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metrics\n* Levenshtein Distance\n\n------------------------------------------------------------\n\n## Data Analysis\n\nReal time metrics which are recalculated on single of data point and posted in msg.result.\nKey and value can be selected from msg.payload. Includes lag (seasonal) along with delta(defference).\nSending message with topic\"@stats\" places message with all stats on second port.\nIf realtime metrics then a third port is shown where the message is sent if it is an outlier\nbeing outside 3 standard deviations from mean. This can be changed to median and number of deviations.\n\n![Data Analysis Realtime](documentation/DataAnalysisRealtime.JPG \"Data Analysis Realtime\")\n![Data Analysis Pearson R](documentation/DataAnalysisPearsonR.JPG \"Data Analysis Pearson R\")\n\nA set of data analysis functions that can be run over an array of data\n\nSingle value metrics:\n\n* Autocorrelation\n* Autocovariance\n* Average/Mean\n* Maximum\n* Median\n* Minimum\n* Range\n* Standard Deviation\n* Skewness\n* Sum\n* Variance\n\nArray metrics:\n\n* Deltas\n* Deltas Normalised\n* difference\n* difference seasonal\n* difference seasonal second order\n* Moving Average Simple (SMA)\n* Moving Average Cumulative (CMA)\n* Moving Average Weighted (WMA)\n* Moving Average Exponential (EMA/EWMA)\n* Normalise\n* Standardization (Z-score Normalization)\n\nArray data\n\n* distances\n* distance(s) minimum between points\n* distance(s) maximum between points\n\n![Data Analysis](documentation/DataAnalysis.JPG \"Data Analysis\")\n\nexample:\n\n![Data Analysis Realtime example](documentation/DataAnalysisTestRealtime.JPG \"Data Analysis Realtime example\")\n\n![Data Analysis Pearson R example](documentation/DataAnalysisTestPearsonR.JPG \"Data Analysis PearsonR example\")\n\n![Data Analysis example](documentation/DataAnalysisTest.JPG \"Data Analysis example\")\n\n------------------------------------------------------------\n\n## logistic regression\n\nPerform logistic regression by setting up model with fit then using the model in other nodes to do prediction probability or class\n------------------------------------------------------------\n\n## columnar store\n\nStore data into a columnar store with sql select access\n\n------------------------------------------------------------\n\n## Matrix\n\nDefine a matrix and perform various functions\n\n* Define / Define Empty / Create / Create Like/ clone\n* Add / Add Row to Row / Add to Cell / Add Row / Subtract Cell\n* Multiple / Multiple Cell / Divide Cell / Divide Row\n* Transpose\n* Adjoint\n* Cofactor\n* Complement Minor\n* Identity\n* Inverse\n* Determinant\n* Backward Substitution\n* Forward Elimination\n* Gaussian Elimination\n* Reduced Row EchelonForm\n* Row Echelon Form\n* Nearly Equals / Is Square / Get Cell\n* Sum Row\n* Swap Rows\n* To Array Object\n\n![Matrix](documentation/matrix.jpg \"Matrix\")\n\n------------------------------------------------------------\n\n## Transform\n\nTranslates a selected msg property to a target property.\nMessages generates a message for each row or record.\n\nTransformations:\n\n* Array to\n  * CSV\n  * HTML\n  * ISO8385\n  * Messages\n  * xlsx / xlsx object (excel uses [xlsx][7])  \n* AVRO to JSON (uses [avsc][6])\n* Buffer to compressed\n* Confluence to JSON\n* Compressed to\n  * Buffer\n  * String\n  * JSON\n* CSV to\n  * Array\n  * HTML\n  * Messages\n* CSVWithHeader to\n  * Array\n  * HTML\n  * JSON\n* Date to\n  * is between\n  * ISO string\n  * locale string\n  * range limit\n* ISO8385 to Array\n* ISO8385 to JSON\n* JSON to\n  * Array\n  * Confluence\n  * CSV\n  * AVRO (uses [avsc][6])\n  * ISO8385\n  * Messages\n  * String\n  * xlsx / xlsx object (excel uses [xlsx][7])  \n  * XML (uses [fast-xml-parser][4])\n* Number\n  * is between\n  * range limit\n* path\n  * Basename\n  * Dirname\n  * Extname\n  * Format\n  * Is Absolute\n  * Join\n  * Parse\n  * Normalize\n  * Resolve\n* snappy compress (uses [snappy][5], must install separately)\n* snappy uncompress (uses [snappy][5], must install separately)\n* String to\n  * Append\n  * Array By Delimiter\n  * At\n  * Camelize\n  * Capitalize\n  * Compressed\n  * Char At\n  * Char Code At\"\n  * Code Point At\n  * Concat\n  * Date\n  * Delimiter On Case\n  * _ to space\n  * _ to space Capitilize\n  * Drop square bracket prefix\n  * Ends With\n  * Float\n  * Get Word\n  * Integer\n  * is Between\n  * Lower Case\n  * Number\n  * Prepend\n  * JSON\n  * Range Limit\n  * Split\n  * Starts With\n  * Timestamp\n  * Title\n  * Title Grammatical\n  * Trim\n  * Trim End\n  * Trim Start\n  * Upper Case\n  * Xml String Encode\n\n* xlsx / xlsx object to array/JSON (excel uses [xlsx][7])  \n* XML to JSON (uses [fast-xml-parser][4])\n\nNote, snappy needs to be installed separately as can have issues with auto install as build binaries.\n\nWith xlsx object one can use the function in [xlsx][7] against the object in functions node.\n\"\nExample AVRO with schema\n\n![Transform AVRO](documentation/transformArvo.jpg \"Transform AVRO example\")\n\nFor Confluence schema contains a list of schemas in form {\"\\<schema id\\>\",\\<schema\\>}\n\n------------------------------------------------------------\n\n## Test\n\nAllows a test case for a message to allow simple testing of nodes. Injects a new message via mouse or message. Message sent to first port which can be consumed by other nodes and returned back to node in a loop. The Test node then checks against detailed expected payload result.\n\n![Test](documentation/Test.JPG \"Test\")\n\nexample:\n\n![Test example](documentation/TestTest.JPG \"Test example\")\n\nafter run\n\n![Test example run](documentation/TestTestRun.JPG \"Test example run\")\n\n------------------------------------------------------------\n\n## append\n\nAppend file(s) to payload. Cached to maximise performance.\nRequire can be used to find file.\n\n![append](documentation/append.JPG \"append\")\n\nTest example:\n\n![append example](documentation/appendTest.JPG \"append example\")\n\n------------------------------------------------------------\n\n## Levenshtein Distance\n\nThe levenshtein distance between two character strings.\n\n![Levenshtein Distance](documentation/levenshteinDistance.jpg \"Levenshtein Distance\")\n\n------------------------------------------------------------\n\n## Load Injector\n\nInject messages for a set period of time with varying think time.\nPrimary purpose is testing and useful for load/stress testing.\n\nHas 3 extra data types\n\n1. generated id - Unique id for each message\n2. generated data - string text generated using [dummy-json][3]\n3. generated json - json generated using [dummy-json][3]\n\n![Load Injector](documentation/loadInjector.png \"Load Injector\")\n\nTest example:\n\n![Load Injector example](documentation/LoadInjectorTest.JPG \"Load Injector example\")\n\n------------------------------------------------------------\n\n## Monitor Flow\n\nAdd on wire between two flows to see message rates in status line.\nRate sampled every second and provides rate last second / 10 seconds / 1 minute / 5 minutes.\n\n![Monitor Flow](documentation/MonitorFlow.JPG \"Monitor Flow\")\n\nTest example:\n\n![Monitor Flow example](documentation/MonitorFlowTest.JPG \"Monitor Flow example\")\n\n------------------------------------------------------------\n\n## Host Available\n\nTest if host is available sending msg to up or down port so action can be taken.\nMessage only sent on state change or if message is sent which doesn't have topic refreshHostAvailable.\nThis topic forces a check rather than time check which can be set.\n\n![Host Available](documentation/hostAvailable.JPG \"Host Available\")\n\nTest example:\n\n![Host Available example](documentation/hostAvailableTest.JPG \"Host Available example\")\n\n------------------------------------------------------------\n\n## Monitor System\n\nSystem monitoring metrics\n\n![Monitor System](documentation/monitorSystem.JPG \"Monitor System\")\n\nTest example:\n\n![Monitor System example](documentation/monitorSystemTest.JPG \"Monitor System example\")\n\n------------------------------------------------------------\n\n## os\n\nThe metrics from node.js os\n\n![os](documentation/os.JPG \"os\")\n\nTest example:\n\n![os example](documentation/osTest.JPG \"os example\")\n\n------------------------------------------------------------\n\n## Spawn Process\n\nSpawn process as per node.js manual with ability to set working directory, environment variables\nand argument passed to process. STDOUT and STDERR are sent as individual messages.\nRC port is sent a message on closure.\nTakes in messages that starts a process with ability to add environment values.\nMessage can be sent to kill the process.\n\n![Spawn Process](documentation/SpawnProcess.JPG \"Spawn Process\")\n\nTest example:\n\n![Spawn Process example](documentation/SpawnProcessTest.JPG \"Spawn Process example\")\n\n------------------------------------------------------------\n\n## Install\n\nRun the following command in the root directory of your Node-RED install\n\n    npm install node-red-contrib-prib-functions\n\n## Tests\n\nTest/example flow in test/generalTest.json\n\n------------------------------------------------------------\n\n## Version\n\n0.26.0 add columnar store node with sql query capabilty\n\n0.24.0 add in logistic regression\n\n0.23.3 Removes bug in test, more translation\n\n0.23.0 Removes bug in test, more translation\n\n0.22.0 Add autocovariance + autocorealationship to real time data analystics, improves test\n\n0.21.0 Add lag/seasonal to real time data analystics\n\n0.20.3 Add difference + monitor system\n\n0.19.0 Improve load injector, fix bug in test comparing buffers, add compression tranforms\n\n0.18.0 Add matrix node\n\n0.17.0 Add finished wire to load injector\n\n## Author\n\n[Peter Prib][3]\n\n[1]: http://nodered.org \"node-red home page\"\n\n[2]: https://www.npmjs.com/package/node-red-contrib-prib-functions \"source code\"\n\n[3]: https://github.com/peterprib \"base github\"\n\n[4]: https://github.com/NaturalIntelligence/fast-xml-parser \"fast-xml-parser\"\n\n[5]: https://www.npmjs.com/package/snappy \"snappy\"\n\n[6]: https://www.npmjs.com/package/avsc \"avsc\"\n\n[7]: https://www.npmjs.com/package/xlsx \"xlsx\"\n","readmeFilename":"README.md"}