+   * |   2   |   12.1% |   11.6% |  10.0% |   8.3% |   5.1% |
+   * |   3   |    9.5% |   10.7% |  10.0% |   8.8% |   5.7% |
+   * |   4   |    7.8% |   10.0% |  10.0% |   9.3% |   6.6% |
+   * |   5   |    6.6% |    9.3% |  10.0% |   9.9% |   7.7% |
+   * |   6   |    5.7% |    8.8% |  10.0% |  10.7% |   9.5% |
+   * |   7   |    5.0% |    8.2% |  10.0% |  11.5% |  12.1% |
+   * |   8   |    4.5% |    7.8% |  10.0% |  12.6% |  16.8% |
+   * |   9   |    4.1% |    7.4% |  10.0% |  13.7% |  27.9% |
+   *
+   * This option is ignored if `base` is specified.
+   *
+   * Defaults to `-1`.
+   *
+   * @throws If `base` is less than or equal to `0`.
+   * @throws If `max` is less than `min`.
+   *
+   * @example
+   * faker.number.exponentialDistribution() // 0.41928964795957224
+   * faker.number.exponentialDistribution(10) // 1.656598169056771
+   * faker.number.exponentialDistribution({ min: 10, max: 100 }) // 88.7273250669911
+   * faker.number.exponentialDistribution({ min: 0, max: 100, base: 10 }) // 6.9442760672808745
+   * faker.number.exponentialDistribution({ min: 0, max: 100, bias: 10 }) // 67.03715679154617
+   *
+   * @since 9.5.0
+   */
+  exponentialDistribution(
+    options:
+      | number
+      | {
+          /**
+           * The minimum value to generate (inclusive).
+           *
+           * @default 0
+           */
+          min?: number;
+          /**
+           * The maximum value to generate (exclusive).
+           *
+           * @default 1
+           */
+          max?: number;
+          /**
+           * The base of the exponential distribution. Should be greater than 0. Defaults to `2`.
+           * The higher/more above `1` the `base`, the more likely the number will be closer to the minimum value.
+           * The lower/closer to zero the `base`, the more likely the number will be closer to the maximum value.
+           * Values of `1` will generate a uniform distribution.
+           * Can alternatively be configured using the `bias` option. `base` takes precedence over `bias`.
+           *
+           * @default 2
+           */
+          base?: number;
+          /**
+           * An alternative way to specify the `base`. Also accepts values below zero.
+           * The higher/more positive the `bias`, the more likely the number will be closer to the maximum value.
+           * The lower/more negative the `bias`, the more likely the number will be closer to the minimum value.
+           * Values of `0` will generate a uniform distribution.
+           * This option is ignored if `base` is specified.
+           *
+           * @default -1
+           */
+          bias?: number;
+        } = {}
+  ): number {
+    if (typeof options === 'number') {
+      options = { min: 0, max: options };
+    }
+
+    const {
+      min = 0,
+      max = 1,
+      bias = -1,
+      base = bias <= 0 ? -bias + 1 : 1 / (bias + 1),
+    } = options;
+
+    if (base === 1) {
+      return this.faker.number.float({ min, max });
+    } else if (base <= 0) {
+      throw new FakerError('Base should be greater than 0.');
+    }
+
+    if (max === min) {
+      return min;
+    } else if (max < min) {
+      throw new FakerError(`Max ${max} should be greater than min ${min}.`);
+    }
+
+    const exponent = this.faker.number.float();
+    const factor = (base ** exponent - 1) / (base - 1);
+    return min + (max - min) * factor;
+  }
 }

test/modules/__snapshots__/number.spec.ts.snap

@@ -20,6 +20,20 @@ exports[`number > 42 > binary > with options 1`] = `"100"`;
 
 exports[`number > 42 > binary > with value 1`] = `"0"`;
 
+exports[`number > 42 > exponentialDistribution > noArgs 1`] = `0.29642623304954707`;
+
+exports[`number > 42 > exponentialDistribution > with high base 1`] = `0.15209599448489752`;
+
+exports[`number > 42 > exponentialDistribution > with high bias 1`] = `0.6420630212280508`;
+
+exports[`number > 42 > exponentialDistribution > with low base 1`] = `0.6420630212280508`;
+
+exports[`number > 42 > exponentialDistribution > with low bias 1`] = `0.15209599448489752`;
+
+exports[`number > 42 > exponentialDistribution > with max 1`] = `2.9642623304954707`;
+
+exports[`number > 42 > exponentialDistribution > with min and max 1`] = `36.67836097445924`;
+
 exports[`number > 42 > float > with max 1`] = `25.84326820046801`;
 
 exports[`number > 42 > float > with min 1`] = `-25.89477488956341`;
@@ -84,6 +98,20 @@ exports[`number > 1211 > binary > with options 1`] = `"1010"`;
 
 exports[`number > 1211 > binary > with value 1`] = `"1"`;
 
+exports[`number > 1211 > exponentialDistribution > noArgs 1`] = `0.9033226590337899`;
+
+exports[`number > 1211 > exponentialDistribution > with high base 1`] = `0.8313808279511881`;
+
+exports[`number > 1211 > exponentialDistribution > with high bias 1`] = `0.9801213540567579`;
+
+exports[`number > 1211 > exponentialDistribution > with low base 1`] = `0.9801213540567579`;
+
+exports[`number > 1211 > exponentialDistribution > with low bias 1`] = `0.8313808279511881`;
+
+exports[`number > 1211 > exponentialDistribution > with max 1`] = `9.0332265903379`;
+
+exports[`number > 1211 > exponentialDistribution > with min and max 1`] = `91.29903931304109`;
+
 exports[`number > 1211 > float > with max 1`] = `64.06789061927832`;
 
 exports[`number > 1211 > float > with min 1`] = `-2.0736333821888806`;
@@ -148,6 +176,20 @@ exports[`number > 1337 > binary > with options 1`] = `"10"`;
 
 exports[`number > 1337 > binary > with value 1`] = `"0"`;
 
+exports[`number > 1337 > exponentialDistribution > noArgs 1`] = `0.1991604233570674`;
+
+exports[`number > 1337 > exponentialDistribution > with high base 1`] = `0.092022676113987`;
+
+exports[`number > 1337 > exponentialDistribution > with high bias 1`] = `0.5033501285097729`;
+
+exports[`number > 1337 > exponentialDistribution > with low base 1`] = `0.5033501285097729`;
+
+exports[`number > 1337 > exponentialDistribution > with low bias 1`] = `0.092022676113987`;
+
+exports[`number > 1337 > exponentialDistribution > with max 1`] = `1.991604233570674`;
+
+exports[`number > 1337 > exponentialDistribution > with min and max 1`] = `27.924438102136065`;
+
 exports[`number > 1337 > float > with max 1`] = `18.079702576075135`;
 
 exports[`number > 1337 > float > with min 1`] = `-30.73293897432999`;

test/modules/number.spec.ts

@@ -65,6 +65,16 @@ describe('number', () => {
         .it('with max as 3999', { max: 3999 })
         .it('with min and max', { min: 100, max: 502 });
     });
+
+    t.describe('exponentialDistribution', (t) => {
+      t.it('noArgs')
+        .it('with max', 10)
+        .it('with low base', { base: 0.1 })
+        .it('with high base', { base: 10 })
+        .it('with low bias', { bias: -9 })
+        .it('with high bias', { bias: 9 })
+        .it('with min and max', { min: 10, max: 100 });
+    });
   });
 
   describe(`random seeded tests for seed ${faker.seed()}`, () => {
@@ -697,6 +707,108 @@ describe('number', () => {
         }).toThrow(new FakerError('Max 100 should be greater than min 500.'));
       });
     });
+
+    describe('exponentialDistribution', () => {
+      it('should generate a number between 0 and 1 by default', () => {
+        const actual = faker.number.exponentialDistribution();
+        expect(actual).toBeTypeOf('number');
+        expect(actual).toBeGreaterThanOrEqual(0);
+        expect(actual).toBeLessThan(1);
+      });
+
+      it('should generate a number between 0 and 10', () => {
+        const actual = faker.number.exponentialDistribution(10);
+        expect(actual).toBeTypeOf('number');
+        expect(actual).toBeGreaterThanOrEqual(0);
+        expect(actual).toBeLessThan(10);
+      });
+
+      it('should generate a number between 10 and 100', () => {
+        const actual = faker.number.exponentialDistribution({
+          min: 10,
+          max: 100,
+        });
+        expect(actual).toBeTypeOf('number');
+        expect(actual).toBeGreaterThanOrEqual(10);
+        expect(actual).toBeLessThan(100);
+      });
+
+      it('should generate a number with low base', () => {
+        const results = Array.from({ length: 10 }, (_, i) => i);
+        for (let i = 0; i < 1000; i++) {
+          results[
+            Math.floor(
+              faker.number.exponentialDistribution({ max: 10, base: 0.1 })
+            )
+          ]++;
+        }
+
+        expect(results[0]).toBeLessThan(75);
+        expect(results[9]).toBeGreaterThan(200);
+      });
+
+      it('should generate a number with high base', () => {
+        const results = Array.from({ length: 10 }, (_, i) => i);
+        for (let i = 0; i < 1000; i++) {
+          results[
+            Math.floor(
+              faker.number.exponentialDistribution({ max: 10, base: 10 })
+            )
+          ]++;
+        }
+
+        expect(results[0]).toBeGreaterThan(200);
+        expect(results[9]).toBeLessThan(75);
+      });
+
+      it('should generate a number with low bias', () => {
+        const results = Array.from({ length: 10 }, (_, i) => i);
+        for (let i = 0; i < 1000; i++) {
+          results[
+            Math.floor(
+              faker.number.exponentialDistribution({ max: 10, bias: -9 })
+            )
+          ]++;
+        }
+
+        expect(results[0]).toBeGreaterThan(200);
+        expect(results[9]).toBeLessThan(75);
+      });
+
+      it('should generate a number with high bias', () => {
+        const results = Array.from({ length: 10 }, (_, i) => i);
+        for (let i = 0; i < 1000; i++) {
+          results[
+            Math.floor(
+              faker.number.exponentialDistribution({ max: 10, bias: 9 })
+            )
+          ]++;
+        }
+
+        expect(results[0]).toBeLessThan(75);
+        expect(results[9]).toBeGreaterThan(200);
+      });
+    });
+
+    it('should throw when min > max', () => {
+      const min = 10;
+      const max = 9;
+
+      expect(() => {
+        faker.number.exponentialDistribution({ min, max });
+      }).toThrow(
+        new FakerError(`Max ${max} should be greater than min ${min}.`)
+      );
+    });
+
+    it('should throw when base is less than or equal to 0', () => {
+      expect(() => {
+        faker.number.exponentialDistribution({ base: 0 });
+      }).toThrow(new FakerError('Base should be greater than 0.'));
+      expect(() => {
+        faker.number.exponentialDistribution({ base: -1 });
+      }).toThrow(new FakerError('Base should be greater than 0.'));
+    });
   });
 
   describe('value range tests', () => {

test/scripts/apidocs/__snapshots__/verify-jsdoc-tags.spec.ts.snap

@@ -329,6 +329,7 @@ exports[`check docs completeness > all modules and methods are present 1`] = `
     [
       "bigInt",
       "binary",
+      "exponentialDistribution",
       "float",
       "hex",
       "int",