function _kldiv(q, p) {
    var plength = p.size().length;
    var qlength = q.size().length;

    if (plength > 1) {
      throw new Error('first object must be one dimensional');
    }

    if (qlength > 1) {
      throw new Error('second object must be one dimensional');
    }

    if (plength !== qlength) {
      throw new Error('Length of two vectors must be equal');
    } // Before calculation, apply normalization


    var sumq = sum(q);

    if (sumq === 0) {
      throw new Error('Sum of elements in first object must be non zero');
    }

    var sump = sum(p);

    if (sump === 0) {
      throw new Error('Sum of elements in second object must be non zero');
    }

    var qnorm = divide(q, sum(q));
    var pnorm = divide(p, sum(p));
    var result = sum(multiply(qnorm, log(dotDivide(qnorm, pnorm))));

    if (isNumeric(result)) {
      return result;
    } else {
      return Number.NaN;
    }
  }
Calculate the Kullback-Leibler (KL) divergence  between two distributions

Syntax:

    math.kldivergence(x, y)

Examples:

    math.kldivergence([0.7,0.5,0.4], [0.2,0.9,0.5])   //returns 0.24376698773121153


@param  {Array | Matrix} q    First vector
@param  {Array | Matrix} p    Second vector
@return {number}              Returns distance between q and p