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\n\n\n![\"\"/](\"https://david-dm.org/rse/mostlikely.png\")
\n\nInstallation\n------------\n\n```shell\n$ npm install mostlikely\n```\n\nAbout\n-----\n\nMostLikely is a library for JavaScript (for use in the Node and Browser\nenvironment), providing a space-efficient probabilistic data structure\nthat can be used to test whether an element is a member of a set. False\npositive matches are possible, but false negatives are not, i.e., a\nquery returns either \"possibly in set\" (within a configured error rate)\nor \"definitely not in set\" (with a 100% accuracy).\n\nInternally, MostLikely is based on a [Bloom\nFilter](https://en.wikipedia.org/wiki/Bloom_filter), which in turn is\nbased on multiple non-cryptographically hash functions and a bit-field.\nThe essential point of Bloom Filters and hence MostLikely is that it is\na very space-efficient data-structure for representing a set.\n\nThe distinct features of MostLikely (compared to standard Bloom Filter\nimplementations) are:\n\n- optionally supports element removal operation through a counting Bloom filter variant,\n- derives its required hash functions from a full set of distinct hash functions (MurmurHash3, Jenkins, CRC32, DJBX33X and FNV),\n- supports exporting/importing through Run-Length Encoding (RLE) compression and Base16/Z85 encoding,\n- is a standalone/dependency-free implementation and\n- supports both Node and Browser run-time environments.\n\nExample\n-------\n\n```js\n/* use MostLikely */\nimport MostLikely from \"mostlikely\"\n\n/* use Pure-UUID and Chai (just for test-driving) */\nimport UUID from \"pure-uuid\"\nimport Chai from \"chai\"\n\n/* configure the expectations */\nconst [ itemCount, errorRate, worstErrorRate ] = [ 1000, 0.005, 0.010 ]\n\n/* create a new set */\nconst ml = new MostLikely(itemCount, errorRate)\n\n/* create 1000 positive test elements and insert them into the set */\nlet uuids1 = {}\nfor (let i = 0; i < itemCount; i++) {\n uuids1[i] = new UUID(1)\n ml.insert(uuids1[i], 16)\n}\n\n/* create 1000 negative test elements (which are NOT inserted into the set) */\nlet uuids2 = {}\nfor (let i = 0; i < itemCount; i++)\n uuids2[i] = new UUID(1)\n\n/* check our expectations */\nlet [ err1, err2 ] = [ 0, 0 ]\nfor (let i = 0; i < itemCount; i++) {\n if (!ml.contains(uuids1[i], 16)) err1++\n if ( ml.contains(uuids2[i], 16)) err2++\n}\nChai.expect(err1 / itemCount).to.be.equal(0)\nChai.expect(err2 / itemCount).to.be.most(worstErrorRate)\n```\n\nApplication Programming Interface\n---------------------------------\n\nMostLikely provides the following API:\n\n- `MostLikely::new(itemCount?: Number = 1000000, errorRate?: Number = 0.005, mask?: Boolean = true, counter?: Boolean = true): MostLikely`:
\n Creates a new MostLikely set, intended for an expected number of\n `itemCount` items, an expected \"false positive\" error rate `errorRate`\n and internally using a `mask`-based bit-field and/or a `counter`-based\n bit-field.\n\n- `MostLikely::export(type?: String = \"rle+z85\"): Object`:
\n Export the MostLikely set into a JSON-encodable object. The returned object\n is of the following type: `{ bits: Number, hashes: Number, mask?:\n String, cntr?: String }`. The `bits` is the number of bits the\n `mask` bit-field contains (the `cntr` bit-field contains `bits * 4`\n bits instead). The `hashes` is the number of distinct hashes which\n are used. The `mask` (if present) is the encoded (and optionally\n compressed) bit-field of `bits` number of bits. The `cntr` (if\n present) is the encoded (and optionally compressed) bit-field of `bits\n * 4` number of bits.\n\n- `MostLikely::import(obj: Object, type?: String = \"rle+z85\"): MostLikely`:
\n Import the MostLikely set from a (previously exported) JSON-encodable object.\n\n- `MostLikely::format(type?: String = \"rle+z85\"): String`:
\n Format the MostLikely set into a network transmitable string representation.\n\n- `MostLikely::parse(str: String, type?: String = \"rle+z85\"): MostLikely`:
\n Parse the MostLikely set from a (previously formatted) network transmitable string representation.\n\n- `MostLikely::insert(data: any[], size?: Number = data.length): MostLikely`:
\n Insert an element into the MostLikely set. The element has to be an\n `Array`-like data structure (usually either a real `Array`, a typed\n array like `Uint8Array` or a `String`).\n\n- `MostLikely::remove(data: any[], size?: Number = data.length): MostLikely`:
\n Remove an element from the MostLikely set. The element has to be an\n `Array`-like data structure (usually either a real `Array`, a typed\n array like `Uint8Array` or a `String`). This operation requires\n the MostLikely set to be instanciated with `counter` enabled.\n\n- `MostLikely::contains(data: any[], size?: Number = data.length): Boolean`:
\n Checks whether an element was inserted into the MostLikely set. The\n element has to be an `Array`-like data structure (usually either a\n real `Array`, a typed array like `Uint8Array` or a `String`). If\n this function returns `false`, you can be 100% sure the element was\n not inserted into the set. If this function returns `true` it is\n most-likely the element was inserted into the set, but it can be also\n a false positive (expected to happen only with a probability of the\n configured `errorRate`). In other words: on `errorRate=0.005` you have\n to expect that this function returns `true` in 5% of all cases even\n for elements which were NOT inserted into the set.\n\n- `MostLikely::clear(): MostLikely`:
\n Removes all previously inserted elements from the MostLikely set.\n\nImplementation Notice\n---------------------\n\nAlthough MostLikely is written in ECMAScript 6, it is transpiled to\nECMAScript 5 and this way runs in really all(!) current (as of 2016)\nJavaScript environments, of course.\n\nAdditionally, there are two transpilation results: first, there\nis `mostlikely.browser.js` for Browser environments. This is a\nsize-compressed variant. Second, there is `mostlikely.node.js` for\nNode.js/IO.js environments. This is a variant without compression.\n\nLicense\n-------\n\nCopyright (c) 2016-2023 Dr. Ralf S. Engelschall (http://engelschall.com/)\n\nPermission is hereby granted, free of charge, to any person obtaining\na copy of this software and associated documentation files (the\n\"Software\"), to deal in the Software without restriction, including\nwithout limitation the rights to use, copy, modify, merge, publish,\ndistribute, sublicense, and/or sell copies of the Software, and to\npermit persons to whom the Software is furnished to do so, subject to\nthe following conditions:\n\nThe above copyright notice and this permission notice shall be included\nin all copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\nEXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\nMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\nIN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\nCLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\nTORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\nSOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\n","maintainers":[{"name":"rse","email":"rse@engelschall.com"}],"time":{"modified":"2023-01-17T16:40:08.450Z","created":"2016-04-16T22:29:49.194Z","0.9.0":"2016-04-16T22:29:49.194Z","0.9.1":"2016-04-16T22:31:01.441Z","0.9.2":"2016-04-24T16:50:36.577Z","0.9.3":"2016-05-19T21:54:00.232Z","0.9.4":"2016-06-25T21:28:30.282Z","0.9.5":"2016-11-20T14:56:46.517Z","0.9.6":"2017-04-10T18:58:23.203Z","0.9.7":"2017-04-29T20:27:28.271Z","0.9.8":"2017-06-03T22:42:30.641Z","0.9.9":"2017-07-27T09:49:31.133Z","1.0.0":"2017-09-06T18:51:13.697Z","1.0.1":"2017-09-06T18:54:21.387Z","1.0.2":"2017-12-02T20:15:44.811Z","1.0.3":"2018-03-26T20:16:48.309Z","1.0.4":"2018-03-30T16:37:46.251Z","1.0.5":"2018-04-06T21:28:44.817Z","1.0.6":"2018-04-22T21:54:03.031Z","1.0.7":"2018-05-11T19:12:26.777Z","1.0.8":"2018-06-15T21:42:02.281Z","1.1.0":"2018-06-16T12:48:04.602Z","1.2.0":"2018-06-16T23:45:31.384Z","1.2.1":"2018-06-23T14:43:38.950Z","1.2.2":"2018-07-07T09:17:57.320Z","1.2.3":"2018-08-10T19:25:47.487Z","1.3.0":"2018-12-22T17:26:28.016Z","1.3.1":"2019-06-16T08:19:26.864Z","1.3.2":"2019-12-22T11:02:00.400Z","1.3.3":"2020-10-11T09:01:52.016Z","1.3.4":"2021-01-08T22:54:06.953Z","1.3.5":"2023-01-17T16:40:08.362Z"},"homepage":"https://github.com/rse/mostlikely","keywords":["most-likely","classification","bloom","filter"],"repository":{"type":"git","url":"git+https://github.com/rse/mostlikely.git"},"author":{"name":"Dr. Ralf S. Engelschall","email":"rse@engelschall.com","url":"http://engelschall.com"},"bugs":{"url":"https://github.com/rse/mostlikely/issues"},"license":"MIT","readmeFilename":"README.md"}