variance-reduce.js

this.getReducedSTD = function(dimensionGroup, variable) {
  // see https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Decremental_algorithm
  var reduceAdd = function (p, v) {
    var obj = p;
    var value = +v.variables[variable];
    if( _.isNaN(value) ) {
      //pass
    } else {
      obj.n = obj.n + 1;
      var oldM2 = obj.M2;
      var delta = value - obj.mean;
      obj.mean = obj.mean + delta/obj.n;
      obj.M2 = obj.M2 + delta*(value - obj.mean);
      if( obj.M2 < 0 ) {
        console.log("ADD passed to negative", variable, oldM2, "delta=", delta, JSON.stringify(obj));
      }
    }
    // console.log("--> ADD", p.n, variable, JSON.stringify(p.valueOf()));          
    // console.log("--> ADD", JSON.stringify(p), "V = ", v);
    return p;
  };

  var reduceRemove = function (p, v) {
    var obj = p;
    var value = +v.variables[variable];
    if( _.isNaN(value) || obj.n < 2 ) {
      //pass
    } else {
      obj.n = obj.n - 1;
      var oldM2 = obj.M2;
      var oldMean = obj.mean;
      var delta = value - obj.mean;
      obj.mean = obj.mean - delta/obj.n;
      obj.M2 = obj.M2 - delta*(value - obj.mean);
      if( obj.M2 < 0 ) {
        console.log("REMOVE passed to negative", variable, oldM2, "delta=", delta, JSON.stringify(obj));
      }
    }
    // console.log("--> REMOVE", p.n, variable, JSON.stringify(p.valueOf()));
    // console.log("--> REMOVE", JSON.stringify(p), "V = ", v);
    return p;
  };

  var reduceInitial = function () {
    var p = {};
    var obj = p;
    obj.n = 0;
    obj.mean = 0;
    obj.M2 = 0;
    obj.valueOf = function() {
      var variance = (obj.n < 2) ? 0 : obj.M2 / (obj.n-1),
      stddev = Math.sqrt(variance);
      return {
        variance: variance,
        stddev: stddev,
        mean: obj.mean
      };
    };
    return p;
  };
  return dimensionGroup.reduce(reduceAdd, reduceRemove, reduceInitial);
};