node-red-contrib-neuralnetwork 0.1.1

SmartNode node package, provided by MakerCollider

npm install node-red-contrib-neuralnetwork

Install


Download node-red-contrib-neuralnetwork to nodered root directory. 
Windows for example: C:\node-red\node_modules
Linux for example: /home/root/node-red/node_modules

You will need to restart Node-RED for it to pick-up the new nodes.

Usage

node-red-contrib-neuralnetwork is based on brain. You need to see it basic usage at first.

Train

When there is no msg.netJSON input, brain node will train with msg.trainData and output net.toJSON in msg.net.

Run

When there is msg.netJSON input, brain node will not train anymore. Instead, it will directory run net.run() with your msg.runData. And output the result in msg.payload.

Example

Train:

[{"id":"d4a484b.f2b5b78","type":"debug","z":"46d50fa1.b92af","name":"","active":true,"console":"false","complete":"net","x":679,"y":175,"wires":[]},{"id":"3b4d60b3.c4b2a","type":"inject","z":"46d50fa1.b92af","name":"","topic":"","payload":"","payloadType":"date","repeat":"","crontab":"","once":false,"x":150,"y":144,"wires":[["6d766489.92899c"]]},{"id":"6d766489.92899c","type":"function","z":"46d50fa1.b92af","name":"fake data","func":"// This function return a fake json array\nvar trainData = [{input: { r: 0.03, g: 0.7, b: 0.5 }, output: { black: 1 }},\n           {input: { r: 0.16, g: 0.09, b: 0.2 }, output: { white: 1 }},\n           {input: { r: 0.5, g: 0.5, b: 1.0 }, output: { white: 1 }}]\n\nmsg.trainData = trainData\nreturn msg;","outputs":1,"noerr":0,"x":333,"y":183,"wires":[["2fe2efbc.d01d1"]]},{"id":"2fe2efbc.d01d1","type":"neuralNetwork","z":"46d50fa1.b92af","name":"neuralNetwork","learningRate":0.3,"errorThresh":0.005,"iterations":20000,"log":false,"logPeriod":10,"x":516,"y":185,"wires":[["d4a484b.f2b5b78"]]}]

Run:

[{"id":"10d56f1d.ef2a91","type":"debug","z":"46d50fa1.b92af","name":"","active":true,"console":"false","complete":"payload","x":687,"y":346,"wires":[]},{"id":"808a1160.7f75f","type":"inject","z":"46d50fa1.b92af","name":"","topic":"","payload":"","payloadType":"date","repeat":"","crontab":"","once":false,"x":131,"y":325,"wires":[["fbed5f0e.0412a"]]},{"id":"fbed5f0e.0412a","type":"function","z":"46d50fa1.b92af","name":"fake data","func":"// This function return a fake json array\nvar netJSON = {\"layers\":[{\"r\":{},\"g\":{},\"b\":{}},{\"0\":{\"bias\":0.5976173927716023,\"weights\":{\"r\":3.5006895738532835,\"g\":-4.542455700505483,\"b\":0.9988932386815509}},\"1\":{\"bias\":0.6470978455858952,\"weights\":{\"r\":3.6115725201557827,\"g\":-4.875546614413311,\"b\":1.211740813346471}},\"2\":{\"bias\":-0.3559477465736521,\"weights\":{\"r\":1.1063595019849224,\"g\":-1.857026678772011,\"b\":0.14886809335684345}}},{\"black\":{\"bias\":3.3336645409591017,\"weights\":{\"0\":-3.7876606581596914,\"1\":-4.023316483216229,\"2\":-1.0819957068479935}},\"white\":{\"bias\":-3.29149645757729,\"weights\":{\"0\":3.782751737648757,\"1\":4.173873416865656,\"2\":0.7154074171638515}}}],\"outputLookup\":true,\"inputLookup\":true}    \nvar runData = { r: 1, g: 0.4, b: 0 }\n\nmsg.runData = runData\nmsg.netJSON = netJSON\nreturn msg;","outputs":1,"noerr":0,"x":315,"y":336,"wires":[["3132e68b.cecd1a"]]},{"id":"3132e68b.cecd1a","type":"neuralNetwork","z":"46d50fa1.b92af","name":"neuralNetwork","learningRate":0.3,"errorThresh":0.005,"iterations":20000,"log":false,"logPeriod":10,"x":501,"y":341,"wires":[["10d56f1d.ef2a91"]]}]

License

MIT License \ No newline at end of file

Node Info

Version: 0.1.1
Updated 9 months, 3 weeks ago
License: MIT

Downloads

6 in the last day
13 in the last week
38 in the last month

Nodes

  • neuralNetwork
  • multiInData
  • dataCollect
  • outputJudge

Keywords

  • node-red
  • node
  • neuralnetwork
  • makercollider

Maintainers

  • makercollider