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36 lines
3.2 KiB
JSON
36 lines
3.2 KiB
JSON
{
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"name": "random-weighted-choice",
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"version": "0.1.1",
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"engines": {
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"node": "*"
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},
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"author": {
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"name": "François Parmentier"
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},
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"main": "lib/random-weighted-choice.js",
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"readmeFilename": "README.md",
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"description": "Node.js module to make a random choice among weighted elements of table.",
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"dependencies": {
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"debug": "0.7.x"
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},
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"devDependencies": {
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"mocha": "1.7.x"
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},
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"scripts": {
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"test": "make test"
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},
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"homepage": "http://github.com/parmentf/random-weighted-choice",
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"repository": {
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"type": "git",
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"url": "https://github.com/parmentf/random-weighted-choice.git"
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},
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"keywords": [
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"random",
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"weighted"
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],
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"license": "BSD",
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"readme": "# Random Weighted Choice\n\n[](http://travis-ci.org/parmentf/random-weighted-choice)\n\nNode.js module to make a random choice among weighted elements of table.\n\n## Installation\n\nWith [npm](http://npmjs.org) do:\n\n $ npm install random-weighted-choice\n\n\n## Examples\n\nAlthough you can add several times the same id\n\n var rwc = require('random-weighted-choice');\n var table = [\n { weight: 1, id: \"item1\"} // Element 1\n , { weight: 1, id: \"item2\"} // Element 2\n , { weight: 4, id: \"item3\"} // Element with a 4 times likelihood\n , { weight: 2, id: \"item1\"} // Element 1, weight added with 2 => 3\n ];\n var choosenItem = rwc(table);\n var choosenUnlikely = rwc(table, 100); // The last shall be first\n var choosenDeterministically = rwc(table, 0);\n\nIt is better to not use the same twice, if you want a temperature other than\nthe default one (50).\n\n var rwc = require('random-weighted-choice');\n var table = [\n { weight: 1, id: \"item1\"} // Element 1\n , { weight: 1, id: \"item2\"} // Element 2\n , { weight: 4, id: \"item3\"} // Element with a 4 times likelihood\n , { weight: 2, id: \"item4\"} // Element 4\n , { weight: 2, id: \"item5\"}\n ];\n var choosenItem = rwc(table);\n var choosenUnlikely = rwc(table, 100); // The last shall be first\n var choosenDeterministically = rwc(table, 0);\n\nWithout temperature (second parameter) or a 50 value, likelihoods are:\n\n { item1: 10%, item2: 10%, item3: 40%, item4: 20%, item5: 20% }\n\nWith a temperature value of 100:\n\n { item1: 30%, item2: 30%, item3: 0%, item4: 20%, item5: 20% }\n\nWith a temperature value of 0, modified weights are:\n\n { item1: 0, item2: 0, item3: 8, item4: 2, item5: 2 }\n\n## Usage\n\n### random-weighted-choice(Array table, Number temperature = 50)\n\nReturn the ``id`` of the chosen item from ``table``.\n\nThe ``table`` parameter should contain an Array. Each item of that Array must\nbean object, with at least ``weight`` and ``id`` property.\n\nWeight values are relative to each other. They are integers.\n\nWhen the sum of the weight values is ``null``, ``null`` is returned (can't choose).\n\nWhen the Array is empty, ``null`` is returned.\n\nMore explanations on how it works on [Everything2](http://everything2.com/title/Blackboard+temperature).\n\n## Also\n\n* https://github.com/Schoonology/weighted",
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"_id": "random-weighted-choice@0.1.1",
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"_from": "random-weighted-choice"
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}
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