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              <div class = "container">
  <div class = "row">
    <div class = "col-md-6 col-sm-6 col-xs-6 col-md-offset-3 col-sm-offset-3 col-xs-offset-3">
      <h3 class = "text-center">SBG <span class = "text-info">Advance</span></h3>
    </div>
  </div>
  <div class = "row">
    <div class = "col-md-12 col-sm-12 col-xs-12" id = "mainContainer">
     
    </div>
  </div>
</div>
            
          
!
            
              .bordered{
border: 1px black solid;
  border-radius:5px;
padding:10px;
  
}

#predictedScoreDisplay{

font-weight:bold;
font-size:250px;
text-align:center  
  
}

.browser-container{
  
 margin:10px;   
}

.form-control{
  font-size:18px;
  
}

            
          
!
            
              
var layer_defs = [];
layer_defs.push({type:'input', out_sx:1, out_sy:1, out_depth:5});
layer_defs.push({type:'fc', num_neurons:20, activation:'relu'});
layer_defs.push({type:'fc', num_neurons:20, activation:'sigmoid'});
layer_defs.push({type:'regression', num_neurons:1});

var net = new convnetjs.Net();
net.makeLayers(layer_defs);

var trainer = new convnetjs.Trainer(net, {method: 'adadelta', l2_decay: 0.001,
                                    batch_size: 1});



function generateDataPoints(number,useNeuralNet) {
  var output = [];
  for (var i = 0; i < number; i++) {

    output.push(generateDataPoint(i,useNeuralNet));
  }

  return output;
}

function generateDataPoint(index,useNeuralNet) {
  var level = _.sample([ 5,6,7,8,9]);
  var arithmeticErrors = _.sample([0, 1]);
  var algebraicErrors = _.sample([0, 1]);
  var conceptualErrors = _.sample([0, 1,2]);
  var problemDifficulty = _.sample([1, 2, 3]);

if(!useNeuralNet){


  var predictedScore = level + 1;


}
else{

  var x = new convnetjs.Vol(1,1,5);
  var my_data = [level,arithmeticErrors,algebraicErrors,conceptualErrors,problemDifficulty]
  x.w[0] = my_data[0]; // Vol.w is just a list, it holds your data
  x.w[1] = my_data[1];
  x.w[2] = my_data[2]; // Vol.w is just a list, it holds your data
  x.w[3] = my_data[3];
  x.w[4] = my_data[4]; // Vol.w is just a list, it holds your data
  


  var predictedScore = Math.round(net.forward(x).w[0])+5;
}

  return {
    currentScore: level,
    arithmeticErrors: arithmeticErrors,
    algebraErrors: algebraicErrors,
    conceptualErrors: conceptualErrors,
    problemDifficulty: problemDifficulty,
    processed: false,
    predictedScore: predictedScore,
    index: index
  };



}

var App = new React.createClass({
  getInitialState: function () {

    var allData = localStorage.getItem("allData");

    if (allData) {

      return { dataPoints: generateDataPoints(10,true), allData: JSON.parse(allData),isLearning:false};
    } else {
      localStorage.setItem("allData",JSON.stringify([]));
      
      return { dataPoints: generateDataPoints(10,false), allData: [], isLearning:false };
    }
  },
  render: function() {
    var dataPoints = _.filter(this.state.dataPoints,function(e){
      return (e.processed==false);
    
    });
    
    var dataComponents = [];
    var component = this;
    
    if(dataPoints.length>0){
    dataPoints.map(function(e, i) {

      dataComponents.push(

 <DataPoint inputData = {e} key = {i}  setParentState = {component.setParentState}  predictedScore = {e.predictedScore}/>

      )

    })
    }
    else{
       
        var allData = this.state.allData;

      allData = allData.concat(this.state.dataPoints);
      
      localStorage.setItem("allData", JSON.stringify(allData));
      var stats;
      var component = this;
        for(var j = 0;j<100;j++){
        
        allData = _.shuffle(allData);
        allData.forEach(function(o){

        var x = new convnetjs.Vol(1,1,5);
        var my_data = [o.currentScore,o.arithmeticErrors,o.algebraErrors,o.conceptualErrors,o.problemDifficulty]
        x.w[0] = my_data[0]; // Vol.w is just a list, it holds your data
        x.w[1] = my_data[1];
        x.w[2] = my_data[2]; 
        x.w[3] = my_data[3];
        x.w[4] = my_data[4]; 

        //console.log(x)
        stats = trainer.train(x, [o.predictedScore-5]);
        //console.log(stats)
        })


        }
      
      //console.log(stats);
      component.setState({ dataPoints: generateDataPoints(10,true), allData: allData});
    
    }
    
    return (
      <div>
      <LearningDisplay isLearning = {this.state.isLearning}/>
        <hr/>
      <div className = "row" >
   <div className = "col-md-12 ">
   {dataComponents}
   </div>
   </div>
        <Browser/>
   </div>
    )
  },
  setParentState:function(index,object){
    
    var inputData = this.state.dataPoints;
    var selectedData = inputData[index];
    var changedProperties = Object.keys(object);
changedProperties.forEach(function(key){

selectedData[key]=object[key]

})
inputData[index]=selectedData;


    
    this.setState({inputData:inputData});
    
  }

})

var DataPoint = new React.createClass({

  render: function() {

  var scoreButtons = [];  
  for(var i = 5;i<=10;i++){
  if(i==this.props.predictedScore){
    
   scoreButtons.push(
  (<div className = "col-md-1  text-center">
    
    <button className = "btn btn-sm btn-danger" key = {i} ref = {i} onClick = {this.setParentState}>{i}</button>
    
  </div>)) 
    
  }
    
    else{
      
   scoreButtons.push((
  <div className = "col-md-1  text-center">
    
    <button className = "btn btn-sm btn-primary" key = {i} ref = {i} onClick = {this.setParentState}>{i}</button>
    
  </div>))   
      
      
    }
    
    
  }  
    
    
    
    
    return (

      <div className = "col-md-3 bordered"> 
<div className = "row">
  
  <div className = "col-md-12 text-center">
    
    <h5>Current Score: <span className = "text-info">{this.props.inputData.currentScore}</span></h5>
    
  </div>
 </div>
<div className = "row">
  
  <div className = "col-md-12 text-center">
    
    <h5>Problem Difficulty: <span className = "text-info">{this.props.inputData.problemDifficulty}</span></h5>
    
  </div>
 </div>

    <div className = "row">
  
  <div className = "col-md-12 text-center">
    
    <h5>Conceptual Errors: <span className = "text-info">{this.props.inputData.conceptualErrors}</span></h5>
    
  </div>
 </div>
    
    
    <div className = "row">
  
  <div className = "col-md-12 text-center">
    
    <h5>Arithmetic Errors: <span className = "text-info">{this.props.inputData.arithmeticErrors}</span></h5>
    
  </div>
 </div>


    <div className = "row">
  
  <div className = "col-md-12 text-center">
    
    <h5>Algebra Errors: <span className = "text-info">{this.props.inputData.algebraErrors}</span></h5>
    
  </div>
 </div>

  <div className = "row">
  {scoreButtons}
 </div>
    
    
</div>
    )

  },
  setParentState:function(e){
  
    this.props.setParentState(this.props.inputData.index, { processed: true,predictedScore:parseInt(e.target.innerText) });
    
  }

})

var LearningDisplay = React.createClass({
render:function(){
  
 return (
<div> 
 <div className = "row">
     
     <div className = "col-md-6 col-md-offset-3">
       {(this.props.isLearning)?"Please Wait...Processing Data":""}
     </div>
  </div>
 <div className = "row">
     
     <div className = "col-md-6 col-md-offset-3 text-center">
       <button className = "btn btn-info" onClick ={ this.resetLearning}>Reset All Data</button>
       <button className = "btn btn-warning" onClick ={ this.clearBrain}>Clear Brain</button>
       <button className = "btn btn-success" onClick ={ this.loadTrainedBrain}>Load Trained Data</button>
       
     </div>
  </div>
 </div>
 ) 
  
},
  
resetLearning:function(){
  
localStorage.setItem("allData",JSON.stringify([]));

  
},
loadTrainedBrain:function(){
  
var allData = JSON.parse(trainingSetWeinberg);  
var stats;
for(var j = 0;j<1000;j++){
        
        allData = _.shuffle(allData);
        allData.forEach(function(o){

        var x = new convnetjs.Vol(1,1,5);
        var my_data = [o.currentScore,o.arithmeticErrors,o.algebraErrors,o.conceptualErrors,o.problemDifficulty]
        x.w[0] = my_data[0]; // Vol.w is just a list, it holds your data
        x.w[1] = my_data[1];
        x.w[2] = my_data[2]; 
        x.w[3] = my_data[3];
        x.w[4] = my_data[4]; 

        //console.log(x)
        stats = trainer.train(x, [o.predictedScore-5]);
        //console.log(stats)
        })


        }  
  
  
}
   
  
})

var Browser = React.createClass({
 getInitialState:function(){
   
    var level = _.sample([ 5,6,7,8,9]);
  var arithmeticErrors = _.sample([0, 1]);
  var algebraicErrors = _.sample([0, 1]);
  var conceptualErrors = _.sample([0, 1,2]);
  var problemDifficulty = _.sample([1, 2, 3]);
   
   
  var x = new convnetjs.Vol(1,1,5);
  var my_data = [level,arithmeticErrors,algebraicErrors,conceptualErrors,problemDifficulty];
  x.w[0] = my_data[0]; // Vol.w is just a list, it holds your data
  x.w[1] = my_data[1];
  x.w[2] = my_data[2]; // Vol.w is just a list, it holds your data
  x.w[3] = my_data[3];
  x.w[4] = my_data[4]; // Vol.w is just a list, it holds your data
  


  var predictedScore = Math.round(net.forward(x).w[0])+5;
   
 return {
    currentScore: level,
    arithmeticErrors: arithmeticErrors,
    algebraErrors: algebraicErrors,
    conceptualErrors: conceptualErrors,
    problemDifficulty: problemDifficulty,
    predictedScore: predictedScore,
  
  };
   
 },
render:function(){
  
return(
<div className = "row bordered browser-container">
  <div className = "col-md-3 col-xs-6">
     <div className="form-group">
    <label for="currentScore">Current Score</label>
    <input type="number" className="form-control" ref="currentScore" onChange = {this.calculateScore} value={this.state.currentScore}/>
  </div>
       <div className="form-group">
    <label for="problemDifficulty">Problem Difficulty</label>
    <input type="number" className="form-control" ref="problemDifficulty" onChange = {this.calculateScore} value={this.state.problemDifficulty}/>
  </div>
       <div className="form-group">
    <label for="conceptualErrors">Conceptual Errors</label>
    <input type="number" className="form-control" ref="conceptualErrors" onChange = {this.calculateScore} value={this.state.conceptualErrors}/>
  </div>
          <div className="form-group">
    <label for="arithmeticErrors">Arithmetic Errors</label>
    <input type="number" className="form-control" ref="arithmeticErrors" onChange = {this.calculateScore} value={this.state.arithmeticErrors}/>
  </div>
             <div className="form-group">
    <label for="algebraErrors">Algebra Errors</label>
    <input type="number" className="form-control" ref="algebraErrors" onChange = {this.calculateScore} value={this.state.algebraErrors}/>
  </div>
         
  </div>
  <div className = "col-md-6">
    <div id = "predictedScoreDisplay">
      {this.state.predictedScore}
    </div>
  </div>
  </div>

)  
  
},
 calculateScore:function(){
   
    var level = parseInt(this.refs.currentScore.value);
  var arithmeticErrors = parseInt(this.refs.arithmeticErrors.value);
  var algebraicErrors = parseInt(this.refs.algebraErrors.value);
  var conceptualErrors = parseInt(this.refs.conceptualErrors.value);
  var problemDifficulty = parseInt(this.refs.problemDifficulty.value);
   
   
  var x = new convnetjs.Vol(1,1,5);
  var my_data = [level,arithmeticErrors,algebraicErrors,conceptualErrors,problemDifficulty];
  x.w[0] = my_data[0]; // Vol.w is just a list, it holds your data
  x.w[1] = my_data[1];
  x.w[2] = my_data[2]; // Vol.w is just a list, it holds your data
  x.w[3] = my_data[3];
  x.w[4] = my_data[4]; // Vol.w is just a list, it holds your data
  


  var predictedScore = Math.round(net.forward(x).w[0])+5;
    
   this.setState({
    currentScore: level,
    arithmeticErrors: arithmeticErrors,
    algebraErrors: algebraicErrors,
    conceptualErrors: conceptualErrors,
    problemDifficulty: problemDifficulty,
    predictedScore: predictedScore,
  
  })
   
   
   
 }
  
})

ReactDOM.render(<App/>, document.getElementById("mainContainer"));
  

var trainingSetWeinberg='[{"currentScore":8,"arithmeticErrors":0,"algebraErrors":0,"conceptualErrors":1,"problemDifficulty":1,"processed":true,"predictedScore":7,"index":4},{"currentScore":9,"arithmeticErrors":0,"algebraErrors":0,"conceptualErrors":2,"problemDifficulty":3,"processed":true,"predictedScore":7,"index":5},{"currentScore":9,"arithmeticErrors":1,"algebraErrors":1,"conceptualErrors":0,"problemDifficulty":3,"processed":true,"predictedScore":9,"index":2},{"currentScore":7,"arithmeticErrors":1,"algebraErrors":1,"conceptualErrors":2,"problemDifficulty":3,"processed":true,"predictedScore":7,"index":1}, 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