Some work graphing a few probability distributions using d3.js

gistfile1.txt

var probability = {
  normal: function(x, mean, stddev) {
    var y = (1 / (stddev * Math.sqrt(2 * Math.PI))) * Math.pow(Math.E, - (Math.pow(x - mean, 2) / (2 * Math.pow(stddev, 2))));
    //console.log('normal', x, mean, stddev, y);
    return y;
  },
  logNormal: function(x, mean, stddev) {
    var y = (1 / (x * Math.sqrt(2 * Math.PI * Math.pow(stddev, 2)))) * Math.pow(Math.E, - (Math.pow(Math.log(x) - mean, 2) / (2 * Math.pow(stddev, 2))));
    //console.log('logNormal', x, mean, stddev, y);
    y = isFinite(y) ? y : 0;
    return y;
  },
  erlang: function(x, kappa, lambda) {
    var y = (Math.pow(lambda, kappa) * Math.pow(x, kappa - 1) * Math.pow(Math.E, - lambda * x)) / probability.factorial(kappa - 1);      
    //console.log('erlang', x, kappa, lambda, y);
    return y;
  },
  erlangScale: function(x, kappa, scale) {
    var y = (Math.pow(x, kappa - 1) * Math.pow(Math.E, - x / scale)) / (Math.pow(scale, kappa) * probability.factorial(kappa - 1));
    //console.log('erlang scale', x, kappa, scale, y);
    return y;
  },
  factorial: function(n) {
    var rval=1;
    for (var i = 2; i <= n; i++)
      rval = rval * i;
    return rval;
  }
};

///////////////////////////

var graph = function(selector) {
  var margin = {top:20, bottom:30, left:20, right:30};
  var setWidth = 100;
  var setHeight = 100;
  var width = setWidth - margin.left - margin.right;
  var height = setHeight - margin.top - margin.bottom;
  var domain = [0, 1];
  var step = 1;
  var max, min;
  var paths = [];

  var graph = d3.select(selector)
    .append("svg:svg")
    .attr("width", setWidth)
    .attr("height", setHeight);
  var g = graph.append("svg:g").attr("transform", "translate(0,0)");

  var x = d3.scale.linear().domain([0, 1]).range([margin.left, width]);
  var y = d3.scale.linear().domain([0, 1]).range([height, margin.top]);

  var line = d3.svg.line()
    .x(function(d,i) {return x(d.x);})
    .y(function(d) {return y(d.y);})
    .interpolate('basis');

  var xAxis = d3.svg.axis().scale(x).tickSize(-height).tickSubdivide(true);
  var yAxis = d3.svg.axis().scale(y).ticks(4).orient("right");

  var chart = function() {}

  graph.append("svg:g")
    .attr("class", "x axis")
    .attr("transform", "translate(0," + height + ")")
    .call(xAxis);

  graph.append("svg:g")
    .attr("class", "y axis")
    .attr("transform", "translate(" + width + ",0)")
    .call(yAxis);

  chart.render = function() {
    graph.select(".x.axis")
      .attr("transform", "translate(0," + height + ")")
      .call(xAxis);
    graph.select(".y.axis")
      .attr("transform", "translate(" + width + ",0)")
      .call(yAxis);
    paths.forEach(function(p) {
      p.path.attr("d", line(p.data));
    });
  };

  chart.width = function(_) {
    if (!arguments.length) return setWidth;
    setWidth = _;
    width = setWidth - margin.left - margin.right;
    graph.attr("width", setWidth);
    x.range([margin.left, width]);
    chart.render();
    return chart;
  };

  chart.height = function(_) {
    if (!arguments.length) return setHeight;
    setHeight = _;
    height = setHeight - margin.top - margin.bottom;
    graph.attr("height", setHeight);
    y.range([height, margin.top]);
    chart.render();
    return chart;
  };

  chart.x = function(_) {
    if (!arguments.length) return x;
    x = _;
    xAxis.scale(x);
    return chart;
  };

  chart.y = function(_) {
    if (!arguments.length) return y;
    y = _;
    yAxis.scale(y);
    return chart;
  };

  chart.domain = function(_) {
    if (!arguments.length) return domain;
    domain = _;
    x.domain(domain);
    return chart;
  };

  chart.step = function(_) {
    if (!arguments.length) return step;
    step = _;
    return chart;
  };

  chart.line = function() {
    if (!arguments.length) return;
    args = Array.prototype.slice.call(arguments, 0);
    color = args.pop();
    fn = args.shift();
    data = [];
    domain = x.domain()
    for (var i = domain[0]; i <= domain[1]; i += step) {
        args.unshift(i);
        data.push({x: i, y: fn.apply(fn, args)});
        args.shift();
    }
    var yVals = data.map(function(d) {return d.y;});

    if (max !== null) yVals.push(max);
    if (min !== null) yVals.push(min);
    max = Math.ceil(d3.max(yVals));
    min = Math.floor(d3.min(yVals));

    y.domain([min, max]);
    chart.render();
    var path = g.append("svg:path")
      .attr("class", "line " + fn.name)
      .attr("d", line(data))
      .attr('style', "stroke:" + color);
    paths.push({path: path, data: data});
    return chart;
  };

  return chart;
};

var width = 300;
var height = 200;

// http://en.wikipedia.org/wiki/Normal_distribution
graph('#normal').width(width).height(height)
  .domain([-5, 5])
  .step(0.2)
  .line(probability.normal, 0, 0.2, "blue")
  .line(probability.normal, 0, 1, "red")
  .line(probability.normal, 0, 5, "orange")
  .line(probability.normal, -2, 0.5, "green");

// http://en.wikipedia.org/wiki/Log-normal_distribution
graph('#logNormal').width(width).height(height)
  .domain([0,3])
  .step(0.2)
  .line(probability.logNormal, 0, 1, "blue")
  .line(probability.logNormal, 0, 0.25, "red")
  .line(probability.logNormal, 0, 0.5, "green");

// http://en.wikipedia.org/wiki/Erlang_distribution    
graph('#erlang').width(width).height(height)
  .domain([0,20])
  .step(0.5)
  .line(probability.erlangScale, 1, 2.0, "red")
  .line(probability.erlangScale, 2, 2.0, "green")
  .line(probability.erlangScale, 3, 2.0, "blue")
  .line(probability.erlangScale, 5, 1.0, "cyan")
  .line(probability.erlangScale, 9, 0.5, "orange");