Skip to content
/ BIDViz Public

Interactive Machine Learning toolkit based on BIDMach

Notifications You must be signed in to change notification settings

BIDData/BIDViz

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

98 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

BIDViz

Add interactivity to existing BIDMach script

This We will use "kmeans.ssc" included in the repository as example file. You can also use the same procedure for other BIDMach scripts that you might have.

###Steps:

Use an alternative version BIDMach that exposes a field in Learner.Options for datasink

Please clone and build BIDMach from this repository by using following commands

  git clone https://github.com/qihqi/BIDMach
  cd BIDMach
  mvn package install 

If you get compile errors you might need to rebuild the latest version of BIDMat first, with these commands

  cd ..
  git clone https://github.com/biddata/BIDMat
  cd BIDMat
  mvn package install 

Then rerun the previously failed commands

Clone this repository and build it

  cd ..
  git clone https://github.com/qihqi/BIDMach_Viz
  cd BIDMach_Viz
  mvn package

Modify the script to add WebDataSink

Here we use the kmeans.ssc script included in BIDMach_Viz as example.

Before the script look like this:

import BIDMach.models.KMeans.MatOptions

import BIDMat.{Mat,SBMat,CMat,DMat,FMat,IMat,HMat,GMat,GIMat,GSMat,SMat,SDMat}
import BIDMat.MatFunctions._
import BIDMat.SciFunctions._
import BIDMach.datasources._
import BIDMach.datasinks._
import BIDMach.updaters._
import BIDMach._
import BIDMach.ui.NetSink

val mat0 = rand(100, 100000)
val opts = new MatOptions
opts.dim = 256
opts.batchSize = math.min(100000, mat0.ncols/30 + 1)
opts.npasses = 1000
val nn = new Learner(
        new MatSource(Array(mat0:Mat), opts),
        new KMeans(opts),
        null,
        new Batch(opts),
        null,
        opts)
nn.train

New we want add WebServerChannel as learner listener to the learner before the line nn.train

import BIDMach.ui.WebServerChannel

nn.opts.observer = new WebServerChannel(nn)

WebServer takes a Learner instance as constructor argument. Save the file. Now we can run it by first running a sbt console using sbt console Then load the file using :load kmeans.ssc

The script will start running, eventually you will see this log

23:49:37.420 [run-main-0] INFO  play.core.server.NettyServer - Listening for HTTP on /0:0:0:0:0:0:0:0:9000

After this the webserver has started and you can access the visualization UI by directing your browser to *http://localhost:10001/

screen

You will see something like the above screen shot.

API Documentation

When the webapp is first launched, it establishes a websocket connection to /ws. All communication between the server and the javascript is done through this websocket. Below describes different messages that the server handles.

Client Initiated Message

Client can send a message of this format:

{
    methodName: <methodName>;
    content: ...
}

The methodName refers the different methods that javascript wants to invoke in the client. The different methodName the server accepts are:

  • addFunction
  • pauseTraining
  • modifyParam
  • evaluateCommand
  • getCode Below will describe what each of them do and what they accept as content.

addFunction

Accepts

{
    methodName: "addFunction",
    content: {
        name: name,
        code: code,
        type: type
    }
}

Returns

{
    success: true,
    data: ""
}

if succeeds, Or

{
    success: false,
    data: "error message"
}

if fails.

pauseTraining

Accepts

{
    methodName: "pauseTraining",
    content: <boolean>
}

Content is true to pause and false to resume. Returns: Nothing

modifyParam

Accepts:

{
    methodName: "modifyParam",
    content: {
      // a map of key to newvalue
    }
}

The server will iterate over that map and set the value using reflexion. Returns: Nothing

evaluateCommand

Accepts:

{
    methodName: "evaluateCommand",
    content: {
        code: "// the command to evaluate"
    }
}

Execute to the command inside of "code". Returns

{
    success: boolean,
    data: "string"
}

if success is true, then data is the result of the evaluation, if success is false, then the data is the error message returned

getCode

Accepts

{
    methodName: "evaluateCommand",
    content: {
       name : "name of the chart"
    }
}

get the Scala code user originally submitted to server for the chart of name. Returns

{
    success: boolean,
    data: "scala code as string"
}

Server initialized messages

Server sends messages to client spontaneously on the following cases:

  • on generating a new data point
  • on run time message of the graph code
  • sending requested parameters

About

Interactive Machine Learning toolkit based on BIDMach

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published