comparative-judgement/lib/csvEstimation.js

Comparative Judgement Algorithms

// Read in a decisions file
// Read in an optional player anchor file
// Estimate the model for players
// Write out the players file

/* jshint -W024, expr:true */
/*jslint node: true */
/*global expect, fx, sinon*/
/*jshint -W083 */

"use strict";
var _ = require('underscore');
var csv = require('fast-csv');
var statutils = require('./statutils');
var estimation = require('./estimation');
var byjudge = require('./byjudge');
var async = require('async');
var fs = require("fs");

var estimateFromCsv = function(decisionsCsv, playersCsv ,callback){
  var decisions = [];
  var anchors = [];
  var players = [];
  var start;
  // Read in the decisions csv
  async.series([
    function(callback){
      csv
        .fromPath(decisionsCsv, {headers:true})
        .on("data", function(data){
          decisions.push(data);
        })
        .on("end", function(){
          callback();
        });
    },
    function(callback){
      if(playersCsv){
      csv
        .fromPath(playersCsv, {headers:true})
        .on("data", function(data){
          anchors.push(data);
        })
        .on("end", function(){
          callback();
        });
      } else {
        callback();
      }
    },
    function(callback){
        var chosen  = _.uniq(_.pluck(decisions, 'Candidate Chosen'));
        var notChosen = _.uniq(_.pluck(decisions, 'Candidate Not Chosen'));
        var playerIds = _.union(chosen, notChosen);
        var myPlayers = [];
        for(var i=0; i<playerIds.length; i++){
          var anchor = _.findWhere(anchors, {Id: playerIds[i]});
          if(anchor) {
            myPlayers.push({
              _id: playerIds[i],
              comparisons: anchor.Comparisons,
              observedScore: anchor['Raw Score'],
              trueScore: anchor['True Score'],
              seTrueScore: anchor['True Score SE'],
              selected: 0,
              infit: anchor.Infit,
              decisions: [],
              opponents: [],
              anchor: true,
            });
          } else {
            myPlayers.push({
              _id: playerIds[i],
              comparisons: 0,
              observedScore: 0,
              trueScore: 0,
              seTrueScore: 0,
              selected: 0,
              infit: 0,
              decisions: [],
              opponents: []
            });
          }
        }
        byjudge.rebuildPlayers(myPlayers, decisions);
        start = new Date().getTime();
        estimation.estimateCJ('',myPlayers, 4, function(task, estPlayers){
          var end = new Date().getTime();
          var time = end - start;
          console.log('Execution time: ' + time);
          for(var k=0; k<estPlayers.length; k++){
            players.push(estPlayers[k]);
          }
          callback();
        });
    },
    function(callback){
      //save scripts collection to csv
      var fn = Date.now() + '-players.csv';
      var ws = fs.createWriteStream(fn);
      csv
        .write(players, {
          headers: true,
          transform: function(row){
            return {
                'Id': row._id,
                'Comparisons': row.comparisons,
                'Observed Score': row.observedScore,
                'True Score': row.trueScore,
                'True Score SE': row.seTrueScore,
            };
          }
        })
        .pipe(ws);
      callback();
    }
    ], function(err){
    if(err) return callback(err);
    callback(null, 'estimation complete');
  });
};

module.exports = {
  estimateFromCsv: estimateFromCsv,
};