flow like the river

VISUALIZACION/node_modules/ngraph.random/.travis.yml

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+language: node_js
+node_js:
+  - node

VISUALIZACION/node_modules/ngraph.random/LICENSE

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+Copyright (c) 2013-2020, Andrei Kashcha
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+  Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+  Redistributions in binary form must reproduce the above copyright notice, this
+  list of conditions and the following disclaimer in the documentation and/or
+  other materials provided with the distribution.
+
+  Neither the name of the Andrei Kashcha nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
+ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

VISUALIZACION/node_modules/ngraph.random/README.md

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+ngraph.random
+=============
+
+Operation with seeded random numbers for ngraph.*.
+
+[![build status](https://secure.travis-ci.org/anvaka/ngraph.random.png)](http://travis-ci.org/anvaka/ngraph.random)
+
+Install
+=======
+
+You can use CDN:
+
+``` html
+<script src='https://cdn.jsdelivr.net/npm/ngraph.random/dist/ngraph.random.js'></script>
+```
+
+or via [npm](http://npmjs.org):
+
+```
+npm install ngraph.random
+```
+
+and then:
+
+``` js
+var ngraphRandom = require('ngraph.random);
+```
+
+Usage
+=====
+API provides random number generation, and array shuffling. 
+
+Let's start with random number generation:
+
+``` js
+// create generator, seeded with 42
+var randomGenerator = ngraphRandom(42);
+
+ // prints double number from [0..1)
+console.log(randomGenerator.nextDouble());
+
+// Get next non-negative random number, less than 100.
+console.log(randomGenerator.next(100)); // prints 20, we are seeded
+// Note: next() always expect maxValue. If you don't pass it it will return NaN.
+// This is done for performance reasons, we don't want to check input arguments
+// on each call.
+```
+
+Second part of the API is array shuffling:
+
+``` js
+var ngraphRandom = require('ngraph.random');
+
+// create "shuffling" iterator:
+var originalArray = [0, 1, 2, 3, 4, 5];
+var randomIterator = ngraphRandom.randomIterator(originalArray);
+
+// iterate over array in random order:
+randomIterator.forEach(function(x) {
+  console.log(x); // prints originalArray's items in random order
+});
+// Note: using random iterator does modify original array.
+// This is done to save memory.
+
+// If you want to re-shuffle array in-place, you can use:
+randomIterator.shuffle();
+
+// Finally if you want to have seeded shuffling you can pass optional seeded 
+// random number generator:
+var seededGenerator = ngraphRandom.random(42);
+ngraphRandom.randomIterator(originalArray, seededGenerator); 
+```
+
+
+## distributions
+
+The library supports random number generation that follow Gaussian distribution:
+
+``` js
+var generator = ngraphRandom(42);
+
+// returns a random number from a gaussian distribution with mean 0 and
+// standard deviation 1
+generator.gaussian();
+```
+
+License
+=======
+BSD 3-clause

VISUALIZACION/node_modules/ngraph.random/dist/ngraph.random.js

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+(function(f){if(typeof exports==="object"&&typeof module!=="undefined"){module.exports=f()}else if(typeof define==="function"&&define.amd){define([],f)}else{var g;if(typeof window!=="undefined"){g=window}else if(typeof global!=="undefined"){g=global}else if(typeof self!=="undefined"){g=self}else{g=this}g.ngraphRandom = f()}})(function(){var define,module,exports;return (function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s})({1:[function(require,module,exports){
+module.exports = random;
+
+// TODO: Deprecate?
+module.exports.random = random,
+module.exports.randomIterator = randomIterator
+
+/**
+ * Creates seeded PRNG with two methods:
+ *   next() and nextDouble()
+ */
+function random(inputSeed) {
+  var seed = typeof inputSeed === 'number' ? inputSeed : (+new Date());
+  return new Generator(seed)
+}
+
+function Generator(seed) {
+  this.seed = seed;
+}
+
+/**
+  * Generates random integer number in the range from 0 (inclusive) to maxValue (exclusive)
+  *
+  * @param maxValue Number REQUIRED. Omitting this number will result in NaN values from PRNG.
+  */
+Generator.prototype.next = next;
+
+/**
+  * Generates random double number in the range from 0 (inclusive) to 1 (exclusive)
+  * This function is the same as Math.random() (except that it could be seeded)
+  */
+Generator.prototype.nextDouble = nextDouble;
+
+/**
+ * Returns a random real number from uniform distribution in [0, 1)
+ */
+Generator.prototype.uniform = nextDouble;
+
+/**
+ * Returns a random real number from a Gaussian distribution
+ * with 0 as a mean, and 1 as standard deviation u ~ N(0,1)
+ */
+Generator.prototype.gaussian = gaussian;
+
+function gaussian() {
+  // use the polar form of the Box-Muller transform
+  // based on https://introcs.cs.princeton.edu/java/23recursion/StdRandom.java
+  var r, x, y;
+  do {
+    x = this.nextDouble() * 2 - 1;
+    y = this.nextDouble() * 2 - 1;
+    r = x * x + y * y;
+  } while (r >= 1 || r === 0);
+
+  return x * Math.sqrt(-2 * Math.log(r)/r);
+}
+
+/**
+ * See https://twitter.com/anvaka/status/1296182534150135808
+ */
+Generator.prototype.levy = levy;
+
+function levy() {
+  var beta = 3 / 2;
+  var sigma = Math.pow(
+      gamma( 1 + beta ) * Math.sin(Math.PI * beta / 2) / 
+        (gamma((1 + beta) / 2) * beta * Math.pow(2, (beta - 1) / 2)),
+      1/beta
+  );
+  return this.gaussian() * sigma / Math.pow(Math.abs(this.gaussian()), 1/beta);
+}
+
+// gamma function approximation
+function gamma(z) {
+  return Math.sqrt(2 * Math.PI / z) * Math.pow((1 / Math.E) * (z + 1 / (12 * z - 1 / (10 * z))), z);
+}
+
+function nextDouble() {
+  var seed = this.seed;
+  // Robert Jenkins' 32 bit integer hash function.
+  seed = ((seed + 0x7ed55d16) + (seed << 12)) & 0xffffffff;
+  seed = ((seed ^ 0xc761c23c) ^ (seed >>> 19)) & 0xffffffff;
+  seed = ((seed + 0x165667b1) + (seed << 5)) & 0xffffffff;
+  seed = ((seed + 0xd3a2646c) ^ (seed << 9)) & 0xffffffff;
+  seed = ((seed + 0xfd7046c5) + (seed << 3)) & 0xffffffff;
+  seed = ((seed ^ 0xb55a4f09) ^ (seed >>> 16)) & 0xffffffff;
+  this.seed = seed;
+  return (seed & 0xfffffff) / 0x10000000;
+}
+
+function next(maxValue) {
+  return Math.floor(this.nextDouble() * maxValue);
+}
+
+/*
+ * Creates iterator over array, which returns items of array in random order
+ * Time complexity is guaranteed to be O(n);
+ */
+function randomIterator(array, customRandom) {
+  var localRandom = customRandom || random();
+  if (typeof localRandom.next !== 'function') {
+    throw new Error('customRandom does not match expected API: next() function is missing');
+  }
+
+  return {
+    forEach: forEach,
+
+    /**
+     * Shuffles array randomly, in place.
+     */
+    shuffle: shuffle
+  };
+
+  function shuffle() {
+    var i, j, t;
+    for (i = array.length - 1; i > 0; --i) {
+      j = localRandom.next(i + 1); // i inclusive
+      t = array[j];
+      array[j] = array[i];
+      array[i] = t;
+    }
+
+    return array;
+  }
+
+  function forEach(callback) {
+    var i, j, t;
+    for (i = array.length - 1; i > 0; --i) {
+      j = localRandom.next(i + 1); // i inclusive
+      t = array[j];
+      array[j] = array[i];
+      array[i] = t;
+
+      callback(t);
+    }
+
+    if (array.length) {
+      callback(array[0]);
+    }
+  }
+}
+},{}]},{},[1])(1)
+});

VISUALIZACION/node_modules/ngraph.random/dist/ngraph.random.min.js

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+(function(f){if(typeof exports==="object"&&typeof module!=="undefined"){module.exports=f()}else if(typeof define==="function"&&define.amd){define([],f)}else{var g;if(typeof window!=="undefined"){g=window}else if(typeof global!=="undefined"){g=global}else if(typeof self!=="undefined"){g=self}else{g=this}g.ngraphRandom=f()}})(function(){var define,module,exports;return function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o<r.length;o++)s(r[o]);return s}({1:[function(require,module,exports){module.exports=random;module.exports.random=random,module.exports.randomIterator=randomIterator;function random(inputSeed){var seed=typeof inputSeed==="number"?inputSeed:+new Date;return new Generator(seed)}function Generator(seed){this.seed=seed}Generator.prototype.next=next;Generator.prototype.nextDouble=nextDouble;Generator.prototype.uniform=nextDouble;Generator.prototype.gaussian=gaussian;function gaussian(){var r,x,y;do{x=this.nextDouble()*2-1;y=this.nextDouble()*2-1;r=x*x+y*y}while(r>=1||r===0);return x*Math.sqrt(-2*Math.log(r)/r)}Generator.prototype.levy=levy;function levy(){var beta=3/2;var sigma=Math.pow(gamma(1+beta)*Math.sin(Math.PI*beta/2)/(gamma((1+beta)/2)*beta*Math.pow(2,(beta-1)/2)),1/beta);return this.gaussian()*sigma/Math.pow(Math.abs(this.gaussian()),1/beta)}function gamma(z){return Math.sqrt(2*Math.PI/z)*Math.pow(1/Math.E*(z+1/(12*z-1/(10*z))),z)}function nextDouble(){var seed=this.seed;seed=seed+2127912214+(seed<<12)&4294967295;seed=(seed^3345072700^seed>>>19)&4294967295;seed=seed+374761393+(seed<<5)&4294967295;seed=(seed+3550635116^seed<<9)&4294967295;seed=seed+4251993797+(seed<<3)&4294967295;seed=(seed^3042594569^seed>>>16)&4294967295;this.seed=seed;return(seed&268435455)/268435456}function next(maxValue){return Math.floor(this.nextDouble()*maxValue)}function randomIterator(array,customRandom){var localRandom=customRandom||random();if(typeof localRandom.next!=="function"){throw new Error("customRandom does not match expected API: next() function is missing")}return{forEach:forEach,shuffle:shuffle};function shuffle(){var i,j,t;for(i=array.length-1;i>0;--i){j=localRandom.next(i+1);t=array[j];array[j]=array[i];array[i]=t}return array}function forEach(callback){var i,j,t;for(i=array.length-1;i>0;--i){j=localRandom.next(i+1);t=array[j];array[j]=array[i];array[i]=t;callback(t)}if(array.length){callback(array[0])}}}},{}]},{},[1])(1)});

VISUALIZACION/node_modules/ngraph.random/index.js

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+module.exports = random;
+
+// TODO: Deprecate?
+module.exports.random = random,
+module.exports.randomIterator = randomIterator
+
+/**
+ * Creates seeded PRNG with two methods:
+ *   next() and nextDouble()
+ */
+function random(inputSeed) {
+  var seed = typeof inputSeed === 'number' ? inputSeed : (+new Date());
+  return new Generator(seed)
+}
+
+function Generator(seed) {
+  this.seed = seed;
+}
+
+/**
+  * Generates random integer number in the range from 0 (inclusive) to maxValue (exclusive)
+  *
+  * @param maxValue Number REQUIRED. Omitting this number will result in NaN values from PRNG.
+  */
+Generator.prototype.next = next;
+
+/**
+  * Generates random double number in the range from 0 (inclusive) to 1 (exclusive)
+  * This function is the same as Math.random() (except that it could be seeded)
+  */
+Generator.prototype.nextDouble = nextDouble;
+
+/**
+ * Returns a random real number from uniform distribution in [0, 1)
+ */
+Generator.prototype.uniform = nextDouble;
+
+/**
+ * Returns a random real number from a Gaussian distribution
+ * with 0 as a mean, and 1 as standard deviation u ~ N(0,1)
+ */
+Generator.prototype.gaussian = gaussian;
+
+function gaussian() {
+  // use the polar form of the Box-Muller transform
+  // based on https://introcs.cs.princeton.edu/java/23recursion/StdRandom.java
+  var r, x, y;
+  do {
+    x = this.nextDouble() * 2 - 1;
+    y = this.nextDouble() * 2 - 1;
+    r = x * x + y * y;
+  } while (r >= 1 || r === 0);
+
+  return x * Math.sqrt(-2 * Math.log(r)/r);
+}
+
+/**
+ * See https://twitter.com/anvaka/status/1296182534150135808
+ */
+Generator.prototype.levy = levy;
+
+function levy() {
+  var beta = 3 / 2;
+  var sigma = Math.pow(
+      gamma( 1 + beta ) * Math.sin(Math.PI * beta / 2) / 
+        (gamma((1 + beta) / 2) * beta * Math.pow(2, (beta - 1) / 2)),
+      1/beta
+  );
+  return this.gaussian() * sigma / Math.pow(Math.abs(this.gaussian()), 1/beta);
+}
+
+// gamma function approximation
+function gamma(z) {
+  return Math.sqrt(2 * Math.PI / z) * Math.pow((1 / Math.E) * (z + 1 / (12 * z - 1 / (10 * z))), z);
+}
+
+function nextDouble() {
+  var seed = this.seed;
+  // Robert Jenkins' 32 bit integer hash function.
+  seed = ((seed + 0x7ed55d16) + (seed << 12)) & 0xffffffff;
+  seed = ((seed ^ 0xc761c23c) ^ (seed >>> 19)) & 0xffffffff;
+  seed = ((seed + 0x165667b1) + (seed << 5)) & 0xffffffff;
+  seed = ((seed + 0xd3a2646c) ^ (seed << 9)) & 0xffffffff;
+  seed = ((seed + 0xfd7046c5) + (seed << 3)) & 0xffffffff;
+  seed = ((seed ^ 0xb55a4f09) ^ (seed >>> 16)) & 0xffffffff;
+  this.seed = seed;
+  return (seed & 0xfffffff) / 0x10000000;
+}
+
+function next(maxValue) {
+  return Math.floor(this.nextDouble() * maxValue);
+}
+
+/*
+ * Creates iterator over array, which returns items of array in random order
+ * Time complexity is guaranteed to be O(n);
+ */
+function randomIterator(array, customRandom) {
+  var localRandom = customRandom || random();
+  if (typeof localRandom.next !== 'function') {
+    throw new Error('customRandom does not match expected API: next() function is missing');
+  }
+
+  return {
+    forEach: forEach,
+
+    /**
+     * Shuffles array randomly, in place.
+     */
+    shuffle: shuffle
+  };
+
+  function shuffle() {
+    var i, j, t;
+    for (i = array.length - 1; i > 0; --i) {
+      j = localRandom.next(i + 1); // i inclusive
+      t = array[j];
+      array[j] = array[i];
+      array[i] = t;
+    }
+
+    return array;
+  }
+
+  function forEach(callback) {
+    var i, j, t;
+    for (i = array.length - 1; i > 0; --i) {
+      j = localRandom.next(i + 1); // i inclusive
+      t = array[j];
+      array[j] = array[i];
+      array[i] = t;
+
+      callback(t);
+    }
+
+    if (array.length) {
+      callback(array[0]);
+    }
+  }
+}

VISUALIZACION/node_modules/ngraph.random/package.json

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+{
+  "name": "ngraph.random",
+  "version": "1.1.0",
+  "description": "Operation with random numbers for ngraph.*",
+  "main": "index.js",
+  "scripts": {
+    "test": "tap test/*.js",
+    "build": "browserify index.js -s ngraphRandom -o dist/ngraph.random.js && uglifyjs dist/ngraph.random.js -o dist/ngraph.random.min.js"
+  },
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/anvaka/ngraph.random.git"
+  },
+  "keywords": [
+    "ngraph",
+    "ngraphjs"
+  ],
+  "author": "Andrei Kashcha",
+  "license": "BSD-3-Clause",
+  "bugs": {
+    "url": "https://github.com/anvaka/ngraph.random/issues"
+  },
+  "devDependencies": {
+    "benchmark": "^2.1.2",
+    "seedrandom": "^2.4.2",
+    "uglify-js": "^3.10.0",
+    "tap": "^14.10.8"
+  }
+}

VISUALIZACION/node_modules/ngraph.random/perf/index.js

@@ -0,0 +1,46 @@
+var random = require('../').random(42)
+var seedrandom = require('seedrandom');
+
+var alea = seedrandom.alea(42);
+var xor128 = seedrandom.xor128(42);
+
+var Benchmark = require('benchmark');
+var suite = new Benchmark.Suite;
+var testCount = 200;
+var randomNumbers = [];
+
+// add tests
+suite.add('Native Math.random()', function() {
+  var sum = 0;
+  for (var i = 0; i < testCount; ++i) {
+    sum += Math.random();
+  }
+  randomNumbers.push(sum);
+}).add('ngraph.random', function() {
+  var sum = 0;
+  for (var i = 0; i < testCount; ++i) {
+    sum += random.nextDouble()
+  }
+  randomNumbers.push(sum);
+})
+.add('xor128', function() {
+  var sum = 0;
+  for (var i = 0; i < testCount; ++i) {
+    var res = xor128.double();
+    sum += res
+  }
+  randomNumbers.push(sum);
+})
+.add('alea', function() {
+  var sum = 0;
+  for (var i = 0; i < testCount; ++i) {
+    var res = alea.double();
+    sum += res
+  }
+  randomNumbers.push(sum);
+})
+.on('cycle', function(event) {
+  randomNumbers = [];
+  console.log(String(event.target));
+})
+.run();

VISUALIZACION/node_modules/ngraph.random/test/random.js

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+var test = require('tap').test,
+    randomAPI = require('..');
+
+test('random iterator returns all items', function (t) {
+    var a = [1, 2, 3, 4, 5, 6],
+        aCopy = a.map(function (i) { return i; }),
+        shuffle = randomAPI.randomIterator(aCopy),
+        iterated = [];
+
+    shuffle.forEach(function (i) {
+        iterated.push(i);
+        t.ok(a.indexOf(i) !== -1, 'Shuffle iterator should return only items from original array. Passed ' + i);
+    });
+
+    t.ok(iterated.length === a.length, 'Number of iterated items does not match number of original array items');
+    t.end();
+});
+
+test('Same seed gives same values', function (t) {
+  var random1 = randomAPI.random(42);
+  var random2 = randomAPI.random(42);
+
+  t.equal(random1.next(100), random2.next(100), "Same seed should give same values");
+  t.end();
+});
+
+test('it can generate gaussian', function (t) {
+    var random = randomAPI.random(42);
+    t.ok(typeof random.gaussian() === 'number', 'number generated');
+    t.end();
+});
+
+test('can use function syntax', function (t) {
+  var random1 = randomAPI(42);
+  var random2 = randomAPI.random(42);
+
+  t.equal(random1.nextDouble(), random2.nextDouble(), "Same seed should give same values");
+  t.end();
+});